VIRTUAL INSTITUTE TEACHING MATERIAL ON TRADE, THE ... · 4.2 Basic game theory notions and concepts...

VIRTUAL INSTITUTE TEACHING MATERIAL ONTRADE, THE ENVIRONMENT AND

SUSTAINABLE DEVELOPMENT: TRANSITION TO A LOW-CARBON ECONOMY

U N I T E D N AT I O N S C O N F E R E N C E O N T R A D E A N D D E V E L O P M E N T

New York and Geneva, 2016

U N I T E D N A T I O N S C O N F E R E N C E O N T R A D E A N D D E V E L O P M E N T

VIRTUAL INSTITUTE TEACHING MATERIAL ON

TRADE, THE ENVIRONMENT AND SUSTAINABLE DEVELOPMENT:

TRANSITION TO A LOW-CARBON ECONOMY

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UNCTAD/GDS/2016/2

Copyright © United Nations, 2016All rights reserved

NOTE

The views expressed in this volume are those of the author and do not necessarily reflect those of the United Nations.

The designations employed and the presentation of the material do not imply the expression of any opinion on the part of the United Nations concerning the legal status of any country, territory, city or area, or of its authorities, or concerning the delimitation of its frontiers or boundaries.

Material in this document may be freely quoted or reprinted, but acknowledgement of the UNCTAD Virtual Institute is requested, together with a reference to the document number. A copy of the publication containing the quotation or reprint should be sent to the UNCTAD Virtual Institute, Division on Globalization and Development Strategies, Palais des Nations, 1211 Geneva 10, Switzerland.

This document has been edited externally.

The UNCTAD Virtual Institute (http://vi.unctad.org) is a capacity-building and networking programme that aims to strengthen teaching and research of international trade and development issues at academic institu-tions in developing countries and countries with economies in transition, and to foster links between research and policymaking. For further information, please contact [email protected].

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ACKNOWLEDGEMENTS

This teaching material was developed by the UNCTAD Virtual Institute, under the overall guidance of Vlasta Macku, and in cooperation with UNCTAD’s Trade, Environment, Climate Change and Sustainable Development Branch. The material was researched and written by Caspar Sauter from the Virtual Institute, and benefitted from comments by Bonapas Onguglo and Robert Hamwey of the Trade, Environment, Climate Change and Sustainable Development Branch. The text was English-edited by David Einhorn, and the design and layout were created by Hadrien Gliozzo.

The financial contribution of the Government of Finland is gratefully acknowledged.

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TABLE OF CONTENTS

The environment, the economy and trade: The importance of sustainable development 5

1 Introduction 6

2 Theeconomyandtheenvironment:Unravellingthelinks 6

2.1 Links between the economy and the environment 7

2.2 Environmental impact of economic activities 11

3 Sustainabilityoftheeconomicsystem 15

3.1 Ecocide: Lessons from history 15

3.2 Sustainability 17

3.3 Sustainable development: The international awakening 17

3.4 Trade as a key component of sustainable development 18

4 Impactoftradeontheenvironment 20

4.1 Trade, trade openness and the environment: A first glance at the data 20

4.2 Environmental impact of trade: What we can learn from theory 23

4.3 Environmental impact of trade: What we can learn from empirical evidence 25

5 Exercisesandquestionsfordiscussion 28

ANNEX 1 29

ANNEX 2 29

REFERENCES 30

The climate science behind climate change 33

1 Introduction 34

2 Climatesystemandclimatechange–thetheoreticalbasis 35

2.1 The five components of the climate system 36

2.2 Earth’s energy balance and the natural greenhouse effect 38

2.3 Internally and externally induced climate change 40

2.4 Measuring the importance of factors driving climate change: radiative forcing and effective radiative forcing 43

2.5 Human-induced climate change 44

3 Observedchangesintheclimatesystem 50

3.1 Observed changes in temperature 50

3.2 Observed changes in precipitation 51

3.3 Observed changes in ice and snow cover 52

3.4 Observed changes in sea levels 52

3.5 Observed changes in extreme events 53

3.6 Impacts on natural and human systems 53

4 Anticipatedchangesintheclimatesystemandpotentialimpactsofclimatechange 55


ANNEX 1 59

ANNEX 2 59

REFERENCES 60

NOTE ii

ACKNOWLEDGEMENTS iii

TABLE OF CONTENTS iv

LIST OF FIGURES vi

LIST OF TABLES vii

LIST OF BOXES vii

LIST OF ABBREVIATIONS ix

INTRODUCTION 1

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The economics of climate change 63

1 Introduction 64

2 ThecompetitivemarketsmodelandParetoefficiency 64

2.1 A simple model of market economies 65

2.2 Pareto efficiency 66

2.3 Competitive market equilibria and Pareto efficiency 66

3 Climatechange:Thegreatestmarketfailureinhumanhistory 68

3.1 The atmosphere: An open-access resource 68

3.2 Greenhouse gas emissions: A negative externality problem 69

4 Whyisitsohardtosolvetheclimatechangeproblem? 71

4.1 Mitigating climate change: A global public good 71

4.2 Basic game theory notions and concepts 72

4.3 Climate change mitigation: A game theory perspective 74


ANNEX 1 80

REFERENCES 81

The politics of climate change – towards a low-carbon world 83

1 Introduction 84

2 Policyoptionsandtechnologicalsolutionstolimitclimatechange 85

2.1 Policy instruments and technologies allowing to stabilize concentrations of greenhouse gases in the atmosphere 85

2.2 Policies allowing to promote technological solutions aimed at increasing the amount of reflected incoming 95 solar radiation back into space

3 Climatechangeadaptationpolicyoptions 96

4 Theinternationalclimatechangepolicyarchitecture 101

4.1 From Rio to Paris – 25 years of climate change negotiations 101

4.2 The Paris Agreement 102


ANNEX 1 108

ANNEX 2 108

REFERENCES 109

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LIST OF FIGURES

Figure 1 The economy and the environment: Two interdependent systems 7

Figure 2 Classification of natural resources 8

Figure 3 World trade, exports and imports by broad category 8

Figure 4 CO2 – IPAT decomposition 12

Figure 5 Kaya decomposition: Annex I countries (left panel) and non-Annex I countries (right panel) 13

Figure 6 United Nations 2015 world population projection 14

Figure 7 IPAT: The impact of projected population growth on CO2 emissions 14

Figure 8 IPAT: The impact of projected GDP per capita growth on CO2 emissions 15

Figure 9 Trade openness and CO2 emissions, 1960–2014 21

Figure 10 Trade openness and CO2 emissions, 2011 22

Figure 11 Relationship between agreement, evidence and confidence levels 34

Figure 12 The climate system 36

Figure 13 Layers of the atmosphere 37

Figure 14 Photosynthesis – the chemical reaction 38

Figure 15 The global mean energy balance of the earth 39

Figure 16 Extreme events - schematic presentation 41

Figure 17 Correlations of surface temperature, precipitation and mean sea level pressure 42 with the Southern Oscillation Index

Figure 18 Externally induced climate changes 43

Figure 19 Atmospheric carbon dioxide, methane and nitrous oxide concentrations from year 0 to 2005 45

Figure 20 Key properties of main aerosols in the troposphere 46

Figure 21 Radiative forcing of the climate between 1750 and 2011 48

Figure 22 Positive and negative feedback mechanisms 49

Figure 23 Observed surface temperature changes from 1901 to 2012 50

Figure 24 Observed change in annual precipitation over the land surface 51

Figure 25 Selected observed changes in snow cover, ice extent and sea level 52

Figure 26 Observed impacts attributed to climate change 54

Figure 27 Carbon dioxide emission trajectories according to the four representative concentration pathways 55

Figure 28 Predicted increases in mean surface temperature 56

Figure 29 Key anticipated risks per region 57

Figure 30 Equilibrium in a single competitive market 65

Figure 31 A Pareto-efficient level of output in a single competitive market 67

Figure 32 Greenhouse gas emissions: A negative production externality problem 70

Figure 33 Payoff matrix of a two-player game with a dominant strategy equilibrium 73

Figure 34 Payoff matrix of a two-player game with two Nash equilibria 74

Figure 35 Reducing greenhouse gas emissions in a world composed of two countries 75

Figure 36 Overview of implemented or scheduled carbon pricing policy instruments 88

Figure 37 Carbon dioxide emissions per unit of GDP 89

Figure 38 Share of renewable energies in Germany’s energy market 93

Figure 39 Number of large-scale carbon capture and storage pilot projects per year 94

Figure 40 Direct industrial air capture system 94

Figure 41 Potential climate change damage share in relation to population share by region in 2050 (per cent) 96

Figure 42 The Local Adaptation Plans for Action framework 100

Figure 43 Estimated climate financing in 2014 104

Figure 44 Kenya’s carbon dioxide abatement potential by sector 106

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LIST OF BOXES

Box 1 The Paris Agreement 2

Box 2 Patterns of world trade in natural resources 8

Box 3 Interactions among environmental services: The Ganga River case 10

Box 4 Kaya decomposition: Providing additional insights 13

Box 5 The ecocide of the Mayan society 16

Box 6 Trade in environmental goods and services 18

Box 7 A decomposition of scale, composition and technique effects 23

Box 8 Selected empirical evidence on the impact of trade on deforestation and water use 26

Box 9 The IPCC’s terminology to report findings to the public 34

Box 10 Extreme events 41

Box 11 The El Niño-Southern Oscillation – an example of an internal interaction among components 42 of the climate system affecting the means and variability of different climate variables

Box 12 Equilibrium in a single competitive market 65

Box 13 A Pareto-efficient level of production in a single market 66

Box 14 Different collective action outcomes for identical collective action problems 77

Box 15 The results of the Swedish carbon tax 89

Box 16 Carbon leakage, competitiveness, and carbon border tax adjustments 90

Box 17 Germany’s Energiewende policy 93

Box 18 Cyclone shelters and early warning systems in Bangladesh 98

Box 19 The camellones project in Bolivia 98

Box 20 Nepal’s National Framework on Local Adaptation Plans for Action 100

Box 21 Kenya’s Nationally Determined Contribution objectives and approaches 105

LIST OF TABLES

Table 1 World population, affluence and technology, 2014 12

Table 2 Trade-induced scale, composition and technique effects 25

Table 3 Selected empirical results on trade and air pollution 35

Table 4 Changes in the probability of occurrence of extreme events 53

Table 5 Reducing greenhouse gas emissions in a world of n countries 76

Table 6 Factors affecting outcomes of collective actions 77

Table 7 Selected policy options to stabilize concentrations of carbon dioxide in the atmosphere 86

Table 8 Comparison of policy options limiting climate change 95

Table 9 Categories and examples of adaptation options discussed in the fifth IPCC assessment report 97

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LIST OF ABBREVIATIONS

DEGREES IN CELSIUSAD HOC WORKING GROUP ON THE DURBAN PLATFORM FOR ENHANCED ACTIONASIA PACIFIC ECONOMIC COOPERATIONARGONFOURTH IPCC ASSESSMENT REPORT FIFTH IPCC ASSESSMENT REPORT BORDER ADJUSTMENTGLUCOSECAP AND TRADECLOUD CONDENSATION NUCLEICARBON CAPTURE AND STORAGECHLOROFLUOROCARBONCARBON MONOXIDECARBON DIOXIDECARBON DIOXIDE EQUIVALENTUNITED NATIONS CLIMATE CHANGE CONFERENCE OF THE PARTIES IN KYOTOUNITED NATIONS CLIMATE CHANGE CONFERENCE OF THE PARTIES IN BALIUNITED NATIONS CLIMATE CHANGE CONFERENCE OF THE PARTIES IN COPENHAGENUNITED NATIONS CLIMATE CHANGE CONFERENCE OF THE PARTIES IN CANCÚNUNITED NATIONS CLIMATE CHANGE CONFERENCE OF THE PARTIES IN DURBANUNITED NATIONS CLIMATE CHANGE CONFERENCE OF THE PARTIES IN BALIUNITED NATIONS CLIMATE CHANGE CONFERENCE OF THE PARTIES IN PARISMETHANEEMISSIONS DATABASE FOR GLOBAL ATMOSPHERIC RESEARCHENVIRONMENTAL GOODS AND SERVICESECONOMIES IN TRANSITIONEXTERNAL MARGINAL COSTSEL NIÑO-SOUTHERN OSCILLATIONEFFECTIVE RADIATIVE FORCINGENERGY SECTOR CARBON INTENSITY INDEXEMISSION TRADING SYSTEMGROSS DOMESTIC PRODUCTGREENHOUSE GASGIGATONNES OF CARBON DIOXIDEGIGAWATTWATERHARMONIZED COMMODITY DESCRIPTION AND CODING SYSTEMINTERNATIONAL ENERGY AGENCYICE NUCLEIINTENDED NATIONALLY DETERMINED CONTRIBUTIONSENVIRONMENTAL IMPACT, POPULATION, AFFLUENCE, AND TECHNOLOGYINTERGOVERNMENTAL PANEL ON CLIMATE CHANGETHOUSANDS OF YEARSLOCAL ADAPTATION PLANS FOR ACTIONMEGATONNENITROGENNITROUS OXIDENATIONAL ADAPTATION PROGRAMME OF ACTIONNATIONALLY DETERMINED CONTRIBUTIONSNITROGEN OXIDESOXYGENOZONEORGANIC AEROSOLSORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENTPRIVATE MARGINAL BENEFITSPRIVATE MARGINAL COSTSPRIMARY ORGANIC AEROSOLSPARTS PER BILLION PARTS PER MILLIONPURCHASING POWER PARITYRESEARCH AND DEVELOPMENT

°CADP

APEC AR

AR4AR5

BAC6H12O6

CATCCNCCSCFCCO

CO2 CO2-EQ

COP3COP 13COP15COP16COP17COP18COP21

CH4

EDGAREGSEIT

EMCENSO

ERFESCII

ETSGDP GHG

GTCO2

GWH2O

HSIEAIN

INDCIPAT IPCC

KALAPA

MTN2

N2ONAPANDCS

NOXO2

O3

OAOECD

PMBPMCPOAPPB

PPMPPP

R&D

ix

RCPRF

SARSMBSMC

SOSO2

SOASOI SSTTAR

TPESTOAUN

UNCEDUNCTADUNDESAUNFCCC

UVVDC

WCED WM-2

WMGHGWTO

RREPRESENTATIVE CONCENTRATION PATHWAYRADIATIVE FORCINGSECOND IPCC ASSESSMENT REPORT SOCIAL MARGINAL BENEFITSSOCIAL MARGINAL COSTSSOUTHERN OSCILLATIONSULPHUR DIOXIDE SECONDARY ORGANIC AEROSOLSSOUTHERN OSCILLATION INDEXSEA SURFACE TEMPERATURETHIRD IPCC ASSESSMENT REPORTTOTAL PRIMARY ENERGY SUPPLYTOP OF THE ATMOSPHEREUNITED NATIONSUNITED NATIONS CONFERENCE ON ENVIRONMENT AND DEVELOPMENTUNITED NATIONS CONFERENCE ON TRADE AND DEVELOPMENTUNITED NATIONS DEPARTMENT OF ECONOMIC AND SOCIAL AFFAIRS POPULATION DIVISIONUNITED NATIONS FRAMEWORK CONVENTION ON CLIMATE CHANGEULTRAVIOLETVILLAGE DEVELOPMENT COMMITTEESWORLD COMMISSION ON ENVIRONMENT AND DEVELOPMENTWATTS PER SQUARE METER WELL-MIXED GREENHOUSE GASESWORLD TRADE ORGANIZATION

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Climate change is the biggest global environ-mental challenge of the 21st century. Changes in the climate system that are having a signifi-cant impact on the environment and on human beings can already be seen today. Since the 1950s, our atmosphere and oceans have been warming, sea levels have been rising, and the amounts of snow and ice have diminished on a global scale (IPCC, 2014).1 Today, human influence on the cli-mate system is a scientifically confirmed fact: ac-cording to the Fifth Assessment Report of the In-tergovernmental Panel on Climate Change (IPCC), human activity is extremely likely to have been the dominant cause of this global warming. If hu-manity continues to emit substantial quantities of greenhouse gases (GHG), additional warming and other long-term changes are likely to occur. IPCC (2014: 64) estimates that these changes will increase the “likelihood of severe, pervasive and irreversible impacts for people, species and ecosystems” and would lead to “mostly negative impacts for biodiversity, ecosystem services and economic development and amplify risks for live-lihoods and for food and human security.” Moreo-ver, the IPCC estimates that these risks are gene-rally greater for people and communities that are socially, economically or otherwise marginalized.

However, there is still scope for action. Human-kind can limit climate risks through a substantial and sustained reduction of GHG emissions over the next few decades (IPCC, 2014). Sustainable Development Goal 13 of the United Nations 2030 Agenda for Sustainable Development calls for urgent action to combat climate change and its impact. This drive to structurally transform

INTRODUCTION

our carbon-based economy into a low-carbon economy is now widely acknowledged by poli-cymakers. At the 21st Session of the United Na-tions Framework Convention on Climate Change (UNFCCC) in December 2015, the international community adopted the Paris Agreement (see Box 1), which uniformly acknowledged the impor-tance of climate change mitigation and adapta-tion actions to tackle this global challenge, and recognized the need “to strengthen the global response to the threat of climate change, in the context of sustainable development and efforts to eradicate poverty” (Paris Agreement, Article 2, §1). Unlike previous international agreements on climate change, the Paris Agreement calls upon developed and developing countries to curb emis-sions while respecting the principle of common but differentiated responsibilities. The 196 parti-cipating parties (195 countries plus the European Union) agreed on an ambitious goal to limit glo-bal warming to “well below 2°C above pre-indus-trial levels and pursuing efforts to limit the tem-perature increase to 1.5°C above pre-industrial levels” (Paris Agreement, Article 2, §1a). Limiting global warming to at most 2°C above pre-indus-trial levels would, according to IPCC (2014), lead to only moderate risks of global aggregate effects on biodiversity and humans. To achieve this ob-jective, our carbon-based economy needs to be radically transformed into an economy based on low-carbon power sources. Such structural trans-formation would in turn reduce human-induced carbon dioxide (CO2) emissions and thereby help reduce global warming. It could also unleash new opportunities for sustainable growth and deve-lopment, and in turn reduce poverty.

1 The IPCC, founded in 1988 by the World Meteorologi-cal Organization and the United Nations Environ-ment Programme, is the international entity that is assessing the science related to climate change. The panel is composed of hundreds of leading scientists who review the work of thousands of scientists. The IPCC regularly provides policymakers with assessment reports of climate change, observed and anticipated effects, and mitigation and adaptation options.

TheParisAgreementBox 1

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The Paris Agreement1 is the outcome of the 21st Session of the UNFCCC held in December 2015 in Paris which brings all its 196 parties under a common, legally binding framework. The agreement is open for signature and ratification at the UN Headquarters in New York from 22 April 2016 to 27 April 2017 and will take effect in 2020.

The Paris Agreement requires any country that ratifies it to act to reduce its GHG emissions in the coming century, with the goal of peaking global GHG emissions as soon as possible and continuing the reductions as the century progresses. Ratifying parties will aim to keep global temperatures from rising more than 2°C by 2100 with an ideal target of keeping the temperature rise below 1.5°C (Article 2, §1a). Ratifying parties will have to submit what are called Nationally Determined Contributions (NDCs), i.e. national commitments to reduce greenhouse gases. By the end of 2015, 188 NDCs had already been submitted. The agreement provides a mechanism that aims to increase the ambition of NDCs over time: it requires all countries to deliver, every five years, a new NDC (Articles 3, 4, 7, 9, 10, 11, and 13). Each new NDC should represent a “progression” over the prior one, and should reflect the country’s “highest possible ambition” (Article 4.3). This process is cru-cial, because current NDCs are not strong enough to limit warming to below 2°C. Moreover, the agreement states that countries will “engage in adaptation planning processes” (Article 9) to ensure that they are ready for the effects of climate change. To finance mitigation and adaptation efforts, the agreement places a legal obligation on developed countries to provide financial resources (Article 9.1) and invites wealthier developing countries to contribute as well. The overall implementation of the agreement will be assessed every five years, starting in 2023 (Articles 14.1 and 14. 2).

Unlike past climate change policy frameworks, which had limited scope and ambitious goals, the Paris regime is based on broad participation and relatively limited ambition at the initial stage. This change from limited to broad participation is important given the global nature of the climate change problem. The broad partici-pation, together with the new architecture of the agreement that combines bottom-up NDCs with top-down procedures for reporting and synthesis of NDCs by the UNFCCC Secretariat, represents significant progress towards an effective climate policy solution.

Source: Author.1 The text of the Paris Agreement is available at http://unfccc.int/paris_agreement/items/9485.php.

This teaching material focuses on the ways and means to address our century’s biggest global environmental, economic and social, challenge: the structural transformation of our current car-bon-based economy into a low-carbon economy. It provides readers with the necessary tools to analyse this challenge and assist them in devi-sing appropriate solutions.

Module 1 offers a general introduction to the to-pic by highlighting the linkages between the eco-nomy and the environment. The module shows that the environment provides several services to the economy and demonstrates that the eco-nomic and environmental systems are connected and interdependent. It then explains that human use of the environment’s services can lead to en-vironmental impacts such as climate change, and discusses factors determining the size of these impacts. Finally it underlines the importance of sustainable economic systems and concludes by discussing the role of trade as an enabler of sus-tainable development and poverty reduction.

Module 2 focuses specifically on the climate and climate change by familiarizing the reader with the climate science behind climate change. The

module discusses the different components of the climate system and shows that they are all influenced by the planet’s energy balance. It then explains that climate change can occur due to factors that are either internal or external to the climate system. External factors such as human activities can affect the climate by influencing climate change drivers such as atmospheric GHG concentrations, which in turn change the energy balance of the planet and thus affect climate. After reviewing different ways in which econo-mic activities affect climate, the module presents the observed changes in the climate system and discusses the impact those changes have had on human and natural systems. It then outlines cli-mate changes that are expected to occur in the future as well as their potential impact.

Following Module 1 and 2, which have covered the general links between the economy and the environment and explained how human beings can effect climate change, Module 3 introduces readers to the economics of climate change. The module demonstrates that climate change is arguably the biggest market failure in human history. It explains that the atmosphere is an open-access resource and that GHG emissions

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are negative externalities. Firms and households produce GHG emissions as an unwanted by-pro-duct of their economic activities, without having to pay the cost of related pollution. Instead, they dump those gases free of charge into the atmos-phere, thereby contributing to climate change, and thus, indirectly, imposing costs on present and future generations. The module concludes by highlighting that the reduction of emissions is a global public good, which generates incen-tives for nations to free-ride and avoid reducing their own emissions, and makes implementation of effective solutions to climate change a difficult task.

Module 3 showed that climate change is the result of a large market failure that can only be corrected by policy interventions at the global level. Over the past 25 years, the international community has not found a convincing solution to this market failure, and global greenhouse

gas emissions have continued to increase. Ne-vertheless, at the 2015 United Nations Climate Change Conference (COP21) in Paris, the interna-tional climate change policy framework took a new and promising direction. Module 4 provides an in-depth analysis of climate change policies and the international politics of climate change. It discusses the different policy instruments and technological solutions that could enable us to limit climate change and transform economies into low-carbon economies. It explains that, in parallel with policies aimed at limiting climate change, a society also needs to undertake actions to adapt human and natural systems so that they are better prepared for the anticipated impacts of climate change. The module then reviews key international climate change policy develop-ments and discusses several issues surrounding the Paris Agreement, with a particular focus on the situation of developing countries.

Module 1The environment,

the economy and trade: The importance of

sustainable development

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The environment, the economy and trade: The importance of sustainable development1

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1 Introduction

Climate change is the most important global en-vironmental challenge of our century. In order to analyse climate change and climate change-re-lated policies from an economist’s point of view, readers need to be equipped with some general conceptual tools. These tools, briefly introduced in this module, allow them to (a) understand that human beings affect the climate because the economy and the environment are related and interdependent; (b) identify the factors that determine the size of the impact an economy has on the environment; (c) describe what can hap-pen if this impact becomes too severe, (d) under-stand the fundamental importance of the com-prehensive concept of sustainable development in today’s context of climate change; (e) analyse why many see trade as an important enabler of sustainable development; and (f) assess the over-all impact of trade on the environment.

Section 2 investigates the general relationship between the economy and the environment and the ways in which they interact. The environment provides four key services to the economy: it serves as a natural resource base, provides life support services, provides amenity services, and acts as the economy’s waste sink. In turn, the economy affects the environment through these four key services. This section shows that climate change is the result of the negative impact caused by the economy’s use of the environment’s resource and waste services. It then explains the factors that influence the overall size of an economy’s impact on the environment using a simple model and applying it to the emissions of CO2, a particularly important greenhouse gas that will be discussed extensively in the remainder of this teaching ma-terial.

Having examined how the economy affects the environment and which factors determine the overall size of this impact, Section 3 starts by ask-ing what could happen if the size of this impact were to become too large. It shows that some societies collapsed in the past because of their excessively negative impact on the environment: this illustrates that economic systems need to be sustainable. Consequently, the section highlights the importance of sustainable development in today’s world.

While trade is currently viewed by many as an important enabler of sustainable development, various concerns have been voiced in recent decades with regard to the effects of trade on the environment. Section 4 therefore attempts

to provide answers to the question of whether international trade harms or benefits the en-vironment. After taking a first glance at data, it introduces the reader to a comprehensive theo-retical framework that allows for assessing dif-ferent channels through which trade affects the environment. These theoretical tools are then ap-plied to review recent empirical evidence on the impact of trade on CO2 emissions.

At the end of this module, readers should be able to:

• Describe why economic activities can affect the climate by discussing the general linkages between the economy and the environment and understanding why and how the two sys-tems are considered to be interdependent;

• Use a simple model to analyse the effects of changes in population, affluence and technol-ogy on the size of an environmental impact such as GHG emissions;

• Understand the potential consequences of unsustainable human behaviour that ignores environmental constraints by referring to ex-amples of collapses of past societies;

• Describe the fundamental importance of sus-tainable development for humankind and as-sess the role of trade as a key enabler of sus-tainable development;

• Identify the main effects that trade has on the environment;

• Analyse important empirical contributions on the impact of trade on emissions;

• Assess the role of trade in the transfer of green technologies by discussing the role of environmental goods and services in the world economy.

To support the learning process, readers will find several exercises and discussion questions in Sec-tion 5 covering the issues introduced in Module 1. Useful data sources and additional reading ma-terial can be found in Annexes 1 and 2.

2 Theeconomyandtheenvironment: Unravellingthelinks

The economy and the environment are intercon-nected and interdependent systems, and both have an impact on economic and social devel-opment. Economic activities can therefore have an impact on the environment and vice versa. This section explains how the environmental system influences the economy, how economic activities affect the environment, and what fac-tors determine the size of the economy’s envi-ronmental impact.2

2 The structure of this section was partially inspired by Chapter 2 of Perman et al. (2011) and Chapters 4 and 7 of Common and Stagl (2004).


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2.1 Linksbetweentheeconomy andtheenvironment

As shown in Figure 1, the economic system and the environmental system are closely related and influence one another.3

Theeconomyandtheenvironment:TwointerdependentsystemsFigure 1

Source: Author's elaboration based on Common and Stagl (2004: 112).Note: G&S: goods and services; L: labour; K: capital; I: investments; R: natural resources.

Rest of the universe

Environmentalsystemboundary

Economic systemboundary

Energy

ResourcesAmenities

Recycling

Life support

Capital Stock

Production by firms

Consumption by households

Waste sink

LR

K I

G&S

It is fundamental to understand that the eco-nomic system is a part, or sub-system, of the en-vironmental system (in simple terms, the earth and its atmosphere). This can be seen graphi-cally in Figure 1, as the boundary of the economic system lies entirely within the environmental system’s boundary. The environmental system, with the economic system inside, is in turn part of a larger system – the rest of the universe, with which it exchanges energy.4

Within the economic system, one finds house-holds that buy and consume goods and services (G&S) produced by firms, and that provide la-bour (L) to firms. Firms use labour (L) provided by households, capital (K) from the capital stock, and natural resources provided by the environmental system (R) as inputs to produce goods and ser-vices. They sell a part of the goods and services they produce to households and other firms, and invest (I) the other portion in the capital stock. Firms and households both produce waste that is partially recycled and reused by firms and par-tially discharged into the environment.

The environmental system, which consists of planet earth and its atmosphere, provides servic-es to the economy. Common and Stagl (2004) de-fine four classes of environmental services, each of them represented by a green box in Figure 1. In particular, the environment provides natural

resources, amenity services, and life support ser-vices to the economy, and acts as the economy’s waste sink. At the same time, the economy af-fects the environment by using these services. Each of the services is analysed in a greater detail in the sections that follow.

2.1.1 Providing natural resources to the economy

Firms extract natural resources from the environ-mental system and use them as inputs in their production processes. Natural resources can be classified according to a common classification system used in recent textbooks on natural re-source economics or ecological economics (Com-mon and Stagl, 2004; Perman et al., 2011). This classification system is based on the two ques-tions presented in Figure 2.

The first question is whether the current use of a resource influences the future availability of that resource. If the current use of the resource reduces its availability in the future, the resource is called a stock resource. For instance, the future availability of animal species, healthy soil, fossil fuels, or minerals is affected by the current use of them. If firms extract coal, they will reduce the remaining quantity of coal available for future usage. Firms can thus affect the environment by extracting stock resources and thereby changing their future availability. If the current use of the

3 When using the terms “eco-nomic system” or “economy” in this section, we are always referring to the world eco-nomic system or the world economy.

4 The environmental system receives energy inputs from the rest of the universe (in the form of solar radiation emitted by our sun) and emits energy outputs to the rest of the universe (as thermal radiation). Refer to Module 2 for a detailed discussion.

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resource does not affect the quantity of the re-source available for future use, that resource is called a flow resource. Typical examples of flow resources are wind or solar radiation. No matter how much solar radiation firms use today, or no matter how many wind turbines the economy deploys today, there is strictly no impact on the quantity of solar radiation or wind that will be

available tomorrow. The distinction between flow and stock resources is fundamental – stock resources can be completely depleted by the economic system, while flow resources cannot. As we will see in Section 3, completely depleting stock resources like healthy soils or forests can have devastating effects on the economic system.

ClassificationofnaturalresourcesFigure 2

Does the current useof a resource affect

future availability of that resource?

Flowresource

Stockresource

Does the resource

regenerate itself?

Non-renewable stock resource

Renewable stock resourceYes Yes

No No

Source: Author's elaboration based on the classification in Common and Stagl (2004) and Perman et al. (2011).

When it comes to stock resources, there is a second question to ask: does the stock resource regener-ate itself? If it does, the stock resource is called a renewable resource. If it does not, it is called a non-renewable resource. Fossil fuels are examples of non-renewable resources. No oil will be available for further use once the economic system has de-

pleted all current oil reserves.5 Animal species like fish are examples of renewable resources. Fish do reproduce at a certain rate, which is often called a natural growth rate. Consequently, as long as the amount of fish the economy extracts (the fish harvest rate) is equal to the fish natural growth rate, the fish stock remains stable over time.

PatternsofworldtradeinnaturalresourcesBox 2

From a trade statistics perspective, natural resources are difficult to define precisely. The World Trade Organi-zation (WTO, 2010: 46) defines natural resources as “stocks of materials that exist in the natural environment that are both scarce and economically useful in production or consumption, either in their raw state or after a minimal amount of processing.” Based on this definition, WTO (2010) classifies fish, forestry products, fuels, ores and others minerals, and non-ferrous metals as natural resources.

Worldtrade,exportsandimportsbybroadcategoryFigure 3

Agriculture Natural Resources Manufacturing0

10

5

15World trade by broad category

trill

ions

of U

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llars

Agriculture Natural Resources ManufacturingImportsExportsImportsExportsImportsExports

0

10

5

15Export and import values by broad category (2014)

trill

ions

of U

S do

llars

Agriculture Natural Resources Manufacturing0

10

5

15World trade by broad category

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ions

of U

S do

llars

Agriculture Natural Resources ManufacturingImportsExportsImportsExportsImportsExports

0

10

5

15Export and import values by broad category (2014)

trill

ions

of U

S do

llars

Source: UNCTAD (2015: 17–18).Note: BRICS: Brazil, Russia, India, People's Republic of China and South Africa; LDCs: least developed countries.

5 Note that this is not entirely correct. While the natural growth rate of oil stocks is indeed zero if we consider human time scales (e.g. years, decades, centuries), there are positive growth rates for lon-ger time horizons (millions of years).

200420112014

Developed countriesDeveloping countries

BRICSLDCs


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PatternsofworldtradeinnaturalresourcesBox 2

Natural resources are unevenly distributed over the planet’s surface. Several resources are highly concen-trated in specific geographic areas. Trade in natural resources is thus unsurprisingly substantial. The share of natural resources in world merchandise trade rose from 11.5 per cent in 1998 to 23.8 per cent in 2008 (WTO, 2010). While manufacturing remained by far the largest broad category of goods traded in 2014, with a share of almost 70 per cent, natural resources were the second largest. In addition, unlike developed countries, de-veloping countries export more natural resources than they import (see Figure 3). Moreover, natural resources still represent a large share of developing countries’ exports, particularly in energy-exporting countries in the Middle East and primary commodity-exporting countries in Africa (UNCTAD, 2015).

Source: Author's elaboration based on UNCTAD (2015) and WTO (2010).

2.1.2 Providing life support services

The second class of environmental services iden-tified by Common and Stagl (2004) are life sup-port services, i.e. basic conditions that enable hu-man life. These conditions include, for instance, liveable temperatures, gravity levels, oxygen levels, etc. Without these services, no human life could exist on earth.

2.1.3 Providing amenity services

The environmental system provides amenity services to households. Such services are diverse: the joy of taking a walk in a forest, or the pleas-ure of swimming in a lake are just two examples. These amenity services often do not need any transformation and can be directly consumed by households. Moreover, consuming environmental amenity services does often not have an impact on the future availability of these services. Enjoy-ing flora and fauna by looking at it does not reduce its future quantity or quality. There are however exceptions. Mass tourism or illegal harvesting of endangered species, for instance, can have a nega-tive impact on wildlife and thus affect the envi-ronmental system if organized unsustainably.

2.1.4 Serving as the economy’s waste sink

The environmental system acts as the economy’s waste sink. Households and firms create waste, an unwanted by-product of economic activity. Waste is understood as a rather broad category contain-ing such items as chemical, paper, plastic and metal waste from consumers, organic food waste, CO2 emissions, smoke from burning biomass, etc. It is important to understand that waste dis-charges into the environment are direct and nec-essary consequences of the extraction and use of resources from the environment. In physics, the law of conservation of mass explains this phe-nomenon. Economists often refer to it using the term “material balance principle,” which states that matter can neither be created nor destroyed. Economic activity can thus only transform inputs into outputs but can never create or destroy mat-

ter. Consequently, all extracted material will have to return to the environment in some form and at some point in time. One can therefore look at the waste sink function as a type of complement of the resource extraction function.

Waste can be partially recycled and subsequently reused as an input in the production process (see Figure 1). Unrecyclable or unrecycled waste discharged in the environment may accumulate as a stock. Environmental processes may subse-quently reduce the waste stock. Whether or not the particular stock is increasing depends on the type of waste, the rate of discharge, and the en-vironment’s capacity to reduce the waste stock. Take, for instance, plastic waste discharged into oceans. The stock of this particular type of waste is growing fast because the world economy’s rate of discharge is high and the environment’s ca-pacity to biochemically transform plastic – and thereby reduce the plastic stock – is low.

Waste is often not harmful to the environment, but in some cases it induces chemical or physical changes that can harm living organisms. This is another example of how the economy affects the environment by using one of the four environ-mental services. There are a variety of relation-ships between the quantity of waste and result-ing environmental damage. Sometimes, waste discharged into the environment has no damag-ing impact until a certain threshold is reached. Sometimes damage increases gradually with the quantity of waste discharged. Take, for instance, CO2 emissions. CO2 itself is not a priori harmful to living organisms. After all, humans and other animal species produce CO2 by breathing, and plants consume it in their respiration and photo-synthesis processes. However, although CO2 does not have direct effects on biological systems, it does have a direct physical impact on the earth’s atmosphere. When emitted in large quantities, CO2 triggers a greenhouse effect (a phenomenon that will be discussed in detail in Module 2) that contributes to changing the climate of the planet and poses a threat to a wide range of living or-ganisms, including humans.

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2.1.5 Interaction among environmental services: Fossil fuel extraction, CO2 emissions, and climate change

The sections above discussed the links between the economic and environmental systems sepa-rately for the four classes of environmental ser-vices. In reality, however, in addition to interact-ing with the economic system, these services also interact among themselves, which makes the overall picture even more complicated. Let us take a first glance at climate change, which is a good example of such multiple interactions.6 Currently, our economic system relies heavily on energy from fossil fuels. Firms extract fossil fuels like coal, petroleum or natural gas from the en-vironment. These resources are then consumed and, as a by-product, emissions of CO2, a major greenhouse gas, are released into the atmos-phere where they accumulate. This is an illustra-tion of a typical interaction between the environ-ment’s resource service (firms extract fossil fuels) and its waste sink service (firms emit CO2 from fossil fuel combustion into the atmosphere). The increased concentration of CO2 in the atmos-

phere then leads to the so-called greenhouse ef-fect, and thus to climate change.

Climate change in turn affects the four environ-mental services in numerous ways. It can induce an increase in extreme weather events like se-vere droughts, which can, for instance, reduce the availability of healthy soils. It can also cause changes in temperature and precipitation, alter-ing life support services and thus causing losses of biodiversity and instability of ecosystems. Amenity services can be affected by the retreat of glaciers, shortened ski seasons, and unusual heat waves during the summer. And the waste sink function of rivers can be altered by changes in the assimilative capacity of rivers due to the rise in temperatures. This illustrative list of potential in-teractions could be extended almost indefinitely given the wide range of effects predicted by the IPCC (2014). Finally, it is important to note that all these changes in turn affect economic activities, for example by slowing economic growth, lower-ing agricultural productivity, reducing tourism activity, decreasing food security, and making it more difficult to reduce poverty.7

6 A second example of interactions among environ-mental services is provided in Box 3.

7 Refer to Module 2 for a detailed discussion.

Interactionsamongenvironmentalservices:TheGangaRivercase

Shortsummary

Box 3

An illustrative example of interacting environmental services is provided by the pollution of the Ganga River in India. For centuries, the Ganga River has served as a major resource base for India’s population by providing fish, water, trade routes, etc. The Ganga basin also provides important amenity services, such as the Hindus’ use of the river for mass bathing and ritual ceremonies that include cremation of dead bodies. Moreover, the Ganga basin also increasingly serves as a major waste sink for domestic and industrial waste. Over 1.3 billion litres of sewage per day and an estimated 260 million litres of largely untreated industrial wastewater pass directly into the river (Behera et al., 2013). At the same time, the Ganga ecosystem plays an important part in providing various life support services for numerous animal species, including endangered ones like the Ganga River dolphin. The Ganga ecosystem has thus been under considerable pressure due to the inflow of household and industrial waste, intensive water and fish extraction, and the religious usage of the river that regularly floods it with remains of the dead. These complex interactions of the Ganga’s waste sink, resource extraction, and amenity service functions has led over recent decades to severe levels of pollution that not only threaten different resource stocks (e.g. water quality) but also the possibility of benefitting from amen-ity services (e.g. health risks associated with taking a bath in the river). Moreover, current pollution levels have an impact on the life support function of the river and threaten the existence of entire species like the Ganga River dolphin (Behera et al., 2013). Awareness of the problem has been increasing over recent decades. Since 1985, several policy initiatives have been put forward, and in 2011 the World Bank decided to support the Indian National Ganga River Basin Authority with a US$1 billion project called the National Ganga River Basin Project.Source: Author's elaboration based on Behera et al. (2013).

Section 2.1 shed some light at the complex interrelationship between the economic and environmental sys-tems, which in turn has an impact on economic and social development. Readers learned that the environ-mental system provides four key services to the economy, and that the economy has an impact on the envi-ronment by using these services. A first glance at climate change showed that this phenomenon is the result of such impacts. The example of climate change also showed how these services can affect one another and lead to severe cases of environmental damage, in turn affecting economic activities.


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8 Note that an identity is an equation that is always true by definition (see footnote 11).

9 See Chertow (2000) for an overview on the history of the IPAT identity.

10 Depending on the appli-cation, there are a variety of sets of units that can be used with the IPAT identity. Accor-ding to Common and Stagl (2004), I can be measured in tons or litres, depending on the particular impact one attempts to analyse. P is always measured in numbers of people. A is measured as the total economic output in currency units (often gross domestic product – GDP - in US dollars) divided by the number of people. T is mea-sured as units of impact (for instance tons or litres) per US dollar of GDP.

2.2Environmentalimpactofeconomic activities

Section 2.1 showed that the economy affects the environment by using the four environmental ser-vices, and illustrated this mechanism using the ex-ample of climate change. However, we have not yet addressed the important related question of tim-ing. Why is climate change the biggest environmen-tal problem of the 21st century rather than having been the biggest problem during the 19th or 20th centuries? Which factors explain why today’s GHG emissions are at levels that start to threaten the climate system of the entire planet? Or, put more generally, which factors explain the magnitude of the environmental impact of economic activities?

Assessing the role of factors that influence the magnitude of the environmental impact of eco-nomic activities is a challenging endeavour. It is therefore useful to rely on simplified models that allow us to identify the main factors that influ-ence the magnitude of such an impact. These models can also be used to simulate future im-pact and thereby provide useful information about potential future scenarios. The following two sections discuss two of these models and ap-ply them to the analysis of the size of one particu-lar impact of economic activity: CO2 emissions.

2.2.1 Unravelling the role of main drivers of environmental impacts by using the IPAT identity8

A simple but very useful way to think about the size of any environmental impact is provided by the Environmental Impact, Population, Affluence and Technology (IPAT) identity. IPAT emerged dur-ing a debate on drivers of environmental impact between Paul R. Ehrlich, John Holdren, and Barry Commoner, three leading ecologists of the 1970s.9 The IPAT identity states that three factors jointly determine the size of any environmental impact (I): population (P), affluence (A), and technology (T). Intuitively this seems rather straightforward. All else being equal, the larger the population, the higher the average per capita consumption, and the more resources a production technology uses and/or the more waste a technology gener-ates, then the more one can expect an economy’s impact on the environment to be bigger.

Let us take a look at the climate change exam-ple discussed above. One generally expects that more fossil fuels are extracted and more CO2 emissions from fossil fuel combustion are emit-ted if more people live on the planet. This is rela-tively easy to understand, as more people means, for instance, increased demand for cars. As most of the cars run on energy from fossil fuels, this will increase CO2 emissions. At the same time, one expects that CO2 emissions will increase if these people are more affluent, i.e. they consume more per person. Higher per capita consumption implies, for instance, increased industrial pro-duction, which requires more energy and in turn increases CO2 emissions from fossil fuel combus-tion. Finally, CO2 emissions are expected to be higher the dirtier the production technology. Put differently, if production technology evolves and becomes cleaner, one would expect, all else be-ing equal, fewer CO2 emissions. If factories start to use machines that require less energy to do the same job, this should reduce CO2 emission levels.

IPAT allows us to visualize the relationship be-tween population, affluence, technology, and the magnitude of the environmental impact they can create. The general form of the IPAT identity captures the three main factors driving the size of environmental impact and can be written as:

where, as stated earlier, I stands for environmen-tal impact, P for population, A for affluence, and T for technology.10

The general IPAT identity can be applied to a va-riety of different environmental effects. Depend-ing on how I is defined, IPAT allows for analysing insertions into the environment (e.g. GHG emis-sions) and extractions from the environment (e.g. fish or coal extraction).

To illustrate how one can use the IPAT identity, we will continue to focus on one specific envi-ronmental impact – CO2 emissions – and apply the IPAT identity to global anthropogenic (i.e. hu-man-induced) CO2 emissions. The sources of data used in this analysis are detailed in Table 1.

I P* A* T,

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Worldpopulation,affluenceandtechnology,2014Table 1

Variable Variable description Year Value Source

P World population 2014 7,260,710,677 persons World Bank’s Data Catalog

A World GDP (PPP, constant 2011 international dollars) per capita 2014 14,287

international dollars/person World Bank’s Data Catalog

TWorld CO2 emissions1 per

world GDP (PPP, constant 2011 international dollars)

2014 0.00000034 kilotons/ international dollars

The Netherlands Environmental Assessment Agency (see Oliver

et al., 2015)

Source: Author.1 CO2 emissions include CO2 emissions generated by the use of fossil fuels and industrial processes but exclude CO2 emissions generated by short-cycle and large-scale biomass burning. Note: PPP: purchasing power parity. International dollar is a hypothetical unit of currency widely used in economics. By construction, it has the same purchasing power parity that the US dollar had in the United States at a given point in time (in this case, 2011).

Using the data for P, A, and T we can calculate the impact I as

I = 7,260,710,677 persons * 14,287

= 35,684,418.06 ktons,

* 0.000000344persons $

$ ktons

A TP

and find that the world economy emitted 35,684,418.06 kilotons of CO2 in 2014. At this point, it is important to note that IPAT is an accounting identity and thus holds by construction.11

Applying IPAT to a particular year allows us to understand how the identity works, but it is by far more interesting to apply the method over a longer time horizon. By doing so, one can analyse which of the three factors have contributed to increase or reduce emissions in the recent past. Figure 4 shows the change in anthropogenic CO2 emissions from the use of fossil fuels and indus-trial processes over the period of 1970-2013. CO2 emissions from fossil fuel use and industrial processes increased by roughly 125 per cent over the last four decades. Figure 4 also shows the de-composition of these emissions into factors that caused them, namely P, A and T. World population and world affluence have been increasing fast (by 97 per cent and 89 per cent, respectively) while technology has become cleaner (by 39 per cent).

Overall, Figure 4 reveals that the emission-reduc-ing effect of cleaner technology has not been able to offset the emission-generating effects of in-creased population and affluence. In other words, the sharp increase of CO2 emissions over recent decades has mainly been driven by population growth and increased affluence. Thus, to answer our initial question, climate change is the biggest environmental problem of the 21st and not the 19th or 20th century because of the joint evolution of population, affluence, and technology: world pop-ulation and affluence have been increasing rapidly and are currently at their highest levels in human history, while technology is still relatively dirty and cannot yet cancel out the emission-increasing ef-fects of population and affluence. Together, these three factors explain why CO2 emissions in the early 21st century have risen to such high levels, causing accumulations of CO2 in the atmosphere that threaten the climate of our planet.

IPAT can thus be very useful in identifying which factors contributed to increasing or reducing the overall size of the economy’s environmental impact. Box 4 shows a related decomposition us-ing the Kaya identity, which provides additional interesting insights into the drivers of past CO2 emissions. Section 2.2.2 will show that IPAT can be used not only to analyse the past, but also to glance at the future.

CO2–IPATdecompositionFigure 4

Source: Author's elaboration based on data on population and GDP at market prices (constant 2005 US dollars) from the World Bank’s Data Catalog, and on CO2 emissions data from The Netherlands Environmental Assessment Agency (Oliver et al., 2015).

1970 1980 1990 2010

5

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15

Year

1970=100I = CO2 emissions

P = Population

A = GDP/population

T = CO2/GDP

11 To see this, note that we calculated . The IPAT identity thus collapses to CO2=CO2, which by definition always holds.

T = GDPCO2

CO2=Population * PopulationGDP

A TI P

* GDPCO2


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Population

TPES/GDP

CO2 emissions

GDP/population

CO2 /TPES (ESCII)

Interactionsamongenvironmentalservices:TheGangaRivercaseBox 4

The IPAT identity discussed in this section has been extended by the Japanese economist Yoichi Kaya (1990) to provide additional insights in the context of CO2 emissions. This identity is frequently used to decompose CO2 emissions (Nakicenovic and Swart, 2000). The so-called Kaya identity can be expressed as follows:

where CO2 = anthropogenic CO2 emissions; P = population; A = GDP per capita; E = primary energy consump-tion; and GDP = gross domestic product.

The Kaya identity decomposes IPAT’s technology variable T into two parts: energy intensity of GDP (E/GDP) and carbon intensity of the energy mix (CO2/E). IEA/OECD (2015) use the Kaya identity and decompose CO2 emis-sions for two groups of countries: Annex I and non-Annex I countries of the UNFCC.1

Figure 5 displays the decompositions by country group. According to IEA/OECD (2015), the recent decline in emissions in Annex I countries was driven by a significant reduction in the energy intensity of GDP (TPES/GDP), and by a slight fall in the CO2 intensity of the energy mix (CO2/TPES). These two emission-reducing ef-fects have offset the emission-generating effects of the growth in GDP per capita and in population. In non-Annex I countries the growth in CO2 emissions was mainly driven by the increase in GDP per capita and to a lesser extent by the increase in population.

Kayadecomposition:AnnexIcountries(leftpanel)andnon-AnnexIcountries(rightpanel)Figure 5

CO2 = P * A * GDP

EE

CO2*

TT

1990 1995 2000 2005 2010 201360

70

110

100

90

120

80

140

1990=100

130

1990 1995 2000 2005 2010 201350

100

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1990=100

1990 1995 2000 2005 2010 201360

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140

1990=100

130

1990 1995 2000 2005 2010 201350

100

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150

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300

1990=100

Source: IEA/OECD (2015: xx)Note: TPES: total primary energy supply. ESCII: energy sector carbon intensity index.1 The UNFCCC divided countries in two broad groups – Annex I and non-Annex I countries – depending on their 1992 commit-ments to fight climate change. Annex I countries consist of countries that were members of the Organisation for Economic Co-operation and Development (OECD) in 1992 plus countries with economies in transition in 1992, such as the Russian Fed-eration. Non-Annex I countries are the remaining ones, mostly developing, countries that signed the convention (see Module 4 for more information about the different groups of countries and their commitments).

Source: Author’s elaboration based on IEA/OECD (2015) and Kaya (1990).

2.2.2 Assessing potential future scenarios of environmental impact using the IPAT equation

The previous section showed that population growth and increased affluence caused a sharp increase in CO2 emissions. This section uses IPAT to glance at the future and analyse the potential impact on emissions of expected future changes in population and affluence. The IPAT framework can help answer a number of questions: What could happen to total emissions if world popu-lation continues to increase? How could differ-ent GDP per capita growth scenarios affect total

emissions? What role do technological improve-ments play in moderating the effects of increased population and affluence on total emissions?

Let us start with population growth. According to 2015 world population projections from the United Nations Department of Economic and Social Affairs (UNDESA) Population Division (Fig-ure 6), world population, currently at 7.35 billion, is unlikely to stop growing this century. On the contrary, the UN estimates that there is an 80 per cent probability that world population in 2100 will be between 10.03 billion and 12.44 billion (with a median of 11.21 billion). How could this

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expected growth in population affect emissions? To address this question we assume that GDP per capita (A) and technology (T) stay at their 2014 levels, and we use the projected UN population data to simulate CO2 emissions using IPAT. Figure 7 displays observed annual CO2 emissions from

1970 to 2014 and then adds the three IPAT-based emission scenarios using the UN population projections. All other factors fixed, the predicted population growth could result in an increase of 38 to 72 per cent of annual CO2 emissions be-tween 2014 and the end of the century.

UnitedNations2015worldpopulationprojection

IPAT:TheimpactofprojectedpopulationgrowthonCO2emissions

Figure 6

Figure 7

1950 2000 21002050

2

4

6

8

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12

14

16To

tal p

opul

atio

n (b

illio

ns)

Year

Median

95 per cent

prediction interval

80 per cent

prediction interval

CO2, observed

CO2, median population

estimate

CO2, low population

estimate

CO2, high population

estimate

Source: Author's elaboration based on data from UNDESA (2015).Note: The 95 (80) per cent prediction interval means that the UN estimates a 95 (80) per cent probability that this situation will occur.

Source: Author's elaboration based on data from UNDESA (2015), World Bank (2016), and the Netherlands Environmental Assessment Agency (see Oliver et. al., 2015).

1971 2014 21002050

30

40

50

CO2

Year

60

20

A related question is how different GDP per capita growth paths might affect emissions if population and technology were to stay at their 2014 levels. To provide an answer we rely on the baseline long-term global growth projection for 2010–2060 published by the OECD (2014).12 We complement this projection (which predicts an average yearly GDP per capita growth rate of slightly below 2.5 per cent) with a low-growth

scenario (with a yearly growth rate of only 1 per cent) and a high-growth scenario (with a yearly growth rate of 4 per cent). Figure 8 shows ob-served CO2 emissions from 1971 to 2014, as well as those under the three GDP per capita growth rate scenarios. As we see, with fixed 2014 population and technology levels, the OECD GDP per capita projection would result in an increase of 200 per cent in CO2 emissions by 2060 with respect to

12 See Johansson et al. (2013) for the model underlying this projection.


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IPAT:TheimpactofprojectedGDPpercapitagrowthonCO2emissionsFigure 8

Source: Author's elaboration based on data from the OECD (2014), World Bank (2016), and the Netherlands Environmental Assessment Agency (Oliver et. al., 2015).

2014. The high-growth scenario would result in an increase of more than 500 per cent, while the

low-growth scenario would result in an increase of roughly 60 per cent.

1971 2014 2060

50

100

150

CO2

Year

200

0

CO2, observed

CO2, 4 per cent GDP

growth rate

CO2, OECD GDP

baseline projection

CO2, 1 per cent GDP

growth rate

The analysis in Figure 7 and Figure 8 revealed that the predicted growth of population and GDP per capita are both likely to increase CO2 emissions considerably over the next couple of decades. The impact of the combined effects of population growth and increased affluence on emissions will be even bigger. This raises the question of how humanity will be able to significantly re-duce CO2 emissions without limiting population or affluence growth. Technology, the third deter-minant of the size of the overall impact within the IPAT model, might be the answer. In the prior

analysis, we held technology fixed at the 2014 lev-el. However, as population and GDP per capita are both expected to increase significantly over the coming decades, technological improvements will have to play an important role if humanity intends to curb CO2 emissions and thereby sta-bilize CO2 concentrations in the atmosphere. To offset the effects of a growing and increasingly affluent population, it will therefore be crucial to rely on cleaner technology that can significantly reduce CO2 emissions per produced US dollar.

Shortsummary

In Section 2.2, readers learned how to use the simple IPAT model to analyse forces influencing the size of the environmental impact of an economy. Higher population levels and increased affluence generally increase the magnitude of the environmental impact, while technology improvements have the potential to decrease the size of that impact. The IPAT model was used to decompose a particular environmental impact, CO2 emis-sions, leading to a conclusion that the observed increase in CO2 emissions was due to an increase in popula-tion and affluence that was not offset by the effects of cleaner production technology. Subsequently, IPAT was used to glance at the future by establishing carbon dioxide scenarios based on various predictions of popula-tion growth and increased affluence.

3 Sustainabilityoftheeconomic system

The previous section showed how an economy affects the environment and discussed different factors that influence the magnitude of the world economy’s environmental impact. This section starts by investigating what could happen if the size of such an impact were to become too large. It shows that some societies in the past collapsed be-cause of their devastating impact on the environ-

ment. It thus illustrates why an economic system should be sustainable. In this context, it introduc-es the concept of sustainable development and shows why trade is currently viewed by many as an important enabler of sustainable development.

3.1 Ecocide:Lessonsfromhistory

As a subsystem of our environmental system, the economic system faces a variety of environmen-tal constraints that, if systematically disregarded,

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could potentially have devastating effects on hu-man societies.13 In 1798, economist Thomas Mal-thus published his famous book An Essay on the Principle of Population in which his central hy-pothesis was that population growth will eventu-ally outpace food production due to diminishing returns in agriculture. Malthus was convinced that the land’s capacity to produce food – an envi-ronmental constraint – could not keep up with hu-man reproduction rates. In his view, this would in-evitably lead to important food shortages, which in turn would significantly reduce human popu-lation and force those who remain to live at sub-sistence levels. Since the Industrial Revolution, we have known that Malthus’s predictions in terms of food production were wrong because innovations enabled increased food production to feed a grow-ing population. Nevertheless, this does not imply that environmental constraints have disappeared.

Economic systems that ignore environmental constraints face problems that might even lead to a collapse of the entire system. In his book Collapse: How Societies Choose to Fail or Survive, Jared Diamond (2006) analysed the role of envi-ronmental constraints in the collapse of past so-cieties like the Vikings, Greenland’s Norse society, Easter Island’s Polynesian society, North Ameri-ca’s Anasazi society, the Mayans, and others.

Diamond (2006: 3) defines collapse as “a drastic decrease in human population size and/or po-litical/economic/social complexity, over a con-siderable area, for an extended time.” According to him, unintended ecological suicide – ecocide – is a major explanatory factor for the rapid de-cline of several past societies. Diamond identi-fies a common pattern of the decline of these collapsed societies. The process started with the growth of population and the intensification of agricultural production (through improved technology and geographical expansion of ag-riculture to agriculturally marginal lands). Un-sustainable agricultural practices then led to a variety of environmental degradation processes (e.g. deforestation, water mismanagement, ero-sion, overhunting, etc.) that forced people to abandon the agriculturally marginal lands, with food shortages and starvation often resulting. People started wars over the remaining resourc-es and overthrew governing elites. Population levels declined and, in parallel, the complexity of the society in terms of economics, politics, and culture decreased. This led in some extreme cases to a complete collapse of the society, with the entire population dying or emigrating. Box 5 illustrates such a collapse using the example of the Mayan society.

13 Environmental constraints are limits imposed on humankind by the environ-ment. For instance, a river’s capacity to absorb toxic waste is limited, which is an environmental constraint that restricts the amount of toxic waste humans can discharge into the river without destroying it. If humans disregard this constraint systematically (e.g. by pumping large quantities of toxic waste into the river), the river’s ecosystem might be destroyed, which in turn might affect the humans and their economic activities. Another environmental constraint, which is very important in the context of climate change, is the limited capacity of the atmosphere to absorb greenhouse gases.

TheecocideoftheMayansocietyBox 5

The ecocide of the Mayan society is a particularly interesting example of a collapse discussed by Diamond (2006). The Maya were one of the culturally most advanced societies of their time in Central America. The classical age of Mayan society begun around the year 250. The Mayan population increased exponentially and reached its peak in the 8th century and then declined rapidly in the 9th century.

Why did the Mayan society collapse? Diamond explains the collapse using the example of the city of Copán studied by Webster et al. (2000). Copán was a small, densely populated city in today’s western Honduras. Fertile land was concentrated in the river valley surrounded by relatively unfertile steep hills. Starting in the 4th century, Copán’s population started to grow rapidly. According to Webster et al. (2000), agricultural production was intensified to satisfy increased demand due to population growth. By the mid-6th century, the productive capacity of the fertile valley land was exhausted and people started to cultivate on the steep hilly land around the valley. They cut down the forests on the hill slopes that had previously protected the hills from erosion. After some time, hill slopes eroded and the quality of soils deteriorated. Consequently, people had to move back into the valley. The infertile acidic hill soils started to spread into the valley and partially covered the fertile valley soils, further reducing the productive capacity of the land. Diamond argues that the deforestation may also have begun to cause a man-made drought in the valley because the water-cycling functions of the forests were reduced as more and more trees were cut down. During this period, the population continued to grow rapidly while the productive capacity of the land diminished equally rapidly. This led to fights over land and food that culminated in the destruction of the royal palace around the year 850. Population size dropped and after 1250, there were no more signs of humans living in the Copán valley.

According to Diamond, Copán’s collapse is a good example of the mechanisms behind the collapse of the entire Mayan society. Population growth outpaced available resources and led to deforestation and erosion, which further reduced the size of fertile lands and potentially triggered local man-made climate change that increased the risks of droughts. Fighting over scarce resources and an inability of the governing elite to ad-dress the problems finally ended in a total collapse of the Mayan society.

Sources: Author’s elaboration based on Diamond (2006) and Webster et al. (2000).


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Diamond (2006: 7) identified several processes through which past societies transgressed en-vironmental constraints and damaged the en-vironment up to the point that these societies collapsed. These processes include overuse of renewable stock resources (e.g. through defor-estation, overhunting, overfishing) and misuse of renewable stock resources (e.g. soil degradation, water mismanagement, adverse effects of intro-duced species on native species). These processes still play a major role today. Moreover, according to Diamond, new environmental problems have been added to the ones that threatened past so-cieties. Climate change is one of these new prob-lems and is arguably the most dangerous one for humanity in the 21st century. Humankind has been systematically ignoring the environment’s limited capacity to absorb greenhouse gases. This unsustainable behaviour is threatening the entire climate system of the earth and will have important consequences for humankind un-less sufficient actions are taken to reduce GHG emissions. With the adoption of United Nations Agenda 2030, the Paris Agreement at the 21st Conference of the Parties, and relevant outcomes of other international summits, the international community has reached agreement to collec-tively address the imminent and present danger of environmental and climate change through national and global actions in the next 15 to 30 years.

3.2 Sustainability

As Diamond (2006) showed, ignoring environ-mental constraints by engaging in unsustain-able economic behaviour at times resulted in the total collapse of entire societies. Cohen (2009) argues that the sustainability question today is even more important than ever. He advances the argument that past competition of different organizational forms of the economic system – some more efficient than others – has almost come to an end and resulted in today’s domi-nance of a single form of economic organization: the modern market economy. Thus, according to Cohen, it is the absence of a viable alternative to the modern market economy that makes the question of its sustainability crucial.

There are various definitions of sustainability that differ depending on the context.14 The Ox-ford English Dictionary states that “sustainabili-ty” is a derivative of the word “sustainable,” which is defined as “able to be maintained at a certain rate or level” or “able to be upheld or defended.” In ecology, the definition of sustainability focuses on the continued productivity and functioning of ecosystems and often involves requirements to

protect genetic resources and biological diversity (Brown et al., 1987). In environmental economics, sustainability is often defined with respect to the continued coexistence of the economic and envi-ronmental systems. We follow this strand of defi-nitions in this material. Common and Stagl (2004: 8) define sustainability as follows: “Sustainability is maintaining the capacity of the joint economy-environment system to continue to satisfy the needs and desires of humans for a long time into the future.” Processes that are threatening the joint economy-environment system in a way that current and future needs and desires of humans cannot be satisfied are thus by definition called unsustainable processes. Processes that do not threaten the joint economy-environment system are called sustainable processes.

3.3 Sustainabledevelopment: Theinternationalawakening

The importance of a sustainable world economy has long been neglected. This changed in 1987 with the publication of the World Commission on Environment and Development (WCED) re-port entitled Our Common Future (WCED, 1987). This report, now frequently called the Brundtland report (after the chair of the commission, Gro Harlem Brundtland), has become a milestone in terms of durably placing sustainability questions on the international policy agenda.

The Brundtland report outlined the complex interactions between the economic and envi-ronmental systems, stressed the importance of environmental constraints, and argued that the current path of economic growth cannot be continued. Acknowledging the need to eradicate poverty and raise per capita income worldwide, the report suggested an alternative pathway of economic growth that it called “sustainable de-velopment.” The report defined sustainable de-velopment as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs. It contains within it two key concepts: the concept of ‘needs,’ in particular the essential needs of the world’s poor, to which overriding priority should be given; and the idea of limitations imposed by the state of technology and social organization on the environment’s ability to meet present and future needs.” (WCED, 1987: 45)

Sustainable development is thus presented as the solution that would simultaneously (a) allow for meeting the needs of the present generation through continued economic growth, thereby raising standards of living worldwide, and (b) maintain the capacity of the joint economy-en-

14 For an overview of dif-ferent usages of the concept of sustainability, see Brown et al. (1987).

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TradeinenvironmentalgoodsandservicesBox 6

vironmental system to meet the needs of future generations. Sustainable development is thus seen as the tool to enable us to steer the world economy towards a sustainable path that serves both people (present and future generations) and the planet.

Since the publication of the Brundtland report, the definition of sustainable development has further evolved and is today considered to be a combination of three pillars: environmental protection, economic development, and social development. Following the 2012 United Nations Conference on Environment and Development (UNCED) conference in Rio de Janeiro, which was a direct consequence of the Brundtland report, this definition of sustainable development was widely adopted by international organizations (Lehtonen, 2004). Twenty years later at the Rio+20 UN Conference on Sustainable Development, the three pillars of sustainable development were elevated to global prominence with the agree-ment to develop sustainable development goals. Today, sustainable development plays a key role in combating climate change and provides the framework within which the Paris Agreement aims to “strengthen the global response to the threat of climate change, in the context of sus-tainable development and efforts to eradicate poverty” (Paris Agreement, Article 2, §1). Module 4 of this teaching material reviews policies pro-moting sustainable development in the context of human-made climate change. The module explains in detail how the current carbon-based economic system is supposed to be transformed into a low-carbon economy.

3.4Tradeasakeycomponentofsustainable development

The previous section argued that sustainable de-velopment is the solution to maintain the capac-ity of the joint economy-environmental system for current and future generations and simulta-neously raise standards of living worldwide. In this context, the international community – in-cluding the United Nations Conference on Trade and Development (UNCTAD), the WTO, the United Nations Environment Programme, and various multilateral environmental agreements – have highlighted the role that trade can play in achiev-ing sustainable development.

Paragraph 6 of the WTO’s Doha Ministerial Decla-ration stipulates that its member countries “are convinced that the aims of upholding and safe-guarding an open and non-discriminatory mul-tilateral trading system, and acting for the pro-tection of the environment and the promotion of sustainable development can and must be mutually supportive.” The contribution of trade to sustainable development has also been recog-nized during several international conferences, including the 1992 UNCED conference in Rio de Janeiro, the 2002 World Summit on Sustain-able Development in Johannesburg, and the 2012 Rio+20 Conference. In the 2030 Agenda for Sus-tainable Development, the international commu-nity recently renewed its commitment to making trade a key enabler of sustainable development.

According to the WTO (2011), increased trade openness leads to increased resource efficiency, higher growth rates, and higher income levels. Trade is thus seen as supporting sustainable de-velopment objectives by affecting at least two of the sustainable development pillars: economic development and environmental protection. By promoting production efficiency, offering new op-portunities for the sale of products, and increas-ing the availability of high-quality and low-price inputs, trade is viewed as helping to reduce pov-erty by stimulating economic development. Trade can also directly affect the environmental protec-tion pillar of sustainable development by (a) in-creasing the efficiency of natural resource use due to a trade-induced increase in competition and resulting efforts to reduce costs by reducing consumption of natural resources, thereby sup-porting conservation efforts; and (b) making ac-cess to environmental goods and services easier for all countries, thereby acting as a channel for green technology transfers (WTO, 2011). Liberali-zation of trade in such eco-efficient technologies might help to support sustainable development globally. This is certainly an important topic, given that Section 2.2.2 showed that technologies will need to moderate the impact of expected increas-es in population and affluence on CO2 emissions. Box 6 takes a closer look at trade in environmental goods and services. Moreover, as UNCTAD (2014) points out, trade can play an important indirect role in sustainable development by mobilizing fi-nancial resources that might be used to finance sustainable development objectives.

One of the ways in which trade can effectively support sustainable development is by facilitating access to environmental goods and services (EGS). Trade in these goods and services is frequently assumed to have the potential for “win-win” outcomes, generating both environmental benefits (by disseminating environmental goods and services) and trade gains for countries involved (UNCTAD, 2003).


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TradeinenvironmentalgoodsandservicesBox 6

The EGS sector only emerged in the 1990s as a distinct sector, but it has since grown and changed rapidly. The relative newness of the concept makes defining the sector difficult. While there are several national definitions that vary in scope, the OECD and Eurostat took the lead at the international level to define the sector (UNCTAD, 2003). According to OECD/Eurostat (1999), the EGS sector consists of “activities which produce goods and ser-vices to measure, prevent, limit, minimize or correct environmental damage to water, air and soil, as well as problems related to waste, noise and ecosystems.” By their nature, EGS are scattered across an array of different economic sectors. Despite the difficulty of defining the sector, there have been attempts at estimating the size – in other words the total value produced – of the EGS market. Using its own definition of the sector, Environ-mental Business International (2012) estimated the global size of the EGS market at US$832.2 billion in 2011, rep-resenting roughly 1.2 per cent of global GDP. While developed countries still dominate the market in absolute terms, developing countries from Africa, the Middle East, and Asia show the highest growth rates in that year.

Global exports of environmental goods as classified by the OECD list of environmental goods and services increased by almost 190 per cent, from US$231 billion to US$656 billion, over 2001–2012 (Bucher et al., 2014).1 These figures would be even higher if one took trade in environmental services into account. In 2012, trade in EGS was dominated by trade between developed countries. During 2008–2013, eight of the 10 leading export-ers and seven of the 10 leading importers of EGS were developed countries (Bucher et al., 2014). It is interesting to note, however, that the People's Republic of China is already now the second largest exporter and importer of EGS. Moreover, other developing countries like the Republic of Korea, Mexico, Brazil, Malaysia, and the Rus-sian Federation also play an increasingly important role in the global EGS market. Generally speaking, most analysts expect that developing countries will significantly increase their global export and import shares over the years to come (Bucher et al., 2014). Hamwey (2005) identifies significant export strengths and po-tential for developing countries in environmentally preferable products, EGS from the manufacturing and chemical sector, and environmental services.

Given the importance of the EGS sector for the environment and its high market growth rate, trade liberali-zation of the sector is considered to be an important issue. During the 2001 Doha WTO Ministerial Confer-ence, WTO member states codified their agreement to open negotiations on “the reduction or, as appropriate, elimination of tariff and non-tariff barriers to environmental goods and services” in paragraph 31 (iii) of the Doha Ministerial Declaration. The declaration emphasizes that negotiations should enhance the mutual sup-portiveness of trade and the environment in terms of both environmental benefits and trade gains for the parties involved (UNCTAD, 2003). Lamy (2008) argues that agreement on paragraph 31 (iii) would be a direct and immediate contribution of the WTO to fighting climate change.

Nevertheless, no WTO agreement on EGS trade liberalization has been reached to date, and important tariff and non-tariff barriers continue to exist in this sector. Much of the environmental goods negotiation has revolved around finding an acceptable sector definition among WTO members, and coming up with a list of EGS for which tariffs and barriers would be reduced. Several proposals have been submitted, most of them based on list approaches,2 but none have gained a consensus due to conflicting interests on product cover-age and negotiation modalities among the negotiating parties (UNCTAD, 2009/2010). Developing countries in particular expressed concerns related to the definitions of EGS, the potential inclusion of dual-use goods, liberalization approaches, environmental regulation, and technology transfer.3

While multilateral negotiations seem stalled, plurilateral negotiations on EGS are taking place. In the Asia Pacific Economic Cooperation (APEC) 2012 Vladivostok Declaration, APEC members announced a reduction in tariffs on 54 environmental goods to a maximum of 5 per cent by 2015. Details of the implementation of these cuts were published in early 2016. Bucher et al. (2014) argue that this particular initiative might provide new impetus for WTO efforts in this area.

1 The OECD list of environmental goods and services covers 164 HS-6 products and includes product categories such as pol-lution management, cleaner technologies, and products and resource management. For an overview of the OECD list and a comparison with other lists of environmental goods and services, see Steenblik (2005). 2 List approaches try to identify sets of products to be considered environmental goods and services. Identification is mostly based on the Harmonized Commodity Description and Coding Systems (HS). Different lists have so far been put forward, for ex-ample by Japan, APEC, OECD, and UNCTAD. According to Ramos (2014), these lists, with the exception of the UNCTAD list, mainly reflect the export interests of developed countries in non-agricultural trade.3 See Ramos (2014) for a discussion and a list of studies identifying these concerns.

Source: Author.

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Although trade is seen by many as an important enabler of sustainable development because of its ability to disseminate environmental goods and services, several civil society environmental groups have raised concerns about negative ef-fects of trade on the environment. These voices

have been particularly loud in the 1990s and 2000s. The following section therefore reviews evidence on this issue by looking at theoretical models and empirical results about the effect of trade on the environment.

Shortsummary

In Section 3, readers learned that unsustainable behaviour played an important part in the decline and col-lapse of some past societies, reminding us to take climate change seriously, as it is this century’s biggest global environmental problem. We illustrated the fundamental role of environmental constraints in the de-velopment of economic systems and societies at large, and thus demonstrated the importance of a sustain-able economic system. We introduced the concept of sustainable development as a means of creating a sus-tainable world economy and showed why trade plays an important role in current sustainable development strategies.

4 Impactoftradeontheenvironment

The previous sections of this module (a) showed that human beings can affect the climate be-cause the economy and the environment are in-terrelated and interdependent; (b) identified the factors that determine the size of the impact an economy has on the environment; (c) illustrated what can happen if these effects become too damaging; (d) introduced the concept of sustain-able development as a means of avoiding ecocide while simultaneously helping reduce poverty; and (e) showed that trade is viewed as an impor-tant enabler of sustainable development.

Over recent decades, especially around the start of the new millennium, numerous environmen-tal groups opposed further trade liberalization, fearing a negative impact on the environment (Copeland and Taylor, 2003). The idea that trade negatively affects the environment is also wide-spread among the general public. A 2007 survey conducted in countries covering 56 per cent of the world population found that in several coun-tries a majority of people perceive trade to be bad for the environment. In none of the surveyed countries did large majorities believe that trade is beneficial for the environment (The Chicago Council on Foreign Affairs and World Public Opin-ion, 2007). In this context, this section aims to provide theoretical tools and empirical insights to shed light on the fundamental question that has been at the heart of these debates: Is inter-national trade good or bad for the environment? Given the overall thrust of this material, the focus will be on climate change.

Section 4.1 introduces the topic by looking at the data on trade openness and CO2 emissions. Sec-tion 4.2 presents a conceptual framework to sys-tematically examine how increased trade open-

ness affects the environment. This theoretical framework is then used in Section 4.3 to discuss several important empirical contributions on the impact of increased trade openness on the envi-ronment.

4.1 Trade,tradeopennessandtheenvironment: Afirstglanceatthedata

Does increased trade openness have an impact on the environment? If so, is this impact positive or negative? To help answer these questions, this section focuses on a particular environmental impact – CO2 emissions – and looks at descriptive statistics about CO2 emissions and trade open-ness. While this type of analysis does not allow for making causal statements, it is a good start-ing point to obtain a general idea of the nature of the relationships at work.

When analysing the question of whether in-creased trade openness increases CO2 emissions, we first examine whether trade openness (meas-ured here as exports and imports as a percentage of GDP, and merchandise exports and imports as a percentage of GDP) and CO2 emissions evolve in a similar manner over time.15 In other words, we look at whether an increase (decrease) in trade openness is paralleled by an increase (decrease) in CO2 emissions. If this is the case, we would have a first hint that trade openness and the particu-lar environmental impact we are looking at (CO2 emissions) could be connected. Results of this initial descriptive analysis are shown in Figure 9.

The left panel of Figure 9 displays the evolution of world CO2 emissions and the two indicators of world trade openness. CO2 emissions and both trade openness indicators have been steeply ris-ing since 1960. While total exports and imports represented 25 per cent of world GDP in 1960,

15 It is important to distin-guish between measures of trade (i.e. the absolute volume of trade flows) and measures of trade openness. Measures of trade openness can either indicate the actual importance of trade in the economy (these are called measures of trade openness in practice) or quantify the number and/or importance of trade policy measures in place (measures of openness in policy). We use here two indicators of measures of trade openness in practice. For an overview of different measures of trade and trade openness, see UNCTAD (2010: 18–21).


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they corresponded to 59 per cent in 2014. Mer-chandise exports and imports rose from 18 per cent of world GDP in 1960 to almost 49 per cent in 2014. Over the same time period, CO2 emis-sions increased by roughly 270 per cent. Both trade openness indicators and CO2 emissions thus seem to evolve in a similar manner. Annual changes in the three variables are displayed in the right panel of Figure 9. Growth rates of CO2 emissions are positively correlated with growth rates of trade openness (correlation coefficients equal 0.26 for total exports and imports and 0.32 for merchandise exports and imports). This means that, on average, CO2 emissions increased

(decreased) in the same year as trade openness increased (decreased). This is a second hint that trade openness and environmental effects could be connected. At first glance it thus seems that increased trade openness goes hand-in-hand with increased CO2 emissions. It is important to note, however, that the results from Figure 9 do not allow for making any causal statement on the relation between trade openness and emissions, as we are only considering correlations. Never-theless, these results provide a clear rationale for a more detailed analysis, as trade openness and CO2 emissions seem to be linked, which could po-tentially reflect a causal relationship.

TradeopennessandCO2emissions,1960–2014Figure 9

Source: Author's elaboration based on data from World Bank’s World Development Indicators database.

1990 2000 20101960 1970 1980

Per c

ent o

f GDP

Year

10

15

20

25

30

35 60

50

40

30

20

1990 2000 20101960 1970 1980Year

-10

0

10

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-20

1990 2000 20101960 1970 1980

Per c

ent o

f GDP

Year

10

15

20

25

30

35 60

50

40

30

20

1990 2000 20101960 1970 1980Year

-10

0

10

20

30

-20

CO2 emissions, millions

of kilotons

Exports and imports

(per cent of GDP)

Merchandise exports and

imports (per cent of GDP)

CO2 emissions growth rate

Growth rate of exports

and imports

Growth rate of merchandise

exports and importsGiven that the results from Figure 9 suggest that trade openness and CO2 emissions are positively associated, we use cross-section data – captur-ing one point in time (here the year 2011) for sev-eral countries – to identify potential underlying reasons for this positive relationship. Following the methodology suggested by Onder (2012), we look at the relation between trade openness (as measured by merchandise exports and imports as a percentage of GDP) and different factors that could explain the link we found in the previous analysis. The results are displayed in Figure 10 which contains four different panels.

The upper left panel shows that there is a positive correlation between trade openness (as meas-ured by the GDP share of merchandise trade) and CO2 per capita emissions. In other words, coun-tries that trade more extensively seem to emit on average more CO2 per person than countries that are less open to trade. This result is in line with the results we found in Figure 9 . Which fac-tors could potentially explain this positive asso-ciation? The remaining three panels offer several possible explanations of this result.

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TradeopennessandCO2emissions,2011Figure 10

CO2 e

mis

sion

s (m

etric

tonn

es p

er ca

pita

)In

dust

ry, v

alue

add

ed (p

er ce

nt o

f GDP

)

GDP

per c

apita

(PPP

; con

stan

t 201

1 int

. $)

CO2 in

tens

ity (k

g of

oil

equi

vale

nt e

nerg

y use

)

Coefficient of correlation .202

Coefficient of correlation .106Coefficient of correlation .221

Coefficient of correlation .077

150 2000 50 100Merchandise exports and imports (per cent GDP)

10

20

30

0

80


20

40

60

015

0000


5000

010

0000

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40


1

2

3

0

5

4

Source: Author's elaboration based on data from the World Bank’s World Development Indicators database. The figure reproduces Figure 2 from Onder (2012) with more recent data. Note: Countries with oil rents higher than 30 per cent of GDP were excluded (oil rents correspond to the difference between the value of crude oil production at world prices and total costs of production). In addition, three outliers (Singa-pore, Aruba, and Hong Kong (China)) with high trade openness indicators were also excluded. Sample sizes differ due to data availability. The sample includes 195 countries in the top panels, 184 in the lower left panel, and 149 in the lower right panel. PPP: purchasing power parity.

A first potential explanation is provided in the upper right panel of Figure 10, which explores the relation between trade openness and GDP per capita. We see that countries that are more open to trade consume and produce more per person than countries with less openness to trade. As we have seen in the previous sections, higher per capita consumption and production (in other words, greater affluence) tends to increase the impact on the environment. Therefore, it is possi-ble that trade indirectly affects the environment by increasing economic output.

A second potential explanation is found in the lower left panel of Figure 10 which analyses the relation between trade openness and the share of value added produced in the industrial sector. This panel shows that countries with a relatively high trade openness ratio seem to produce a larg-er proportion of their value added in industrial sectors, which are typically relatively energy-in-tensive. This could mean that the sectoral compo-sition of countries that trade frequently is biased

towards energy-intensive goods, which also pro-duce more CO2 emissions. One could interpret this observation as an empirical hint that trade affects the sectoral composition of countries, which in turn indirectly affects the environment.

Finally, a third potential explanation is found in the lower right panel of Figure 10 which analy-ses the relation between trade openness and CO2 emission intensity (CO2 emissions per dollar produced). This panel shows that countries with higher trade openness ratios seem to have higher average CO2 emission intensity. In other words, it is possible that countries that are relatively more open to trade use more polluting technologies in their production processes than countries that are less open to trade. This observation could be an empirical hint that trade somehow affects technology and thereby indirectly influences the environment.

The first cursory look at data in Section 4.1 reveals two important findings on whether increased

Linear fit

95 per cent confidence interval


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trade openness increases CO2 emissions. First, trade openness and CO2 emissions evolved in par-allel over recent decades, and per capita CO2emis-sions are higher for countries with greater trade openness. Evidence thus seems to indicate that there is at least a positive correlation between trade openness and CO2 emissions. Second, with-out being able to make any causal statement, data provide preliminary evidence for at least three different possible explanations for this positive correlation: (a) higher trade openness seems to go hand-in-hand with increased per capita production; (b) the sectoral composition of countries that trade frequently seems to be bi-ased towards energy-intensive goods, which pro-duce more CO2 emissions; and (c) countries that trade frequently seem to employ more polluting technologies than countries that trade less. The following section will take a look at theoretical concepts that could explain these preliminary empirical results. 4.2Environmentalimpactoftrade: Whatwecanlearnfromtheory

The analysis in Section 4.1 revealed several rea-sons that might explain why CO2 emissions are different for countries with different degrees of trade openness. The theoretical framework out-lined in this section aims to explain these results and serve as a starting point for empirical work on the environmental impact of trade.

4.2.1 Scale, composition and technique effects

The current theoretical discussion on trade and the environment is framed by the concepts intro-duced by Grossman and Krueger (1993) in their now-famous work analysing the environmental impact of the North American Free Trade Agree-ment. The authors distinguish three effects that economic activities such as trade can have on the environment: the scale effect, the composition ef-fect, and the technique effect (Table 2). The scale effect is rather straightforward: if the overall scale of economic activity increases, all else being equal, the environmental impact will increase. Besides the overall scale of activities, the production mix of an economy is also important. All else being equal, a shift in the composition of an economy in terms of the share of clean and dirty sectors will affect the overall environmental impact of that economy. If an economy changes its industry mix and starts to produce relatively more dirty goods, the overall environmental impact increases. The opposite will happen if an economy’s production mix shifts towards cleaner industries. This effect is called the composition effect. Finally, technol-ogy also matters – if the scale and composition of the economy are fixed, but production technology becomes cleaner, then the overall environmental impact of the economy decreases, and vice versa. This is called the technique effect. Box 7 shows how these effects can be derived formally. Each of these effects and their relation to trade are analysed individually in the sections that follow.

Adecompositionofscale,compositionandtechniqueeffectsBox 7

Scale, composition and technique effects as introduced by Grossman and Krueger (1993) can be formally de-rived. Let us focus again on CO2 emission. Furthermore, let us make our life easier by assuming that an econ-omy produces only two types of goods, dirty goods and clean goods, and that emissions are only a by-product of the production process of dirty goods (clean goods do not produce any emissions). We can then express total CO2 emissions of the economy (E) as the product of total economic output (Y) times the share of dirty goods in total output (S) times emissions per unit produced of the dirty good (A):

Let us take logarithms and use the properties of the logarithm to obtain:

And finally, let us totally differentiate the above equation, which yields:

From the above, we see that the percentage change in emissions is equal to the percentage change in total output plus the percentage change in the share of dirty goods in the economy plus the percent-age change in the emissions per unit produced of the dirty good . We see that the scale effect (a change in the overall scale of the economy , the composition effect (a change in the composition of the economy in terms of dirty and clean goods , and the technique effect (a change in emissions per produced unit of the dirty good all affect overall emissions .

E = Y* S* A

ln(E) = ln(Y) + ln(S) + ln(A)

+= +ΔEE

ΔYY

ΔSS

ΔAA

Source: Author’s elaboration based on Grossman and Krueger (1993).

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4.2.2 Trade-induced scale effect

It is often claimed that increased trade openness stimulates economic growth, and hence the scale of economic activities (production, consumption, and transportation) in trading countries.16 Conse-quently, if nothing else changes, these increased economic activities will in turn have a higher to-tal impact on the environment. (See Section 2.2.2 for an example of how GDP growth can affect CO2

emissions.) Grossman and Krueger (1993) called this mechanism the trade-induced scale effect. Researchers generally expect trade-induced scale effects to have negative consequences for the environment. Since the seminal contribution of Grossman and Krueger, numerous empirical pa-pers (Antweiler et al., 2001; Copeland and Taylor, 2003; Frankel and Rose, 2005; Managi et al., 2009) have attempted to analyse the existence and size of trade-induced scale effects. Some of this em-pirical evidence is reviewed in Section 4.3.

4.2.3 Trade-induced composition effect

Increased trade openness not only influences the scale of economic activities but also the sec-toral composition of trading economies. Stand-ard trade models assume that countries that increase their openness to international trade specialize in sectors where they have a compara-tive advantage.17 Thus, opening up to trade may change a country’s sectoral structure. The coun-try may specialize in relatively clean sectors if it has a comparative advantage in these sectors, or in relatively “dirty” or polluting sectors if it has a comparative advantage in those sectors. Increased trade openness worldwide may there-fore lead to a change in production patterns across countries and thus modify the impact of the world economy on the environment. The question then is whether trade-induced changes in economies’ sectoral composition increase or reduce overall environmental impacts.

From a theoretical point of view, this depends on the sources of the countries’ comparative advan-tage. The literature (De Melo and Mathys, 2010; Grossman and Krueger, 1993; Managi et al., 2009) frequently distinguishes two types of trade-in-duced composition effects. The first type, factor-endowment effects, arises from classical sources of comparative advantage (factor abundance and technology differences). The second type, pollution-haven effects, results from differences in environmental policy stringency in different countries.

Taken in isolation, the potential net environmen-tal impact of factor-endowment effects is un-

clear. Theory predicts that developed countries with relatively high capital-labour ratios tend to specialize in capital-intensive sectors after open-ing up to trade. As production technologies in capital-intensive industries are often resource- and/or pollution-intensive (Managi et al., 2009), this tends to increase the environmental impact in these countries. Developing countries with rather low capital-labour ratios tend to special-ize in labour-intensive sectors after opening up to trade. This tends to decrease the environmen-tal impact in these countries. The net impact of factor-endowment effects on the world environ-ment is thus ambiguous.

Theory generally predicts a negative net envi-ronmental impact of pollution-haven effects. Pollution-haven effects tend to increase the com-parative advantage of developing countries in polluting industries because environmental reg-ulations are often less stringent in these coun-tries. This can lead to shifting the production of these industries from developed countries where industry is heavily regulated to developing coun-tries where there is less regulation. Such a shift would lead to an increase of the environmental impact worldwide.

While explaining these mechanisms, theory can-not help in determining whether the overall im-pact of trade-induced composition effects is pos-itive or negative for the environment. Everything depends on the net impact of factor-endowment effects and the relative strength of factor-endow-ment and pollution-haven effects. Section 4.3 will look at several empirical studies that have con-tributed to this debate.

4.2.4 Trade-induced technique effect

Trade can also influence the environment through the so-called trade-induced technique effect, which refers to the fact that production technology may change after a country opens up to trade. If technology changes, it is possible that the amount of resources used or the amount of emissions generated per unit produced also change. This would in turn affect the overall environmental impact of trade. Grossman and Krueger (1993) identify two mechanisms through which trade can alter production technology: trade-induced technology transfers, and changes in environmental policies. Both mechanisms are particularly important for developing countries.

The first mechanism concerns trade-induced technology spillover effects. Firms may bring new technologies to economies that have opened up to trade. As newer technologies are frequently

16 The link between trade and growth has long been one of the key questions in econo-mics. Numerous theoretical models have been tested by an armada of empirical contributions. While there are many theoretical arguments in favour of a positive rela-tionship between trade and growth, one also finds various arguments against the existence of such a positive relationship. Empirical tests of these arguments have so far not been conclusive, sometimes showing a positive and sometimes a negative relation between trade and growth. For an introduction to this topic, see UNCTAD (2010), Chapter 1 of Module 2.

17 For an overview of different trade models, see UNCTAD (2010), Chapter 1.


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assumed to be cleaner than older ones, trade-in-duced technology transfers are generally expect-ed to have a positive impact on the environment.

The second mechanism is indirect. Environmen-tal quality is usually assumed to be a normal good (Antweiler et al., 2001). In economics, a good is referred to as normal when the demand for that good increases with increased incomes. Saying that environmental quality is a normal good means that demand for it increases when

per capita income increases. One of the reasons for such an increase of per capita income can be opening to trade (see Section 4.2.2). Rising per capita income then increases the demand for improved environmental quality in the countries concerned. Their citizens put pressure on their governments to tighten environmental regula-tions, which in the end is beneficial for the en-vironment. Stricter environmental regulations might thus be an indirect consequence of greater openness to trade.

18 Note that while emissions correspond to the amount of a gas released into the atmosphere from a specific source and over a specific time interval, a concentration is the amount of the gas in the atmosphere per volume unit at a specific point in time.

Trade-inducedscale,compositionandtechniqueeffectsTable 2

Channel Theoretical mechanism Expected net effect

Trade- induced scale effectIncreased trade openness increases the overall scale of eco-nomic activities. All other factors fixed, this increases overall production, consumption, and transport.

All else being equal, the effect on the environment is expected to be negative.

Trade-induced composition effect

Factor-endowment effect: after opening up to trade, economies specialize in sectors in which they have a comparative advan-tage due to differences in factor endowments or technology. Capital-abundant countries specialize in capital-intensive industries, thus increasing their environmental impact, and labour-abundant countries specialize in labour-intensive indus-tries, thus reducing their environmental impact.

The net effect on the environment is ambiguous.

Pollution-haven effect: after opening up to trade, economies specialize in sectors that do not have strict environmental regulations and outsource production of strictly regulated industries to less regulated countries.

All else being equal, the effect on the environment is expected to be negative.

Trade-induced technique effect

Technology transfers: increased trade openness leads to the transfer of newer and cleaner technologies.

All else being equal, the effect on the environment is expected to be positive.

Environmental policy: increased trade openness increases per capita income, which in turn increases the demand for environmental quality, thus leading to stricter environmental regulations.

All else being equal, the effect on the environment is expected to be positive.

Net effect of trade on the environment

The net effect of trade openness on the environment is a com-bination of the trade-induced scale, composition and technique effects.

No clear theoretical prediction regarding the net impact of trade on the environment can be made.

Source: Author's elaboration based on the theoretical framework of Grossman and Krueger (1993) and on the distinction in De Melo and Mathys (2010) between factor-endowment and pollution-haven effects.

4.3 Environmental impact of trade: What we can learn from empirical evidence

Before the seminal work of Grossman and Krue-ger (1993), which outlined the theoretical founda-tions that allow for systematically analysing the effects of trade openness on the environment, few empirical contributions had been made in the field. Since then, however, empirical research to assess the effects of trade on the environment has been growing rapidly. Most of the research has so far focused on local pollutants (De Melo and Mathys, 2010). Recently some authors also started to analyse the effects of trade on defor-estation or water use (see Box 8). In line with the focus of this material, this section contin-ues to concentrate on the empirical evidence on trade openness and CO2 emissions, the most researched greenhouse gas to date. Our review, however, also includes a second gas, sulphur di-

oxide (SO2), which is the gas responsible for acid rain. While SO2 is not a greenhouse gas, SO2 and CO2 emissions are highly correlated, with the same energy-intensive industries being the main emitters (De Melo and Mathys, 2010). It is there-fore meaningful to include SO2 in the analysis.

Antweiler et al. (2001) analyse the impact of in-creased trade openness on concentrations of SO2.18 They estimate scale, composition and tech-nique effects and show for the first time that these effects can actually be measured using available data and therefore are not just abstract theoretical concepts. Their sample covers 43 countries over the period 1971–1996. The empiri-cal results reveal the existence of a trade-induced composition effect that is lowering SO2 concen-trations, i.e. SO2 concentrations decrease due to a trade-induced change in the sectoral composi-tion of the average economy. Moreover, they find

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evidence for a scale effect (SO2 concentrations in-crease when GDP increases) and a technique ef-fect (SO2 concentrations decrease when per cap-ita income increases). According to their results, if an increase in trade openness generates a 1 per cent increase in income and output, then pol-

lution concentrations will fall by approximately 1 per cent due to the joint impact of scale and technique effects. Overall, their results suggest that increased trade openness seems to have a beneficial effect on reducing SO2 concentrations.

SelectedempiricalevidenceontheimpactoftradeondeforestationandwateruseBox 8

While Section 4.3 discusses the empirical evidence on the influence of trade on selected air pollutants, it is im-portant to note that trade also affects other aspects of the environment, such as water use and deforestation. However, the empirical literature on the impact of trade on other aspects of the environment is still scarce, and more research is needed.

The links between deforestation and trade have been empirically assessed by Frankel and Rose (2005) and Van and Azomahou (2007). These contributions do not find a significant effect of trade openness on deforestation and are thus inconclusive. However, in analysing the effects of increased trade openness on deforestation for 142 countries over 1990–2003, Tsurumi and Managi (2012) find a significant effect: their results indicate that trade-induced changes in the sectoral composition of economies accelerated deforestation in developing countries but slowed deforestation in developed countries.

The effects of increased trade openness on water use (the degree to which water is withdrawn and consumed) have been analysed by Kagohashi et al. (2015). Their sample covers 43 countries over 1960–2000. Their results indicate that trade increased water use through the scale and composition effects. However, these two effects are more than offset by the water use reducing technique effect. Overall, their results suggest that a 1 per cent increase in trade openness reduces water use by roughly 1 to 1.5 per cent on average. Thus trade seems to promote efficient water use. The authors argue that their results can be explained by the role of trade in diffusing water-saving technologies and modifying industrial composition.

Source: Author.

Building on Antweiler et al. (2001), several other papers used a similar empirical approach to es-timate scale, technique and composition effects for different gases and different countries. The findings of some of these papers are summarized in Table 3. The first finding is that the overall effect of increased trade openness on the environment depends on the gas. For SO2, the results from Ant-weiler et al. (2001) have been partially confirmed. Overall, increased trade intensity seems to lower SO2 emissions. However, more trade seems to in-crease CO2 emissions. The second finding is that the impact of trade on emissions differs substan-tially depending on the countries considered. Managi et al. (2009) find that trade decreases SO2 and CO2 emissions in OECD countries but

increases them in non-OECD countries. Finally, the third finding is that the sign and magnitude of scale, composition and technique effects also depend on the combination of the gas and the country considered: trade seems to increase emissions through scale effects and lower them through technique effects. Depending on the gas and the country, these two effects can offset one another. The impact of composition effects related to the change of economic structures to-wards cleaner or more polluting production are gas-specific and rather small, which Cole and Eliot (2003) attribute to the simultaneous exist-ence of pollution-haven and factor-endowment effects that cancel each other out.


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SelectedempiricalresultsontradeandairpollutionTable 3

Study Gas Countries Effects Net effect of trade

Antweiler et al. (2001) SO2

All countries in sample

Scale: concentration increasing Technique: concentration decreasing

Composition: concentration decreasing

Decreases SO2 concentrations

Cole and Eliot (2003)

SO2All countries in

sampleCombined scale and technique: emissions decreasing

Composition: emissions increasing Unclear

CO2All countries in

sampleCombined scale and technique: emissions increasing

Composition: emissions increasingIncreases CO2

emissions

Managi et al. (2009)

SO2

Non-OECD countries

Combined scale and technique: emissions increasingComposition: emissions increasing

Increases SO2 emissions

OECD countries

Combined scale and technique: emissions decreasing Composition: emissions increasing

Decreases SO2 emissions

CO2

Non-OECD countries


Increases CO2 emissions

OECD countries


Decreases CO2 emissions

Source: Author.Note: The “Effects” column reports the observed impact of scale, technique and composition effects on the concentrations or emissions of the gas. Not all papers separated the scale and technique effects – sometimes combined scale and technique effects are reported.

In short, empirical contributions show that while trade does have an effect on the environ-ment, it is not possible to make a generally valid statement that this effect is positive or negative. Sometimes, more trade seems to have a positive

impact on the environment, while other times it seems to have a detrimental effect. As results differ from one case to another, further research is needed on a case-to-case basis to deepen our understanding of this important question.

Shortsummary

Section 4 addressed the question of whether trade is harmful or beneficial to the environment, using the example of CO2 emissions. After showing that trade openness and CO2 emissions are correlated, the section discussed three theoretical effects through which trade could affect the environment. Table 2 summarized the expectations with regard to the environmental impact of each of these effects. While theory provides a frame-work that enables us to conceptualize the effects of trade on the environment, it cannot by itself make a final prediction as to whether trade is harmful or beneficial to the environment. The section therefore reviewed selected empirical work relevant in the context of climate change, concluding that trade seems to sometimes have a positive impact and sometimes a negative impact on the environment.

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1 Whyaretheeconomyandtheenvironmentconsideredtobetwointerdependentsystems?Describetheservicestheeconomyprovidestotheenvironment.

2 Howcanyouclassifynaturalresourcesintoflowresources,non-renewablestockresources,andrenewablestockresources?Classifythefollowingnaturalresourcesandexplainyourreasoning:

(a) Poweroftides (b) Coal (c) Powerofwind (d) Cattle (e) Petroleum (f) Wood (g) Solarradiation (h) Fish (i) Cobalt

3 DescribethegeneralformoftheIPATidentityanddiscusstheroleofeachcomponent(P,A,andT).

4 Download the Excel dataset from http://vi.unctad.org//tenv/files/data_exercise.xlsx. The dataset covers1970–2014 and contains three variables: world population (P); world GDP per capita (A); and world CO2emissionsperworldGDP(T).

(a) UsingtheIPATidentity,calculateworldCO2emissionsforeachyearinthedataset. (b) Plotallfourvariablesovertime,anddiscusstheeffecteachdriver(P,A,andT)hasonemissions(I). (c) Supposetheworldwantstostabilizeitsemissionsatthe1970level.Supposefurtherthattheworld

canonlyinfluenceTtoachievethisobjective(i.e.theevolutionoftheworldpopulationandworldGDP per capita for the years 1970–2014 is fixed as given by the data). Calculate how much emission intensity of technologies (T) would need to decrease each year to achieve the objective, given the growthinpopulationandGDP.Hint:Foreachyeart,calculatethetechnologylevelTtneededtokeep emissionsatthe1970level,giventhepopulationandGDPpercapitalevelsinyeart.

(d) CompareanddiscusstheobservedevolutionofTandthehypotheticalevolutionofTt.

5 UsingtheexamplesprovidedbyDiamond(2006),illustratewhyeconomicsystemsthatignoreenvironmen-talconstraintsfaceproblems.Canyouthinkofotherexamplesnotmentionedinthisteachingmaterial?

6 Definesustainabledevelopment.Discusspotentialimplicationsofsustainabledevelopmentfordevelop-ingcountries.

7 Identifykeyenvironmentalgoodsandservicesproducedinyourcountry.

8 HowcantradeaffectCO2emissions?Distinguish,define,anddiscussthescale,compositionandtechniqueeffects.

5 Exercisesandquestionsfordiscussion


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ANNEX 1

ANNEX 2

Database Description Link

Davis et al. (2011) dataset on trade and carbon dioxide

These data represent a consistent set of carbon accounts at points of extraction (of fuels), production (of emissions), and consumption (of goods) for 112 nations/regions and 58 sectors, including trade linkages.

https://supplychainco2.dge.carnegiescience.edu/data.html

World Bank (2016) Data Catalog

The data catalogue covers a wide range of indicators relevant to the environment, including data on pollution, emissions, forests, and biodiversity. It also covers a wide range of general economic indicators including data on trade.

http://data.worldbank.org/indicator

Emissions Database for Global Atmospheric Re-search (EDGAR)

EDGAR provides data on global anthropogenic emissions of greenhouse gases and air pollutants at the country level. Data are also available at a high spatial resolution, allowing for detailed spatial analysis.

http://edgar.jrc.ec.europa.eu/

OECD environmental indicators

The OECD environmental indicators, modelling and outlooks database contains data on a range of environmental topics covering mostly OECD countries.

http://www.oecd.org/env/indicators-modelling-outlooks/

Topic

Links between the economy and the environment

Chapters 2–4 and 7 of Common M and Stagl S (2004). Ecological Economics – An Introduction. Cambridge University Press. Cambridge, MA.

Chapters 2.1–2.4 of Perman et al. (2011). Natural Resource and Environmental Economics, Fourth Edition. Pearson Education Limited. Essex, UK.

Chapter 1 of Kolstad C (2000). Environmental Economics. Oxford University Press. Oxford, UK.

Chapters 1 and 2 of Tietenberg T, and Lewis L (2012). Environmental and Natural Resource Eco-nomics, Ninth Edition. Pearson International Edition. Addison Wesley. Boston.

Sustainability

Chapter 2.5 of Perman et al. (2011). Natural Resource and Environmental Economics, Fourth Edi-tion. Pearson Education Limited. Essex, UK.

Chapters 5 and 20 of Tietenberg T, and Lewis L (2012). Environmental and Natural Resource Economics, Ninth Edition. Pearson International Edition. Addison Wesley. Boston.

Chapters 1.4, 4.11, 9.5, and 10 of Common M, and Stagl S (2004). Ecological Economics – An Intro-duction. Cambridge University Press. Cambridge, UK.

Strange T, and Bayley A (2008). Sustainable Development, Linking Economy, Society, Environment. OECD Publishing. Paris.

Diamond J (2006). Collapse: How Societies Choose to Fail or Survive. Penguin. London.

Trade and the environment

Chapter 10 of Perman et al. (2011). Natural Resource and Environmental Economics, Fourth Edi-tion. Pearson Education Limited. Essex, UK.

Copeland BR, and Taylor MS (2003). Trade and the Environment: Theory and Evidence. Princeton University Press. Princeton, NJ and Oxford, UK.

Someusefuldatabases

Selectedadditionalreadingmaterial

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Antweiler W, Copeland BR, and Taylor MS (2001). Is free trade good for the environment? American Economic Review 91(4): 877–908.

Behera SK, Singh H, and Sagar V (2013). Status of Ganges River dolphin (Platanista gangetica gangetica) in the Ganga River basin, India: A review. Aquatic Ecosystem Health & Management 16: 425–32.

Brown BJ, Hanson ME, Liverman DM, and Merideth RW (1987). Global sustainability: Toward definition. Environmental Manage-ment 11: 713–19.

Bucher H, Drake-Brockman J, Kasterine A, and Sugathan M (2014). Trade in environmental goods and services: Opportunities and challenges. International Trade Centre Technical Paper. Geneva.

Chertow MR (2000). The IPAT equation and its variants. Journal of Industrial Ecology 4: 13–29.

Cole MA Elliott RJR (2003). Determining the Trade-Environment Composition Effect: The Role of Capital, Labor and Environmental Regulations. Journal of Environmental Economics and Management 46(3): 363–383.

Cohen D (2009). La prospérité du vice. Une Introduction (inquiète) à l’économie. Albin Michel. Paris.

Common M, and Stagl S (2004). Ecological Economics – An Introduction. Cambridge University Press. Cambridge, UK.

Copeland BR, and Taylor MS (2003). Trade and the Environment: Theory and Evidence. Princeton University Press. Princeton, NJ and Oxford, UK.

Davis SJ, Peters GP, and Caldeira K (2011). The supply chain of CO2 emissions. Proceedings of the National Academy of Sciences 108(45): 18554–8559.

De Melo J, and Mathys N (2010). Trade and climate change: The challenges ahead. CEPR Discussion Paper No. 8032. Centre for Economic Policy Research. London.

Diamond J (2006). Collapse: How Societies Choose to Fail or Survive. Penguin. London.

Dihel NC (2010). Understanding trade in environmental services: Key issues and prospects. In: International Trade in Services: New Trends and Opportunities for Developing Countries, Cattaneo O, Engman M, Saez S, and Stern R, eds. World Bank. Washington, DC.Environmental Business International (2012). Global environmental markets. Environmental Business Journal 25(6/7). Available at: http://ebionline.org/ebj-archives/1355-ebj-v25n06-07.

Frankel JA, and Rose AK (2005). Is trade good or bad for the environment? Sorting out the causality. The Review of Economics and Statistics 87(1): 85–91.

Grossman G, and Krueger AB (1993). Environmental impacts of a North American Free Trade Agreement. In: The Mexico-US Free Trade Agreement, Garber P, ed. MIT Press. Cambridge, MA.

Hamwey R (2005). Environmental goods: Where do the dynamic trade opportunities for developing countries lie? Cen2eco Work-ing Paper. Centre for Economic and Ecological Studies.

IEA/OECD (2015). CO2 Emissions from Fuel Combustion 2015. International Energy Agency and Organization for Economic Coopera-tion and Development. OECD Publishing. Paris.

IPCC (2014). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, Pachauri RK, and Meyer LA (eds.)]. Intergovernmental Panel on Climate Change. Geneva.

Johansson A, Guillemette Y, Murtin F, Turner D, Nicoletti G, de la Maisonneuve C, Bagnoli P, Bousquet G, and Spinelli F (2013). Long-term growth scenarios. OECD Economics Department Working Paper No. 1000. OECD Publishing. Paris.

Kagohashi K, Tsurumi T, and Managi S (2015). The effects of international trade on water use. PLoS ONE 10(7).

Kaya Y (1990). Impact of carbon dioxide emission control on GNP growth: Interpretation of proposed scenarios. Paper presented to the Intergovernmental Panel on Climate Change Energy and Industry Subgroup, Response Strategies Working Group, Paris.

Kolstad C (2000) Environmental Economics. Oxford University Press. Oxford, UK.

Lamy P (2008). A consensual international accord on climate change is needed. Paper presented at the Temporary Committee on Climate Change, The European Parliament. Brussels.

Lehtonen M (2004). The environmental–social interface of sustainable development: Capabilities, social capital, institutions. Ecological Economics 49(2): 199–214.


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Managi S, Hibiki A, and Tsurumi T (2009). Does trade openness improve environmental quality? Journal of Environmental Eco-nomics and Management 58(3): 346–63.

Nakicenovic N, and Swart R (eds.) (2000). IPCC Special Report on Emissions Scenarios - A Special Report of IPCC Working Group III. Intergovernmental Panel on Climate Change. Cambridge University Press, UK.

OECD (2014). OECD Economic Outlook No. 95 (Edition 2014/1). Organization for Economic Cooperation and Development Eco-nomic Outlook: Statistics and Projections (database). Available at: http://dx.doi.org/10.1787/data-00688-en.

OECD/Eurostat (1999). Environmental Goods and Services Industry Manual for the Collection and Analysis of Data. Organization for Economic Cooperation and Development. Paris.

Olivier JGJ, Janssens-Maenhout G, Muntean M, and Peters JHAW (2015). Trends in global CO2 emissions - 2015 report. PBL Report 1803. PBL Netherlands Environmental Assessment Agency and European Commission Joint Research Centre. Available at http://edgar.jrc.ec.europa.eu/news_docs/jrc-2015-trends-in-global-co2-emissions-2015-report-98184.pdf.

Onder H (2012). Trade and climate change: An analytical review of key issues. Economic Premise No. 86. World Bank, Washington, DC.

Perman R, Ma Y, Common M, Maddison D, and McGilvray J (2011). Natural Resource and Environmental Economics, Fourth edition, Pearson Education Limited. Essex, UK.

Ramos MP (2014). The impact of trade liberalization of environmental products on welfare, trade, and the environment in Argen-tina. UNCTAD Virtual Institute Project on Trade and Poverty. United Nations. Geneva.

Steenblik R (2005). Environmental goods: A comparison of the APEC and OECD lists. OECD Trade and Environment Working Paper No. 2005-4. Organization for Economic Cooperation and Development. Paris.

Strange T, and Bayley A (2008). Sustainable Development, Linking Economy, Society, Environment. OECD Publishing. Paris.

The Chicago Council and World Public Opinion.org (2007). World public favors globalization and trade but wants to protect envi-ronment and jobs. Available at: http://www.worldpublicopinion.org/pipa/pdf/apr07/CCGA+_GlobTrade_article.pdf.

Tietenberg T, and Lewis L (2012). Environmental and Natural Resource Economics, Ninth Edition. Pearson International Edition. Addison Wesley. Boston.

Tsurumi T, and Managi S (2012). The effect of trade openness on deforestation: empirical analysis for 142 countries. Environmental Economics and Policy Studies 16: 305–24.

UNCTAD (2003). Trade and Environment Report 2003. United Nation. Geneva.

UNCTAD (2009/2010). Trade and Environment Report 2009/2010. United Nations. Geneva.

UNCTAD (2010). Virtual Institute Teaching Material on Trade and Poverty, United Nations. New York and Geneva.

UNCTAD (2014). The role of trade in financing for sustainable development. Discussion Paper. Available at: http://www.un.org/esa/ffd/wp-content/uploads/2014/12/10Dec14-UNCTAD-input.pdf.

UNCTAD (2015). Key statistics and trends in international trade. United Nations. Geneva.

UNDESA (2015). World Population Prospects: The 2015 Revision. United Nations Department of Economic and Social Affairs Popula-tion Division. New York.

Van PN, and Azomahou T (2007). Nonlinearities and heterogeneity in environmental quality: An empirical analysis of deforesta-tion. Journal of Development Economics 84: 291–309.

WCED (1987). Our Common Future. World Commission on Environment and Development. Oxford University Press and United Nations. New York.

Webster D, Freter A, and Golin N (2000). Copan: The Rise and Fall of an Ancient Maya Kingdom. Harcourt Brace Publishers. Fort Worth, TX.

World Bank (2016). Open Data Catalog. World Bank. Washington, DC. Available at: http://datacatalog.worldbank.org/.

WTO (2010). World Trade Report: Trade in Natural Resources. World Trade Organization. Geneva.

WTO (2011). Harnessing Trade for Sustainable Development and a Green Economy. World Trade Organization. Geneva.

Module 2The climate science behind

climate change

The climate science behind climate change

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21 Introduction

Module 1 showed that human actions can influ-ence the climate because the economy and the environment are interdependent. This module focuses specifically on the climate system and the climate science behind climate change. By reviewing key points, the module enables read-ers to understand how the climate system works, why climate change occurs, and how humans induce climate change. The module highlights recent empirical evidence pointing towards the existence of human-induced climate change, and discusses climate-change-related impacts that can already be observed today. To conclude, the module outlines different scenarios for the

future and discusses the anticipated impacts of climate change.

To this end, this module draws on the work of the Intergovernmental Panel on Climate Change (IPCC) Working Group I, which deals with the physical science basis of climate change. As mentioned in Module 1, the IPCC is the leading body collecting, reviewing, and assessing recent state-of-the-art scientific work related to climate change. The five IPCC assessment reports and the different IPCC special reports19 together form the most comprehensive and reliable source of scien-tific work today on climate change. The module therefore uses some of the terminology intro-duced by the IPCC (see Box 9).

TheIPCC’sterminologytoreportfindingstothepublicBox 9

Relationshipbetweenagreement,evidenceandconfidencelevels

The Intergovernmental Panel on Climate Change (IPCC) developed specific terminology to report its findings to the public. In the fifth assessment report (IPCC, 2013a), a finding is assessed in terms of the underlying evi-dence and the agreement among scientists regarding that finding. In addition, the IPCC often assigns a level of confidence to the different findings that is based on evidence and agreement (see Figure 11).

Figure 11

19 All these reports are available on the IPCC home-page at: http://www.ipcc.ch/publications_and_data/pu-blications_and_data_reports.shtml#1.

High agreementLimited evidence

High agreementMedium evidence

High agreementRobust evidence

Medium agreementLimited evidence

Medium agreementMedium evidence

Medium agreementRobust evidence

Low agreementLimited evidence

Low agreementMedium evidence

Low agreementRobust evidence

Source: Mastrandera et al. (2010: 3).

Source: Author's elaboration based on Mastrandera et al. (2010).

Confidence scale

Agre

emen

t

Evidence (type, amount, quality, consistency)

To rate the degree of agreement among scientists regarding the evidence, it uses the terms “low,” “medium,” and “high.” Confidence levels are expressed using the terms “very low,” “low,” “medium,” “high,” and “very high.” If the likelihood of an outcome or a result has been assessed using statistical techniques, the IPCC reports probability values using the following terminology: “virtually certain” (99–100 per cent probability); “very likely” (90–100 per cent probability); “likely” (66–100 per cent probability); “about as likely as not” (33–66 per cent probability); “unlikely” (0–33 per cent probability); “very unlikely” (0–10 per cent probability); and “exceptionally unlikely” (0–1 per cent probability). Sometimes it also uses the terms “extremely likely” (95–100 per cent probability); “more likely than not” (>50–100 per cent probability); “more unlikely than likely” (0–<50 per cent probability); and “extremely unlikely” (0–5 per cent probability). For more details, see Mastrandrea et al. (2010).

Section 2 introduces the theoretical basis of the climate system and climate change. Section 2.1 familiarizes the reader with the concepts of weather, climate, and climate change, and intro-duces the five components of the climate system (i.e. atmosphere, hydrosphere, cryosphere, land surface, and biosphere). Section 2.2 focuses on the planet’s energy balance, which influences all five components of the climate system and is

therefore of crucial importance for the climate. The section stresses that the natural greenhouse effect plays an integral role in the planet’s en-ergy balance and is generally responsible for the relatively warm average temperature on the sur-face. With the module having outlined how the climate system works, Section 2.3 then explains that the climate not only changes in response to factors within the climate system but also in re-


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20 This section draws on the work of the IPCC, in particu-lar Chapter 1 of the contri-bution of Working Group I to the third IPCC assessment report (Baede et al., 2001), as well as several chapters of the fifth assessment report (especially Boucher et al., 2013, Cubasch et al., 2013, Masson-Delmotte et al., 2013, and Myhre et al., 2013).

sponse to some factors that are external to the climate system. In fact, some external factors (e.g. human activities) affect climate change drivers (e.g. greenhouse gases), which in turn affect the energy balance of the planet. Because the earth’s energy balance affects all five components of the climate system, external factors can thus affect the climate. Section 2.4 introduces two impor-tant concepts that allow for assessing how the planet’s energy balance changes as a result of externally induced variations in climate change drivers: radiative forcing and effective radiative forcing. These two important concepts allow for quantifying the extent to which different exter-nal factors influence the climate. Finally, Section 2.5 specifically focuses on the different ways in which humans affect the climate, altering at-mospheric concentrations of greenhouse gases and aerosols, and influencing properties of the land surface. It concludes by assessing the rela-tive strength of these different human-induced perturbations of the climate system, and high-lights the importance of feedback effects.

Section 3 then provides an overview of the main changes that have occurred in the climate system and highlights to what extent human activities have contributed to these observed changes. To this end, the section discusses observed changes in the means of temperature, precipitation, ice and snow cover, and sea levels. It then shows that not only the mean state of climate variables has changed, but that the frequency of extreme cli-mate events has also been affected. The section concludes with a short discussion on the impact of these observed changes on human and natu-ral systems.

To conclude Module 2, Section 4 looks at the fu-ture of the planet’s climate system. To this end, it introduces different scenarios describing pos-sible pathways of climate change drivers that are used by the IPCC’s climate models to project fu-ture changes in the climate system. After discuss-ing these scenarios, Section 4 highlights the most important predicted changes in the main climate variables (temperature, precipitation, snow and ice cover, and sea levels) that are likely to occur until 2100. The section ends by providing selected examples of anticipated future risks for humans and natural systems that might result from the simulated changes in the climate system.


• Distinguish the five components of the cli-mate system;

• Understand the radiative balance of the planet;

• Explain how the natural greenhouse effect operates;

• Define and understand the concept of radia-tive forcing;

• Explain how economic activities can alter the climate;

• List major observed human-induced changes of the climate system;

• Discuss anticipated future impacts of climate change.

To support the learning process, readers will find several exercises and discussion questions in Sec-tion 5 covering the issues introduced in Module 2. Additional reading material can be found in Annex 2.

2 Thetheoreticalbasisoftheclimate systemandclimatechange20

When speaking about climate change, it is im-portant to clearly distinguish three distinct but related concepts: weather, climate, and climate change. Weather can be defined as the changing state of the atmosphere, which is characterized by temperature, precipitation, wind, clouds, etc. (Baede et al. 2001). Weather fluctuates frequently as a result of fast-changing weather systems. Weather systems, and hence the weather, can only be predicted with some degree of reliabil-ity for a very short period of time (one or two weeks). They are unpredictable over longer time horizons. Climate, on the other hand, is, loosely speaking, “long-term average weather.” IPCC (2001a: 788) defines climate as “the statistical description in terms of mean and variability of relevant quantities [such as temperature, precip-itation, and wind] over a period of time ranging from months to thousands or millions of years. The classical period is 30 years, as defined by the World Meteorological Organization.” Climate not only varies from location to location (depending on a variety of factors such as distance to the sea, latitude and longitude, the presence of moun-tains, etc.) but also over time (e.g. from season to season, year to year, century to century, etc.). Based on this definition, IPCC (2001a: 788) defines climate change as “a statistically significant vari-ation in either the mean state of the climate or in its variability, persisting for an extended period (typically decades or longer).”

Understanding the interactions of the variety of factors that influence the climate is complicated. Climate, climate change, and the role of human activities in changing the climate can only be understood if one has an understanding of the whole climate system. The following section


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2looks briefly at the components of the planet’s climate system and shows how they interact.

2.1 Thefivecomponentsoftheclimatesystem

The climate system, schematically displayed in Figure 12, is part of the environmental system

discussed in Module 1. It consists of five main components (Baede et al., 2001): the atmosphere, hydrosphere, cryosphere, land surface, and bio-sphere (in bold in Figure 12). These five compo-nents interact with each other (thin arrows in Fig-ure 12) and are all affected by the planet’s energy balance, which will be discussed in Section 2.2.

TheclimatesystemFigure 12

Source: Baede et al. (2001: 88).

The most variable and rapidly changing part of the climate system is the atmosphere (Baede et al., 2001), which marks the boundary of our envi-ronmental system as defined in Module 1. The en-tire atmosphere lies within 500 km from the sur-face of the planet,21 with 99 per cent of its total mass within 50 km from the surface (Common and Stagl, 2004). The atmosphere can be subdi-vided (or stratified) into the five layers displayed in Figure 13. The troposphere is the lowest layer of the atmosphere and extends up to approxi-mately 11 km from the planet’s surface. It con-tains most of the atmosphere’s mass and plays a key role in determining the planet’s climate.

Mean temperature in the troposphere decreases with distance from the surface. In the text that follows, we will often refer to the so-called sur-face-troposphere system, which encompasses the planet’s surface and the troposphere. The next layer is called the stratosphere and extends to roughly 50 km above the surface. Most of the incoming ultraviolet radiation is absorbed by ozone that is concentrated in the stratosphere. The boundary between the troposphere and the stratosphere is called tropopause. The strato-sphere is followed by the mesosphere (50–90 km above the surface) and the thermosphere (90–500 km above the surface).22

21 We exclude here the exos-phere and consider that the atmosphere stops at the top of the thermosphere.

22 Many consider the ther-mosphere as the boundary of the atmosphere. But strictly speaking the thermosphere is followed by the exosphere (500–10,000 km above surface), which is considered by some to mark the actual boundary of the atmosphere and thus the environmen-tal system (discussed in Module 1) with the rest of the universe.

Atmosphere

Atmosphere-iceinteraction

Land-atmosphereinteraction

Precipitation-evaporation

Atmosphere-biosphereinteraction

Heatexchange

Changes insolar inputs

Soil-biosphereinteraction

Biosphere

Land surfaceSea ice

Changes in the ocean:

Ice-ocean coupling

Windstress Human influences

Terrestrial

Volcanic activity

radiation

Hydrosphere:rivers & lakes

Cryosphere:sea ice, ice sheets, glaciers

Clouds

Changes in thehydrological cycle

Hydrosphere:ocean

text

Changes in the atmosphere:composition, circulation

circulation, sea level, biogeochemistryChanges in/on the land surface:

orography, land use, vegetation, ecosystems

N2, O2, Ar,H2O, CO2,CH4, N2O, O3, etc.Aerosols

Glacier Ice sheet


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leLayersoftheatmosphereFigure 13

Source: National Aeronautics and Space Administration (NASA), Climate Science Investigations, available at: http://www.ces.fau.edu/nasa/module-2/atmosphere/earth.php.Note: The average temperature varies with altitude and is indicated by the red line.

The atmosphere is mainly a mixture of different gases but also contains some solid and liquid matter, namely aerosols and clouds. The com-position of the atmosphere has been changing throughout the history of the planet. Today the main bulk of the volume of the earth’s atmos-phere is composed of approximately 78.1 per cent nitrogen (N2), 20.9 per cent oxygen (O2), and 0.93 per cent argon (Ar). Additionally, the atmosphere contains several trace gases such as carbon di-oxide (CO2), methane (CH4), nitrous oxide (N2O), and ozone (O3). These trace gases, which consti-tute less than 0.1 per cent of the atmosphere’s volume, are called greenhouse gases (GHG). Wa-ter vapour (H2O) is also a greenhouse gas whose volume in the atmosphere is volatile depending on the hydrosphere’s hydrological cycle. Despite their small share in the total volume of the at-mosphere, greenhouse gases are of crucial im-portance for the earth’s climate. While the three main gases (N2, O2, and Ar) do not absorb or re-flect the infrared radiation emitted by the planet, greenhouse gases are different – they absorb in-frared radiation coming from the planet’s surface and emit this radiation towards space and back towards the earth’s surface, thereby increasing the temperature at the surface (see Section 2.2 for a detailed discussion). Consequently, green-house gases are crucial for our planet’s climate (Baede et al., 2001).

The hydrosphere consists of all forms of liquid water and includes oceans, rivers, and lakes. Ap-proximately 70 per cent of the total surface of the planet is covered by water. Oceans alone store roughly 97 per cent of all forms of water (liquid, solid, and gas) available on earth, while rivers and lakes store roughly 0.009 per cent (Common and Stagl, 2004). The basic process that takes place in the hydrosphere is called the hydrological cycle. The cycle starts with the water evaporating from the oceans, lakes, and rivers and being released into the atmosphere, which leads to an exchange of heat between the hydrosphere and the atmos-phere. The water then returns from the atmos-phere to the surface in the form of precipitation, either directly into the oceans or indirectly on the land from where it reaches the oceans through riv-ers. Water that returns from land to oceans then in turn influences the composition and circulation of oceans. Through this cycle, oceans not only ex-change water but also heat energy, carbon dioxide, and aerosols with the atmosphere. As oceans are able to gradually store and release large quantities of heat, carbon dioxide, and aerosols over a long time period, they act as the planet’s climate regu-lator and thus are an important source of long-term natural climate variability (Baede et al., 2001).

The cryosphere, consisting of solid water, includes continental glaciers, snow fields, sea ice, perma-

2o1o

3o4o5o6o7o8o9o

1101oo

120130140150160170

490500510520

Exosphere

Thermosphere

Mesosphere

Stratosphere

Troposphere Altit

ude

(km

)100 150 200 500/150050-50 0-100

Temperature °C


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2frost, and the large ice sheets of Antarctica and Greenland. The cryosphere is relevant for the plan-et’s climate because of its capacity to store heat, its low capacity to transfer heat (in other words, its low thermal conductivity), its high reflectivity of incoming solar radiation, and its influence on ocean circulation and sea levels (Baede et al., 2001).

The land surface, made up of soils and vegetation, encompasses all parts of the planet that are not covered by oceans. Land surface matters for the climate because it determines how energy from solar radiation is returned to the atmosphere. Part of the energy from the sun is directly returned to the atmosphere as longwave infrared radiation and part of the energy is used to evaporate wa-ter, which then returns as water vapour to the at-mosphere. The texture of the land surface, which depends on the type of soil and/or vegetation cov-ering the surface, also influences the atmosphere indirectly, as different textures influence winds in different ways (Baede et al., 2001).

The biosphere is composed of all living organ-isms (also called biota). While it only represents a very thin layer of the planet (roughly 0.4 per cent of the planet’s radius (Common and Stagl, 2004), biota plays a key role in influencing the composition of the atmosphere and thus the climate of the planet. Plants perform photosyn-thesis, a process by which they use energy from solar radiation and specific enzymes to trans-form carbon dioxide from the atmosphere and water from the hydrosphere into glucose (a car-bohydrate) and oxygen (Figure 14). During this process, they extract large amounts of carbon from carbon dioxide present in the atmosphere and store it in the form of glucose, and release oxygen, a by-product of photosynthesis, into the atmosphere. The biosphere also has an impact on atmospheric concentrations of other greenhouse gases like methane or nitrous oxide (Baede et al., 2001). Some digestive processes of animal species release for instance methane as a by-product.

Photosynthesis–thechemicalreactionFigure 14

6 CO2 + 6 H2O C6H12 O6 + 6 O2

Carbon dioxide Water Glucose Oxygen

Enzymes

Solar radiation

Source: Author.

The five components of the climate system inter-act in numerous ways, as schematically illustrat-ed by the thin arrows in Figure 12. For instance, water vapour is exchanged between the atmos-phere and the hydrosphere, carbon dioxide is con-stantly extracted from the atmosphere by plants from the biosphere, and ice sheets from the cryo-sphere influence the hydrosphere’s ocean circu-lations and levels. These are just a few examples of the physical, chemical, and biological interac-tions that make the climate system extremely complex. Some of these processes are still only partly known, and there may be processes that are still completely unknown (Baede et al., 2001).

All five components of the system and all pro-cesses happening within the system use energy. The balance between energy flowing into the sys-tem and energy leaving the system is called the energy balance. Changes in the energy balance have a profound impact on all the components and processes of the system. Given the crucial importance of the energy balance, Section 2.2 fa-

miliarizes readers with this term and discusses the natural greenhouse effect that is an integral part of the balance.

2.2Theearth’senergybalanceandthenatural greenhouseeffect

The planet’s energy balance influences all five components of the climate system that were in-troduced in Section 2.1.23 Understanding the en-ergy balance and how it can be altered is there-fore of crucial importance for understanding the mechanisms behind climate change.

Solar radiation is the energy source that powers the entire climate system. Roughly 50 per cent of solar radiation consists of visible light, with the rest consisting mostly of infrared and ultraviolet light (Baede et al., 2001). New satellite-based data allow for accurately quantifying the exchange of radiative energy between the sun, the earth, and space. However, it is more difficult to quantify energy flows within the climate system because

23 In this material, we also use the term “radiative balance” as a synonym for energy balance.


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TheglobalmeanenergybalanceoftheearthFigure 15

Source: Wild et al. (2013: 3108).Note: TOA: top of the atmosphere. Wm-2: watts per square meter.

those flows cannot be directly measured. Conse-quently, it is not surprising that estimates of the global energy balance differ considerably (Wild, 2012). IPCC (2013a) updated its energy balance diagram in the fifth assessment report build-ing on the newly available estimates of Wild et al. (2013),24 which use satellite and ground-based radiation network data combined with models from the fifth IPCC assessment report.

Figure 15 provides a schematic illustration of the planet’s energy balance as outlined by Wild

et al. (2013) and used in the fifth IPCC report. Ar-rows represent radiation flows, numbers indicate best estimates of the magnitude of these flows, and numbers in parentheses provide the uncer-tainty range of these magnitudes, representing present-day climate conditions at the beginning of the 21st century. Accounting for day and night as well as for different yearly seasons, an aver-age amount of energy equivalent to 340 watts per square meter (Wm-2) enters the earth’s at-mosphere, and hence the environmental system, each second.

24 In the third and fourth assessment reports, the IPCC used the energy balance dia-gram of Kiehl and Trenberth (1997).

Of these 340 Wm-2, roughly 76 Wm-2 are directly reflected back to space by clouds, atmospheric gases, and aerosols. Another 24 Wm-2 reach the earth’s surface and are directly reflected back to space by the surface (due to surface reflec-tivity, technically referred to as surface albedo). As white light-coloured surfaces reflect more light compared to dark-coloured surfaces, most of these 24 Wm-2 are reflected back to space by snow fields, glaciers, ice sheets, and deserts. Of the remaining 240 Wm-2, roughly 79 Wm-2 are ab-sorbed by the atmosphere. This leaves 161 Wm-2 that warm the planet’s land surface and oceans (see the lower left-hand side of Figure 15). The planet’s land surface and oceans subsequently return this energy towards the atmosphere and space as sensible heat, water vapour, and long-wave infrared radiation.

In order to have a stable climate, there needs to be a balance between incoming solar radiation and out-going radiation emitted by the earth. Thus, the 240 Wm-2 of incoming radiation absorbed by the plan-et’s surface and atmosphere should be returned back to space. If this does not happen, the radiative balance of the planet is not in equilibrium. If signifi-cantly more radiation were to enter the planet than leave, the planet would become too hot for life; if significantly more radiation were to leave than en-ter, the planet would become too cold for life. Note that our planet’s energy balance is currently not in a complete equilibrium: Wild et al. (2013) as well as other recent studies (Hansen et al., 2011; Murphy et al., 2009; Trenberth et al., 2009) find a small posi-tive imbalance of the earth’s radiative balance. In fact, instead of 240 Wm-2, only 239 Wm-2 leave the planet (see the upper right-hand side of Figure 15).


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2The earth returns the incoming solar radiation as longwave infrared radiation,25 which is the heat energy you can feel, for instance, emanating out from a fire. The quantity and wavelengths of en-ergy radiated by physical objects are specific to the temperature of the object. Hotter objects ra-diate more longwave infrared radiation (in terms of magnitude and energy) than colder objects. In order to radiate 239 Wm-2 in longwave infrared radiation, the radiating surface should have an average temperature of roughly -19°C (Baede et al., 2001). However, the average temperature of the earth’s surface is not -19°C but 14°C. At this temperature, the surface alone radiates on aver-age 397 Wm-2 (Figure 15), which is a considerable higher amount than 239 Wm-2. So how is the planet able to “only” radiate the 239 Wm-2 re-quired to (almost) maintain its radiative balance and have at the same time a relatively high aver-age temperature on the surface?

As discussed in Section 2.1, the atmosphere con-tains several trace gases such as water vapour (H2O), carbon dioxide (CO2), methane (CH4), ni-trous oxide (N2O), and ozone (O3). These gases are able to absorb longwave infrared radiation from the surface of the planet and from the atmos-phere itself.26 Greenhouse gases then emit in-frared radiation in all directions. This means that they emit radiation towards space but also back towards the surface (see the right-hand side of Figure 15). The downward-directed flux, currently estimated at 342 Wm-2, heats up the lower lay-ers of the atmosphere and the surface, and thus maintains the relatively high surface tempera-ture of 14°C. Hence, greenhouse gases act like a “blanket” that traps heat in the lower layer of the atmosphere.27 This effect, known as the natural greenhouse effect, results in a net transfer of in-frared radiation from warm areas near the sur-face to higher levels of the atmosphere (Baede et al., 2001). The main part 28 of the 239 Wm-2 of out-going longwave radiation that are needed to bal-ance the incoming solar radiation is subsequent-ly radiated back towards space from relatively high altitudes and not directly from the surface. These areas in the higher level of the troposphere are approximately five km above the surface at mid-latitudes and have an average temperature of roughly -19°C (see the upper right-hand part of Figure 15). Thus, the natural greenhouse effect is an integral part of the planet’s energy balance system that is responsible for the relatively warm average temperature on the planet’s surface.

Having covered the components of the climate system as well as the radiative balance that in-fluences all these components, we can now turn

our attention towards climate change. Section 2.3 provides an overview and a classification of factors that can alter the climate system.

2.3 Internallyandexternallyinduced climatechange

Sections 2.1 and 2.2 showed that the earth’s cli-mate is shaped by factors that are internal to the climate system (i.e. processes within and be-tween components of the climate system, such as interactions between the atmosphere and oceans). It is important to understand that in addition to these internal factors, some external factors are also able to shape the climate. Why is this so?

Section 2.2 showed that the climate system is in its equilibrium if the net incoming solar radia-tion is balanced by the outgoing longwave radia-tion. Such an equilibrium is marked by a stable climate (e.g. stable mean temperature, mean precipitation, etc.). If the radiative balance of the planet changes, the climate is likely to change as well because through various interactions and feedback mechanisms a change in the radiative balance affects virtually all components of the climate system. For example, a change of the ra-diative balance can affect means or variances of climate variables but also other statistics such as the occurrence of extreme events (Baede et al., 2001; see Box 10 for a definition of extreme events). Hence, factors that are external to the climate system but somehow influence the ra-diative balance of the planet can also shape the climate. External factors can be further subdi-vided into natural external factors and human-induced (i.e. anthropogenic) external factors. The most obvious example of a natural external fac-tor is solar activity whose variations result in a changing amount of incoming solar radiation. Volcanic activity is another example: volcanic eruptions emit aerosol particles into the atmos-phere, which can influence the amount of incom-ing solar radiation reflected back towards space. Among the human-induced external factors, hu-man industrial activity influences greenhouse gas concentrations in the atmosphere and there-by affects the amount of longwave radiation that is being radiated from earth back towards space. In short, external factors (e.g. solar activ-ity, volcanic activities, or human activities) have an influence on so-called climate change drivers (e.g. solar radiation, aerosol particles, greenhouse gases),29 which in turn affect the radiative bal-ance and thereby shape the climate (see Figure 18 for a schematic illustration of externally induced climate changes).

25 In the text that follows we use the terms “longwave radiation,” “infrared radia-tion,” and “longwave infrared radiation” synonymously.

26 In other words, these greenhouse gases make the atmosphere opaque (i.e. impenetrable) to a lot of the longwave radiation emitted from the planet’s surface, but not to the incoming shortwave radiation, which explains why much of this incoming radiation can directly reach the surface.

27 Note that clouds also act as such a “blanket.” At the same time, due to their brightness, they reflect incoming solar radiation. As a net impact, clouds tend to have a slight cooling effect on the climate system (Baede et al., 2001).

28 With the exception of a small share of infrared radia-tion that is directly radiated from the surface through the so-called atmospheric window towards space.

29 Drivers of climate change are substances and processes that alter the planet’s energy balance.


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Extremeevents-schematicpresentationFigure 16

ExtremeeventsBox 10

30 Internally induced climate change means that factors internal to the climate sys-tem affect the mean or the variability of the climate, while externally induced climate change means that factors external to the climate system affect the mean or the variability of the climate.

31 See the IPCC reports listed in Annex 2 for additional rea-dings on internally induced climate variability.

32 Note that these concepts can a priori also be used to measure the influence of most internal factors on climate change.

Climate change does not only affect the means of climate variables such as temperature or precipitation, but can also affect the likelihood of the occurrence of extreme weather and climate events (Cubasch et al., 2013). Examples of such extreme events are droughts, cyclones, or heat waves. The Intergovernmental Panel on Climate Change (IPCC) defines an extreme weather event as an event that is “rare at a particular place and/or time of year. Definitions of ‘rare’ vary, but an extreme weather event would normally be as rare as or rarer than the 10th or 90th percentile of a probability density function estimated from observations” (Cubasch et al., 2013: 134). Extreme climate events can be defined as extreme weather events that persist for some time (Cubasch et al., 2013).

Cubasch et al. (2013) show that statistical reasoning can illustrate that increases or decreases of the frequency of extreme weather events (e.g. an increase of extremely hot days) can result from small changes in the dis-tribution of climate variables (e.g. an increase in the mean temperature). For example, Figure 16 displays the probability density function of temperature. Note that temperature is almost normally distributed (other climate variables such as precipitation are not normally distributed but have skewed distributions). Now suppose that climate change increases the mean temperature. As a result, the probability density function of temperature shifts to the right (i.e. average temperature increases) as illustrated by the solid curve in Figure 16. This shift of the average temperature affects the frequency of extreme events. On the one hand, one ob-serves more hot extremes; on the other, one observes fewer cold extremes. Changes in the variance, skewness, or shape of distributions can also affect the frequency of extreme events (see Cubasch et al., 2013: 134–35, for a more detailed discussion).

HotAverage

Temperature

Cold

Fewer cold extremes

(a) Increase in mean

More hot extremes

Source: Author's elaboration based on Cubasch et al. (2013:134).

The climate of our planet is thus shaped by fac-tors that are internal to the climate system and by factors that are external to the climate sys-tem (Baede et al., 2001). This implies that climate change, which is defined as a persistent variation in either the mean state of the climate or in its variability (see the introduction to Section 2), can be induced internally or externally.30 The El Niño-Southern Oscillation (ENSO), described in Box 11, is an example of an internally induced climate vari-ability (Baede et al., 2001). The ENSO is the result of an interaction between the atmosphere and

the Pacific ocean, and affects different climate variables such as precipitation and temperature in many parts of the world. As this teaching ma-terial focuses on human-induced (i.e. externally induced) climate change, we will not address internally induced climate variability further,31 and limit ourselves to a discussion of externally induced climate change. To do so, Section 2.4 will introduce two concepts – radiative forcing and ef-fective radiative forcing – that allow for measur-ing the influence of natural and human-induced external factors on climate change.32


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2

Correlationsofsurfacetemperature,precipitationandmeansealevelpressurewiththeSouthernOscillationIndex

Figure 17

TheElNiño-SouthernOscillation–anexampleofaninternalinteractionamongcomponentsoftheclimatesystemaffectingthemeansandvariabilityofdifferentclimatevariables

Box 11

El Niño-Southern Oscillation (ENSO) events are naturally occurring phenomena that result from an interaction be-tween the atmosphere and the hydrosphere. According to the Intergovernmental Panel on Climate Change (IPCC), “El Niño involves warming of tropical Pacific surface waters from near the International Date Line to the west coast of South America, weakening the usually strong sea surface temperature (SST) gradient across the equato-rial Pacific, with associated changes in ocean circulation. Its closely linked atmospheric counterpart, the Southern Oscillation (SO), involves changes in trade winds, tropical circulation and precipitation” (Trenberth et al., 2007: 287). Historically, the ENSO alternates between two states: El Niño and La Niña, each of which has specific regional impacts on climate variables such as temperature or precipitation (Figure 17). For example, surface temperature is above average during El Niño events and below average during La Niña events in the eastern tropical Pacific region. El Niño events occur every 3 to 7 years and alternate with their counterpart La Niña (Trenberth et al., 2007).1

Source: Trenberth et al. (2007). Note: Correlations with the Southern Oscillation Index (SOI), based on standardized Tahiti minus Darwin sea level air pres-sure, for annual (May to April) means of sea level air pressure (top left), surface temperature (top right) for 1958 to 2004, and precipitation for 1979 to 2003 (bottom left). In the SOI graph (bottom right), red (blue) values indicate El Niño (La Niña) condi-tions. The graph shows the long-term periodic fluctuation between these conditions since 1850.

Source: Author's elaboration based on Trenberth et al. (2007).1 An intuitive explanation of the El Niño-Southern Oscillation can be found in geoscientist Keith Meldahl’s video (available at https://www.youtube.com/watch?v=GTgz6ie2eSY). A more extensive explanation of the phenomenon is provided by a Yale University open course given by Ronald Smith, a professor of geoscience, geophysics and mechanical engineering, available at https://www.youtube.com/watch?v=bK-n0CeFWtk.

The ENSO influences regional climate patterns in several parts of the globe and has a global impact on climate variables such as surface temperature and precipitation. Figure 17 illustrates these effects based on annual mean correlations between the climate variables and the Southern Oscillation Index (SOI). The SOI (bottom right panel) uses observed atmospheric pressure at sea level to infer the presence of El Niño and La Niña events. It is calculated as the standardized air pressure in Tahiti (Eastern Pacific) minus the standardized air pressure in Darwin, Australia (Western Pacific). Positive values (higher pressure in Tahiti) indicate a La Niña event; negative values (higher pressure in Darwin) indicate an El Niño event. The bottom left panel of Figure 17 shows the correlation between SOI and precipitation: one observes, for example, a strong positive correlation among the variables over the Western Pacific, indicating that this region experiences above (below) average precipitation during La Niña (El Niño) events. The upper right panel displays the correlation between SOI and surface temperature. One observes, for example, that there is a strong negative correlation between the two variables over the eastern tropical Pacific region, indicating that in this region, surface temperature is above (below) average during El Niño (La Niña) events. Thus, as shown in Figure 17, internal interactions such as the El Niño-Southern Oscillation can have significant effects on the climate.

192018901860 1950 1980 2010

-1

0

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1

Stan

dard

dev

iatio

ns

Year

Darwin southern oscillation index3

-3

-2


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2.4Measuringtheimportanceoffactors drivingclimatechange:radiativeforcing andeffectiveradiativeforcing

In theory, there are many ways to assess how strongly different external factors change the climate. One could, for instance, try to directly measure the effect of a change in a single cli-mate change driver (e.g. greenhouse gases) that has been induced by an external factor (e.g. hu-man industrial activity) on different climate variables (e.g. temperature and precipitation). However, identifying and isolating such effects is extremely difficult. Climate scientists there-fore rely on intermediate measures that quan-tify the influence of external factors on climate change indirectly. The basic idea behind these measures is rather intuitive. First, climate scien-tists measure how strongly the radiative balance is affected by an externally induced variation in a climate change driver. Then they estimate how this change of the radiative balance affects the climate (Figure 18). To do so, they use a measure called “radiative forcing.”

Radiative forcing is the most commonly used in-dicator that allows for capturing how externally induced changes in climate change drivers affect the radiative balance and subsequently change the climate (Myhre et al. 2013). The term “forcing” indicates that the radiative balance of the earth is forced away from its equilibrium state by an externally induced variation in a climate change driver (Perman et al., 2011).33 Intuitively, radiative forcing measures the radiative imbalance that occurs from an externally induced change in a climate change driver. IPCC (2001a: 795) defines radiative forcing as “the change in the net vertical irradiance (expressed in Watts per square metre: Wm-2) at the tropopause34 due to… a change in the external forcing of the climate system, such as, for example, a change in the concentration of carbon dioxide or the output of the Sun.”

While the radiative forcing concept is the most widely used measure to assess and compare the size of the radiative imbalance created by externally induced variations in climate change drivers, it has some weaknesses. The main one is that the concept keeps all surface and tropospheric properties fixed and does not allow them to respond to the changes induced by the variations in climate change driv-ers. In the fifth assessment report, the IPCC there-fore introduced a new, complementary concept called “effective radiative forcing.” Radiative forc-ing and effective radiative forcing are very similar, with the exception that effective radiative forcing allows some surface and tropospheric properties to respond to perturbations in the short term. Ef-fective radiative forcing is defined as “the change in [the] net top of atmosphere downward radiative flux after allowing for atmospheric temperatures, water vapour and clouds to adjust, but with sur-face temperature or a portion of surface conditions unchanged… Hence effective radiative forcing in-cludes both the effects of the forcing agent itself and the rapid adjustments to that agent (as does radiative forcing, though stratospheric tempera-ture is the only adjustment for the latter)” (Myhre et al., 2013: 665). Due to the inclusion of short-term adjustments of some surface and tropospheric properties, the effective radiative forcing concept is believed to be a better indicator of potential tem-perature responses (Myhre et al., 2013).

Radiative forcing (and effective radiative forc-ing) can be negative or positive. Positive radiative forcing implies that incoming radiation is larger than outgoing radiation, leading to an energy increase in the environmental system (i.e. a posi-tive energy imbalance). To rebalance the system, temperatures in the surface-troposphere system have to increase. Negative radiative forcing im-plies that incoming radiation is smaller than out-going radiation (i.e. a negative imbalance), lead-ing to an energy decrease in the environmental system. To rebalance the system, temperatures in the surface-troposphere system have to decrease.

33 Climate change drivers are subsequently also called “for-cing agents,” while externally induced variations in climate change drivers are also called “external forcings” or some-times simply “forcings.” For the sake of simplicity, we do not adopt this terminology in this teaching material and continue to use the terms “climate change driver” and “externally induced variations in climate change drivers.” However, the terms “external forcings,” “forcings,” and “forcing agents” do appear in direct citations from the IPCC.

34 The tropopause is the boundary between the troposphere and the stratosphere (see Figure 13). For practical reasons, the tropopause is defined as the top of the atmosphere (see Ramaswamy et al., 2001, for a detailed discussion).

Source: Author's elaboration based on Forster et al. (2007: 134). Note: Non-initial radiative forcing effects have been omitted from the figure as they are not addressed by this teaching material. Feedback effects are discussed in Section 2.5.

Natural external factors

(e.g. solar activity, volcanic activity)

Human-inducedexternal factors(e.g. industrial activity)

Radiativeforcing

Feedbackeffects

Direct and indirectchanges in climate change drivers

(e.g. greenhouse gases, aerosols, solar irradiance)

Climate perturbationsand responses

(e.g. temperature, precipitation, extreme weather events)

ExternallyinducedclimatechangesFigure 18


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2Before we focus entirely on human influences on the climate in Section 2.5, let us briefly il-lustrate the radiative forcing concept by listing some examples of radiative forcing induced by certain natural external factors. First, let us con-sider solar activity. Solar activity, and hence solar output, is not constant but fluctuates over time at various time scales, including centennial and millennial scales (Myhre et al., 2013). Solar output has increased gradually during the industrial era (from 1750 up until today), which has led to an increase in incoming solar radiation and thereby caused a small amount of positive radiative forc-ing. This has had a small warming effect on the surface-troposphere system (Forster et al., 2007). Another natural external factor, the astronomical alignment of the sun and the earth, also varies and induces cyclical changes in radiative forcing. However, these changes are only substantial over very long time horizons, and partially explain, for instance, different climatic periods such as ice ages (Myhre et al., 2013). Volcanic eruptions are another natural external factor that can, over a short period of time lasting from several months up to a year, increase the concentration of sul-phate aerosol particles in the stratosphere that block parts of incoming solar radiation, induc-ing short-term negative radiative forcing, which tends to have a cooling effect on the surface-troposphere system (Forster et al., 2007).

While such natural external factors are important, they have played a relatively small role during the industrial era. In its fifth assessment report, the IPCC states that “there is a very high confidence that industrial-era natural forcing is a small frac-tion of the anthropogenic forcing except for brief periods following large volcanic eruptions. In particular, robust evidence from satellite obser-vations of the solar irradiance and volcanic aero-sols demonstrates a near-zero (-0.1 to +0.1) Wm-2 change in the natural forcing compared to the anthropogenic effective radiative forcing increase of 1.0 (0.7 to 1.3) Wm-2 from 1980 to 2011. The natu-ral forcing over the last 15 years has likely offset a substantial fraction (at least 30 per cent) of the anthropogenic forcing” (Myhre et al., 2013: 662).

2.5 Human-inducedclimatechange

After outlining basic mechanisms that influence the climate system and introducing concepts that allow for measuring climate change, we are now equipped with the necessary tools to ana-lyse human-induced climate change.

Human activities cause changes in the amounts of greenhouse gases, aerosols, and clouds in the earth’s atmosphere. These human-induced

changes in climate change drivers influence the planet’s radiative balance and hence the climate system. Human activities also change the land surface of the planet, which can effect, for in-stance, surface reflectivity (albedo), influencing the radiative balance and thus also the climate system (IPCC 2001b, 2007, 2013a). The sections that follow first discuss these human-induced changes in climate change drivers separately, then assess their respective impact on the radia-tive balance, and finally take a look at feedback effects that can amplify or reduce the impacts of the different climate change drivers.

2.5.1 Human-induced greenhouse gas emissions and the enhanced greenhouse effect

The main greenhouse gases emitted by human activities are carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and halocarbons (Forster et al., 2007). Carbon dioxide, methane, nitrous oxide, and many halocarbons are called “well-mixed greenhouse gases” because they mix sufficiently in the troposphere for reliable concentration measurements to be made from only a few re-mote observations (Myhre et al., 2013).

Anthropogenic carbon dioxide emissions mainly result from human use of fossil fuels in sectors such as transportation, energy, and ce-ment production. Anthropogenic methane is mostly emitted during agricultural activities and natural gas distribution, and from landfills. Anthropogenic nitrous oxide emissions stem mostly from burning of fossil fuels and the use of fertilizers in agricultural soil. Anthropogenic halocarbons, which include chlorofluorocarbons (see also Box 14 in Module 3), are emitted by di-verse industrial activities and have in the past also been released by refrigeration processes. In addition to the four main greenhouse gases, human activities also emit other pollutants such as carbon monoxide (CO), volatile organic compounds, nitrogen oxides (NOx), and sulphur dioxide (SO2). While these gases are negligible greenhouse gases, they indirectly influence con-centrations of other greenhouse gases such as methane or ozone through chemical reactions (Cubasch et al., 2013).

So how strongly have humans influenced atmos-pheric concentrations of greenhouse gases?

Instrumental measurements provide accurate atmospheric GHG concentrations back to 1950, while indirect measures are used for dates prior to 1950: ice core data allow for analysing air bub-bles enclosed in ice and thus provide an indirect record of past atmospheric concentrations of


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Source: Forster et al. (2007: 135).Note: Concentration units are parts per million (ppm) or parts per billion (ppb), indicating the number of molecules of the greenhouse gas per million or billion air molecules, respectively, in an atmospheric sample.

well-mixed greenhouse gases (Masson-Delmotte et al., 2013). Figure 19 combines data based on in-strumental measurements and ice core data to show that while atmospheric carbon dioxide,

methane, and nitrous oxide concentrations were fairly stable for more than a thousand years be-fore the industrial revolution (starting around 1750), they have increased rapidly since then.

Atmosphericcarbondioxide,methaneandnitrousoxideconcentrationsfromyear0to2005Figure 19

10005000 1500 2000

300

350

CO2 (p

pm), N

2O (p

pb)

CH2 (p

pb)

Year

400

250

1000

1200

1400

1600

1800

2000

600

800

Carbon dioxide (CO2)

Methane (CH4)

Nitrous oxide (N2O)

Ice core data also allow us to look further back in history and track atmospheric GHG concentra-tions dating several hundreds of thousands of years. The fifth IPCC assessment report provides information covering the past 800,000 years (IPCC, 2013a). Data indicate that pre-industrial ice core GHG concentrations stayed within natural limits. For carbon dioxide, maximum concentra-tions of 300 parts per million (ppm) and mini-mum concentrations of 180 ppm have been found. For methane, data indicate maximum concentra-tions of 800 parts per billion (ppb) and minimum concentrations of 350 ppb. And for nitrous oxide, ice core data show maximum concentrations of 300 ppb and minimum concentrations of 200 ppb (Masson-Delmotte et al., 2013). The fifth IPCC assessment report reaches the conclusion that “it is a fact that present-day (2011) concentrations of CO2 (390.5 ppm), CH4 (1803 ppb) and N2O (324 ppm) exceed the range of concentrations recorded in the ice core records during the past 800 ka.35 With very high confidence, the rate of change of the observed anthropogenic WMGHG [well-mixed greenhouse gases] rise and its RF [radiative forc-ing] is unprecedented with respect to the highest resolution ice core record back to 22 ka for CO2, CH4 and N2O, accounting for the smoothing due to ice core enclosure processes. There is medium confi-dence that the rate of change of the observed an-thropogenic WMGHG rise is also unprecedented with respect to the lower resolution records of the past 800 ka” (Masson-Delmotte et al., 2013: 391).

In short, given the data and the methods to de-termine the origin of GHG emissions,36 the sci-

entific community has reached a consensus: hu-mans have substantially altered the composition of the atmosphere and continue to do so. Since the industrial revolution, anthropogenic GHG emissions have substantially increased GHG con-centrations in the atmosphere (IPCC 2001b, 2007, 2013a). The rate of this increase is unprecedented over the last 800,000 years, and the concentra-tions are currently higher than all concentra-tions recorded in ice cores over those years (IPCC, 2013a). So how does this human-induced change of the atmosphere affect the climate?

The answer is relatively straightforward: the anthropogenic increase in GHG concentrations amplifies the natural greenhouse effect (see Sec-tion 2.2). Increased GHG concentrations lead to an increased rate of absorption and subsequent emissions of infrared radiation coming from the surface. In other words, increased GHG concen-trations increase the atmosphere’s opacity to longwave radiation, but more so at lower alti-tudes where air density and GHG concentrations are higher than at higher altitudes where they are both lower. Thus the share of upward flux longwave radiation leaving the atmosphere from higher, relative to lower altitudes, increases. As a result of the increase in GHG concentrations, the altitudes from where earth’s radiation is emit-ted towards space thus become higher. At these higher altitudes, the troposphere is colder (Figure 13) and therefore, less energy is emitted towards space, causing a positive radiative forcing (Baede et al., 2001). This effect is called the enhanced greenhouse effect.

35 ka is a unit of time indica-ting a thousand years. 36 For instance, one can analyse the changing isotopic composition of atmospheric CO2. By doing so, it can be shown that the observed increase in the atmospheric CO2 concen-tration is of anthropogenic origin, because the changing isotopic composition of atmospheric CO2 betrays the fossil origin of the increase (Baede et al., 2001).


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22.5.2 Human-induced changes in aerosols

In addition to increasing concentrations of greenhouse gases, human activities also increase the amount of aerosols in the atmosphere (IPCC 2001b, 2007, and 2013a). Atmospheric aerosols are generated either by emissions of primary particulate matter or by formation of second-ary particulate matter from gaseous precursors. These consist mainly of inorganic compounds (e.g. sulphate, nitrate, ammonium, sea salt), or-

ganic matter, black carbon, mineral compounds (e.g. desert dust) and primary biological aerosol particles (Boucher et al., 2013). Humans emit aer-osols through diverse industrial, energy-related, and land-use activities (Baede et al., 2001). Unlike greenhouse gases, aerosols remain in the atmos-phere only for a short time as they are washed out by rain. Figure 20 provides an overview of key properties of the main aerosols in the tropo-sphere, including their main sources and their most important climate-relevant properties.

KeypropertiesofmainaerosolsinthetroposphereFigure 20

Aerosol species Size distribution Main sources Main sinks Tropospheric

lifetimeKey climate-

relevant properties

Sulphate Primary: Aitken, accumulation and coarse modesSecondary: Nucleation, Aitken, and accumula-tion modes

Primary: marine and volcanic emissionsSecaondary: oxidation of SO2 and other S gases from natural and anthro-pogenic sources

Wet depositionDry deposition

~ 1 week Light scattering. Very hygroscopic. Enhances absorp-tion when depos-ited as a coating on black carbon. Cloud condensation nudei (CCN) active.

Nitrate Accumulation and coarse modes

Oxidation of NO2 Wet depositionDry deposition

~ 1 week Light scattering. Hygroscopic. CCN active

Black carbon Freshly emitted: <100 nmAged: accumulation mode

Combustion of fossil fuels, biofuels and biomass


1 week to 10 days

Large mass absorp-tion efficiency in the shortwave. CCN active when coated. May be ice nudei (IN) active.

Organic aerosol

POA: Aitken and accumulation modes. SOA: nucleation, Aitken and mostly accumula-tion modes. Ages OA: accumulstion mode

Combustion of fossil fuel, biofuel and biomass. Continetal and marine ecosystems. Some an-thropogenic and biogenic non-combustion sources


~ 1 week Light scattering. Enhances absoption when desposited as a coatind on black carbon: CCN active (depending on ag-ing time and size).

… of which brown carbon

Freshly emitted: 100–400 nmAged: accumulation mode

Combustion of biofuels and biomass. Natural humic-like substances from the biosphere


~ 1 week Medium mass absorption efficiency in the UV and visible. Light scattering.

… of which terrestrial PBAP

Mostly coarse mode Terrestrial ecosystems SedimentationWet depositionDry deposition

1 day to 1 week depending on size

May be IN active. May from giant CCN

Mineral dust Coarse and super-coarse ,modes, with a small accumulation mode

Wind erosion, soil resus-pension. Some agricultur-al practices and induytrial activities (cement)

SedimentationWet depositionDry deposition


IN active: Light scattering and absorption. Grennhouse effect.

Sea Spray Coarse and accumulation modes

Breaking of air bubbles induces e.g., by wave breaking. Wind erosion.



Light scattering. Very hygroscopic. CCN active. Can include primary organiccompounds in smaller size range

… of whichmarine POA

Preferentially Aitken and accumulation modes

Emitted with sea spray in biologically active oceanic regions


~ 1 week CCN active.

Source: Boucher et al. (2013: 597).Note: CNN: cloud condensation nuclei; IN: ice nuclei; OA: organic aerosols; POA: primary organic aerosols; PBAP: primary biological aerosol particles; SOA: secondary organic aerosols; UV: ultraviolet.


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The effects of increased amounts of aerosols on ra-diative forcing and hence the climate are still not fully known (Baede et al., 2001). As the fifth IPCC assessment report states, aerosols and clouds are still contributing the largest uncertainty to estimates of the changing energy balance of the planet (Boucher et al., 2013). Two main channels of effect have been identified. First, some aerosols (Figure 20) absorb and scatter incoming solar ra-diation, and to some extent also longwave radia-tion from the surface. They thus directly affect the radiative balance of the planet by sending parts of the incoming radiation back into space (hence one speaks of the “direct effect”). This direct ef-fect causes a negative radiative forcing (Baede et al., 2001; Boucher et al., 2013). Second, aerosols interact with clouds. According to Boucher et al. (2013), some aerosols (Figure 20) act as cloud con-densation nuclei (CCN) and ice nuclei (IN), around which cloud droplets and ice crystals form. Aero-sols thus play an important role in cloud forma-tion and are often described as “cloud seeds.” By interacting with clouds, aerosols indirectly influ-ence cloud albedo and the lifetimes of clouds (this effect is often referred to as the “indirect effect”). This has an impact on the reflection of incoming shortwave radiation as well as the absorption of outgoing longwave radiation by the atmosphere and thus on the planet’s energy balance.

2.5.3 Human-induced land-use change

Humans not only affect the climate by emit-ting GHG emissions and aerosols, but also by changing the surface characteristics of land. This so-called “land-use change” can result from various human activities including agriculture, irrigation, deforestation, urbanization, and traf-fic, and it influences physical and/or biologi-cal properties of the land surface (Baede et al., 2001). Hurtt et al. (2006) estimate that between 42 and 68 per cent of the total land surface was affected by human activities over the 1700–2000 period.

By changing the land surface, humans directly and indirectly alter the planet’s energy balance, water cycles, carbon cycles, and heat fluxes (Cu-basch et al., 2013; Myhre et al., 2013). Changes in physical properties of the land surface can influ-ence the reflectivity of the surface (land albedo) and hence affect the amount of incoming solar radiation reflected towards space, thereby direct-ly influencing the energy balance of the planet (Baede et al., 2001). Irrigation and other water-intensive activities can affect the water cycle and thus indirectly affect the energy balance. Chang-

es in biological properties can also have impor-tant consequences, especially in terms of GHG emissions. If humans convert forests into culti-vable land, they cut or burn the existing forests. They thereby destroy carbon sinks, which reduces carbon storage, releases carbon dioxide into the atmosphere, and changes surface albedo (Cu-basch et al., 2013). The combined effect of these physical and biological changes is complex and difficult to assess.

2.5.4 Human-induced radiative forcing

Sections 2.5.1 to 2.5.3 explained different ways in which humans influence climate change drivers, and thereby affect the radiative balance of the earth and thus change the climate. This leads to the question of the importance of the different ef-fects as well as the overall effect humans have on the climate. The previously introduced radiative forcing and effective radiative forcing concepts are very useful to this end. IPCC (1996, 2001, 2007, 2013a) estimated mean radiative forcing of each of the climate change drivers that are affected by humans. As knowledge about the climate system and climate change is constantly growing, these numbers have been revised several times. Figure A1 in Annex 1 provides an overview of the esti-mates of the different assessment reports.

Figure 21 displays the IPCC (2013a) estimates of radiative forcing (hatched) and effective radia-tive forcing (solid) of different climate change drivers over the 1750–2011 period. Uncertainties are displayed by dotted and solid lines that in-dicate 5 to 95 per cent confidence intervals. They vary widely depending on the climate change driver under consideration. The largest positive radiative forcings are due to carbon dioxide and other well-mixed greenhouse gases. Together, their human-induced concentration increases are responsible for an estimated radiative forc-ing of 2.83 Wm-2. Human-induced increases of tropospheric ozone (where ozone acts as a green-house gas) caused an effective radiative forcing of 0.4 Wm-2. Ozone increases in the stratosphere (where they block parts of incoming solar radia-tion) caused a negative radiative forcing of -0.1 Wm-2. Changes in surface albedo caused by land-use change are estimated to cause negative ef-fective radiative forcing (-0.15 Wm-2), while black carbon particles on snow and ice cause positive effective radiative forcing (0.04 Wm-2). The great-est uncertainty is associated with aerosols. While both aerosol-radiation and aerosol-cloud inter-actions are estimated to cause negative radiative forcing, confidence intervals are very large.


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2Radiativeforcingoftheclimatebetween1750and2011

Figure 21

Anth

ropo

geni

c

Forcing agent

Well-mixed greenhouse gases

Ozone

Surface albedo

Contrails

Aerosol-radiation interaction

Aerosol-cloud interaction

Total anthropogenic

Solar irradiance

Stratospheric water vapour from CH4

Nat

ural

Radiative forcing (Wm-2)-1 0 1 2 3

Contrail-induced cirrus

Black carbon on snowLand use

Stratospheric

Other WMGHGHalocarbons

CH4 N2O

CO2

Tropospheric

Source: Myhre et al. (2013: 697).Note: This figure is a bar chart for radiative forcing (hatched) and effective radiative forcing (solid) for the period 1750–2011. Uncertainties (5 to 95 per cent confidence range) are given for radiative forcing (dotted lines) and effective radiative forcing (solid lines). WMGHG: well-mixed greenhouse gases.

According to IPCC findings, total anthropogenic radiative forcing is virtually certain to be positive and is estimated to be 2.3 Wm-2. The probability of negative anthropogenic radiative forcing is estimated to be smaller than 0.1 per cent and thus exceptionally unlikely (Myhre et al., 2013). This confirms that human activities contribute to increase the level of solar energy stored in the climate system, which results in the warming of the lower atmosphere and the earth’s surface. Compared to the human influence, natural fac-tors had only a low influence on the planet’s en-ergy balance and thus on climate change (Figure 21). The IPCC (Myhre et al., 2013: 661) therefore concludes that “it is unequivocal that anthropo-genic increases in the well-mixed greenhouse gases [WMGHG] have substantially enhanced the greenhouse effect, and the resulting forcing continues to increase. Aerosols partially offset the forcing of the WMGHGs and dominate the uncertainty associated with the total anthropo-genic driving of climate change.”

2.5.5 Feedback effects and non-linearity

While we have seen that anthropogenic radia-tive forcing has been positive and has increased during the industrial era, hence warming the climate system, we have not yet discussed what specific impacts this radiative forcing has had on the climate system (see Section 3 for a dis-cussion of observed impacts, and Section 4 for a discussion of anticipated impacts). A priori we know that positive (negative) radiative forcing increases (decreases) the temperature of the cli-mate system.

However, this relationship is complicated because of the existence of so-called feedback effects that can either amplify or diminish the effect that specific radiative forcings have on variables such as temperature or precipitation (IPCC 2001, 2007, 2013a). Feedback effects that amplify the effect of driver-induced radiative forcing are called “posi-tive feedbacks,” while those that reduce the ef-fect of driver-induced radiative forcing are called “negative feedbacks” (Le Treut et al., 2007). Due to these internal feedback mechanisms, climate variables like temperature will in general not re-act in a linear way to changes in climate change drivers (IPCC 2001, 2007, 2013a).37 While a detailed discussion of all known feedback mechanisms is out of the scope of this teaching material, Figure 22 provides some examples that have been listed in the first chapter of the fifth IPCC report (Cu-basch et al., 2013).

Figure 22 schematically displays some key feed-back mechanisms related to increases in carbon dioxide concentrations that, as we have seen, cause positive radiative forcing and hence tend to warm the surface-troposphere system, all else being equal. Some of these feedback mecha-nisms are positive (i.e. they additionally warm the system), some are negative (i.e. they cool the system), and some can be positive or negative. For example, the so-called water-vapour feed-back is a positive feedback: as the planet gets warmer due to the stronger greenhouse effect, more water evaporates. This leads to an increase of water vapour in the atmosphere, where it acts as a strong greenhouse gas, further enhancing the greenhouse effect. Snow and ice albedo are

37 The example in the next paragraph illustrates this non-linearity.


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PositiveandnegativefeedbackmechanismsFigure 22

Source: Cubasch et al. (2013:128).Note: Climate feedbacks related to increasing CO2 and rising temperature include negative feedbacks (-), positive feedbacks (+) and positive or negative feedbacks (±). The smaller box highlights the large difference in timescales for the various feedbacks. GHG: greenhouse gas.

at the root of another positive feedback mecha-nism: increasing temperatures cause additional snow and ice to melt, which changes the size of the land surface. White reflecting surfaces are transformed into darker, absorbing surfaces. This lowers the planet’s reflectivity of incoming solar radiation and thus increases the amount of energy the planet’s surface absorbs, leading

to additional warming. If the average tempera-ture of the planet increases, the planet starts to radiate more infrared radiation, sending more energy back towards the atmosphere and ulti-mately space. This infrared radiation mechanism is an example of a negative feedback mechanism, which is however almost negligible for a small temperature change of the order of 1-4°C.

Shortsummary

Section 2 reviewed basic elements of climate science. It showed that the climate system has five components: atmosphere, hydrosphere, cryosphere, land surface, and biosphere. These components interact in complex ways. All of them depend on the planet’s energy balance (or radiative balance), i.e. the difference between the energy that flows into the climate system and the energy that flows out of the climate system. For a stable climate, incoming energy should equal outgoing energy. Section 2 explained that climate can change due to variations in factors that are either internal or external to the climate system. External factors such as hu-man activities can affect the climate by influencing climate change drivers such as atmospheric greenhouse gas concentrations. Externally induced changes in climate change drivers then change the energy balance of the planet and thus affect the climate. The radiative forcing concept introduced in Section 2 measures how strongly external factors influence the radiative balance. Positive radiative forcing indicates that more energy is flowing into the system than out of the system, leading to higher temperatures. Negative radiative forcing indicates that less energy is flowing into the system than out of the system, leading to lower tempera-tures. Section 2 then showed that human activities influence several climate change drivers (atmospheric greenhouse gases, aerosol concentrations, reflectivity of the planet’s surface) and have thereby caused overall positive radiative forcing since the start of the industrial era, which is heating up the planet. Section 2 con-cluded by highlighting the importance of feedback mechanisms that can amplify or diminish the effects that positive or negative radiative forcing has on different climate variables such as temperature or precipitation.


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23 Observedchangesin theclimatesystem

Section 2 introduced the climate system and ex-plained how it can be affected by human activi-ties. This section provides a short summary of hu-man-induced changes of the climate system that have been observed and assessed by the scientific community. To do so, we focus on observed chang-es as reported in the fifth IPCC assessment report.

IPCC reports observed changes in the climate based on research undertaken using a variety of different instrumental measurements. These measurements are either on-site measurements, which measure variables such as temperature or precipitation di-rectly on site, or off-site measurements. Off-site measurements (also called “remote sensing”) gath-er data from so-called remote sensing platforms,38 which measure climate variables from a certain distance (i.e. “off-site”). Instrumental data are com-plemented with paleoclimate reconstructions (e.g. the ice core data used to analyse carbon dioxide concentrations mentioned in Section 2.5), which al-low for extending the covered period considerably.

Based on an extensive review of available re-search, IPCC (2013b: 4) finds that the “warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprec-edented over decades to millennia. The atmos-phere and ocean have warmed, the amounts of snow and ice have diminished, sea level has ris-en, and the concentrations of greenhouse gases have increased.” In the text that follows, we take a closer look at the most important climate pertur-bations and responses (see the scheme in Figure

18) – namely, observed changes in mean tempera-ture, precipitation, ice cover, sea levels, and occur-rence of extreme events. The section concludes with a short overview of the impacts of these ob-served changes on human and natural systems.

3.1 Observedchangesintemperature

Climate change has resulted in an increase in the annual average global surface temperature. Data from several independent datasets concur that the combined mean land and ocean surface tem-peratures increased by 0.85°C over the 1880–2012 period. The magnitude of this increase lies with 90 per cent probability within the range of 0.65°C to 1.06°C. Over the 1951–2012 period, this increase is estimated to have been 0.72°C, lying with 90 per cent probability within the range of 0.49°C to 0.89°C (Hartmann et al., 2013). The longest avail-able dataset with data sufficiently detailed to al-low for calculating regional trends shows that al-most the entire planet experienced an increase of average surface temperature over the 1901–2012 period, as illustrated by Figure 23. It is important to note that while the long-term warming trend is highly robust, short-term temperature trends vary due to natural variability and are thus sensi-tive to the start and end year of the period under observation. This leads to a high inter-annual and decadal variation in short-term warming trends (Hartmann et al., 2013). As an example, the IPCC states that the rate of warming from 1998 to 2012 was slower than the overall rate from 1951 to 2012. The IPCC explains this lower rate by the fact that the 1998–2012 period started with a strong El Niño event, which led to a relatively high mean temper-ature in the first year of the measurement period.

38 Satellites are examples of remote sensing platforms.

Observedsurfacetemperaturechangesfrom1901to2012Figure 23

Source: IPCC (2013b: 6) based on Hartmann et al. (2013).


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Mean temperature increases can be observed not only at the planet’s surface, but also in oceans and in the troposphere. The IPCC states that it is virtually certain that the average tem-perature in the upper ocean (0 to 700 meters below the surface) increased over the 1971–2012 period, and it is likely that the temperature also increased during the 1870–1971 period (Rhein et al., 2013). Ocean temperature also likely in-creased in lower ocean segments during the 1975–2009 period (700 to 2,000 meters below the surface) and the 1992–2005 period (3,000 meters below the surface to the bottom of the ocean). Rhein et al. (2013) estimate that oceans have absorbed by far the most of the climate system’s energy increase (i.e. 93 per cent of the energy accumulated during 1971–2010). It is also virtually certain that the troposphere has warmed since the mid-20th century (Hartmann et al., 2013).

The IPCC states that it is extremely likely that human-induced changes in the climate sys-tem have been the dominant cause of these observed temperature increases. More spe-cifically, it states that it is extremely likely that more than 50 per cent of the increase in mean surface temperature is attributable to human-induced increases in GHG concentrations. Hu-man-induced variations in atmospheric GHG concentrations alone likely increased average surface temperature by 0.5°C to 1.3°C between 1951 and 2010. The joint effect of other human-induced variations in climate change drivers (e.g. aerosols) on mean surface temperature is likely to be within -0.6°C to 0.1°C, while naturally

induced changes only account for -0.1°C to 0.1°C. Human activities have also very likely substan-tially contributed to the observed warming of upper ocean levels and the troposphere (Bindoff et al., 2013).

3.2 Observedchangesinprecipitation

Climate change also affects precipitation lev-els. While the fourth IPCC assessment report concluded that global precipitation increased north of 30°N between 1900 and 2005 and has decreased in the tropics since 1971, the fifth as-sessment report relativizes these findings (Hart-mann et al., 2013). It states that even if all availa-ble long-term datasets point towards an increase in global mean precipitation over the 1901–2008 period, the order of magnitude of this increase varies widely depending on the data source. The IPCC thus attributes only a low confidence level to evidence indicating global precipitation in-creases over land surfaces prior to 1950 and a medium confidence level to evidence indicating precipitation increases after 1950.

Changes in precipitation seem to differ widely by region. Figure 24 displays precipitation increases in middle and higher latitudes in the northern and southern hemisphere. Hartmann et al. (2013) have medium confidence in the evidence sug-gesting that precipitation increased in mid-lati-tudes of the northern hemisphere for the period before 1950, and high confidence for the period after 1950. For all other regions, however, confi-dence in the evidence of precipitation increases is low due to data quality.

ObservedchangeinannualprecipitationoverthelandsurfaceFigure 24

Source: IPCC (2013b: 8) based on Hartmann et al. (2013).Note: mm yr-1: millimeters per year.


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2

Selectedobservedchangesinsnowcover,iceextentandsealevelFigure 25

Despite this uncertainty, the IPCC has medium confidence that human actions have contributed to these observed changes in mean precipitation since 1950. The IPCC also has medium confidence that since 1973, human activities have affected atmospheric humidity, which is another impor-tant variable of the hydrological cycle (Bindoff et al., 2013).

3.3 Observedchangesiniceandsnowcover

Ice and snow cover are also affected by climate change. The IPCC reports a very likely decrease of 3.5 to 4.1 per cent per decade in the extent of annual Arctic sea ice over the 1979–2012 period (in fact, the extent decreased in every season and in every decade after 1979 – see panel b in Figure 25). There is also high confidence that per-ennial and multi-year Arctic sea ice shrank over the same period and that the average winter sea ice thickness decreased between 1980 and 2012. Both the Greenland and Antarctic ice sheets have also been losing mass at an accelerated speed (Vaughan et al., 2013). Finally, there is very high confidence that the average snow cover in the northern hemisphere has decreased since the 1950s (see panel a in Figure 25).

These observed changes in the cryosphere are also at least partly human-driven. The IPCC esti-mates that it is (a) very likely that human actions have contributed to the sea ice loss in the Arc-tic since 1979; (b) likely that human actions have contributed to the ice surface melting of Green-land since 1993; (c) likely that human actions have contributed to the retreat of glaciers since the 1960s; and (d) likely that human actions have contributed to the snow cover reductions in the northern hemisphere (Bindoff et al., 2013).

3.4Observedchangesinsealevels

Global sea levels also respond to variation in climate change drivers. The IPCC has high confidence in find-ings suggesting that the rate of sea level rise since the 1850s is higher than the mean increase over the last 2,000 years. As panel c of Figure 25 shows, global sea levels increased by almost 0.2 meters over the 1901 to 2010 period. Most of these increases since the 1970s are attributable to the aforementioned re-ductions in glaciers and to the thermal expansion of oceans, which are due to the mean temperature in-creases in oceans (Rhein et al., 2013). Hence, the IPCC concludes that it is very likely that humans have also substantially contributed to the observed increase of sea levels since the 1970s (Bindoff et al., 2013).

Source: IPCC (2013b: 10).

1940 1960 1980 20001900 1920Year

1940 1960 1980 20001900 1920Year

(mill

ion

km2 )

(mill

ion

km2 )

(mm

)

30

35

40

8

6

4

10

12

14

1940 1960 1980 20001900 1920Year

8

6

4

10

12

14

45Northern hemisphere spring snow cover(a) (b) Artic summer sea ice extent

(c) Global average sea level change


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3.5 Observedchangesinextremeevents

Besides affecting mean states of variables such as temperature, precipitation, snow cover, ice cover, and sea levels, variations in climate change drivers have also altered the probability of occurrence of extreme events (see Box 10 for a

definition of extreme events), such as droughts, floods, heat waves, cyclones, or wildfires. Table 4 summarizes the IPCC’s evidence of changes in the occurrence of these types of extreme events, and provides an overview of its assessment of the role of humans in driving these observed changes.

ChangesintheprobabilityofoccurrenceofextremeeventsTable 4

Extreme event and direction of trendAssessment of whether changes

occurred (typically since 1950 unless otherwise indicated)

Assessment of a human contribution to observed changes

Warmer and/or fewer cold days and nights over most land areas. Very likely Very likely

Warmer and/or more frequent hot days and nights over most land areas Very likely Very likely

Warm spells/heat waves. Frequency and/or duration of increases over most land areas.

Medium confidence on a global scale.Likely in large parts of Europe, Asia, and Australia.

Likely

Heavy precipitation events. Increase in the frequency, intensity, and/or amount of heavy precipitation

Likely more land areas with increases than decreases. Medium confidence

Increases in intensity and/or duration of drought.

Low confidence on a global scale. Likely changes in some regions. Low confidence

Increases in intense tropical cyclone activity.

Low confidence in long-term (centen-nial) changes.Virtually certain in North Atlantic since 1970

Low confidence

Increased incidence and/or magnitude of extreme high sea level Likely (since 1970) Likely

Source: Author's elaboration based on IPCC (2013b: 7)

3.6Impactsonnaturalandhumansystems

Sections 3.1–3.5 showed that human-induced variations in climate change drivers such as at-mospheric greenhouse gas or aerosol concentra-tions have already affected the climate system to a considerable extent. These observed changes in temperature, precipitation, ice and snow, sea levels, and occurrence of extreme events have in turn had several impacts on natural and hu-man systems on a global scale (see Figure 26 for a schematic overview).

The IPCC’s evidence is the strongest for climate change impacts on natural systems (Field et al.,

2014). The IPCC has medium confidence that the observed changes in precipitation and snow and ice cover have affected hydrological systems and the quantity and quality of water resources. There is high confidence that climate change has af-fected various terrestrial, freshwater, and marine species. Some of these species have changed their geographical range, seasonal activities, and mi-gration routes in response to a changing climate (Field et al., 2014). The population sizes of species have also been affected by climate change: the IPCC reports, for instance, that climate change has increased tree mortality in some regions and con-tributed to the extinction of some animal species in Central America (Field et al., 2014).


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Source: Field et al. (2014: 42).

ObservedimpactsattributedtoclimatechangeFigure 26

Shortsummary

Section 3 reviewed changes in the climate system that have been observed and reported by the IPCC. It high-lighted that, in response to human activities, mean temperature increased, precipitation patterns changed, ice and snow cover diminished, and sea levels rose. The section also pointed out that the frequency of some extreme events such as the number of hot days increased as a result of human activities. The section con-cluded by reviewing the key impacts of these observed changes on human and natural systems.

While evidence is the strongest for natural sys-tems, some impacts on humans that are attrib-utable to a changing climate have also been reported. Overall, crop yields have been nega-tively affected. The IPCC has high confidence in evidence suggesting that negative impacts on crop yields have been more frequent than posi-tive impacts on crop yields (Field et al., 2014). In particular, wheat and maize yields seem to have been reduced as a result of a changing climate (medium confidence). While economic losses due to extreme weather events have increased on a global scale, the IPCC has only low confi-dence in evidence suggesting that these ob-served economic losses are directly attributable to climate change (Field et al., 2014). Evidence of negative health impacts attributable to climate change is spare but growing. The IPCC has me-

dium confidence in findings suggesting that heat-related mortality has increased and cold-related mortality has decreased regionally as a result of mean temperature increases. Medium confidence is also attributed to findings indicat-ing that the distribution of some waterborne illnesses has changed due to climate change (Field et al., 2014).

Evidence suggests that climate change has al-ready negatively affected human and natural systems. Furthermore, the IPCC expects that “the likelihood of severe, pervasive and irreversible im-pacts on people and ecosystems” will increase if humans continue to emit large quantities of GHG emissions and thereby change the climate system (Field et al., 2014: 62). Section 4 briefly discusses these possible future impacts of climate change.


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4 Anticipatedchangesintheclimate systemandpotentialimpactsof climatechange

Section 3 outlined the changes in the climate sys-tem that have been observed over past decades and explained that the main part of these chang-es is attributable to human actions. To inform policymakers about possible future changes in the climate system and to assess potential future impacts on humankind and natural systems, the IPCC relies on model predictions. This section in-troduces readers briefly to the different scenar-ios used by climate scientists to predict future changes in the climate system, outlines the most important anticipated changes, and lists key ex-pected impacts on human and natural systems.

In the fifth assessment report, IPCC reviews and assesses the results of numerous studies that use climate models to simulate future changes within the climate system. Climate models are mathematical models that describe key aspects and processes of the climate system. To simulate changes in the climate system, these models need information on how climate change drivers such as atmospheric greenhouse gas and aerosol con-centrations will evolve over the coming decades. As this information cannot yet be observed, re-searchers have to rely on plausible scenarios of the future. This means that they have to rely on infor-mation generated using plausible assumptions on how human activities will evolve and what consequences they will have on climate change drivers. To facilitate worldwide climate research, the IPCC provides such scenarios, which are called Representative Concentration Pathways (RCPs).

Each RCP is based on different assumptions about future economic activities, population growth,

energy sources, and other factors, and contains corresponding values of estimated future green-house gas and aerosol emission trajectories and concentrations until 2100. The IPCC provides four main scenarios, which are called RCP2.6, RCP4.5, RCP6.0, and RCP8.5. The numbers indicate the projected radiative forcing by the end of the 21st century (van Vuuren et al., 2011), e.g. RCP8.5 pro-jects radiative forcing of 8.5Wm-2 by 2100.

While a detailed discussion of all the assump-tions behind the RCPs is out of the scope of this teaching material, we will provide a short over-view of the main characteristics of each scenario. RCP2.6 assumes that drastic climate policy inter-ventions manage to reduce GHG emissions such that they peak before 2020, leading in 2100 to a slight reduction in today’s emission levels and atmospheric GHG concentrations that result in radiative forcing of 2.6 Wm-2 (Wayne, 2013). RCP2.6 can thus be viewed as the IPCC’s best-case scenario. Directly opposed to RCP2.6 is RCP8.5, which can be viewed as the IPCC’s worst-case scenario. RCP8.5 assumes a world with no addi-tional climate change policies and high popula-tion growth (Wayne, 2013). In this scenario, green-house gas emissions continue to grow over the entire century and result in radiative forcing of 8.5 Wm-2. RCP4.5 and RCP6.0 are located between these two “extreme” scenarios. In both of them, GHG emissions would peak during the century (however, considerably later than in RCP2.6), leading to radiative forcing of 4.5 Wm-2 and 6.0 Wm-2 by 2100, respectively. The solid lines start-ing from 2012 in Figure 27 illustrate the projected pathways of carbon dioxide emissions for all four scenarios. Note that IPCC (2014) estimates that if humans were to continue to live as they are today, they would end up in a scenario between RCP6.0 and RCP8.5.

CarbondioxideemissiontrajectoriesaccordingtothefourrepresentativeconcentrationpathwaysFigure 27

1950 2000 2050 2100Year

200

100

-100

0

Annu

al e

mis

sion

s (Gt

CO2/y

r)

Annual anthropogenic CO2 emissions

Historical emissions

RCP scenarios:

RCP8.5

RCP6.0

RCP4.5

RCP2.6

Source: IPCC (2014: 9).Note: GTCO2/yr: Gigatonnes of carbon dioxide per year; RCP: representative concentration pathways.


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PredictedincreasesinmeansurfacetemperatureFigure 28

Source: IPCC (2014: 63). Note: Dots indicate decadal averages, with selected decades labelled. The two overlapping dark-orange and grey surfaces indicate the spread of total human-induced as well as carbon-dioxide-induced warming obtained by different models and scenarios. GTCO2: Gigatonnes of carbon dioxide; GtC: Gigatonnes of carbon.

Numerous studies have used these four RCP sce-narios in their climate models to predict future changes in the climate system. Based on these studies, the IPCC anticipates major changes within the climate system that we summarize below separately for different climate variables (temperature, precipitation, snow and ice cover, and sea level).

Simulations based on all four scenarios predict an increase of mean temperature over the 21st century, as indicated by Figure 28. While the mag-nitudes of the rise in global mean surface tem-perature are comparable for all four scenarios over the 2016–2035 period, mean temperature estimates differ widely for the 2035–2100 period,

depending on the scenario (IPCC, 2014). Compared to the mean of pre-industrial temperature levels (1861–1880), RCP8.5 is estimated to lead to an in-crease of more than 4°C, RCP6.0 to an increase of roughly 3°C, RCP4.5 to an increase of roughly 2.5°C, and RCP2.6 to an increase below 2°C.40 As explained in Modules 1 and 4 of this teaching material, a mean temperature increase below 2°C is the main target of the Paris Agreement. This implies that “limiting total human-induced warming (accounting for both CO2 and other hu-man influences on climate) to less than 2°C rela-tive to the period 1861–1880 with a probability of >66 per cent would require total CO2 emissions from all anthropogenic sources since 1870 to be limited to about 2900 Gt” (IPCC, 2014: 63).

40 For the sake of clarity, the spread of these estimates has been omitted. However, the total spread (using all models and scenarios) of total human-induced war-ming and carbon dioxide-in-duced warming is displayed in Figure 28.

0

1

2

3

4

51000 2000 3000 4000 5000 6000 7000 8000

2090s

2090s

2090s

2090s

2000s

1990s

1970s

5000 1000 1500 2000 2500

Cumulative total anthropogenic CO2 emissions from 1870 (GtC)

Cumulative total anthropogenic CO2 emissions from 1870 (GtCO2)

Total human-induced warming

CO2 -induced warming

Tem

pera

ture

chan

ge re

lativ

e to

1861

– 18

80 (˚

C)

1940s

1880s

RCP8.5

RCP6.0

RCP4.5

RCP2.6

Unlike temperature, no clear global trend is iden-tifiable for precipitation. Some scenarios (RCP8.5) project an increase in annual mean precipitation for high latitude regions, for the equatorial Pacif-ic region, and for some mid-latitude regions, but a decrease in other mid-latitude and subtropical regions (IPCC, 2014). The IPCC also expects an in-crease in extreme precipitation events in some regions of the globe.

All simulations predict decreases in Arctic sea ice (RCP8.5-based simulations even predict a nearly ice-free Arctic ocean in the summer season be-fore the 2050s), near-surface permafrost (with expected decreases of 37 per cent in RCP2.6 up to 81 per cent in RCP8.5), and decreasing glacier

volume (with expected decreases of 15 to 55 per cent in RCP2.6 up to 35 to 85 per cent in RCP8.5, excluding glaciers in the Arctic and Greenland, and Antarctic ice sheets) (IPCC, 2014).

Finally, all RCP scenario-based simulations pre-dict ongoing increases in sea level over the entire 21st century. IPCC (2014) estimates that by 2081–2100, sea levels will have risen from 0.26 to 0.55 meters (RCP2.6) up to 0.45 to 0.82 meters (RCP8.5) compared to their 1986–2005 levels.

All these anticipated changes in the climate sys-tem will have impacts on human and natural systems. Generally speaking, IPCC (2014: 64) ex-pects that climate change “will amplify existing


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Source: IPCC (2014: 14).

risks and create new risks for natural and human systems. Risks are unevenly distributed and are generally greater for disadvantaged people and communities in countries at all levels of devel-opment. Increasing magnitudes of warming increase the likelihood of severe, pervasive, and irreversible impacts for people, species, and eco-systems. Continued high emissions would lead to mostly negative impacts for biodiversity, eco-system services, and economic development, and would amplify risks for livelihoods and for food and human security.”

Some of these risks are global, including (a) in-creased risk of ecosystem and biodiversity losses; (b) increased risk of food and water insecurity;

(c) increased risk of loss of rural livelihoods and income, especially affecting poor segments of the population; (d) increased risk to human health and of disrupting livelihoods due to ex-treme events and sea level rise; and (e) increased systemic risk as the anticipated increase in the frequency of extreme weather events could lead to breakdowns of infrastructure networks (IPCC, 2014). Other anticipated risks vary locally, as shown in Figure 29. IPCC (2014: 73) emphasizes that many “aspects of climate change and its as-sociated impacts will continue for centuries, even if anthropogenic emissions of greenhouse gases are stopped. The risks of abrupt or irreversible changes increase as the magnitude of the warm-ing increases.”

KeyanticipatedrisksperregionFigure 29

Shortsummary

Section 4 introduced readers to different scenarios used by the IPCC to predict future changes in the climate system. The section highlighted that it is likely that future changes in the climate system (such as increases in temperature) will occur as a result of human activities. It then concluded by showing that these anticipated changes in the climate system will have important negative impacts on human and natural systems.


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21 Whatisthedifferencebetweenweatherandclimate?

2 Name and define the five components of the climate system. Discuss two interactions among selectedcomponents.

3 DiscusstheglobalenergybalanceoftheplanetbyusingFigure15asabasisforyourdiscussion.Whyistheglobalenergybalanceofcrucialimportancefortheplanet’sclimatesystem?

4 Whyistheaveragesurfacetemperature14°Candnot-19°C?Definethenaturalgreenhouseeffect.

5 Listtwointernalfactorsthatcanaffecttheclimate.

6 Listfourexternalfactorsthatcanchangetheclimateandexplainhowtheycandoso.

7 Defineradiativeforcing.Whyisthisconceptausefultooltomeasuretheinfluenceofexternalfactorsontheplanet’sclimate?

8 Discussthedifferentwaysinwhichhumanactivitiescanaffecttheclimateoftheplanet.

9 Whathuman-inducedchangesinclimatevariablescanalreadybeobservedtoday?Discusschangesthataffectyourcountry.

10 WhatistheroleofscenariosintheIPCC’ssimulationoffutureclimatechangeimpacts?

11 Listfiveanticipatedimpactsofclimatechange.Discusswhichchangeswillbemostimportantforyourcountry.



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ANNEX 1

EstimatesofglobalmeanradiativeforcingprovidedbythedifferentIPCCassessmentreports

IPCCassessmentreports

Figure A1

Global mean radiative forcing (Wm-2) ERF (Wm-2)

SAR(1750–1993)

TAR(1750–1998)

AR4(1750–2005)

AR5(1750–2011) Comment AR5

Well-mixed greehouse gases(CO2, CH4, N2O, and halocarbons)

2.45 (2.08 to 2.82)

2.43 (2.19 to 2.67)

2.63 (2.37 to 2.89)

2.83 (2.54 to 3.12)

Change due to increase in concentrations

2.83 (2.26 to 3.40)

Tropospheric ozone

+0.40 (0.20 to 0.60)

+0.35 (0.20 to 0.50)

+0.35 (0.25 to 0.65)

+0.40 (0.20 to 0.60)

Slightly modified estimate

Stratosphericozone

-0.1 (-0.2 to -0.05)

-0.15 (-0.25 to -0.05)

-0.05 (-0.15 to +0.05)

-0.05 (-0.15 to +0.05)

Estimate unchanged

Stratospheric water vapour from CH4

Not estimated +0.01 to +0.03 +0.07 (+0.02 to +0.12)

+0.07 (+0.02 to +0.12)

Estimate unchanged

Aerosol-radiation interactions

Not estimated Not estimated -0.50 (-0.90 to +0.10)

-0.35 (-0.85 to +0.15)

Re-evaluated to be smaller in magnitude

-0.45 (-0.95 to + 0.05)

Aerosol-cloudinteractions

0 to -1.5(sulphate only)

0 to -2.0(all aerosols)

-0.70 (-1.80 to -o.30)(all aerosols)

Not estimated

Replaced by ERF and re-evaluated to be smaller in magnitude

-0.45 (-1.2 to 0.0)

Surface albedo (land use) Not estimated -0.20

(-0.40 to 0.0)-0.20

(-0.40 to 0.0)-0.15

(-0.25 to -0.05)

Re-evaluated to be slightly smaller in magnitude

Surface albedo (black carbon aerosol on snow and ice)

Not estimated Not estimated +0.10 (0.0 to +0.20)

+0.04 (+0.02 to

+0.09)

Re-evaluated to be weaker

Contrails Not estimated +0.02 (+0.006 to +0.07)

+0.01 (+0.003 to +0.03)

+0.01 (+0.005 to +0.03) No major change

Combined contrails and contrail-induced cirrus

Not estimated 0 to +0.04 Not estimated Not estimated 0.05 (0.02 to 0.15)

Total anthropologic Not estimated Not estimated 1.6 (0.6 to 2.4) Not estimated

Stronger positive due to changes in various forc-ing agents

2.3 (1.1 to 3.3)

Solar irradiance +0.30 (+0.10 to +0.50)

+0.30 (+0.10 to +0.50)

+0.12 (+0.06 to +0.30)

+0.05 (0.0 to +0.10)

Re-evaluated to be weaker

Source: Myhre et al. (2013: 696).Note: ERF: Effective radiative forcing; SAR: Second IPCC Assessment Report; TAR: Third IPCC Assessment Report; AR4: Fourth IPCC Assessment Report; AR5: Fifth IPCC Assessment Report.

URL

Fifth Assessment Report (AR5) https://www.ipcc.ch/report/ar5/

Fourth Assessment Report (AR4) https://www.ipcc.ch/report/ar4/

Third Assessment Report (TAR) https://www.ipcc.ch/ipccreports/tar/

Second Assessment Report (SAR) https://www.ipcc.ch/pdf/climate-changes-1995/ipcc-2nd-assessment/2nd-assessment-en.pdf

First Assessment Report (FAR) https://www.ipcc.ch/publications_and_data/publications_ipcc_first_assessment_1990_wg1.shtmlhttps://www.ipcc.ch/publications_and_data/publications_ipcc_first_assessment_1990_wg2.shtmlhttps://www.ipcc.ch/publications_and_data/publications_ipcc_first_assessment_1990_wg3.shtml

ANNEX 2


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Rhein M, Rintoul SR, Aoki S, Campos E, Chambers D, Feely RA, Gulev S, Johnson GC, Josey SA, Kostianoy A, Mauritzen C, Roemmich D, Talley LD, and Wang F (2013). Observations: ocean. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, and Midgley PM, eds. Cambridge University Press. Cambridge, UK and New York.

Trenberth KE, Fasullo JT, and Kiehl J (2009). Earth’s global energy budget. Bulletin of the American Meteorological Society 90: 311–24.

Trenberth, KE, Jones PD, Ambenje P, Bojariu R, Easterling D, Klein Tank A, Parker D, Rahimzadeh F, Renwick JA, Rusticucci M, Soden B, and Zhai P (2007). Observations: surface and atmospheric climate change. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, and Miller HL, eds. Cambridge University Press. Cambridge, UK and New York.

Van Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt GC, Kram T, Krey V, Lamarque JF, Masui T, Meinshausen M, Nakicenovic N, Smith SJ, and Rose SK (2011). The representative concentration pathways: An overview. Climatic Change 109: 5–31.

Vaughan DG, Comiso JC, Allison I, Carrasco J, Kaser G, Kwok R, Mote P, Murray T, Paul F, Ren J, Rignot E, Solomina O, Steffen K, and Zhang T (2013). Observations: cryosphere. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, and Midgley PM, eds. Cambridge University Press. Cambridge, UK and New York.

Wayne G (2013). The Beginner’s Guide to Representative Concentration Pathways. Sceptical Science. Available at: http://www.skepti-calscience.com/rcp.php?t=3.

Wild M (2012). New directions: a facelift for the picture of the global energy balance. Atmospheric Environment 55: 366–67.

Wild M, Folini D, Schär C, Loeb N, Dutton EG, and König-Langlo G (2013). The global energy balance from a surface perspective. Climate Dynamics 40: 3107–134.

Module 3The economics of

climate change

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1 Introduction

Module 1 showed that economic activities can influence the climate because the economy and the environment are interdependent. Module 2 explained the climate science behind climate change and showed how human activities con-tribute to change the climate. This module shows how economic theory explains the occurrence of transboundary environmental problems, such as climate change, and clarifies why it can be so dif-ficult to implement solutions to these problems even though those solutions are well known.

Neoclassical economic theory stipulates that markets allocate resources in an optimal, i.e. ef-ficient, way. At the same time, however, economic behaviour leads to important negative effects on the environment such as climate change. If markets allocate resources efficiently, how is it possible that severe environmental problems like climate change exist? Sections 2 and 3 of this module aim to answer this question.

Section 2 reviews the basic concepts of economic theory on markets and optimal allocations. It in-troduces the standard theoretical model describ-ing market economies and the concept of Pareto efficiency used to evaluate whether resources are allocated efficiently. It shows that, in theory, fully competitive markets allocate resources in a Pareto-efficient way and thus optimally from a social point of view. However, this theoretical result only holds up provided that certain assumptions are satis-fied; if these assumptions are not met, markets fail and generate outcomes that are not socially opti-mal. This is what is called a “market failure.”

Section 3 shows that climate change is the re-sult of such a market failure occurring because two assumptions are not met. First, contrary to the assumption of all commodities being pri-vate goods, the atmosphere is an open-access re-source (see Section 3.1). As such, there are no legal constraints on its use, and therefore any country can release any amount of greenhouse gases into the atmosphere at any time. Open-access re-sources cannot be “efficiently” exploited in mar-ket economies because countries tend to overuse them. Second, GHG emissions are negative exter-nalities (see Section 3.2). Negative because they detract from social welfare and externalities be-cause they are external to any accounting within the economic system. Economic agents do not take negative externalities into account when making their decisions, and consequently over-emit greenhouse gases into the atmosphere. Due to the combination of these two factors, markets fail to generate a Pareto-optimal situation. This

gives rise to climate change, considered to be the biggest market failure in human history.

Since markets have failed, policy interventions are needed to mitigate climate change. Even though it has been known for some time how policy in-terventions could mitigate climate change, the international community has been struggling for decades to solve the issue. Section 4 investi-gates how economic theory explains the inability of governments and societies to mitigate climate change. It shows that climate change mitiga-tion is a global “public good” that has non-rival and non-excludable benefits (see Section 3.1). As no country can single-handedly take actions to eliminate the threat of climate change, interna-tional cooperation is needed. However, such co-operation is extremely difficult to achieve when dealing with a global public good. To illustrate this difficulty, the section introduces game the-ory concepts that are used to analyse strategic interaction among countries. It shows that the main cause of the failure of collective action is that countries have strong incentives to free-ride and not contribute to reducing emissions. This leads to an outcome that is not socially optimal. The section concludes by drawing several lessons from game theory models that allow us to iden-tify ways to foster cooperation among countries.


• State the implications of the first welfare theorem;• Understand the conditions under which the

first welfare theorem does not hold and define market failures;

• Explain why the atmosphere is considered to be an open-access resource;

• Explain why greenhouse gas emissions are neg-ative externalities;

• Discuss why climate change is considered to be the biggest market failure in human history;

• Use game theory tools to analyse how econo-mists explain the fact that the international community has been struggling to implement climate change mitigation policies.

To support the learning process, readers will find several exercises and discussion questions in Sec-tion 5 covering the issues introduced in Module 3. Additional reading material can be found in Annex 1.

2 Thecompetitivemarketsmodel andParetoefficiency

Neoclassical economic theory stipulates that markets allocate resources efficiently. If this is in-deed the case, then why do markets sometimes


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fail to do so, producing highly inefficient out-comes leading to environmental problems such as climate change? To answer this question we first have to understand why economic theory concludes that markets produce efficient out-comes, in particular, understand (a) how econo-mists conceptualize market economies, and (b) how economists evaluate the efficiency of market economies. This section clarifies these two points and shows that, given certain conditions, eco-nomic theory predicts that markets indeed pro-duce efficient outcomes. Section 3 subsequently shows that in the context of climate change, some of these conditions are violated, and there-fore markets fail to achieve efficient outcomes.

2.1 Asimplemodelofmarketeconomies

Economic processes are inherently complex and difficult to understand. Economists thus rely on theoretical models of the economy to improve their understanding of these processes. Eco-nomic models are theoretical constructs that aim to represent different aspects of economic processes in a simplified way. They therefore rely on assumptions that might not necessarily hold in reality. Nevertheless, the models are very use-ful tools because they shed light on complex eco-nomic mechanisms and their relationships with the environment. Market economies, currently the dominant form of economic organization (Cohen, 2009), have been extensively studied and

modelled. Economists have developed a standard model of a competitive market economy,41 which we will now briefly introduce and which will serve as a starting point to understand how eco-nomic theory explains the occurrence of climate change.

In this standard model, the economy is assumed to be composed of economic agents (firms and households) acting purely in their own self-interest – i.e. trying to optimize their behaviour to achieve the outcome that is best for them. In other words, firms try to maximize their profits while households try to maximize their utility (i.e. consume a mix of goods and services that makes them as satisfied as they can be on a giv-en budget). The model assumes that there are many different markets, one for each commodity. Each competitive market connects demand (how much households are willing to pay for the com-modity) and supply (how much firms want to be paid to produce the commodity), thereby deter-mining how much of the specific commodity is produced. In such a competitive market, the price of a commodity adjusts until demand equals supply. This is called equilibrium. Put differently, a market is in equilibrium if the sum of the quanti-ties of commodities that households want to buy at current prices equals the quantities of com-modities that firms want to produce at current prices (see Box 12 for a graphical illustration of an equilibrium in a single competitive market).

41 Going into the details of the microeconomic foun-dations of the competitive market model is beyond the scope of this material. Interested readers may refer to standard microeconomic textbooks such as Varian (2010). Additional readings can also be found in Annex 1.

EquilibriuminasinglecompetitivemarketBox 12

Figure 30 displays a single competitive market for a normal good and shows the demand and supply curve for this particular good. The demand curve relates the quantity demanded by consumers to the market price. It is downward sloping, meaning that the cheaper the good, the more of it consumers are willing to buy. The supply curve relates the quantity supplied to the price and is upward sloping, meaning that the higher the price firms can charge, the more they are willing to supply. The market is in equilibrium at price P* and cor-responding quantity Q*, as this is the only point where demand equals supply. Note that given the supply and demand curves, this is the only equilibrium in this particular market. For any other price, supply does not equal demand. To see this, look for instance at price Pl: at this price, consumers demand Q ld, but producers are only willing to supply Q ls. This situation is clearly not an equilibrium, as the quantity demanded is higher than the quantity supplied.

EquilibriuminasinglecompetitivemarketFigure 30

Q* Q ldQ l

s

Pl

P*

Price

Demand

Supply

Quantity

Source: Author.

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If all firms maximize their profits, all consumers maximize their utility given their budget con-straints, and all individual commodity markets are in equilibrium, then the resulting allocation of commodities and the corresponding set of prices is called a competitive equilibrium. Put differently, in this state, the whole market economy, and not only a single commodity market, is in equilibrium.

While the model allows us to understand how market economies allocate resources, it remains silent about how efficient those economies are in allocating these resources. This is important to know, however, as resources are scarce and al-locating them improperly is costly. Economists have tried to answer this question by using the competitive market model and a very specific concept of efficiency – Pareto efficiency – intro-duced in the next section.

2.2Paretoefficiency

Various conceptual tools are used to evalu-ate different allocations of resources. The most commonly used tool is called Pareto efficiency,42 named after the 19th century Italian economist Vilfredo Pareto. An allocation of resources in which one can find a way to make one or more persons better off without making another person worse off is called a Pareto-inefficient allocation. If there is no way to make one or more persons better off without making another person worse off an al-location is called a Pareto-efficient allocation.

Pareto-inefficient allocations are a priori not de-sirable. After all, if you could improve the situa-tion of at least one person without deteriorating the situation of another person, i.e. if you could “Pareto-improve” a situation, why not do it? When all such Pareto improvements have been made and no more are available, the allocation of resources is said to be Pareto-optimal.

While the Pareto-efficiency criterion is useful as a benchmark for evaluating whether or not an al-location is efficient, it has its limits. If two alloca-tions are Pareto-efficient, the criterion is unable to evaluate which of the two allocations is prefer-able. Amartya Sen (1970: 22) made this point ex-plicit by writing that an economy may be Pareto-efficient “even when some people are rolling in luxury and others are near starvation, as long as the starvers cannot be made better off without cutting into the pleasures of the rich... [A]n econ-omy can be Pareto optimal and still be perfectly disgusting.” Thus, Pareto efficiency does not al-low us to identify allocations that optimize jus-tice or equality. The criterion can only determine whether a society is allocating resources waste-fully or not (Mas-Colell et al., 1995) and whether allocations can be changed in a way that unam-biguously improves the welfare of a society.

2.3 Competitivemarketequilibria andParetoefficiency

Despite its limitations, Pareto efficiency allows for evaluating whether market economies, as mod-elled by the competitive market model, allocate resources efficiently. According to neoclassical eco-nomic theory, this is indeed the case. The first wel-fare theorem states that, as long as some conditions are satisfied, competitive markets’ equilibria are Pareto-efficient allocations.43 The first welfare the-orem thus formalizes Adam Smith’s conjecture in The Wealth of Nations in 1776 of an “invisible hand,” and is one of the most central theoretical results in economics. It implies that markets composed of economic agents acting purely in their own self-interest will achieve an allocation of resources that constitutes a social optimum from which nobody’s position can be improved without harming some-one else. Box 13 illustrates this through the exam-ple of production in a single market.

42 Pareto efficiency is sometimes also referred to as economic efficiency or Pareto optimality.

APareto-efficientlevelofproductioninasinglemarketBox 13

43 Lerner (1934, 1944) was the first economist to (graphical-ly) prove the existence of the first welfare theorem. Lerner (1944) also outlined the foundations of the second welfare theorem, stating that any Pareto-efficient equilibrium can be achieved by a market after lump-sum transfers of the initial wealth endowment, a theorem that was first formally proved by Arrow (1951).

Let us take an intuitive look at why market equilibria can be considered Pareto-efficient, using the example of production output in a single market. Figure 31 displays supply and demand curves of a normal good in a competitive market. As we have already seen, competitive markets determine the total quantity produced by taking into account how much consumers are willing to pay for the good and how much suppliers have to be paid to produce the good. In an equilibrium, demand and supply are balanced so that the willingness of con-sumers to pay an amount P* for an extra unit is equal to the willingness of suppliers to be paid the amount P* to supply an extra unit.

Why is the resulting equilibrium production amount considered to be Pareto-efficient? Suppose that in-stead of producing the equilibrium quantity Q*, suppliers would produce less, say, Ql. Then some producer would be willing to produce an additional unit and sell it at a price slightly above P lS, but well below the price that someone would be willing to pay for an extra unit (which would be a price slightly below P ld).


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44 In addition to the assump-tions highlighted in this section, there is an additional technical assumption on consumer preferences called local nonsatiation of prefe-rences, which also has to be satisfied for the first welfare theorem to hold (Mas-Colell et al., 1995: 549–50).

45 Note that, strictly spea-king, assumptions (e) and (f) are already implied by assumption (d). If enforceable private property rights for all resources and commodities do exist, then all benefits and/or costs accrue to the agent holding the property right for the commodity or resource. This implies that there would not be any externalities and only private goods. However, we follow Perman et al. (2011) and list these assumptions separately for the sake of clarity, as we will discuss assumptions (e) and (f) extensively in sections 3.1 and 3.2.

APareto-efficientlevelofproductioninasinglemarketBox 13

This would clearly be a win-win scenario, as by producing and exchanging that additional unit, at least these two persons would be better off. The same holds for all quantities below Q*. Thus as long as less than Q* is produced, at least one person could be made better off by increasing total production. Would producing a quantity greater then Q* also be a Pareto improvement? The answer is no. As the price any supplier asks for an extra unit produced would be higher than any consumer’s willingness to pay for that unit, nobody would buy this extra unit, and thus no person would be better off. At the same time, the supplier producing the extra unit that cannot be sold would be even worse off. Therefore, only the market equilibrium allocation Q* with the corresponding price P* can be considered to be a Pareto-efficient allocation. This is an intuitive illustration of the claim that competitive markets determine a Pareto-efficient amount of output.

APareto-efficientlevelofoutputinasinglecompetitivemarketFigure 31

Q*Q ls

P ls

Pld

P*

Price

Demand

Quantity

Supply

Source: Author's elaboration based on a similar discussion in Varian (2010: 310–12).

The first welfare theorem depends, however, on a series of assumptions that Perman et al. (2011: 103) call “institutional arrangements.” These ar-rangements have to be satisfied or the first wel-fare theorem does not hold and competitive mar-kets do not produce socially optimal situations. These assumptions require that (a) markets exist for all goods and services; (b) these markets are perfectly competitive (no agent can influence the price); (c) all agents have full information on cur-rent and future prices; (d) private property rights exist for all resources and commodities; (e) there

are no externalities; and (f) all commodities are private goods.44, 45 In reality, these assumptions are often violated (Sandler, 2004). Consequently, markets fail to achieve Pareto-efficient alloca-tions and economists speak of market failures, which can potentially have devastating conse-quences and lead to situations that are not so-cially optimal. As we will see in Section 3, climate change is the result of such a market failure. Some have even argued that climate change is the biggest market failure in human history (Stern, 2007).

Shortsummary

Section 2 reviewed basic elements of economic theory that are needed to understand how economic theory explains climate change. The section started by introducing the standard model of a competitive economy and discussed the concept of market equilibrium. It then briefly introduced the Pareto-efficiency criterion used to evaluate different allocations of resources. Finally, it showed that markets allocate resources in a Pareto-efficient way provided that certain conditions are satisfied, but fail to do so if these conditions are not met. These so-called market failures are at the heart of economists’ explanations of the occurrence of climate change and are analysed in greater detail in the following sections.

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3 Climatechange:Thegreatestmarket failureinhumanhistory

Section 2 of this module showed that, according to the first welfare theorem of neoclassical eco-nomic theory, markets composed of economic agents acting purely in their own self-interest al-locate resources in a Pareto-efficient way, i.e. pro-duce a socially optimal situation in which no one’s welfare can be improved without harming some-one else’s welfare. In this ideal theoretical world, human-induced climate change would not occur.

However, current empirical evidence points to-wards the existence of such human- induced cli-mate change (IPCC, 2014a). Economists maintain that this empirical finding is due to the viola-tion of two underlying assumptions of the first welfare theorem. The first of these assumptions, assumption (f), is that all goods have to be pri-vate goods. But since the atmosphere is an open-access resource (see Section 3.1), this assumption is violated. As we will see, open-access resources are very different from “normal” private goods, and markets cannot Pareto-efficiently handle the former. The second violated assumption, assump-tion (e), concerns the absence of any externality. As we will see in Section 3.2, GHG emissions are an example of a negative externality that again leads to a Pareto-inefficient outcome.

Because these two assumptions are violated, the first welfare theorem does not hold up, markets fail, and economic agents over-emit greenhouse gases, leading to growing GHG accumulation in the atmosphere that exacerbates climate change. In Sections 3.1 and 3.2, we discuss both violations in detail and show why climate change is consid-ered to be the result of a major market failure.

3.1 Theatmosphere:Anopen-accessresource

Theory tells us that markets achieve Pareto-op-timal allocations if they deal with private goods, but tend to fail if market systems involve non-private goods. This section will show that the at-mosphere, in its function as a GHG repository, is not a private good. The section will then help us understand the consequences of this fact.

Goods can be classified as private or public us-ing two criteria that characterize the benefits of their consumption: rivalry and excludability (Sandler, 2004; Perman et al., 2011).46 Benefits of consumption are rival when a unit of a good can only be consumed by one individual, meaning that one individual’s consumption is at the ex-pense of somebody else’s consumption. Benefits of consumption are excludable when one can

prohibit another person from consuming the good. Pure private goods are defined as having completely rival and excludable benefits. To illus-trate the concept, let us look at a particular pure private good: bread. If an individual eats a loaf of bread, the loaf is destroyed and cannot be eaten by anybody else. Thus, the benefits of consuming a loaf of bread are completely rival. At the same time, consuming bread is completely excludable, as bread comes in separable units and one can identify who owns a specific unit and thus has the right to consume it. The right to consume the loaf can be traded or gifted, but everything else is considered stealing and is punishable by law. This means that any individual not owning the right to consume the loaf can be excluded from eating a particular loaf of bread; in other words, the benefits of consuming the loaf are exclud-able. Bread, similar to most goods we consume in our daily life, is therefore a pure private good.

The opposite of pure private goods are pure public goods. These types of goods were first de-scribed in 1954 by the American economist Paul Samuelson (1954). The benefits of pure public goods are non-rival and non-excludable. Non-ex-cludability means that nobody can be excluded from consuming the good, and consumption en-titlements can be neither identified nor traded or gifted. Non-rivalry means that an individual can consume a particular unit of the good without affecting the possibility of another individual consuming the same unit. Let us illustrate this with a classical example of a pure public good: national defence. Once a certain level of defence is provided by the military, no citizen who is living within the country can be excluded from being protected by the military (in other words, from consuming the benefits of the provided defence level). Hence, the benefits of national defence are non-excludable. If a citizen consumes the pro-vided defence level, he or she does not diminish in the slightest the possibility of another citizen consuming the same level of defence. Thus, the benefits of national defence are also non-rival.

The economics governing pure private and pure public goods are thus very different. Within these two extreme cases, the literature identifies a vari-ety of goods with different degrees of rivalry and excludability, or in other words, with different degrees of publicness (Perman et al., 2011).47 For our purpose, we will not discuss all these differ-ent types of goods,48 but rather concentrate on one particular type – open-access resources – to which the atmosphere belongs.

Open-access resources are part of a larger class of goods called common-pool resources. They are

46 Note that some scholars (e.g. Tietenberg and Lewis, 2012) use the term “divisi-bility” as an equivalent of “rivalry.”

47 It is important to understand that the attri-bute “public” refers to the publicness property of rivalry and excludability, not to the way a good is produced (by public or private agents). It is possible that a public good is privately produced and/or a private good is publicly produced.

48 See Sanders (2004) for an overview on the different types of these goods.


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defined by Tietenberg and Lewis (2012: 629) as “common-pool resources with unrestricted ac-cess.” Because scholars are still struggling to un-ambiguously define common-pool resources, we will follow Ostrom (2008: 11) who defines them as “sufficiently large that it is difficult, but not im-possible, to define recognized users and exclude other users altogether. Further, each person’s use of such resources subtracts benefits that others might enjoy.” Thus, the benefits of consuming common-pool resources are rival (which distin-guishes them from pure public goods) but ex-cludable only with difficulties. If no individual or group owns a common-pool resource or is able to exercise full control over such a resource, the resource is called an open-access resource. Exam-ples of such open-access resources are fisheries, forests, or the atmosphere.

To be specific, the atmosphere is an open-access resource with respect to its function as a reposi-tory of GHG emissions. Everybody can use the atmosphere to dump their GHG emissions free of charge, and it is difficult (although not impos-sible) to restrain this usage. Thus, the benefits of using the atmosphere’s function as a GHG repos-itory are only partly excludable. Moreover, if firms and individuals use the atmosphere as a GHG re-pository, other firms and individuals cannot do the same without causing serious negative envi-ronmental consequences like climate change. In that sense, the benefits of using the atmosphere as a GHG repository are rival.

Considering that the atmosphere is an open-access resource and not a pure private good, economic theory tells us that it cannot be effi-ciently exploited by a market economy. If market economies exploit open-access resources such as the atmosphere, they tend to overuse these re-sources. The resulting market failure then leads to outcomes that are not socially optimal. The main reason for this overuse is the open access to the resource. As no individual or group is able to control who is dumping greenhouse gases into the atmosphere, economic actors adopt a “use it or lose it” mentality and use the GHG repository function of the atmosphere on a “first come, first serve” basis, thereby collectively overusing the re-source (Tietenberg and Lewis, 2012) by dumping massive amounts of greenhouse gases into the atmosphere. This problem is widely known as the “tragedy of the commons,”49 and is at the heart of economists’ explanation of the occurrence of climate change.

As we will see in Section 3.2, the overuse induced by the open-access problem is made worse by what economists call negative externalities: eco-

nomic agents make their decisions to exploit the atmosphere’s GHG repository function solely on the basis of their own benefits and costs. By do-ing so, they ignore the negative impact their GHG emissions have on others. This leads to a situa-tion in which no agent has an incentive to reduce its GHG dumping activities and to conserve the atmosphere’s capacity to absorb greenhouse gases.

3.2 Greenhousegasemissions:Anegative externalityproblem

Section 3.1 showed that market economies over-use the GHG repository function of the atmos-phere because they cannot efficiently manage open-access resources. In addition to the open-access problem, there is a second related factor contributing to the overuse of the atmosphere’s GHG repository function: emitting greenhouse gases is a negative externality problem. This is an additional reason why markets fail and hence climate change occurs.

An externality exists if actions by one economic agent unintentionally affect other agents. To be more precise, according to Perman et al. (2011: 121), an externality occurs if “the production or consumption decisions of one agent have an im-pact on the utility or profit of another agent in an unintended way, and when no compensation/payment is made by the generator of the impact to the affected party.” A priori, externalities can be positive or negative.50 Whereas positive ex-ternalities have a positive unintended effect on other agents, negative externalities have a nega-tive unintended effect on others. Vaccinations are examples of positive externalities. They pro-tect the vaccinated person as intended, but also have a positive unintended external effect, low-ering the probability that other non-vaccinated persons catch the disease. GHG emissions are a typical example of negative externalities. While they are the by-product of an intended produc-tion process, they have a negative unintended ef-fect on others by contributing to climate change.

Markets fail in the presence of externalities be-cause agents do not take these effects into ac-count when making their decisions. The reason why they do not take them into account is that, by definition, these effects are unintended and hence, there is no monetary reward or penalty to the agent generating the externality. Thus, in the case of positive externalities, generating the pos-itive effect, in itself, is not sufficiently encouraged as there is no reward for doing so. In the case of negative externalities the opposite happens: as there is no monetary punishment for generating

49 Actually, as noted by Common and Stagl (2004), the expression “tragedy of the commons” – introduced in a famous article by Garrett Hardin in 1968 – is mislea-ding because the problem is not related to common pro-perty rights, but to the open access to the common pro-perty. Thus, as Common and Stagl suggest, the tragedy should have been labeled “the open-access tragedy.” 50 Note that there are various ways to classify externa-lities. Besides classifying externalities into positive and negative, one can also classify them by the economic acti-vity in which they originate (production or consumption) and by the economic activity that they affect (production or consumption). See Perman et al. (2011) for an overview on classifications of different externalities.

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negative effects, agents are not sufficiently dis-couraged from generating them. Consequently, markets produce too much of the negative ex-ternality, thereby exacerbating the negative ex-ternal effect. As we will see, this is exactly what happens in the case of GHG emissions.

Human beings produce greenhouse gases as by-products of production processes (e.g. by burning fossil fuels to produce energy, by raising cattle, and through a very wide variety of other activi-ties). Emitting large quantities of greenhouse gases into the atmosphere causes climate change and thus indirectly imposes costs on present and future generations. These costs are not borne by the emitting firms or consumers of goods whose production emits greenhouse gases, but rather by all people across the planet, and by future gen-erations. Thus, when making a production and/or consumption decision involving GHG emissions, economic agents only take their personal costs and benefits into account, ignoring the addi-

tional costs they impose on others. Consequently, they emit more than what is socially optimal. To clarify this, let us look at Figure 32 for a graphical illustration of the case of production decisions involving greenhouse gases.51

Figure 32 displays a market for a given good from the point of view of a specific firm that emits greenhouse gases during its production process. The x axis displays the quantity produced and the y axis the price of the good. The demand curve represents consumers’ demand for the good. As usual, the lower the price, the more of the good people want to buy. Note that the demand curve also represents the firm’s private marginal bene-fits (PMB). A firm’s private marginal benefit corre-sponds, loosely speaking, to the price the firm can charge per unit produced. For simplicity, we shall assume here that there are no consumption-related externalities, and thus private marginal benefits equal social marginal benefits (SMB).52

51 The following example of a negative production externality closely follows the discussion in Common and Stagl (2004: 327–29).

52 Consumption-based externalities would drive a wedge between the marginal benefits perceived by a firm (PMB) and the marginal benefits perceived by society (SMB).

53 To be precise, it is possible that the firm bears some of the costs of climate change, but the bulk of these costs accrue either to other indi-viduals on the planet or to future generations.

Greenhousegasemissions:AnegativeproductionexternalityproblemFigure 32

QSO Q M

PM

PSO

PriceSMC

Demand (=PMB =SMB)

Quantity

PMC

Source: Author's elaboration based on Common and Stagl (2004: 327).

Figure 32 also displays a second curve labeled PMC, which stands for the firm’s private marginal costs. This curve indicates, loosely speaking, the costs the firm incurs for producing the last unit of its total production output. These costs are also used by the firm’s managers to decide how much the firm will produce. In order to maximize the firm’s profits, the manager will equate the firm’s PMCs with the firm’s PMBs (represented by the demand curve). Thus, the firm will produce the quantity QM, selling each unit at the price PM, as this is the only point where PMC equals PMB. The problem is that this allocation is not Pareto-efficient and thus not optimal from society’s point of view. Why is this the case?

As mentioned earlier, the firm emits greenhouse gases during the production process and thus contributes to climate change. The costs associat-ed with emitting greenhouse gases (i.e. the costs of climate change) are, however, not borne by the firm, but by the rest of the society.53 From the point of view of the society, these are additional costs associated with the production of the good that have to be taken into account. Therefore, the social marginal costs of producing the good (SMCs) are higher than the firm’s private margin-al costs (PMCs). The difference between the social marginal cost and private marginal cost is known as the external marginal cost and is given by EMC = SMC-PMC. In our example, the external margin-


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54 See Section 3.1 for a defini-tion of pure private goods.

al costs correspond to the climate change-related costs occurring as a result of greenhouse gases emitted during the production of the good. The Pareto-efficient point of production would thus not be the production level the firm chooses, but the pair QSO and PSO, where social marginal benefits equal social marginal costs. We thus see in Figure 32 that the firm produces too much of the good (QM instead of QSO) and sells the good at a price that is too low (PM instead of PSO) be-cause it ignores the climate change-related costs it imposes on others. The existence of the nega-tive production externality therefore leads to a market failure due to which the firm emits too much greenhouse gases into the atmosphere compared to a Pareto-efficient situation. This ex-

ample can be generalized and extended to also include negative consumption externalities, such as the pollution created by using cars.

In conclusion, as GHG emissions are negative ex-ternalities and the atmosphere can be used as an open-access resource to dump them, markets fail to achieve Pareto-optimal situations. Instead of optimally allocating resources, market econo-mies dump unprecedented quantities of GHG emissions into the planet’s atmosphere, and are thereby changing the climate of the earth. This massive market failure represents a danger for present and future generations and as such has been identified by Stern (2007) as the biggest market failure in the history of humankind.

Shortsummary

Sections 2 and 3 showed that while markets theoretically achieve Pareto-efficient outcomes, they fail to do so if some conditions are not satisfied. The occurrence of climate change is an example of such a failure, identi-fied by some influential authors as the biggest market failure in human history. As shown in Section 3, this failure has two causes. First, the atmosphere’s function as a GHG repository is an open-access resource and is therefore overused by economic actors because, unlike pure private goods, open-access resources cannot be efficiently dealt with by market economies. Second, greenhouse gas emissions are negative externalities. Economic actors do not directly bear the climate change-related costs associated with the emissions that they can dump free of charge into the atmosphere; consequently, they emit too much greenhouse gases. Together, these two reasons explain why markets fail and, hence, why climate change occurs.

4 Whyisitsohardtosolvetheclimate changeproblem?

As shown in Section 3, climate change occurs because markets fail and do not achieve Pareto-optimal allocations. As we have seen, rational economic agents, pursuing their own self-inter-est in an uncoordinated way, overexploit the at-mosphere’s GHG repository function and ignore the costs they impose on others. Consequently, they emit too much greenhouse gases into the atmosphere and cause climate change. There-fore, to solve the problem one cannot simply rely on a market system, as it is precisely this system that fails and which is at the root of the problem.

Climate change can only be fixed by a policy in-tervention that corrects the market failure. A pri-ori, the solution is simple: if humans emitted less greenhouse gas into the atmosphere, they could stop or at least considerably slow climate change. If each country’s politicians decided to cut GHG emissions, climate change could be mitigated or even avoided altogether. Thus, where is the prob-lem? Why is humankind still struggling to imple-ment this solution on a global scale? Since Man-cur Olson’s now-famous work in 1965, The Logic of Collective Action, economists have been working on a theory to explain this puzzling situation. Sec-

tion 4 will show how economic theory explains the fact that the international community has been struggling for decades to solve the climate change problem despite the fact that the appar-ently simple solution has long been known. As we will see, much of the problem is related to the fact that solving global environmental problems like climate change requires cooperation among countries, which is not necessarily easy to achieve.

4.1 Mitigatingclimatechange:Aglobal publicgood

Mitigating climate changes requires reducing anthropogenic GHG emissions (IPCC, 2014b). Economists conceptualize climate change miti-gation as a good that can be supplied and con-sumed. To supply the good, efforts have to be taken to reduce GHG emissions. Consumption of the good is passive: everybody can reap the benefits of climate change mitigation by living in a world that is not affected by the potentially catastrophic effects of a changing climate (IPCC, 2014a). However, climate change mitigation is not a “normal” good, i.e. it is not a pure private good like most of the commodities we consume in our daily lives.54 From an economist’s point of view, climate change mitigation is a so-called global public good (Ferroni et al., 2002; IPCC, 2001; Per-

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man et al., 2011; Sandler, 2004). The public-good nature of climate change mitigation is at the heart of economists’ explanation for the inability of the international community to solve the cli-mate change problem. As we will see in the sec-tions that follow, supplying global public goods in sufficient quantities is difficult and involves several problems that are hard to overcome.

Section 3.1 introduced pure public goods and de-fined them as those having non-excludable and non-rival benefits. As we explained, non-exclud-ability means that nobody can be excluded from consuming the good, i.e. once the goods are sup-plied, their benefits are instantly available to eve-rybody. Non-rivalry means that a particular unit of the good can be consumed by an individual or group without affecting the possibility of anoth-er individual or group consuming the same unit. Sandler (2004) compares this property of global public goods to magic, stating that, like magic, a unit of a public good can be consumed by any number of individuals without any degradation in quality or quantity of that unit.

Climate change mitigation has exactly these two properties and is thus considered to be a pub-lic good. If a country decides to reduce its GHG emissions, the benefits are instantly available to all humans worldwide. Cutting a country’s GHG emissions directly lowers the global GHG con-centration in the atmosphere and thereby slows climate change compared to a business-as-usual scenario. Thus all countries gain from such a re-duction. For the country that cuts its emissions, it is impossible to limit the benefits of its GHG reductions only to itself. The benefits of climate change mitigation are therefore non-excludable. Moreover, the benefits of climate change miti-gation are also non-rival. The benefit a country obtains from reducing its GHG emissions does not reduce in the slightest the benefits other countries obtain from this reduction. Thus, con-suming the benefits of GHG reductions does not affect the possibility of other nations enjoying these benefits. As the benefits are both non-rival and non-excludable, GHG reductions are con-sidered to be pure public goods. Moreover, given that the benefits of a country’s GHG reduction can be consumed by all countries on the globe, the literature has labelled climate change miti-gation a “global public good” (Ferroni et al., 2002; Perman et al., 2011; Sandler, 2004).

Supplying global public goods such as climate change mitigation is a challenge. As shown in Section 3, markets cannot efficiently supply this type of good because they cannot deal with non-private goods. Policymakers therefore need to in-

tervene and correct this market failure. But also nations struggle to supply global public goods. No country can single-handedly solve the prob-lem, as no single country can by itself change the composition of the world’s atmosphere and mitigate climate change (IPCC, 2001). Countries therefore need to collaborate in order to miti-gate climate change. As we will see, many of the problems associated with supplying global pub-lic goods come from the fact that the costs and benefits for one country do not only depend on that country’s actions, but also on the actions – or lack thereof – of other countries. This makes sup-plying (global) public goods what is called a “col-lective action problem” (Sandler, 2004). This type of problems often result in collective action fail-ures that occur when rational decisions by indi-vidual countries result in an inefficient outcome that a single country cannot change (Sandler, 2004). As we will show, the non-excludability of climate change mitigation has a devastating im-plication for the supply of such a good: instead of supplying the good by reducing GHG emissions, countries might just wait for other countries to supply the good and then, as they cannot be ex-cluded from receiving the benefits, benefit from the result. This is a behaviour that the literature calls “free-riding.” As every country can make the same reasoning, it is quite possible that at the end of the day no country will actually be reduc-ing its emissions.

Section 4.2 introduces basic theoretical elements of game theory, a theoretical tool that allows for systematically analysing the problems associat-ed with the strategic interactions between coun-tries trying to mitigate climate change.

4.2Basicgametheorynotionsandconcepts55

In order to understand why countries struggle to reduce their GHG emissions, or in other words, why countries struggle to supply the global pub-lic good of climate change mitigation, we have to introduce basic game theory tools. Using these tools will enable readers to understand the na-ture of the problem at stake and grasp different important concepts like free-riding. Game theory is a theoretical apparatus that allows for study-ing any form of strategic interaction among individuals, groups, or countries (Varian, 2010). Widely used to study political negotiations and economic behaviour, it is particularly useful to analyse the issues involved in collective action problems such as climate change mitigation. Be-fore we start with the analysis of climate change mitigation, we will introduce basic game theory notions and concepts that allow for analysing strategic interactions among countries.56

55 Note that this short review only covers the essential concepts and notions needed for the analysis of climate change mitigation. Annex 1 provides additional readings on game theory.

56 The presentation of basic notions of game theory in this section draws on Chapter 28 of Varian (2010).


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57 Actually, this is not com-pletely accurate. Formally, strategies are defined to be a “complete contingent plan, or decision rule, that specifies how the player will act in every possible distinguishable circumstance in which she might be called upon to move” (Mas-Colell et al., 1995: 228). However, as the game we are currently looking at consists of only one move (writing down the word) and the players have to write down the word simultaneously, and because we exclude the possibility of mixed strategies, the choices “Top” and “Bottom” are the two strategies of player A, while the choices “Left” or “Right” are the two strategies of player B.

Strategic interactions involve at least two indi-viduals or groups called “players.” A priori, any strategic interaction can involve many players and each player can have a large set of different strategies. An example of a strategic interac-tion would be climate change mitigation nego-tiations among different countries (the players), with each country pursuing its own strategy. A country’s strategy could be, for instance, to re-duce GHG emissions or to not reduce GHG emis-sions. A formal representation of such strategic interactions is called a “game.” Games are the game theorist’s tool to formally capture situa-tions in which individuals or groups interact in a context where their welfare not only depends on their own actions, but also on the actions of others (Mas-Colell et al., 1995). To introduce the basic game theory notions and concepts we limit ourselves for now to strategic interactions with only two players. This kind of game can be repre-sented in what is called a “payoff matrix.” To illus-trate how to represent a game in a payoff matrix, we use an example by Varian (2011: 522).

Suppose you have two players (player A and player B) playing a game. Each player has a sheet of paper and has to write one out of two words on his or her sheet. Player A can either write “Top” or “Bot-tom.” Simultaneously, player B can choose to write “Left” or “Right.” Player A does not see what player B is writing and vice versa. Each player will obtain a payoff that depends not only on his or her actions, but also on the actions of the other player. And each player has been informed about the potential pay-offs he or she could get before playing the game. In the game theory terminology, the players’ options to play the game are called “strategies.” Thus in this game, each player has two strategies: player A’s strategies are “Top” and “Bottom,” and player B’s strategies are “Left” and “Right”.57 After both play-ers have written down their word, the sheets of paper are examined and the players receive their payoffs. These payoffs are listed in a payoff matrix. The payoff matrix of this simple game is displayed in Figure 33. It shows the payoffs to each player for each combination of strategies, and it is known to each player before they start to play the game.

Payoffmatrixofatwo-playergamewithadominantstrategyequilibriumFigure 33

Source: Author's elaboration based on Varian (2010: 523).

Player B

Left Right

Player A

Top 2,3 1,2

Bottom 4,2 2,1

As an example, if player A plays the strategy “Top” and player B plays the strategy “Right,” we ex-amine the upper right field of the payoff matrix that contains the payoffs for this combination of strategies. If the players play in this way, player A will receive a payoff of 1 (the first entry in the upper right box), while player B will receive a pay-off of 2 (the second entry in the upper right box). Similarly, if player A plays “Bottom” and player B plays “Left,” we see in the lower left box of the matrix that player A will receive a payoff of 4 while player B receives a payoff of 2.

Having understood how one reads a payoff ma-trix, we can now ask ourselves what happens if these two players actually play this game. Player A has a strong incentive to always play “Bottom,” because the payoffs from playing “Bottom” (4 and 2) are always higher compared to the correspond-

ing payoffs of playing “Top” (2 and 1). Player B has a strong incentive to always play “Left,” as the payoffs from playing “Left” (3 and 2) are always higher than the corresponding payoffs of playing “Right” (2 and 1). Thus, we expect that in equilibri-um we end up in the lower left box of the matrix, as player A will always play “Bottom” and player B will always play “Left.”

We have been able to quickly find the solution to this game because each player has what is called a “dominant strategy,” which is a player’s best strategy regardless of what the other player plays (Mas-Colell et al., 1995).58 Here, player A’s “Bottom” strategy dominates his or her “Top” strategy, as the player will get a higher payoff playing “Bottom” no matter what player B choos-es. On the other hand, player B’s dominant strat-egy is playing “Left” because no matter what

58 Note that this kind of strategy is called “strictly dominant” as opposed to “weakly dominant,” but for the sake of simplicity we will not discuss this difference as it is not needed to understand our main point. For more information see the additional readings listed in Annex 1.

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player A plays, he or she will get a higher payoff if he or she plays “Right.” The resulting equilib-rium is therefore called a “dominant strategy equilibrium.”

As Varian (2010) points out, dominant strategy equilibria are simple to find, but do not happen often. Let us look at a game with the same rules

but a different payoff structure displayed in Fig-ure 34. As one can see, this game has no dominant strategies. If player A chooses “Top,” then player B wants to choose “Left,” but if player A chooses “Bottom,” then player B wants to choose “Right.” Thus there is no dominant strategy for player B (or for player A, as you can easily verify) and there-fore also no dominant strategy equilibrium.

59 The game theory work of Nash was popularized in Ron Howard’s 2001 biographical movie “A Beautiful Mind.”

60 As you can verify, using similar reasoning, “Bottom”/ ”Right” is a second Nash equilibrium in this game

61 One of the problems is that it is possible that a game has more than one Nash equilibrium, as illustrated by the game in Figure 34. Another problem is that some games might not have a Nash equilibrium if one considers only so-called “pure strategies.” Pure strategies are the ones we have looked at so far and which consist of choosing an option once and for all. Instead of choosing an option and playing this option with 100 per cent probability, players can also randomize their choices. If they do so, game theorists speak of “mixed strategies” or “randomized strategies.” When players play mixed strategies they assign probabilities to each of their choices and play the choices according to the probabilities assigned (Varian, 2010). If one takes mixed strategies into account, one can show that Nash equilibria exist for a fairly broad range of games, making the concept very popular (see Chapter 8 in Mas-Colell et al., 1995, for a discussion on this topic). We will not further discuss mixed strategies in this teaching material as we do not need them to analyse climate change mitigation.

Payoffmatrixofatwo-playergamewithtwoNashequilibriaFigure 34

Player B

Left Right

Player A

Top 4,2 0,0

Bottom 0,0 2,4

Source: Author's elaboration based on Varian (2010:524).

In real-life strategic interactions, players fre-quently do not have dominant strategies. Game theorists therefore developed alternative con-cepts that allow for analysing strategic inter-actions. One of these concepts, called the Nash equilibrium, was introduced in 1951 by John Nash, an American economist and Nobel Prize laureate.59 Instead of requiring that a player’s strategy be optimal for all possible choices of the other player, this concept only requires that a player’s strategy be optimal given optimal strategies of the other player (Varian, 2010). In other words, in a Nash equilibrium, each player’s strategy choice is the best strategy that the play-er can choose, given the strategy that is actually played by the other player. In that sense, Nash equilibria are weaker solution concepts than dominant strategy equilibria: each dominant strategy equilibrium is also a Nash equilibrium, but not each Nash equilibrium is a dominant strategy equilibrium.

In Figure 34, “Top”/”Left” would be such a Nash equilibrium: if player B plays “Left,” the best strate-gy player A can choose is to play “Top.” At the same time, if player A plays “Top,” the best strategy play-er B can choose is “Left.” Thus, “Top”/”Left” is a Nash equilibrium.60 Of course, neither of the two play-ers knows what the other player will play before they make their move, but each player might have some idea about what the other player’s choice will be. A Nash equilibrium can thus be interpret-ed as “a pair of expectations about each person’s choice such that, when the other person’s choice is revealed, neither individual wants to change his

behavior” (Varian, 2010: 525). For instance, if player A expects player B to choose “Left,” player A will choose “Top,” and if player B expects player A to choose “Top,” player B will choose “Left” and the game ends in the Nash equilibrium “Top”/”Left.” From this Nash equilibrium no player would want to unilaterally change his or her strategy if he or she had the opportunity, as the player could only lose. While the concept of the Nash equilibrium has several problems,61 it is a very useful concept to analyse strategic interactions.

Having covered the basic notions and concepts of game theory, we now have the necessary tools to analyse why countries struggle to reduce GHG emissions and solve the global climate change problem. Climate change mitigation involves a strategic interaction among countries, as a coor-dinated effort by different countries is needed to mitigate climate change. Using the game theory tools introduced above, we will analyse this stra-tegic interaction, showing what goes wrong and highlighting the reasons for the failure of the international community to mitigate climate change so far.

4.3Climatechangemitigation:Agametheory perspective

We now turn our attention towards the analysis of the decade-long failure of the international community to mitigate climate change. To do so we use game theory tools to model a strategic in-teraction among countries trying to supply the global public good of climate change mitigation.


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ReducinggreenhousegasemissionsinaworldcomposedoftwocountriesFigure 35

Country B

Not reduce Reduce

Country A

Not reduce 0,0 10,-2

Reduce -2,10 8,8

Source: Author.

4.3.1 Climate change mitigation in a world composed of two countries

We start our investigation of this strategic in-teraction by making a simplifying assumption. We suppose that the world is composed of two identical countries that try to mitigate climate change: country A and country B. Each individual country can play two strategies: it can choose to either reduce its GHG emissions by 20 per cent, or not to reduce its GHG emissions at all.

If the country chooses not to reduce its emis-sions, it does not bear any costs but also does not receive any benefit. If the country chooses to reduce its emissions, it has to pay a cost of 12 in order to finance the GHG reduction. At the same time, the emission reduction yields a benefit of 10 for the country, as it reduces the negative ef-fects of climate change. While these cost and benefit numbers have been chosen arbitrar-ily, they reflect an important property of climate change mitigation. As the climate is the product of the behaviour of all nations on the planet, no single country can change the composition

of the atmosphere alone and mitigate climate change single-handedly (IPCC, 2001). The benefits of a single country reducing GHG emissions will therefore be relatively small compared to the costs the country incurs in doing so. Hence, the cost of financing the GHG reduction for a single country (12) has been chosen to be bigger than the benefit (10) the country obtains from single-handedly reducing its emissions.

As mentioned in Section 4.1, climate change mitigation is a global public good, meaning that the benefits of abating are non-rival and non-excludable. This implies that if country A chooses to abate – paying the cost of 12 and receiving the benefit of 10 – country B also receives a benefit of 10 without doing anything whatsoever. This is a crucial point one has to understand. Country B receives a benefit from the emission reductions made by country A, because country A’s emission reductions lower global concentrations of atmos-pheric emissions. Country A’s efforts thereby slow climate change, which positively affects country A and country B. This leads to the payoff matrix displayed in Figure 35.62

As can be seen in Figure 35, if both countries de-cide not to reduce their emissions, nothing will happen: country A and country B both obtain a payoff of 0 as there are neither mitigation costs nor mitigation benefits associated with inaction. If country A decides to reduce its emissions while country B decides not to reduce, country A ob-tains a payoff of -2 (the benefits it produces (10) minus its costs of doing so (12)) while country B receives a payoff of 10. Similarly, if country B de-cides to reduce while country A decides not to re-duce, country B receives a payoff of -2 and country A receives a payoff of 10. Finally, if both countries decide to reduce, each country obtains a payoff of 8 (country A receives the benefit produced by itself (10) plus the benefit produced by country B (10) and pays its reduction costs (12); the same goes for country B).

Clearly, from the point of view of the whole plan-et, the best outcome of the game would be that both countries reduce their emissions and there-by contribute to mitigating climate change. This would yield an overall benefit of 16 (8+8), which is the highest possible payoff for the whole planet in the game.63 Thus, “Reduce”/”Reduce” is a so-called “social optimum.” But in this game, the so-cial optimum is not the likely outcome. Or stated differently, “Reduce”/”Reduce” is not a Nash equi-librium because the best choice country A could make given that country B reduces its emissions is not to reduce its emissions. In that case, coun-try A would receive a payoff of 10, which is greater than the payoff of 8 the country would obtain by also reducing its emissions. The exact same reasoning applies for country B. This free-riding behaviour is the main problem associated with

62 In game theory, this game structure is called a “prisoner’s dilemma” and is probably the best-known application of game theory. This game was introduced by Merrill Flood and Melvin Dresher in 1952. Albert Tucker used a fictive interaction between two prisoners as an illustrating anecdote, which gave the game its name (Poundstone, 1992). Varian (2010: 527) outlines Tucker’s original story as follows: “[T]wo prisoners who were partners in a crime were being questioned in separate rooms. Each prisoner had a choice of confessing to the crime, and thereby implica-ting the other, or denying that he had participated in the crime. If only one prisoner confessed, then he would go free, and the authorities would throw the book at the other prisoner, requiring him to spend 6 months in prison. If both prisoners denied being involved, then both would be held for 1 month on a technicality, and if both prisoners confessed they would both be held for 3 months.” This game has a similar payoff matrix as in Figure 35, leading both ratio-nal prisoners to confess, while they would have been better off denying the crime.

63 The other options yield planetary payoffs of 0 (0+0), 8 (-2+10), and 8 (10-2), respectively.

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the provision of public goods like climate change mitigation. Actually, the best payoff a country could hope for in the whole game (10) is obtained if the country free-rides, that is, if it lets the other country take action and benefits from these ac-tions without doing anything by itself.

So what is the likely outcome of the game? One can easily see that country A’s dominant strategy in this game is not to reduce its emissions: coun-try A will be better off by not reducing, no matter the choice of country B. The same holds true for country B: for both choices of country A, country B obtains a higher payoff if it does not reduce its emissions. Hence “Not reduce”/”Not reduce” is the dominant strategy equilibrium and at the same time also the Nash equilibrium of the game. At this equilibrium, neither country A nor country B has an incentive to alter its choice unilaterally if given the opportunity. If a country were to unilat-erally alter its choice in the Nash equilibrium, it would obtain a payoff of -2 instead of 0. The game thus predicts that no country will reduce its emis-sions, as both prefer to free-ride. At the same time, the whole planet would clearly be better off if both countries simultaneously decided to reduce their emissions and thereby mitigate climate change.

Although the game is very simple, it perfectly il-lustrates the problem underlying all collective action failures: “individual rationality is not suffi-cient for collective rationality. That is, individuals [or countries] who abide by the tenets of ration-ality may make choices from which the collective is left in an inferior position” (Sandler, 2004: 18). Instead of contributing to mitigating climate

change by reducing emissions, countries have strong incentives to free-ride; climate change will thus not be mitigated.

4.3.2 Climate change mitigation in a world composed of n countries 64

So far we have analysed a strategic interaction in a world composed of two countries. Given that there are considerably more than two countries in the world, we relax this restrictive assumption and generalize the collective action problem to incorporate any number of countries.

To do so, suppose the planet consists of a total of n identical countries. Each country can choose be-tween two strategies: to reduce GHG emissions by 20 per cent or not to reduce GHG emissions. Sup-pose further that for a given country i, the cost of reducing its GHG emissions by 20 per cent equals ci. By reducing its greenhouse gases by 20 per cent, the country produces a non-rival and non-exclud-able benefit of bi (whereas ci>bi), benefiting it and each of the other n-1 nations. Table 5 displays the payoffs of this game from the perspective of coun-try i. The rows show the two strategies of country i while the columns indicate the actions of the other n-1 countries. The top row displays the free-rider payoffs for country i: if one other country re-duces its emissions, country i receives a benefit of bi, if two other countries reduce their emissions, country i obtains 2bi , etc. The bottom row shows the payoffs for country i when it does reduce its emissions: if no other country contributes, coun-try i obtains a payoff of bi-ci, if one other country contributes, country i receives 2bi-ci, etc.

64 This section draws on the presentation of the n country prisoner’s dilemma in Sandler (2004) and Perman et al. (2011).

ReducinggreenhousegasemissionsinaworldofncountriesTable 5

Number of greenhouse-gas-reducing countries other than country i

0 1 2 (…) n-1

Country i does not reduce GHG emissions by 20 per cent

0 bi 2bi (…) (n-1)bi

Country i does reduce GHG emissions by 20 per cent

bi-ci 2bi-ci 3bi-ci (…) nbi-ci

Source: Author's elaboration based on Figure 2.2 in Sandler (2004) and Table 9.1 in Perman et al. (2011).

As one can see, even if n-1 countries reduce their emissions, country i’s dominant strategy is to free-ride because the payoffs in the upper row exceed the payoffs in the bottom row by ci-bi, no matter how many other countries contribute. As the same holds for all other countries, the unique Nash equilibrium of the game is that nobody re-duces its emissions. Given that nobody has an in-centive to take action, the aggregated planetary payoff in the Nash equilibrium is 0.

The Nash equilibrium is clearly not a socially op-timal outcome. The socially optimal outcome of the game occurs when all countries limit their emissions, leading to a maximized planetary payoff of n2bi-nci. Again, we want to emphasize that this social optimum is not a stable solution. Even if all other n-1 countries contribute, country i always has an incentive to free-ride because it will obtain (n-1)bi, which is greater than nbi-ci. As the free-rider payoffs are higher for all countries


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no matter how many other countries contribute, the world ends up in the unique Nash equilib-rium with nobody reducing its emissions.65

Hence, the modified game structure does not result in a different prediction. Even in a world composed of many countries, rational countries would still free-ride and not contribute to miti-gating climate change. While the game theory approach reveals the essential nature of the problem (free-riding), things are even more com-plicated in reality. Countries are not identical as we assumed in the games above: they vary in terms of size, wealth and technology. Costs and benefits of mitigation also differ widely among countries and are only imperfectly known (Com-mon and Stagl, 2004; Perman et al., 2011; Sandler, 2004; Stern, 2007). Countries are not equally af-fected by the consequences of climate change, thus they would not equally benefit from mitiga-

tion efforts. Mitigation costs and opportunities also differ between countries. Finally, there is the issue of international and intergenerational jus-tice affecting negotiations about the financing of climate change mitigation (see the discussion on the principle of common but differentiated responsibilities in Module 4). All these factors further complicate the collective action problem and influence the likely outcome (or prognoses) of strategic interactions.66

In addition to factors related to the global public good nature of climate change mitigation and their game theory implications, there are other factors that can influence the outcome of collec-tive action. Box 14 illustrates this issue by show-ing the vastly different outcomes of two, at first sight similar, collective action problems – mitiga-tion of ozone-shield depletion and mitigation of climate change.

65 To illustrate these results with numbers, assume that the costs and benefits are the same as in the two-country example (ci = 12 and bi = 10) and assume further that the world is composed of the 194 United Nations member countries (n = 194). Then, the planetary payoff in the social optimum would equal 1942*10-194*12=374,032, with each individual country obtaining a payoff of 194*10-12=1,928. But the socially optimal outcome is not an equilibrium, because nation i (and thus also all other nations) would have an incentive to free-ride (the country’s payoff would be greater if it free-rides and all the other n-1 countries contri-bute: (194-1)*10=1,930>1,928). Thus the world ends up in the unique Nash equilibrium with a planetary payoff of 0, which is clearly less than the social optimum.

66 More complicated game structures can incorporate some of these additional factors. See Annex 1 for additional reading material on this issue.

DifferentcollectiveactionoutcomesforidenticalcollectiveactionproblemsBox 14

Sandler (2004) highlights that seemingly identical collective action problems like the provision of a global public good can have vastly different collective action outcomes. To illustrate his point, he compares the col-lective action outcome of two pollution problems. One the one hand, the international community has been rather efficient in mitigating stratospheric ozone shield depletion caused by chlorofluorocarbons (CFCs) and bromide-based substances. On the other hand, it is still struggling with mitigating climate change caused by the accumulation of greenhouse gases in the atmosphere. Mitigating CFCs and mitigating greenhouse gases are both global public goods. Moreover, both problems are pollution problems and their solution requires international cooperation to reduce emissions. In the CFC case, humankind succeeded, while efforts to reduce GHG emissions have not been successful to date. Sandler explains this difference in the outcomes of collec-tive action by the differences listed in Table 6. All these factors make finding a collective action solution more difficult in the case of climate change as compared to ozone-shield depletion.

FactorsaffectingoutcomesofcollectiveactionsTable 6

Ozone-shield depletion Climate change

Emissions concentrated in relatively few countries Emissions are added by virtually every country

Every country loses from a thinning ozone layer There are winners and losers from global warming

There are substantial commercial gains from CFC substi-tutes

Uncertainty about substantial commercial gains from GHG substitutes

Uncertainty in terms of process and consequences has been resolved Uncertainty remains in terms of process and consequences

Dominant strategy for some key polluters is to curb emis-sions, since bi-ci>0

Dominant strategy for most key polluters is not to curb pollutants, since bi-ci<0

Leadership by key polluters Lack of leadership by key polluters

Intertemporal reversibility within 50 years No intertemporal reversibility within 50 years

Decision makers were more informed about benefits than costs

Decision makers were more informed about costs than benefits

Relatively few economic activities add to ozone-shield depletion Many economic activities add to global warming

Source: Table 10.4 in Sandler (2004), updated by the author.

Source: Author's elaboration based on Sandler (2004)

Consequently, as Sandler (2004: 213) states, “the contrast between global collective action and inaction hinges on factors that go beyond the non-rivalry and non-excludability of these global public good’s benefits…. Knowl-edge of just the properties of a public good is not always sufficient to provide a prognosis for collective action.”

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4.3.3 Climate change mitigation: Lessons from game theory models

Section 4 started by asking how economic theory explains the fact that the international commu-nity has been struggling for decades to solve the climate change problem, even though the appar-ently simple solution has been known for a long time. Sections 4.1, 4.3.1 and 4.3.2 provided the the-oretical answer to this question. The two games modelling the strategic interaction between countries showed that, due to the global public good nature of mitigating climate change, the payoff countries obtain from free-riding is higher than the payoff they would obtain from reducing their emissions. Rationally behaving countries thus have strong incentives to free-ride and not reduce their emissions. This results in a massive collective action failure.

In addition to explaining this outcome, game theory also provides certain insights on how this outcome might be changed. Clearly, payoffs from acting alone matter. If they were positive, each country would have an incentive to act alone and reduce emissions. This would lead to a situation where the Nash equilibrium corresponds to the social optimum. Stated differently, if the payoffs from acting alone were positive, the social opti-mum would be incentive-compatible: individual countries would have incentives to reduce emis-sions single-handedly because of the positive payoff, leading automatically to a socially opti-mal situation.

Such an outcome could be reached through a binding international agreement between coun-tries (Common and Stagl, 2004; Perman et al., 2011; Sandler, 2004; Tietenberg and Lewis, 2012). The countries would have to agree that they all reduce their emissions. However, as each country has a strong incentive to sign on to such a treaty and subsequently free-ride to maximize its pay-off, the agreement would need to contain penal-ties. In theory, any penalty larger than ci-bi would do the job. With this penalty, the payoff of acting alone (bi-ci) would be larger than the payoff of not acting (0-p, whereas p>ci-bi is the penalty) and the Nash equilibrium would correspond to the social optimum. However, putting in place such a pen-alty system is not straightforward, as the history

of climate change negotiations has shown (see Module 4).67 At least equally difficult would be enforcement of such a penalty system. Countries could only be forced to pay penalties if there were a third party with the power to force countries to pay (Perman et al., 2011). As today’s world con-sists of sovereign states, no such enforcer exists on the global level. International environmental agreements therefore rely on voluntary actions of countries and should thus be designed in a self-enforcing way. The theoretical literature (see Perman et al., 2011, for a short review) on interna-tional environmental agreements consequently offers rather pessimistic views regarding their efficiency: treaties seem to largely codify actions countries intended to take anyway, and achieve little when the number of affected countries is large. Moreover, as climate change mitigation illustrates, effective cooperation seems hardest to achieve when the stakes are high and when the cooperation is most needed (Barret, 1994). Reviews of international environmental agree-ments show that effective cooperation requires that (a) the treaty yield positive net benefits for all participating countries, (b) the parties reach a consensus on the design of the treaty, and, most importantly, (c) the treaty can be enforced by the participating countries (Finus, 2003).

Besides self-enforcing international agreements, game theory suggests a number of alternative mechanisms to enforce cooperation.68 Coop-eration can be fostered if countries are able to make credible commitments to reduce emis-sions regardless of what other countries are doing. Transfers and other side payments could increase the number of cooperating countries. Furthermore, the co-benefits of emission reduc-tions, such as those achieved by linking develop-ment and climate change policy issues, might alter the payoffs for countries and thus change the nature of the game. Moreover, theory indi-cates that the prospects for cooperation are less pessimistic when games are repeated. The two games we introduced above are “one-shot games” played only once. If the same game is played repeatedly over an undefined time hori-zon, and if countries communicate, a variety of different options emerge. As will be seen in Mod-ule 4, the Paris Agreement has been partially built on these mechanisms.

67 Putting in place a penalty system is itself a pure public good problem (Sandler, 2004).

68 See Chapter 9.3 in Perman et al. (2011) for an overview.


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Shortsummary

How does economic theory explain why the international community has been struggling for decades to solve the climate change problem, even though the apparently simple solution has been known for a long time? To answer this question, Section 4 showed that climate change mitigation is a global public good with non-rival and non-excludable benefits. As no country is able to change the composition of the atmosphere single-handedly, international cooperation is needed. The section introduced game theory concepts that were subsequently used to analyse the strategic interaction between countries. Two games illustrated the main cause of the collective action failure: that countries have strong incentives to free-ride and not contribute to emission reductions because the benefits of mitigating climate change are non-rival and non-excludable. This leads to an outcome that is not socially optimal. The section concluded by drawing several lessons from game theory models that would allow for fostering cooperation between countries.

1 DefineParetoefficiencyanddiscusstheadvantagesanddisadvantagesoftheconcept.

2 Describethefirstwelfaretheorem.Whyisthistheoremafundamentalresultineconomics?Whatassump-tionsunderlyingthefirstwelfaretheoremareviolatedinthecaseofclimatechange?

3 Whatcriteriaareusedtoclassifygoodsasprivateandpublicgoods?Listtwoexamplesofaprivateandapub-licgoodanddiscusswhythesegoodsareconsideredprivate/publicbyusingthecriteriayoudefinedabove.

4 Whatareopen-accessgoods?Whyistheatmosphereconsideredtobeanopen-accessgood?Whathap-pensifmarketsdealwithopen-accessgoodssuchastheatmosphere?

5 Defineexternalitiesandprovideanexampleofapositiveandanegativeexternality.Howcouldgovern-mentssolveanegativeexternalityproblem?IllustrateyourreasoningusingtheexampleofGHGemissions.

6 ConsideracoalplantthatreleasesCO2emissionsintotheatmospherewhileproducingunitsofenergy.SupposethattheprivatemarginalcostoftheplantisgivenbyPMC=50+0.25*Q,wherePMCistheprivatemarginalcostinUSdollarsperunitproducedandQisunitsofenergyproduced.BecausethefirmreleasesCO2emissionsintotheatmosphere,itimposesanexternalcostonsocietythatequalsUS$2perunitofen-ergyproduced.Supposefurtherthattheprivatemarginalbenefit(PMC)–whichequalsthesocialmarginalbenefit(SMC)–perunitofenergyproducedisgivenbyPMB = SMB=100-0.25*Q.

(a) Derivethesocialmarginalcost(SMC)functioninUSdollarsperunitproduced. (b) Drawadiagramillustratingtheprivatemarginalcostfunction,thesocialmarginalcostfunction,and

theprivatemarginalbenefitfunction. (c) Findtheprofit-maximizingenergyoutputofthecoalplantandthecorrespondingpriceperunitof

energyproduced. (d) Findthesociallyoptimalenergyoutputandthecorrespondingprice. (e) Comparetheprivateequilibriumwiththesociallyoptimaloutcomeanddiscussunderlyingexternalityissues.

7 SupposeplayerAandplayerBplayagamewiththefollowingpayoffmatrix:

(a) Definedominantstrategies.DoesplayerAhaveadominantstrategy?DoesplayerBhaveadominant strategy?

(b) Howmanypure-strategyNashequilibriacanyoufindinthegame? (c) Canyoufindareal-worldexamplethatcouldbedescribedbysuchapayoffmatrix?

8 Howdoeseconomictheoryexplainwhytheinternationalcommunityhasbeenstrugglingfordecadestosolvetheclimatechangeproblem?Toanalysethisquestion,supposethattheworldiscomposedoftwocountriesanddiscussthepayoffmatrixofthemitigationgame.Whatisthelikelyoutcomeofthisgame?Explainthelessonsthatcanbelearnedfromthissimplegame.

Player B

Left Right

Player ATop 1,1 -1,-1

Bottom -1,-1 1,1


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ANNEX 1

Topic

Microeconomic foundations of the competitive market model

Chapters 1–9, 14–16, 18–23, and 31–33 of Varian HR (2010). Intermediate Microeconomics a Modern Approach, Ninth Edition. W. W. Norton & Company. New York.

Chapters 1–5, 10, and 15–20 of Mas-Colell et al. (1995). Microeconomic Theory. Oxford University Press. New York.

Chapters 1–9 and 16 of Pindyck R, and Rubinfeld D (2012). Microeconomics, Eighth Edition. Pearson Series in Economics. Prentice Hall. Upper Saddle River, NJ.

Public goods and externalities

Chapters 2–4 of Sandler T (2004). Global Collective Action. Cambridge University Press. New York.

Chapters 34 and 36 of Varian HR (2010). Intermediate Microeconomics: A Modern Approach, Ninth Edition. W.W. Norton & Company. New York.

Chapter 11 of Mas-Colell et al. (1995). Microeconomic Theory. Oxford University Press. New York.

Chapter 18 of Pindyck R, and Rubinfeld D (2012). Microeconomics, Eighth Edition. Pearson Series in Economics. Prentice Hall. Upper Saddle River, NJ.

Chapter 4 of Perman R et al. (2011). Natural Resource and Environmental Economics, Fourth Edition. Pearson Education Limited. Essex, UK.

Game theory

Chapters 7–9 of Mas-Colell et al. (1995). Microeconomic Theory. Oxford University Press. New York.

Chapter 28 of Varian HR (2010). Intermediate Microeconomics: A Modern Approach, Ninth Edition. W.W. Norton & Company. New York.

Chapter 13 of Pindyck R, and Rubinfeld D (2012). Microeconomics, Eighth Edition. Pearson Series in Economics. Prentice Hall. Upper Saddle River, NJ.

Straffin P (2004). Game Theory and Strategy, Fifth Edition. The Mathematical Association of America. Washington, DC.

Environmental economics


Perman et al. (2011). Natural Resource and Environmental Economics. Fourth Edition. Pearson Education Limited. Essex, UK.

Kolstad CD (2000). Environmental Economics. Oxford University Press. New York.

Common M and Stagl S (2004). Ecological Economics – An Introduction. Cambridge University Press. Cambridge, MA.

Selectedadditionalreadingmaterial


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REFERENCES

Arrow K (1951). An extension of the basic theorems of welfare economics. In: Proceedings of the Second Berkeley Symposium of Mathematical Statistics and Probability, Neyman J, ed. University of California Press. Berkeley and Los Angeles.

Barrett S (1994). Self-enforcing international environmental agreements. Oxford Economic Papers 46: 874–94.

Cohen D (2009). La prospérité du vice. Une Introduction (inquiète) à l’économie. Albin Michel. Paris.

Common M, and Stagl S (2004). Ecological Economics – An Introduction. Cambridge University Press. Cambridge, UK.

Ferroni M, Mody A, Morrissey O, Willem te Velde D, Hewitt A, Barrett S, and Sandler T (2002). International public goods: incentives, measurement, and financing. World Bank. Washington, DC.

Finus M (2003). Stability and design of international environmental agreements: The case of transboundary pollution. In: The International Yearbook of Environmental and Resource Economics 2003/2004: A Survey of Current Issues, Folmer H and Tietenberg T, eds. Cheltenham: Edward Elgar: 82–158.

IPCC (2001). Climate Change 2001: Mitigation of Climate Change. Contribution of Working Group III to the Intergovernmental Panel on Climate Change Third Assessment Report (TAR). Cambridge University Press. Cambridge, UK and New York.

IPCC (2014a). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Pachauri RK, and Meyer LA, eds. Cambridge University Press. Cambridge, UK and New York.

IPCC (2014b) Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Edenhofer O, Pichs-Madruga R, Sokona Y, Farahani E, Kadner S, Seyboth K, Adler A, Baum I, Brunner S, Eickemeier P, Kriemann K, Savolainen J, Schlömer S, von Stechow C, Zwickel T, and Minx JC, eds. Cambridge University Press. Cambridge, UK, and New York.

Kolstad CD (2000). Environmental Economics. Oxford University Press. New York.

Lerner AP (1934). The concept of monopoly and the measurement of monopoly power. Review of Economic Studies 1: 157–75.

Lerner AP (1944). The Economics of Control. Principles of Welfare Economics. Macmillan. New York.

Mas-Colell A, Whinston MD, and Green JR (1995). Microeconomic Theory. Oxford University Press. New York.

Nash J (1951). Non-cooperative games. The Annals of Mathematics 54(2): 286–95.

Olson M (1965). The Logic of Collective Action: Public Goods and the Theory of Groups. Harvard University Press. Cambridge, MA.

Ostrom E (2008). The challenge of common-pool resources. Environment 50: 9–20.

Perman R, Ma Y, Common M, Maddison D, and McGilvray J (2011). Natural Resource and Environmental Economics, Fourth Edition. Pearson Education Limited. Essex, UK.

Pindyck R, and Rubinfeld D (2012). Microeconomics, Eighth Edition. Pearson Series in Economics. Prentice Hall. Upper Saddle River, NJ.

Poundstone W (1992). Prisoner’s Dilemma. Doubleday. New York.

Samuelson PA (1954). The pure theory of public expenditure. Review of Economics and Statistics 36: 387–89.

Sandler T (2004). Global Collective Action. Cambridge University Press. New York.

Sen A (1970). Collective Choice and Social Welfare. Holden Day. San Francisco.

Stern N (2007). The Economics of Climate Change. The Stern Review. Cambridge University Press. New York.

Straffin P (2004). Game Theory and Strategy, Fifth Edition. The Mathematical Association of America. Washington, DC.


Varian HR (2010). Intermediate Microeconomics: A Modern Approach, Ninth Edition. W.W. Norton & Company. New York.

Module 4The politics of climate change –

towards a low-carbon world

The politics of climate change – towards a low-carbon world

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41 Introduction

Modules 1 and 2 outlined the links between the environment and the economy, explained how human activities change the climate, and dis-cussed the observed and anticipated impacts of climate change. Module 3 showed that climate change is the result of a large market failure that can only be corrected by policy interventions at the global level. Such a correction is not easy to achieve, however, because the world is composed of sovereign countries. These countries need to coordinate their efforts to transform their econo-mies into low-carbon economies and thus limit greenhouse gas (GHG) emissions. However, as shown in Module 3, such coordination represents a collective action problem that is difficult to overcome. For the past 25 years, the international community has not found a convincing solution, as global GHG emissions continue to increase. Nevertheless, at the United Nations Climate Change Conference of the Parties in Paris (COP21) in 2015, the international climate change policy framework took a new and promising direction. This module provides an in-depth analysis of cli-mate change policies and the international poli-tics of climate change.69

Section 2 discusses the different policy instru-ments and technological solutions that could enable us to limit climate change. Section 2.1 focuses on policy measures that aim to stabilize the concentrations of greenhouse gases in the atmosphere. Such stabilization requires either reducing the flow of emissions reaching the atmosphere, or extracting the already-emitted greenhouse gases from the atmosphere. Sec-tion 2.1.1 discusses policies that aim to directly or indirectly decarbonize our economic systems by pricing CO2, increasing energy efficiency, and substituting fossil fuels with alternative sourc-es of energy.70 Section 2.1.2 explains how policy could promote technological solutions to help capture and store already-emitted CO2 emis-sions before they reach the atmosphere. Section 2.1.3 discusses the role of policies in promoting carbon geoengineering, a technology that could directly extract CO2 out of the atmosphere. Un-like the other policy options to stabilize GHG concentrations, carbon geoengineering would not require transforming economies into low-carbon economies. After having discussed the different policy and technological options to stabilize GHG concentrations, Section 2.2 focus-es on solar geoengineering, a technology that allows for reflecting additional incoming solar radiation back into space and thus stabilizing temperatures on the planet. While most of the policy measures discussed in Section 2 are sub-

ject to the collective action problem explained in Module 3, carbon geoengineering and solar geo-engineering are not: they could be implemented by only a few nations. However, these technolo-gies are not yet fully developed, their implemen-tation may entail considerable environmental risks, and carbon geoengineering is currently expected to be very expensive.

In parallel with policies aimed at limiting climate change, which are discussed in Section 2, socie-ties also need to undertake actions to adapt hu-man and natural systems so that they are better prepared for the anticipated impacts of climate change. These policies are described in Section 3. Adaptation needs differ from one place to an-other because the anticipated impacts of climate change differ locally. The first step of any com-prehensive adaptation policy thus should be to assess local risks and vulnerabilities in order to identify adaptation needs. Only then can specific adaptation options be selected and implement-ed. The section also presents a schematic over-view of adaptation policies drawing on the IPCC’s classification of adaptation options, and provides examples of adaptation measures implemented by developing countries.

After having described the different climate change limitation and adaptation policy options, Section 4 focuses on the international climate change policy architecture. The section reviews key international climate change policy devel-opments and explains that of the policy instru-ments outlined in Sections 2 and 3, international climate change policy negotiations have so far focused mostly on those policy instruments that aim to limit the net flow of emissions. As ex-plained in Module 3, these policy instruments are subject to a severe collective action problem. The section shows that up until now, international policy negotiations have been based on a top-down approach that has been unable to over-come this collective action problem. At COP21, the international climate change policy frame-work considerably changed with the adoption of the Paris Agreement. Unlike the past 25 years of international climate change policy, the Paris Agreement is based on a bottom-up approach. The section ends by discussing several key issues of the Paris Agreement, with a particular focus on the situation of developing countries.


• Distinguish the two fundamental options to limit climate change;

• Describe different policy instruments to sta-bilize atmospheric GHG concentrations;

69 To do so, it relies on, among other sources, the work of the Intergovernmen-tal Panel on Climate Change (IPCC) and on Barrett et al. (2015), who present a collec-tion of studies and reviews on climate change policy.

70 While the section focuses on policies capable of redu-cing CO2, note that many of the policies discussed simul-taneously also reduce other energy-related greenhouse gases like nitrous oxide.


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• Analyse advantages and disadvantages of the different policy instruments to stabilize at-mospheric GHG concentrations;

• Understand how geoengineering could limit climate change;

• Evaluate the importance of climate adapta-tion policies;

• Describe the international climate change policy architecture;

• Evaluate the links between the Paris Agree-ment and development.

To support the learning process, readers will find several exercises and discussion questions in Sec-tion 5 covering the issues introduced in Module 4. Useful data sources and additional reading ma-terial can be found in Annexes 1 and 2.

2 Policyoptionsandtechnological solutionstolimitclimatechange

As explained in Section 4 of Module 2, the IPCC anticipates that, compared to the pre-industrial era, mean surface temperature on the planet will increase by roughly 4°C by the end of the 21st cen-tury if the world does not implement additional policies to limit climate change. This human-in-duced temperature increase is expected to trigger “severe, pervasive and irreversible impacts on peo-ple and ecosystems” (Field et al., 2015: 62; see also Module 2). If climate change policies could limit the warming to less than 2°C above pre-industrial temperatures, these risks would be substantially reduced (IPCC 2014a, 2014b). Stabilizing tempera-tures at less than 2°C above pre-industrial levels is thus a crucial policy objective that is currently on the agenda of almost all countries (see Section 4).

To limit warming to 2°C and thereby avoid the main bulk of the negative effects of climate change, humankind has essentially two options (Edenhofer et al., 2015). The first is to stabilize con-centrations of greenhouse gases in the atmos-phere (see Section 2.1). The second is to offset the expected temperature increase by increasing the amount of reflected incoming solar radiation us-ing solar geoengineering technologies (see Sec-tion 2.2). The following sections discuss different policy instruments that could be used to imple-ment both these options.

2.1 Policyinstrumentsandtechnologies tostabilizeconcentrationsofgreenhouse gasesintheatmosphere

IPCC (2014b) estimates that the atmospheric con-centration of greenhouse gases in 2100 must be stabilized at below 450 parts per million (ppm)

CO2-equivalent (CO2-eq)71 if the increase in mean surface temperatures is to stay below 2°C. GHG concentrations can be stabilized by either reduc-ing the flow of GHG emissions towards the at-mosphere or by removing those gases from the atmosphere.

While all four major greenhouse gases contrib-ute to the warming of the planet, stabilizing CO2 concentration is of crucial importance, because climate perturbations from accumulated fossil-fuel-based CO2 emissions last for thousands of years (Archer et al., 2009). Recall as well that the fifth IPCC assessment report found an almost linear relationship between total cumulative CO2 emissions emitted since the start of the in-dustrial era and global mean surface warming (see Section 4 of Module 2). This implies that the larger the total sum of emitted CO2 emissions (and hence the larger atmospheric CO2 concen-trations), the higher the mean temperature will be in the 21st century. Due to the importance of CO2in limiting climate change, this section most-ly focuses on policies to stabilize the concentra-tion of CO2 in the atmosphere.72

CO2 concentrations can be stabilized in three complementary ways (Barrett and Moreno-Cruz, 2015): (a) by gradually reducing anthropogenic CO2 emissions to zero (see Section 2.1.1); (b) by capturing and storing CO2 emissions before they reach the atmosphere (see Section 2.1.2); and/or (c) by reducing concentrations of CO2 in the at-mosphere through direct removal of CO2 from the atmosphere (see Section 2.1.3).

The first two options affect the flow of emissions to the atmosphere by either reducing the amount of emitted CO2 or by preventing the emitted CO2 from reaching the atmosphere. Policy instru-ments available for this purpose are listed in Ta-ble 7 and further discussed in Sections 2.1.1 and 2.1.2. To meet the 2°C target with a probability of at least 66 per cent – taking all other human influ-ences on the climate into account - IPCC (2014b) estimates that the above policies need to keep total cumulative CO2 emissions since the start of the industrial era below 2,900 gigatonnes of CO2 (GtCO2) by 2100. By 2014, roughly 2,000 GtCO2 had already been emitted. Hence, if humans intend to reach the 2°C target, they have roughly 900 GtCO2 left to emit in the future, all else being equal. This does not leave too much space for further emis-sions, as 900 GtCO2 is equivalent to less than 25 years of emissions at the 2014 level (Edenhofer et al., 2015). Policies aimed at emission reduction and emission capture and storage thus jointly need to limit future CO2 emissions to 900 GtCO2. Unfortunately, these policy options are subject to

71 CO2-equivalent concentra-tion is a measure to compare radiative forcing of a mix of different greenhouse gases. It indicates the concentration of CO2 that would cause the same radiative forcing as a given mixture of CO2 and other greenhouse gases (IPCC, 2014c).

72 Note, however, that several of these policies simulta-neously address emissions of other greenhouse gases resulting from fossil fuel combustion


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4the collective action problem discussed in Mod-ule 3. This makes the prospects for transforming current carbon-based economies into low-carbon economies and thereby stabilizing atmospheric CO2 concentrations below the 450 ppm CO2-eq concentration level relatively bleak.

The third option is different. It does not reduce the flow of emissions towards the atmosphere as the first two options do, but lowers atmospheric

CO2 concentrations by directly removing the al-ready emitted CO2 from the atmosphere. As such, this third option – called carbon geoengineering – has the potential to stabilize CO2 concentra-tions even if humans continue to emit CO2 emis-sions as they do today. The most promising car-bon geoengineering technology – industrial air capture (see Table 7) – will be discussed in Section 2.1.3. As we will see, collective action prospects are entirely different for this option.

SelectedpolicyoptionstostabilizeconcentrationsofcarbondioxideintheatmosphereTable 7

Ways to stabilize CO2 emissions Policy category Examples of policy instruments

Reducing CO2 emissions

Price CO2 emissions (directly or indirectly)

Carbon tax

Cap and trade system

Removal of fossil fuel subsidies

Fuel taxation

Energy conservation Promotion of energy efficiency

Fossil fuel substitutionPromotion of nuclear energy

Promotion of renewable energy sources

Capturing and storing CO2 emissions before they reach the atmosphere Carbon capture and storage Development and implementation of

carbon capture and storage technologies

Directly removing CO2 from the atmosphere Carbon geoengineering Promotion of industrial air capture

technologies

2.1.1 Policy instruments to reduce anthropogenic carbon dioxide emissions

We first look at policy instruments capable of re-ducing CO2 emissions that have been at the cen-tre of the international policy debate on climate change mitigation (see Section 4) and have been well known for several decades (see also Module 3). Generally speaking, there are three policy in-strument categories directed towards reducing anthropogenic CO2 emissions. The first contains policy instruments that put a price on carbon di-oxide, the second consists of policy instruments that conserve energy, and the third contains policy instruments to directly decarbonize the energy system by substituting energy from fossil fuels with alternative energy sources.

2.1.1.1 Policy instruments that price carbon dioxide emissions

Module 3 showed that GHG emissions are a typi-cal example of a negative externality. Economic actors do not directly bear the climate-change-related costs associated with the emissions, which they can dump free of charge into the at-mosphere. Consequently, they produce too much GHG emissions. This externality problem can be partly corrected by putting a price on carbon. If economic actors have to pay a price for emit-

ting CO2, they directly bear (part) of the climate change-related costs associated with their emis-sions. As emitting CO2 would then no longer be free of charge, economic actors would emit less emissions compared to a scenario without a price on carbon. Pricing carbon would reduce emissions not only directly by affecting the de-cisions of economic actors, but also indirectly by making investments in cleaner technologies and research and development (R&D) of new tech-nologies more attractive. It is thus not surprising that the necessity of putting a price on carbon has been clear for a long time (Barrett et al., 2015). Several policy instruments can be used to price carbon and thereby help decarbonize economies. The most important ones are carbon taxes, cap and trade systems, removal of fossil fuel subsi-dies, and fuel taxation.

Carbon taxes directly tax the amount of CO2 emitted. The level of the tax is often expressed per tonne of CO2 (e.g. US$50 per tonne of CO2). Carbon can be taxed at various points of the energy supply chain. Usually one distinguishes between so-called upstream and downstream carbon taxes, although combinations of the two approaches are also possible (Wang and Murisic, 2015). Upstream carbon taxes impose a charge on producers or importers of raw materials such as coal, oil, or natural gas that contain CO2 (Mansur,

Source: Author.


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2012). The levied charge is designed to be propor-tional to the amount of carbon contained in the raw material. As upstream carbon taxes directly tax fossil fuel producers or importers, the levies are subsequently passed forward and affect the economy-wide prices of electricity, petroleum products, and energy-intensive goods. Down-stream carbon taxes impose a charge on direct sources of CO2 emissions such as cars, power plants, energy-intensive industries, etc. (Man-sur, 2012). The charge levied is proportional to the amount of CO2 emitted by the source of the emission. A fully inclusive downstream carbon tax thus also affects all prices of commodities whose production or consumption processes in-volve the release of CO2 emissions. One of the dif-ferences between the two types of carbon taxes is the amount of affected agents and hence the administrative simplicity: upstream carbon tax-es are often imposed on relatively few firms (the fossil fuel producers and importers), while down-stream carbon taxes, if they are fully inclusive, af-fect many different agents.

Economists consider carbon taxes the most cost-efficient policy instrument to reduce CO2 emis-sions. In their recent review on different carbon pricing policy instruments, Sterner and Köhlin (2015: 252) note that a carbon tax is “generally more efficient than direct regulation of technol-ogy, products, and behaviour, as it affects con-sumption and production levels as well as tech-nologies, it covers all industries and production and provides dynamic incentives for innovation and further emissions reductions. In addition, the tax revenue can be used to facilitate the transi-tion toward renewable energy, cover administra-tive and implementation costs, or lower taxes on labour.… Furthermore, a tax is easy to incorporate in the existing administration.” Besides these direct effects, carbon taxes can also generate considerable national co-benefits. One example of such a co-benefit of carbon taxes is improve-ment in health: carbon taxes decrease the use of coal and thus have the potential to reduce deaths related to air pollution (Parry et al., 2014).

While carbon taxes are an appealing policy in-strument from an economic point of view, they

face severe political hurdles at the national level. Among them are (a) the presence of strong fossil fuel lobbies actively opposing implementation of carbon taxes; (b) pressure from the public to not implement carbon taxes in order to avoid increases in commodity prices; (c) a general perception that taxes reduce consumption and production and thereby induce welfare losses; (d) the fact that carbon taxes, unlike other policy instruments, clearly identify winners and losers of the policy, leading to stronger opposition; and (e) potential institutional preferences favouring other carbon pricing instruments (Sterner and Köhlin, 2015).

Despite these political hurdles, some countries have already implemented carbon taxes. Figure 36 presents an overview of countries that have implemented carbon taxes or cap and trade sys-tems. Following Finland in 1990, several North-ern European countries implemented carbon taxes in the early 1990s. By 2016, 16 countries and one subnational entity (the Canadian prov-ince of British Columbia) had implemented a carbon tax.73 While most of these countries are developed ones, two developing countries (Mexico and South Africa) have implemented a carbon tax and a third one (Chile) plans to im-plement such a tax in 2017. However, only eight countries (Sweden, Finland, Switzerland, Norway, Denmark, Ireland, Slovenia, and France) and the province of British Columbia have a tax rate that is higher than US$10 per tonne of CO2 (World Bank, 2015). To put this figure into perspective, most simulations suggest that a global average carbon price of US$80 to US$120 per tonne of CO2 would be consistent with the 2°C target (World Bank, 2015). Sweden is currently the only country with a carbon price in this range, as it imposes a carbon tax of US$130 per tonne. This tax is by far the highest in the world – the second high-est carbon price (US$65 per tonne) is in Switzer-land. Hence, besides the fact that carbon taxes are only imposed on a fraction of global CO2 emissions, there is also a large gap between the required and the actual price of carbon. Having said that, the Swedish experience does clearly il-lustrate that carbon taxes are effective in reduc-ing CO2 emissions, as shown in Box 15.

73 Finland, Poland, Sweden, Norway, Denmark, Latvia, Slovenia, Estonia, Switzer-land, Ireland, Iceland, Japan, France, Mexico, Portugal, and South Africa. Note that a 17th country (Chile) plans to implement a carbon tax in 2017.


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4Overviewofimplementedorscheduledcarbonpricingpolicyinstruments

Figure 36

Source: World Bank (2015: 11).Note: The Regional Greenhouse Gas Initiative (RGGI) is a cooperative cap and trade effort among the US states of Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New York, Rhode Island, and Vermont.

Cap and trade (CAT) implemented or scheduled for implementation

Carbon tax implemented or scheduled for implementation

CAT or carbon tax under consideration

CAT and carbon tax implemented or scheduled

CAT implemented or scheduled, tax under consideration

Carbon tax implemented or scheduled, CAT under consideration

NEW ZEALAND

BRITISH COLUMBIA

WASHINGTONOREGON

CALIFORNIA

MEXICO

CHILE

BRAZIL

RIO DE JANEIROSÃO PAULO

RGGI

ALBERTA MANITOBA

ONTARIO

QUÉBEC

ICELAND

EU

TURKEY

UKRAINEKAZAKHSTAN

CHINA

THAILAND

JAPAN

SOUTH AFRICA

REPUBLIC OF KOREA

PORTUGAL

IRELAND

SWEDEN

FRANCESWITZERLAND

SLOVENIA

ESTONIA

FINLAND

LATVIA

UK

POLAND

NORWAY

DENMARK

Tally of carbon pricing instruments

KYOTOBEIJING

TIANJIN

HUBEISHANGHAI

CHONG- QING

SHENZHEN

GUANGDONG

TOKYOSAITAMA

REPUBLIC OF KOREA

The circles represent subnational jurisdictions. The circles are not representative of the size of the carbon pricing instrument, but show the subnational regions (large circles) and cities (small circles).

Note: Carbon pricing instruments are considered “scheduled for implementation” once they have been formally adopted through legislation and have an official, planned start date. National level Subnational level

21

14

439

23

1

22

TAIWAN PROVINCE OF CHINA


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leTheresultsoftheSwedishcarbontaxBox 15

Sweden’s carbon tax of US$130 per tonne (as of 1 August 2015) is the highest carbon tax worldwide to date. It particularly affects the Swedish transport sector, as the country taxes gasoline and diesel strictly in propor-tion to carbon emissions. It also applies to commercial use, residential heating, and partly to the industrial sector, which is, however, subject to a reduced tax rate (Sterner and Köhlin, 2015).

Given that Sweden also uses other climate change policies, it is difficult to precisely isolate the impact of the Swedish carbon tax on emissions. Nevertheless, Sterner and Köhlin (2015) note that the tax has achieved a cost-effective and efficient emission reduction over recent decades and has enabled the country to meet the commitments made in the Kyoto Protocol. Since 1990, Swedish CO2 emissions have declined by 22 per cent while the country’s economy has been growing. Sterner and Köhlin thus note that the country has success-fully managed to decouple domestic CO2 emissions and economic growth and thus made strides towards a low carbon-economy. As illustrated in Figure 37, Sweden’s CO2 emissions per US dollar of GDP are about one-third of the world average and have been constantly declining for more than 40 years. Note, however, that this figure does not account for potential carbon leakage effects of the Swedish carbon tax (relocation of polluting industries towards countries with less stringent climate change policies and hence lower costs of emitting CO2).

CarbondioxideemissionsperunitofGDPFigure 37

1971 1983 1987 1991 1999 20031975 1979 200719950.0

0.2

0.4

0.6

0.8

1.0

CO2 e

mis

sion

s/GD

P ra

tio

World

USA

OECD

UK

Sweden

Norway

Source: Sterner and Köhlin (2015: 254).

Source: Author's elaboration based on Sterner and Köhlin (2015).Note: OECD: Organisation for Economic Co-operation and Development.

A second policy instrument to price CO2 emis-sions is known as cap and trade (CAT) systems (also called emissions trading systems - ETS). Unlike carbon taxes, CAT systems do not directly regulate the price of CO2, but rather its quantity. Regulators decide on an upper limit of emissions that a country, region, or specific industry can emit (hence the “cap” in “cap and trade”), and then allocate permits to emit CO2 emissions to differ-ent firms. Each permit allows the firm to emit a certain quantity (often a tonne) of CO2. Each firm initially receives a certain quantity of permits, al-lowing it to emit a certain quantity of emissions. If the quantity emitted is smaller than the quan-tity of permits the firm possesses, the firm can sell its excess permits. If the quantity emitted is larger than the quantity of permits the firm pos-sesses, the firm has to buy additional permits. In

this way, a CAP system creates a market for CO2 emissions (hence the “trade” in “cap and trade”). The basic idea is to generate incentives for firms to reduce their emissions, as they can sell excess permits and make money out of emitting less. At the same time, the system penalizes firms that pollute too much, as they have to spend money to buy additional permits.

Regulators can allocate permits through auc-tions, free allocation, or a hybrid system that combines free allocation and auctions (Sterner and Köhlin, 2015). If the regulating authority de-cides to allocate permits by auction, it can gener-ate extra revenue for the government and does not need to devise a specific mechanism for the allocation of permits to firms. If permits are allo-cated freely, no government revenue is raised, as


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Carbonleakage,competitiveness,andcarbonbordertaxadjustmentsBox 16

firms do not have to pay to obtain the initial per-mits (“free allocation”). In that case, the regulat-ing authority must determine how to distribute the permits. It can, for instance, allocate permits proportional to firm output or based on histori-cal emission levels of firms. Regulators can adapt the cap over time, lowering the total quantity of emissions allowed to be emitted by issuing fewer permits, and thereby tighten the CAT system.

While CAT systems can in theory achieve any amount of emission reduction in a cost-effective way, they face considerable political obstacles, making stringent implementation difficult. In-dustry lobbying and fears that carbon prices might skyrocket and slow economic develop-ment often lead to a lax design of CAT systems with extremely high caps, resulting in only few emission reductions.

Several CAT systems are currently in place and more are scheduled for implementation (see Figure 36). The People's Republic of China, for in-stance, has already implemented several regional pilot CAT systems. Based on these pilots, it is plan-ning to launch a national CAT system in 2017 that is expected to cover major industry and energy sectors (World Bank, 2015). The largest CAT system currently in place is the European Union’s (EU) ETS, which was launched in 2005 and covers ap-proximately 45 per cent of the EU’s CO2 emissions (Sterner and Köhlin, 2005). The success of the programme has so far been mixed at best: most studies find evidence of only small if any emis-sion reductions (Anderson and Di Maria, 2010; Bel and Joseph, 2015; Ellerman et al., 2010; Georgiev et al., 2011). The main reason for these mixed re-sults lies in the design of the European system,

which has led to issuance of too many permits during the first two phases of the programme (2005–2007 and 2008–2012). This oversupply of emission allowances resulted in an extremely low price of CO2 emissions, reaching even zero euros in 2007. The third phase of the programme, which started in 2013, aimed to correct these ini-tial design flaws. The EU replaced the previous system of national caps with a single EU-wide cap that will be reduced annually by 1.75 per cent, made auctioning (instead of free allocation) the default rule to allocate permits, and included more sectors and gases in the system (European Commission, 2015). The European Commission is confident that due to these design changes, the system will achieve substantial emission reduc-tions in the years to come.74

Carbon taxes and CAP systems are the main policy instruments to directly price CO2 emis-sions. Together, these instruments were applied in roughly 40 countries (including 10 developing and transition countries) and 20 subnational re-gions in 2015 (World Bank, 2015; see also Figure 36). In many cases both instruments were applied in a complementary way in the same country. The instruments put a price on roughly half of the emissions emitted in these countries and re-gions, which represent about 12 per cent of global emissions (World Bank, 2015). As long as the inter-national carbon pricing landscape remains this fragmented, carbon leakage may be a major prob-lem for all carbon pricing policy instruments (see Box 16). Based on (rather spare) existing empirical evidence, however, the World Bank (2015) notes that carbon leakage has so far not materialized on a significant scale and that it affects mainly sec-tors that are both emissions- and trade-intensive.

74 The European Commission (2015) states that since the start of the third phase, emis-sions have fallen by 5 per cent and are expected to fall by 21 per cent in 2020 (compared to 2005) and 43 per cent in 2030 (compared to 2005).

Domestic carbon pricing is a major policy instrument, allowing countries to reduce their domestic CO2 emis-sions. In a world marked by a fragmented carbon pricing landscape, costs of emitting CO2 differ widely among countries. This cost difference raises two major concerns (Flannery, 2016). First, countries that put a high price on CO2 worry about the international competitiveness of their firms, as high carbon taxes are assumed to increase relative production costs and hence relative prices (especially in energy-intensive sectors). Second, countries worry that the impact their climate change policies have on global emissions might be limited by carbon leakage. Carbon leakage refers to the possibility that firms relocate their production or future in-vestments towards countries with less stringent climate change policies and thereby shift their emissions to these countries.

While carbon leakage does not yet seem to have materialized on a significant scale (World Bank, 2015), and while results from empirical economic analysis suggest that the overall macroeconomic impact on competi-tiveness, investment, and employment is small and statistically insignificant compared to other factors (Aldy, 2016), policymakers worry about these two possible effects. One possibility to mitigate them is so-called car-bon border adjustments (BAs). Kortum and Weisbach (2016: 2) define border adjustments as “taxes or other prices on imports and rebates on exports based on ‘embedded carbon,’ the additional emissions of carbon dioxide caused by production of a good. For imports, they can be thought of as the carbon tax that would have


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been imposed had the good been produced domestically (but using the production process and fuel that was actually used abroad). They therefore reduce the advantage of producing abroad and selling domestically because the carbon price is the same regardless of where production takes place. For exports, BAs are a rebate of the tax that was previously paid when the exported good was produced. By rebating previously paid taxes or carbon prices on exports, BAs reduce the disadvantage of producing domestically when selling into foreign markets.”

Such border tax adjustments can limit potential leakage and competitiveness effects, but in turn they pose several difficulties and risks. BAs are administratively complex instruments that are difficult to design and implement (Flannery, 2016). A major challenge of designing BAs is to avoid conflict with World Trade Organi-zation rules. Moreover, their effects on the welfare of the country imposing them are also difficult to estimate and not necessarily positive (Flannery, 2016).

Source: Author’s elaboration based on Flannery (2016).

While carbon taxes and CAP systems are the main policy instruments to tax carbon directly, two other policy instruments can achieve this goal indirectly. The first is removing fossil fuel subsidies that encourage consumption of fossil-fuel-based energy, discourage investments in clean energy sources and energy efficiency, and impose large costs on governments (Sterner and Köhlin, 2015). Phasing out these types of subsi-dies is an administratively simple way of making carbon-based fuels more expensive, thereby indi-rectly pricing CO2 and contributing to lower CO2 emissions. The second policy instrument, directly linked, is fossil fuel taxation. While fossil fuel taxes do not tax fossil fuels in proportion to their carbon content, they still provide an effective way to indirectly tax CO2 emissions in the transport sector. As such, they lower total consumption of fossil fuels as people adapt their behaviour (a fuel price increase of 1 per cent is estimated to lead to a reduction in fuel consumption of 0.7 per cent in the long run), create incentives for invest-ments in fuel-saving technologies, and favour the development of energy-efficient cars (Sterner and Köhlin, 2015). Fossil fuel taxes such as taxes on petrol and diesel have been around for a very long time, are frequently applied, and have been well-studied. Reviewing various studies, Sterner (2007), finds that fuel taxation is the policy in-strument that has had the highest impact on global carbon emissions.

2.1.1.2 Policy instruments that save energy

Policy instruments that increase the energy ef-ficiency of economies can also contribute to re-ducing anthropogenic CO2 emissions, especially if they are implemented together with carbon pricing instruments. By increasingly relying on energy-efficient technologies and thereby using less energy from fossil fuels, CO2 emissions per US dollar of GDP can be substantially reduced. The

emission reduction potential of energy conser-vation policies is large. For example, the Interna-tional Energy Agency (IEA) estimated that if its 25 energy efficiency recommendations were imple-mented globally, up to 7.6 GtCO2 per year (roughly 21 per cent of global CO2 emissions emitted in 2014) could be saved by 2030 (IEA, 2011).

IEA (2011) identified seven priority areas where increases in energy efficiency can substantially affect CO2 emissions. These areas include cross-sectoral energy efficiency increases, and sectoral energy efficiency increases in buildings, appli-ances and equipment, transport, lighting, indus-try, and energy utilities. A wide variety of policy instruments are available to increase energy ef-ficiency in these areas, including the following (World Energy Council, 2013):

• Institutional approaches (e.g. setting up ener-gy-efficiency agencies, energy- efficiency laws, or national energy-efficiency programmes);

• Product regulations (e.g. energy labels and/or minimum energy-efficiency standards for cars, buildings, domestic appliances and motors; or bans of specific energy-intensive products);

• Consumer regulations (e.g. mandatory ener-gy audits for selected customers, energy-sav-ing quotas, mandatory energy-consumption reporting, and energy-saving plans);

• Financial and fiscal measures (e.g. energy-ef-ficiency funds, subsidies for energy audits by sector, subsidies or soft loans for energy-effi-ciency investment and equipment by sector, tax credits or deductions on cars, appliances, and buildings; accelerated depreciation for industry, tertiary or transport sectors; or tax reductions by type of equipment such as ap-pliances, cars, lamps, etc.);

• Cross-cutting measures (e.g. voluntary agree-ments, mandatory professional training, or promotion of energy-saving companies).


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4While energy-saving policy instruments can re-duce anthropogenic CO2 emissions, their poten-tial to save energy and thus reduce CO2 emis-sions might be reduced by so-called rebound effects. Rebound effects can be illustrated by the following example: if you buy a more fuel-efficient car you will be driving more often, as you will have to pay less for fuel (Gillingham et al., 2013). Such behavioural changes in reaction to increased availability of energy-efficient tech-nologies might offset parts of the energy-saving potential. However, the literature finds that re-bound effects are too small to offset the energy-saving effects of energy-efficiency policy instru-ments (Gillingham et al. 2013).

2.1.1.3 Policy instruments that substitute energy from fossil fuels with alternative energy sources

These instruments aim to reduce the use of en-ergy from fossil fuels and thus facilitate the de-carbonization of the global energy system. IPCC (2014a) estimated that by 2100, the share of low-carbon energy sources (e.g. renewable energy sources or nuclear power) in total energy should increase from the current roughly 20 per cent to over 80 per cent. If this is not achieved, it is un-likely that the atmospheric GHG concentration in 2100 will stay below the level compatible with the 2°C temperature target. Fundamental pro-gress in new and more efficient energy technolo-gies is needed for such a transformation, as low-carbon energy technologies are currently not cost-competitive with fossil-fuel-based technolo-gies when applied on a large scale (Toman, 2015).

While carbon pricing and some energy-saving policy instruments alter incentives of economic agents and thus indirectly promote investments in a low-carbon economy, the energy-substitu-tion policy instruments try to directly promote the replacement of fossil-fuel-based energy with low-carbon energy. To decarbonize the energy system, policies need to stimulate the develop-ment and implementation of new low-carbon technologies. A priori, policies can promote two technological options: nuclear energy technolo-gies and renewable energy technologies. While next-generation nuclear reactors might replace a share of fossil-fuel-based energy and address the cost and safety issues undermining current generation reactors (Toman, 2015), we focus in this section on the promotion of renewable en-ergy technologies.

Renewable energy technologies – hydropower, wind and solar energy, tidal and wave energy, ocean and geothermal energy, and biomass en-

ergy – are expected to play a key role in decarbon-izing the energy system (Bossetti, 2015). Renewa-bles not only have the potential to substantially contribute to a low-carbon world, but might also generate important co-benefits, including (a) increased energy security due to more widely di-versified energy sources; (b) reduced local pollu-tion as fossil-fuel-based energy carriers such as coal are replaced; (c) promotion of green growth; and (d) new possibilities for development in many regions of the world, as renewables such as solar power are more evenly distributed glob-ally than fossil fuels (Bossetti, 2015). For example, the African Development Bank (2015) estimates that Africa has enormous potential for renew-able energy, and that its capacity for renewable energy generation could reach more than 10,000 gigawatts (GW) for solar energy, 109 GW for wind energy, 350 GW for hydro energy, and 15 GW for geothermal energy. The African Development Bank (2015) is confident that when the continent unlocks its full potential for renewable energy, it could tackle fundamental inefficiencies in its energy system, hugely expand power generation, and contribute towards the development goal of universal access to energy. Hence, policies fa-cilitating the adoption, integration, and develop-ment of renewable energy sources play a key role in mitigating climate change and can also have huge co-benefits in terms of health and econom-ic development.

The cost of renewable energy technologies can be considerably lowered by publicly funded R&D programmes and by providing incentives (e.g. tax incentives) for private programmes (Bossetti, 2015). These kinds of policies can di-rectly promote development and adoption of re-newable energy sources by making them more cost-competitive. A second way to promote adoption is to subsidize renewable energy tech-nologies. Germany’s Energiewende (see Box 17) is an example of probably the most aggressive subsidy policy to date favouring renewable en-ergy sources. Demand-side promotion policies such as standards, energy certificates, or feed-in tariffs75 are another policy option directly pro-moting adoption of renewable energy sources. Such policies have contributed considerably to the adoption of solar and wind power in Europe (Bossetti, 2015). Because renewable energy – un-like energy from fossil fuels - is highly unpredict-able and volatile (depending, for instance, on weather conditions in the case of wind or solar energy), infrastructure has to be adapted. Hence, public investments in new energy storage and distribution infrastructure can facilitate the in-tegration of renewables into the existing energy infrastructure.

75 Feed-in tariffs are policy mechanisms that aim to provide long-term contracts to renewable energy produ-cers based on the cost of the technology, thus stimulating investments in renewable energy production.


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76 Theoretically, it is also possible to apply CCS technologies to biomass burning, which could remove CO2 directly from the atmosphere, creating a so-called “negative emission technology” (Tavoni, 2015; see also Section 2.1.3). Biomass is a renewable resource which extracts and binds CO2 out of the atmosphere during its process of growing. By bur-ning biomass, CO2 is emitted back into the atmosphere. If CCS technologies are applied to biomass burning, the CO2 that biomass extracts from the atmosphere when it is growing could be captured and stored. This is one way to remove CO2 from the atmos-phere. See Section 2.1.3 for a discussion of other negative emission technologies.

77 Most of these technolo-gies store CO2 in its super-critical form in geological or oceanic storage sites. Super-critical CO2 is a fluid state of CO2 in which it is held at or above its critical temperature and critical pressure.

Germany has been pursuing an ambitious energy transformation policy for almost two decades based on massively subsidizing solar and wind energy. The policy, known as Energiewende, aims to achieve a transi-tion from a coal- and nuclear-power-based energy system to a system relying on renewable energy. Germany intends to reduce its GHG emissions by between 80 and 95 per cent (compared to 1995) within the next four decades. To achieve this target, it plans to increase the share of renewable energy in totally consumed energy to 80 per cent and simultaneously increase energy efficiency by 50 per cent (Sterner and Köhlin, 2015).

From 2000 to 2015, Germany increased its share of renewable energy in the energy production sector from 6 to almost 30 per cent (Figure 38). However, the share of renewable energy in the production of heat (9.9 per cent) and transport (5.4 per cent) is still relatively low. Prices of renewable energy technologies have decreased sub-stantially as a result of the massive subsidies and continue to do so (Sterner and Köhlin, 2015). However, CO2 emis-sions per kilowatt of produced energy have not yet dropped substantially, which Sterner and Köhlin attribute to the simultaneous phasing out of nuclear energy, which has required continued use of fossil fuel power stations.

ShareofrenewableenergiesinGermany’senergymarketFigure 38

Per c

ent

0

5

10

15

20

25

27.8%

12.4%

5.4%

30

19901991

19921993

19941995

19961997

19981999

20002001

20022003

20042005

20062007

20082009

2010 20112012

20132014

9.9%

Electricity

Heat

Mobility

Final energy (up to 2013)

While the Energiewende policy has clearly reduced costs and promoted widespread adoption of renewables, the subsidies have also generated important costs for the German government and for German households.

Source: BEE (2015: 1).

Source: Author's elaboration based on Sterner and Köhlin (2015) and BEE (2015).

2.1.2 Policies to promote technological solutions to capture and store carbon dioxide emissions

Section 2.1.1 described different policy instru-ments to reduce the production of anthropogen-ic CO2 emissions. In addition to these emission reduction policy instruments, governments can also implement policies that aim to capture and store already-emitted CO2 emissions before they reach the atmosphere.

Carbon capture and storage (CCS) technologies capture CO2 emissions from large sources such as coal power plants,76 transport them to a carbon storage site, and store them there so that they do not reach the atmosphere (Tavoni, 2015). Dif-ferent technological storage solutions are avail-able, including geological and oceanic storage sites.77 CCS has the capacity to make the ongoing large-scale use of fossil-fuel-based energy com-patible with climate change mitigation targets: if CCS technologies could be sufficiently up-scaled,

there would not be an immediate need to de-carbonize the economy. Tavoni (2015: 344) notes in his recent review on CCS technologies and policies that “CCS could effectively allow for the procrastinated use of fossil fuels while limiting – if not eliminating – their impact in terms of greenhouse gas emissions.” Given the appealing nature of CCS, it is not surprising that it plays an important role in the IPCC’s climate mitigation strategies (IPCC, 2014a).

While CCS technologies generate high hopes as an alternative mitigation option to reduce the flow of emissions towards the atmosphere, the technology is still in the early phases of develop-ment. In 2016, only 15 large-scale CCS pilot pro-jects were operational on a worldwide scale, with an additional four expected to enter into opera-tion (see Figure 39). These large-scale projects are complemented by small-scale pilot projects. So far, the existing projects have the capacity to cap-ture and store 28 million tonnes of CO2 per year (Global CCS Institute, 2015).


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4Numberoflarge-scalecarboncaptureandstoragepilotprojectsperyear

Directindustrialaircapturesystem

Figure 39

Figure 40

Num

ber o

f pro

ject

s

0

5

10

15

20

25

2010

7 8 812 13

15 15

47

15

2011 2012 2013 2014 2015 2016 2017

Projects currently under construction that

will enter into operationProjects in

the operational stage

Source: Global CCS Institute (2015: 4).

Source: Carbon Engineering. Available at: http://carbonengineering.com/air-capture.

It should be noted, however, that several tech-nological, political, and economic problems would need to be solved in order to apply CCS technologies on a sufficiently large scale. First, it is still not clear which CCS technology works best and if it will be able to operate at the re-quired scale. Policy measures are therefore re-quired to launch and (partially) fund additional pilot projects to test the different CCS designs (Tavoni, 2015). To do so, it would also be neces-sary to overcome public fears opposing the in-stallation of CCS infrastructure. This has led to the cancellation of CCS pilot projects in Europe in the past. It is also of crucial importance that storage solutions be safe and long-lasting, as leaking CO2 escaping towards the atmosphere would undermine the entire purpose of CCS. Second, the economic viability of CCS projects has to be improved, as the cost of capturing a tonne of CO2 is currently estimated at about US$100 (Tavoni, 2015). Policies to increase the price of carbon (thereby making higher-cost CCS technologies economically viable) and poli-cies to fund R&D could help achieve such a cost reduction (Tavoni, 2015).

2.1.3 Policies to promote technological solutions aimed at removing carbon dioxide directly from the atmosphere

While Sections 2.1.1 and 2.1.2 discussed policy op-tions to reduce the flow of emissions towards the atmosphere, this section discusses a policy in-strument that aims to remove CO2 directly from the atmosphere: carbon geoengineering.

Several technologies could remove CO2 from the atmosphere. One of them, already briefly intro-duced in Section 2.1.2, is the application of CCS technologies to biomass. According to Barrett and Moreno-Cruz (2015), this approach could be use-ful but will be limited in scale by design. A second technology is industrial air capture, a carbon geo-engineering technology that could be a viable al-ternative with the potential to be scaled up to any level (Barrett and Moreno-Cruz, 2015). Industrial air capture is a technology in which a capture so-lution (e.g. a chemical sorbent like alkaline liquid) is exposed to air, resulting in a chemical reaction removing CO2 from the air. The CO2 is subsequent-ly filtered out of the CO2-enriched capture solu-tion and is stored in suitable storage sites while the chemical sorbent is recycled (Figure 40).

Air

Capture solutions CO2

EnergyNatural gasWindNuclear

CO2 rich solutions


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If industrial air capture is powered by renew-able energy, the technology has the capacity to remove any amount of CO2 from the atmos-phere. If enough renewable energy is available to operate this technology on a sufficiently large scale, no other policies to stabilize CO2 concentrations would be needed. As such, car-bon geoengineering is considered to be the only true backstop technology to address cli-mate change (Barrett and Moreno-Cruz, 2015). However, this technology can only be imple-mented provided it is further developed and available at an affordable cost.

Several studies reviewed in the survey by Bar-rett and Moreno-Cruz (2015) estimate the costs of removing a tonne of CO2 through industrial air capture. These estimates range from US$30 per tonne up to US$600 per tonne. Barrett and Moreno-Cruz argue that if costs turn out to be as high as US$600 per tonne, the technology will not take off within a reasonable time frame. If, however, costs are as low as US$30 per tonne, the technology could revolutionize climate change policy and could even be implemented by a small coalition of countries. This coalition could uni-laterally mitigate climate change (Barrett and Moreno-Cruz, 2015) by bypassing the collective action problem associated with conventional emission reductions, and emission capture and storage policies.

Because this technology is not yet on the table of climate change policy negotiations (see Section 4), and because there are still many unknowns about it, the first policy step should be to fund and coordinate R&D efforts to evaluate the costs

and risks of industrial air capture technologies. Only if and when costs and risks are known can further policy instruments to promote carbon geoengineering be designed and implemented.

2.2Policiestopromotetechnologicalsolutions aimedatincreasingtheamountofincoming solarradiationreflectedbackintospace

Section 2.1 provided an overview of policy in-struments to stabilize atmospheric GHG con-centrations. Alternatively, however, humans could also try to offset the positive radiative forcing resulting from increasing GHG concen-trations by reflecting more of the incoming so-lar radiation back into the space. This approach, known as solar geoengineering, is able to offset increases in mean temperature rather quickly. But it does not address certain other impacts of increased GHG concentrations such as ocean acidification (Barrett and Moreno-Cruz, 2015). For this reason, Barrett (2014) labels solar geo-engineering a quick fix but not a true solution to climate change.

Solar geoengineering can be implemented in many ways. One option seems to be particularly promising in terms of costs: the injection of sul-phate aerosols into the stratosphere. Barrett and Moreno-Cruz (2015) cite a study by McClellan et al. (2012) that provides an estimate of less than US$8 billion per year to offset the positive radia-tive forcing expected to occur over coming dec-ades due to rising GHG concentrations. Unlike all other options, it seems that, in theory, even one willing country could implement such a solution single-handedly (Table 8).78 78 This raises international

governance questions, which today are far from settled. See Barrett and Moreno-Cruz (2015) for a short discussion on possible international governance frameworks.

ComparisonofpolicyoptionslimitingclimatechangeTable 8

Options Objectives Cost Risks Unknowns Collective action

Substantial reduction of the flow of CO2 emissions reaching the atmosphere

Reduce fossil fuel consumption and apply capture and storage technologies High Low None Difficult (see Module 3)

Carbon geoengineering Reduce the concentration of CO2 in the atmosphere Very high Moderate Few Coalition of the willing

Solar geoengineering Limit solar radiation reaching the lower atmosphere Low High Many Easy, apart from

governance

Source: Author’s elaboration based on Barrett and Moreno-Cruz (2015).

However, as in the case of carbon geoengineer-ing, many unknowns remain about solar geo-engineering. Most importantly, the technology may entail severe environmental risks that are not yet (fully) understood (Barrett and Moreno-

Cruz, 2015). Funding and coordinating R&D to assess the risks, feasibility, and efficiency of solar geoengineering is therefore needed before such technologies could be deployed.


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4Shortsummary

Section 2 reviewed the three fundamental policy options humans have to limit climate change: (1) substantial reduction of the flow of greenhouse gas emissions reaching the atmosphere, (2) direct removal of CO2 from the atmosphere by using carbon geoengineering, and (3) offsetting the positive radiative forcing resulting from increasing GHG concentrations by using solar geoengineering. These three options, including their ex-pected costs, risks, unknowns, and the prospect of collective action, are summarized in Table 8. While policies to substantially reduce the flow of emissions (carbon pricing, promotion of renewables, conventional carbon capture and storage) are well known and entail only few risks, there are two main caveats regarding their implementation: associated costs are high and there are collective action problems. Despite this, actions to limit climate change have so far focused almost exclusively on these options, which have also been imple-mented by several developed countries and some developing countries. Carbon geoengineering could be an alternative to these policies because it could be implemented by only a handful of nations, thereby bypassing the collective action problem. However, the associated environmental risks and especially the costs are higher than those associated with policies to reduce the flow of emissions. Finally, solar geoengineering has the advantage of being easy to implement single-handedly by only one country and of having very low costs. At the same time, however, it does not address some impacts of climate change, and entails even higher environ-mental risks than carbon geoengineering.

3 Climatechangeadaptation policyoptions

In addition to policies to limit climate change, humans can also try to reduce or even avoid the anticipated impacts of climate change by adapt-ing to climate change. IPCC (2014c: 118) defines climate change adaptation as the “process of adjustment to actual or expected climate and its effects. In human systems, adaptation seeks to moderate or avoid harm or exploit beneficial op-portunities. In some natural systems, human in-tervention may facilitate adjustment to expected climate and its effects.”

Given that the anticipated impacts of climate change are expected to be largest in developing and least developed countries (see Module 2),

adaptation policies are especially important for these countries. Drawing on Sauter et al. (2015, 2016), Figure 41 displays the projected population and damage shares of different regions.79 Re-gions mostly composed of developing countries (especially South Asia, sub-Saharan Africa, and the Middle East and North Africa) are expected to have a higher share in world damages in propor-tion to their share in world population by 2050. In other words, these regions will most likely be over-proportionally affected by the impact of climate change. Regions mostly composed of de-veloped countries (especially Europe and North America) are anticipated to have lower damage shares in proportion to their population shares. While these are only rough estimates, the num-bers clearly indicate that adaptation policies are of crucial importance for developing countries.

Potentialclimatechangedamageshareinrelationtopopulationsharebyregionin2050(percent)Figure 41

0

5

15

20

25

30

10

Dam

age s

hare

ove

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65

South Asia

Sub-Saharan AfricaEast Asia & Pacific

Europe & Central Asia

Latin America & Caribbean

Middle East & North AfricaNorth America

0 15 20 255 10 30Population share (projection in 2050)

Source: Mekonnen (2015: 88), adapted from Sauter et al. (2015, 2016).

79 Sauter et al. (2015, 2016) used a rough proxy of poten-tial damages based on pre-dicted increases in extreme temperature events.

Humans have a long history of adapting to a changing climate. Throughout history, human beings have changed the locations or construc-tion of their settlements, adapted their agricul-

tural technologies, and changed entire economic processes in response to climate variations (Bur-ton, 2006). Humans have been rather successful in doing so, but history also provides examples of


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local adaption failures that resulted in the col-lapse of entire societies (see Module 1). Adapting to human-induced climate change thus repre-sents a new chapter in a long history of human adaptation to climatic conditions, but this time, the dimension of the challenge is global.

Climate change adaptation policies have gained increased attention recently. Since about 10 years ago, adaptation has figured more prominently on the international policy agenda as the failure of current policies to reduce emissions has become evident (Barrett and Moreno-Cruz, 2015). As will be shown in Section 4, these policies are currently one of the two main pillars of international cli-mate change policy (the second pillar being poli-cies to reduce the flow of emissions towards the atmosphere). Given that climate change impacts,

risks, and vulnerabilities differ locally, different adaptation policies are needed in different places on the planet. The first step of any comprehensive adaptation policy therefore consists of assessing local risks and vulnerabilities in order to identify local needs (Noble et al., 2014). Once local needs are known, the government can choose appropri-ate measures from a wide range of adaptation options. While a detailed discussion of all these options is out of the scope of this teaching mate-rial, we provide a schematic overview by using the IPCC’s classification of adaptation measures. Table 9 lists the three broad categories of adap-tation options as classified in the fifth IPCC as-sessment report: structural and physical options, social options, and institutional options (Noble et al., 2014).

CategoriesandexamplesofadaptationoptionsdiscussedinthefifthIPCCassessmentreportTable 9

Category Examples of adaptation options

Structural and physical

Engineered and built environment

Seawalls and coastal protection structures; flood levees and culverts; water storage and pump storage; sewage works; improved drainage; beach nourishment; flood and cyclone shelters; building codes; storm and waste water management; transport and road infrastructure adap-tation; floating houses; adjusting power plants and electricity grid

Technological

New crop and animal varieties; genetic techniques; traditional technologies and methods; efficient irrigation; water-saving technologies, including rainwater harvesting; conservation agriculture; food storage and preservation facilities; hazard mapping and monitoring technol-ogy; early warning systems; building insulation; mechanical and passive cooling; renewable energy technologies; second-generation biofuels

Ecosystem- based

Ecological restoration, including wetland and floodplain conservation and restoration; increasing biological diversity; afforestation and reforestation; conservation and replanting mangrove forest; bushfire reduction and prescribed fire; green infrastructure (e.g. shade trees, green roofs); controlling overfishing; fisheries co-management; assisted migration or managed translocation; ecological corridors; ex situ conservation and seed banks; community-based natural resource management; adaptive land use management

ServicesSocial safety nets; food banks and distribution of food surplus; municipal services, including water and sanitation; vaccination programmes; essential public health services, including reproductive health services and enhanced emergency medical services; international trade

Social

Educational

Awareness raising; gender equity in education; extension services; sharing local and tradi-tional knowledge, including integrating it into adaptation planning; participatory action research and social learning; community surveys; knowledge-sharing and learning platforms; international conferences and research networks; communication through media

Informational

Hazard and vulnerability mapping; early warning and response systems, including health early warning systems; systematic monitoring and remote sensing; climate services, including im-proved forecasts; downscaling climate scenarios; longitudinal datasets; integrating indigenous climate observations; community-based adaptation plans, including community-driven slum upgrading and participatory scenario development

Behavioural

Accommodation; household preparation and evacuation planning; retreat and migration, which has its own implications for human health and security; soil and water conservation; livelihood diversification; changing livestock and aquaculture practices; crop-switching; changing crop-ping practices, patterns, and planting dates; silvicultural options; reliance on social networks

Institutional

EconomicFinancial incentives, including taxes and subsidies; insurance, including index-based weather insurance schemes; catastrophe bonds; revolving funds; payments for ecosystem services; water tariffs; savings groups; microfinance; disaster contingency funds; cash transfers

Laws and regulations

Land zoning laws; building standards; easements; water regulations and agreements; laws to support disaster risk reduction; laws to encourage insurance purchasing; defining property rights and land tenure security; protected areas; marine protected areas; fishing quotas; pat-ent pools and technology transfer

Government policies and programs

National and regional adaptation plans; sub-national and local adaptation plans; urban upgrading programmes; municipal water management programmes; disaster planning and preparedness; city- and district-level plans and sector plans, which may include integrated water resource management, landscape and watershed management, integrated coastal zone management, adaptive management, ecosystem-based management, sustainable forest management, fisheries management, and community-based adaptation

Source: Noble et al. (2014: 845).


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4Structural and physical options include the use of engineering (e.g. building sea walls or coastal protection structures), the application of specific technologies (e.g. the use of new crop varieties resistant to local anticipated climate impacts or the implementation of early warning sys-tems to prepare for the increased frequency of extreme weather events), the use of ecosystems

and ecosystem services (e.g. assisted migration of threatened species or ecological restauration measures), and the delivery of specific services at various levels (e.g. the creation of food banks to counter anticipated food shortages or the imple-mentation of vaccination programmes to limit expected health risks). Box 18 provides an example of a structural adaptation project in Bangladesh.

CyclonesheltersandearlywarningsystemsinBangladesh

ThecamellonesprojectinBolivia

Box 18

Box 19

Bangladesh has experienced a number of extreme weather and climate events over its history. According to the Intergovernmental Panel on Climate Change (IPCC), approximately 500,000 people died during a cat-egory 3 cyclone in 1970. In 1991, another category 3 cyclone killed 140,000 people.

As climate change increases, the likelihood of such extreme weather and climate events, including future cy-clones, is probable. Bangladesh has therefore undertaken a collaborative process between local communities, government, and private organizations to implement adaptation measures. This collaboration has improved overall education about disasters (a social adaptation measure), deployed early warning systems based on high-technology information systems and measures such as training volunteers to distribute warning mes-sages by bicycle (a structural and physical adaptation measure), and built a network of cyclone shelters (an-other structural and physical adaptation measure).

As a result of these adaptation efforts, Bangladesh was able to achieve a remarkable reduction in mortality: during the category 4 cyclone in 2007, 3,400 people died, considerably down from the 500,000 and 140,000 deaths recorded during the previously mentioned cyclones. The achievement is even more remarkable consid-ering that the country experienced population growth of more than 30 million between the cyclone events.

Source: Author's elaboration based on Smith et al. (2014).

Social options aim to reduce local vulnerabilities of disadvantaged segments of the population and actively address social inequities (Noble et al., 2014). They include educational measures (e.g. awareness-raising and knowledge-sharing about adaptation planning), informational measures (e.g. the development and dissemina-tion of improved climate forecasts to better iden-

tify risks), or behavioural measures (e.g. changing agricultural practices, switching crop varieties, or developing household evacuation plans). Table 9 outlined additional examples of social adapta-tion options. Box 19 provides an example of an adaptation project implemented in Bolivia that combines a behavioural measure with a struc-tural measure.

In Bolivia, the frequency of extreme weather events has increased in recent years and is expected to further increase in the future due to climate change. Increased frequency of floods particularly threatens the poor population living in remote rural areas of the country. Devastating floods in Beni in 2007 prompted people from locations around Trinidad to participate in a project known as camellones that was jointly implemented by the Kenneth Lee Foundation and Oxfam.

The project consists of a combination of behavioural adaptation – a change of an agricultural practice – and a structural adaptation – the building of the camellones platforms. The aim of the project was to avoid future agricultural losses due to increased occurrence of floods. Instead of using a conventional farming technique, the project implemented the camellones farming technique that is based on a traditional farming method. Several modern camellones were built in 2007 and have since been used for farming (see photo). These mod-ern camellones are essentially earth platforms. Each platform measures roughly 500 m2 and varies in height between 0.5 and 3 meters, depending on the predicted height of the local flooding and the area’s capacity for water run-off (Oxfam, 2009). Because these platforms are above the flood levels, they protect the crops from the flood. The ditches surrounding the camellones become canals in the event of a flood and act as an irriga-tion and nutrient source during the dry season (Oxfam, 2009).


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leThecamellonesprojectinBoliviaBox 19

Source: http://valorandonaturaleza.org/noticias/manejo_precolombino_de_ecosistema_amaznico_

Source: Author's elaboration based on Oxfam (2009).

CamellonesinBolivia

As a result of the new agricultural practices, farmers did not lose their crops and seeds during floods in 2008. The system seems to be a sustainable solution to address increased flooding, and it also preserves water for times of drought, acts as a natural seed bank, and improves soil quality and ultimately food security (Oxfam, 2009).

Institutional options aim to increase the poten-tial for adaptation (Noble et al., 2014) through a variety of economic measures (e.g. disaster con-tingency funds or financial incentives to imple-ment adaptation options), legal and regulatory measures (e.g. mandatory building standards, or

laws to encourage contracting and insurance), and governmental plans and programmes (e.g. national and regional adaptation plans to coordi-nate adaptation efforts). Table 9 listed additional institutional options. An example of an institu-tional adaptation policy is provided in Box 20.


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4Nepal’sNationalFrameworkonLocalAdaptationPlansforAction

Box 20

In 2011, Nepal adopted the Nepal National Framework on Local Adaptation Plans for Action (LAPA). The LAPA framework aims to integrate climate adaptation into local and national development planning processes in a bottom-up, inclusive, responsive, and flexible manner (Government of Nepal, 2011). Figure 42 outlines schematically how climate adaptation actions are integrated into and harmonized with local and national planning. The LAPA framework foresees seven steps: (1) information gathering; (2) vulnerability and adaption assessment; (3) prioritization of adaptation options; (4) formulation of LAPAs; (5) integration of LAPAs into lo-cal planning processes; (6) implementation of LAPAs; and (7) assessment of the progress of LAPAs. These steps are followed by implementation of a village- or district-specific LAPA (Government of Nepal, 2011).

ThelocaladaptationplansforactionframeworkFigure 42

Climate change policy, 2011 and NAPA, 2010

Implementation

Identification of most climate unerable districts

Integration of adaptation optionsinto national anddistrict plans

Clim

ate

vuln

erab

ility

ass

essm

ent

Clim

ate

adap

tatio

n re

silie

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plan

ning

Integration of local adaptation plan for action and/or adaptation options into district-leveldevelopment plan

Local plans for adaptationand collective action

Climate vulnerabilityassessment to identityVDC, municipalyty andlivelihoods at risks

Support for adaptation of public goods by local bodies

Collective actions by groupesand enterprises

Adaptation households,enterprises and groups

Climate vulnerabilityassessment to identitycommunities and people at risk

Bottom-up planning of adaptation that involves identification and prioritization

of needs and options

Village/town/community

National

District

VDC/Municipality

By 2014, a total of 70 LAPAs had been prepared (69 at the village level and one at the municipality level) and implemented by the affected communities (Mimura et al., 2014).

Source: Government of Nepal (2011: 6). Note: NAPA: National Adaptation Programme of Action; VDC: Village Development Committees.

Source: Author's elaboration based on Government of Nepal (2011) and Mimura et al. (2014).

Identifying adaptation needs and implement-ing adaptation options is costly and requires funding. As risks and vulnerabilities and thus adaptation needs are unevenly distributed and are often highest in poor countries, local adapta-

tion requires globally coordinated financing. As Section 4 will show, negotiations on adaptation financing are a central part of global climate change negotiations.

Shortsummary

Section 3 reviewed adaptation policies that aim to reduce or even avoid the anticipated impacts of climate change by adapting economies to climate change. Given that climate change impacts, risks, and vulnerabili-ties differ locally, different adaptation policies are needed in different places on the planet. The section ex-plained that the first step of any comprehensive adaptation policy therefore consists of assessing local risks and vulnerabilities in order to identify local needs. Once local needs are known, the government can choose appropriate measures from a wide range of adaptation options. The section also highlighted that adaptation policies are especially important for developing and least developed countries, as the anticipated impacts of climate change are expected to be largest in these countries.


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4 Theinternationalclimatechange policyarchitecture

Having discussed the different options for cli-mate change limitation and adaptation policies, we now turn our attention towards the interna-tional climate change policy framework. Multi-lateral climate change negotiations to date have mainly focused on emission reduction policies and, more recently, have also started to integrate adaptation policies. We structure our discussion around three milestones in the development of the multilateral climate change policy frame-work: (a) the signature of the 1997 Kyoto Proto-col, which was the first substantial international agreement to reduce GHG emissions by estab-lishing country-specific, legally binding emission targets for developing countries; (b) the failure of the COP15 in Copenhagen that marked the end of the Kyoto Protocol approach; and (c) the suc-cessful conclusion of the COP21 in Paris, which marked the start of a new era of international climate policy architecture. Unlike what has hap-pened over the past two decades, the Paris Agree-ment does not impose legally binding emission targets for developed countries, but rather is built on voluntary national contributions by all countries. As such, it represents a major change from the Kyoto Protocol approach, which had a more limited scope albeit high ambitions, to a regime based on broad participation, even if its ambitions are initially relatively modest.

4.1 FromRiotoParis–25yearsofclimate changenegotiations80

The 1992 Conference in Rio adopted the United Nations Framework Convention on Climate Change (UNFCCC), which required signatory countries to undertake national inventories of GHG emissions and develop action plans to re-duce national emissions. Signatory countries of the UNFCCC then held yearly conferences (called Conferences of the Parties - COPs) starting in 1995. From the very beginning of the UNFCCC process, a key principle guiding the negotiations was that of common but differentiated responsibilities. This principle is enshrined in Principle 7 of the Rio Dec-laration on Environment and Development:

“In view of the different contributions to glob-al environmental degradation, States have common but differentiated responsibilities. The developed countries acknowledge the responsibility that they bear in the interna-tional pursuit of sustainable development in view of the pressures their societies place on the global environment and of the technolo-gies and financial resources they command.”

In other words, the principle of common but dif-ferentiated responsibilities takes into account that the bulk of cumulative human-induced GHG emissions have been emitted by the cur-rent developed countries. For this reason, these countries should bear a greater responsibility in solving the climate change issue.

The Kyoto Protocol was the first substantial in-ternational agreement to reduce GHG emissions. Signed at the COP3 in Kyoto in 1997, it fully em-braced the principle of common but differentiat-ed responsibilities (Flannery, 2016). The protocol used the UNFCCC classification of countries into Annex I, Annex II, and Non-Annex I Parties. An-nex I Parties encompassed industrialized mem-ber countries of the Organisation for Economic Co-operation and Development (OECD) as of 1992 and countries with economies in transition (EIT Parties), which included Russia, Central and Eastern European countries, and Baltic countries. Annex II Parties consisted of a subset of Annex I countries, namely those countries that were members of the OECD in 1992. Non-Annex I Par-ties were mostly developing countries.

Based on this country classification, the Kyoto Protocol imposed legally binding mitigation tar-gets for Annex I Parties and established a mar-ket mechanism to facilitate reductions in GHG emissions. In accordance with the principle of common but differentiated responsibilities, it excluded all developing countries (Non-Annex I Parties) from any legally binding obligation to reduce emissions. Moreover, it imposed an ob-ligation on Annex II parties to provide financial support to Non-Annex I Parties.

The Kyoto Protocol used the so-called top-down approach (Flannery, 2016): negotiations conduct-ed at the international level focused essentially on determining country-specific, legally bind-ing emission targets for Annex I countries. Each country then had to implement the required emission reductions using suitable policy instru-ments (many of which were described in Section 2.1). The overall goal of the protocol was to reduce emissions of all major greenhouse gases by 5 per cent by 2012 relative to 1990.

To enter into force, the Kyoto Protocol needed to be ratified by at least 55 countries, responsible for at least 55 per cent of 1990 CO2 emissions. While it was signed in 1997, the required conditions for entering into force were only met in 2005. The first phase of the protocol thus started in 2005 and was set to end in 2012. The United States, at the time the country with the highest GHGs emissions worldwide, never ratified the protocol.

80 This section draws on Flannery (2016).


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4Its absence from the Kyoto Protocol illustrates the collective action problem (see Module 3) and has been one of the factors that considerably weak-ened the Kyoto process.

After 2005, efforts quickly concentrated on nego-tiating the roadmap for future developments to shape international climate change policy after the first commitment phase of Kyoto expired in 2012. During COP13 in Bali in 2007, a roadmap was agreed upon with two key points. The first was to prepare a second Kyoto commitment period with legally binding emission reductions for Annex I Parties for the COP15 to be held in Copenhagen. The second was to open negotiations for a new agreement involving all UNFCCC parties. Accord-ing to Flannery (2016), it was this latter decision that signalled, for the first time, that the princi-ple of common but differentiated responsibili-ties could evolve.

The COP15 in Copenhagen in 2009 resulted in an outcome that many observers qualified as a failure: the conference did not agree on a legally binding extension of the Kyoto Protocol. Flannery (2016: 72) states that by failing to reach such a legally binding extension, “Copenhagen dealt a deathblow to the top-down approach in which nations negotiated terms for one another’s ac-tions as the basis for agreement. Going forward, national pledges will be based on voluntary sub-missions that reflect national circumstances and priorities.” Such an approach based on voluntary national contributions is generally called a bot-tom-up approach. In retrospective, Copenhagen indeed marked the end of top-down approaches in international climate change negotiations. Such an outcome could have been anticipated, however, as many heads of state (including those of the United States and the People's Republic of China) had announced earlier that they would not sign a legally binding agreement. After the Copenhagen failure, negotiations remained stalled for several years. It was only in 2012 at the COP18 in Doha that there was agreement on a second Kyoto commitment period (until 2020).

With regard to global GHG emissions, the top-down approach of the Kyoto Protocol can be considered a failure (Barrett et al., 2015): the IPCC notes that while the group of Annex I countries indeed managed to collectively meet their Kyoto target by reducing their aggregate emissions more than 5.2 per cent below 1990 levels by 2012, these reductions were largely offset by emission growth in Non-Annex I countries (Stavins et al., 2014).81 Consequently, global GHG emissions, in-stead of being reduced, have been growing at an unprecedented rate over the past two decades.

In parallel with negotiations on a second Kyoto commitment period, negotiations were taking place to develop a post-2020 climate change policy framework. To this end, the COP17 in Dur-ban established the Ad Hoc Working Group on the Durban Platform for Enhanced Action (ADP) with a mandate to (a) increase the ambition of the climate change limitation policy for the pre-2020 period, and (b) negotiate a global agree-ment for the post-2020 period by 2015 (Flannery, 2016). Compared to the political landscape of the 1990s that led to adoption of the Kyoto Protocol, the situation has changed considerably. Besides the obvious failure of the top-down approach of the Kyoto Protocol, GHG emissions from develop-ing countries have been growing rapidly. While the United States had been the largest emitter of CO2 until the mid-2000s, the People's Republic of China has been the largest emitter since 2005. Other developing countries such as India are cur-rently also among the top emitters worldwide. Following intense negotiations, the ADP’s work ultimately led to the outcome of the COP21: the Paris Agreement.

4.2TheParisAgreement

Negotiations for a post-2020 climate change framework initiated by the ADP concluded suc-cessfully in 2015 with the adoption at COP21 of the Paris Agreement. The agreement brings the 197 parties to the United Nations Framework Convention on Climate Change (all United Na-tions Member States, the State of Palestine, the Cook Islands, Niue and the European Union) un-der a common legal framework. This represents a change from the Kyoto Protocol, which had a more limited scope, albeit high ambitions, to a regime based on broad participation, even if am-bitions initially are relatively more modest. This departure from the past two decades of a top-down climate policy, which suffered from lim-ited coverage of only a small subset of countries required to cut emissions, towards a bottom-up framework, which involves all UNFCCC parties, is important given the paramount significance of long-term action by all countries to address cli-mate change.

Together with the new architecture combining bottom-up Nationally Determined Contributions (NDCs) – i.e. national commitments to reduce GHG emissions, with top-down procedures for reporting and synthesis of NDCs by the UNFCCC Secretariat – the Paris Agreement represents sig-nificant progress towards a climate regime that could limit climate change. Prior to the Paris Con-ference, 186 parties had submitted Intended Na-tionally Determined Contributions (INDCs),82 and

81 This growth can be partially attributed to carbon leakages from developed countries.

82 Note that INDCs became NDCs when the Paris Agreement was concluded.


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83 Note that the agreement specified the Secretary-Ge-neral of the United Nations as Depositary. He or she will be responsible for ensuring the proper execution of all treaty actions related to the agreement.

two more did so during the conference, bringing the total to 188 INDCs. The Paris Agreement will take effect in 2020 when the Kyoto Protocol ends. In the interim, parties agreed to promote climate action, ramp up financing, and begin implemen-tation of their climate plans. They will have an opportunity, as part of a collective review in 2018, to update these plans. Equally important is the fact that the private sector has been involved in a major way in contributing to climate action. Over 5,000 global companies in 90 countries covering all industrial sectors pledged actions to combat climate change.

It is important to note that the new policy ar-chitecture incorporates several elements that have been identified by game theory models (see Module 3) as being able to increase cooperation. NDCs can be viewed as national commitments to reduce emissions (to some extent) regardless of what other countries are doing. If they turn out to be credible commitments, they will be a key element fostering cooperation. The financial transfer mechanisms and the repeated follow-up procedures (see Section 4.2.2), as well as the pros-pect of linking development and climate change policy issues (see Section 4.2.3), are additional el-ements that strengthen cooperation under the Paris Agreement. So far, these elements seem to have positively affected the agreement’s sig-nature and ratification process. The Paris Agree-ment was opened for signature on 22 April 2016. By 29 June 2016, 179 countries had signed it. To date, 19 of the 179 signatories have also deposited their instruments of ratification, acceptance, or approval, accounting in total for 0.18 per cent of total global GHG emissions (UNFCCC, 2016). Ac-cording to Article 21, §1, of the Paris Agreement, the agreement will enter into force 30 days af-ter the date on which at least 55 parties to the convention, accounting in total for at least 55 per cent of total global GHG emissions, have depos-ited their instruments of ratification, acceptance, approval, or accession with the Depositary.83

Similar to the Kyoto Protocol, the Paris Agree-ment reflects the principle of common but differ-entiated responsibilities and thus takes on board the equity and fairness concerns of developing countries. The following sections review the con-tent and the ambition of the agreement, explain the follow-up procedures, and discuss climate financing.

4.2.1 Objectives of the Paris Agreement

Parties to the agreement aim to limit “the in-crease in the global average temperature to well below 2°C above pre-industrial levels and to pur-

sue efforts to limit the temperature increase to 1.5°C above pre-industrial levels” (Article 2.1.a of the agreement). This formulation represents a win for small island developing states and other developing nations that argue that a tempera-ture increase above 1.5°C would be devastating for them.

Parties also aim to “reach global peaking of GHG emissions as soon as possible,” without specify-ing a date. They will “undertake rapid reductions thereafter in accordance with best available sci-ence, so as to achieve a balance between anthro-pogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century” (Article 4.1). This does not mean that emissions would go to zero, but that they would go low enough that they could be offset by natu-ral processes or advanced technologies that are able to remove greenhouse gases from the air (see Sections 2.1.2 and 2.1.3).

Put simply, the Paris Agreement requires any country that ratifies it to act to stem its GHG emissions in the coming century, with the goal of peaking GHG emissions “as soon as possible” and continuing the reductions as the century progresses. Parties will aim to prevent global temperatures from rising more than 2°C by 2100 with an ideal target of keeping the temperature rise below 1.5°C.

4.2.2 Follow-up procedures and financing

The Paris Agreement calls on all countries to sub-mit a new NDC every five years (Articles 3, 4, 7, 9, 10, 11, and 13) that should represent a “progres-sion” over the prior one, and should reflect the country’s “highest possible ambition” (Article 4.3). This process is crucial, because the commitments in current NDCs are not sufficient to limit warm-ing to below 2°C, much less 1.5°C. The UNFCCC Secretariat’s assessment of the collective impact of over 146 INDCs submitted by 1 October 2015 (i.e. prior to the Paris Conference) concluded that they will result in a fall in global emissions and keep the rise in global warming to around 2.7°C by 2100. While not enough to avert a dangerous warming of the earth, these commitments are important steps forward.

Implementation of the agreement will be as-sessed at “global stocktakes” every five years, with the first global stocktake scheduled for 2023 (Arti-cles 14.1 and 14.2).

In addition to climate change mitigation, the agreement also stipulates that countries will “en-gage in adaptation planning processes” (Article


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49) to ensure that they are ready to cope with the effects of climate change. For impacts to which countries cannot adapt, the agreement contains a “loss and damage” section, suggesting that these cases will be addressed through a variety of means including “risk insurance facilities, cli-mate risk pooling and other insurance solutions” (Article 8.4.f). This provision is another key win for small island states and other vulnerable de-veloping nations.

The agreement states that developed countries “shall provide financial resources to assist de-veloping country parties with respect to both mitigation and adaptation” (Article 9.1) – i.e. to help them brace for impacts and shift to cleaner energy systems. The text suggests, however, that wealthier developing countries can also contrib-ute such funds if they so choose. Several such countries have considered doing so (e.g. Brazil), and the People's Republic of China has already pledged to provide US$3.1 billion over a three-year period. Developed countries should report on their climate donations every two years (Ar-ticle 9.5). Such financial assistance will to a large

extent determine the level of implementation of NDCs by developing countries. The commit-ment of developing countries to address climate change is thus largely contingent on financial as-sistance from wealthier countries.

In this context, developed countries should con-tinue their existing collective financing mobi-lization goal agreed upon in Cancún at COP16 through to 2025. That goal was to provide funds equal to US$100 billion per year by 2020. Prior to 2025, the parties to the Paris Agreement shall set a new collective quantified financing goal of at least US$100 billion per year, taking into account the needs and priorities of developing coun-tries (Article 9, §3, Decision 54). To put this goal of US$100 billion per year into perspective, note that available climate financing in 2014 was esti-mated at US$62 billion (Mai et al., 2016). As Figure 43 shows, roughly one-third of this amount came from multilateral sources, slightly more from bi-lateral sources, and the remaining part from pri-vate sources. Considerable efforts will thus have to be made to reach the US$100 billion per year target by 2020.

Estimatedclimatefinancingin2014Figure 43

Targets and (actual and potential) sources of climate finance

Goals for 2020 Mobilize from advanced economies US$100 billion per year for climate mitigation and adapatation in developing countries by 2020

Actual flows in 2014

US$23.1 bn Bilateral (e.g Official development assistance)

US$20.4 bn Multilateral (moslty Multilateral development banks)

US$16.7 bn Private finance (leveraged from public sources

US$1.6 bn Export credits (mainly for renewable energy

US$61.8 bn Total flows

Potential extra revenues US$25 bn $30/ton CO2 charge, advanced economy domestic fuels (7 per cent apportioned).

US$25 bn $30/ton CO2 charge, international aviation/maritime fuels.a

Source: Mai et al. (2016: 28)a Includes only revenues from developed countries.

Financial resources to support climate mitiga-tion and adaptation actions in developing coun-tries are managed by four funds: the Green Cli-mate Fund, the Global Environment Facility, the Least Developed Countries Fund, and the Special Climate Change Fund (Decision 59). While raising the required US$100 billion per year is clearly the most pressing challenge, several other challenges remain on the spending side and still need to be addressed. Mai et al. (2016: 27) note that there “are concerns on the spending side about the balance between mitigation and adaptation (currently most is on the former), allocating funding across countries and projects accounting for efficiency and equity, and avoiding paying for projects that would have gone ahead without funding.”

4.2.3 Paris Agreement and development

Compared to the previous climate change pol-icy architecture, the Paris Agreement marks a change for developing countries: they are now also called upon to implement climate change limitation policies by submitting their own NDCs, which was not the case under the Kyoto Protocol. These countries have a strong inter-est in limiting climate change, as they are over-proportionally exposed to the associated risks (see Module 2 and also Section 3 of this Mod-ule). However, they also have a strong interest in rapid economic growth that would allow them to eradicate poverty and increase standards of living (Collier, 2015).


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To pursue these two objectives simultaneously, the transformation towards low-carbon and resource-efficient economies must proceed in a way that allows for decoupling economic growth and social development from climate change. UNCTAD (2015: 1) notes that for developing coun-tries, “such a decoupling should facilitate, and not undermine, opening new trade and investment opportunities, generating jobs, growing national economies, widening access to basic necessities and essential services and reducing poverty.” To be able to achieve these objectives while limiting climate change, developing countries thus firmly demanded the inclusion of the principle of com-mon but differentiated responsibilities in the Paris Agreement.

Given that they succeeded and that the Paris Agreement is built upon this principle, developing countries can count on financial and technological support from developed countries to implement their NDCs. The financial transfer mechanisms aiming at transferring at least US$100 billion per year from developed to developing countries by 2020 is one of the two key factors expected to enable developing countries to implement their NDCs. Technology transfer from developed to de-veloping countries in areas such as renewable en-ergy and energy conservation technologies is the second key factor for successful implementation of developing countries’ NDCs. Financial and tech-nological transfers should jointly ensure that the implementation of NDCs does not hurt develop-ing countries’ growth prospects.

Several observers are confident that due to the finance and technology-transfer mechanisms developing countries might not only be able to contribute to limit global GHG emissions by im-plementing their NDCs, but could also benefit from important co-benefits of these policies. The African Development Bank (2015: 3) notes that the need to respond to climate change repre-

sents “an opportunity to drive the economic transformation that Africa needs: climate-re-silient, low-carbon development that boosts growth, bridges the energy deficit and reduces poverty. Climate change gives greater urgency to sound, growth-stimulating policies irrespective of the climate threat.” The African Development Bank (2015) identifies several important co-ben-efits in different sectors. The African energy sec-tor could greatly benefit from a transformation towards renewable energies, which could tackle fundamental inefficiency in Africa’s energy sys-tems and generate important investment op-portunities. A second set of major co-benefits relates to the agricultural sector. Implementa-tion of climate-smart agriculture could increase Africa’s annual agricultural output from the current US$280 billion to an estimated US$880 billion by 2030, which would offer the potential to increase food security and generate jobs (Af-rican Development Bank, 2015). The third major set of co-benefits lies in low-carbon and climate-resilient investments in African cities. Such in-vestments could make cities less vulnerable to anticipated climate change impacts, and also improve economic productivity, security, air qual-ity, and public health, as well as reduce poverty (African Development Bank, 2015). The combina-tion of finance and technology-transfer mecha-nisms with policies that help mitigate climate change and also produce significant co-benefits stimulating growth is thus key for the success-ful transformation of developing economies into low-carbon economies.

Many developing countries were among the first parties to sign the Paris Agreement: 18 of the 19 countries that had ratified the agreement as of this writing are developing countries. Many de-veloping countries have also already submitted detailed NDCs. Box 21 briefly illustrates the objec-tives and approaches of the NDC of one such de-veloping country, Kenya.

Kenya’sNationallyDeterminedContributionobjectivesandapproachesBox 21

Kenya’s experience is typical for a lower-income country that aspires to high growth but also wants to pursue climate change policies. According to Kaudia (2015), Kenya’s GHG emissions were estimated to be 73 MtCO2-eq in 2010, with roughly 75 per cent of them attributable to activities such as agriculture, forestry, and free-range rearing of livestock. Historically, Kenya’s contribution to cumulative global GHG emissions has been very low, ranging around 0.1 per cent, with cumulative per capita emissions of less than 1.26 MtCO2-eq (the global average is 7.58 MtCO2-eq). Kaudia (2015) notes that the country plans to attain 10 per cent GDP growth by 2030, which would double its emissions if no additional climate change policies were implemented. The Intended Nationally Determined Contribution Kenya submitted before the COP21 in Paris foresees reducing the country’s emissions by 30 per cent compared to their 2014 levels (see the low-carbon pathway in Figure 44). Kenya thus intends to pursue ambitious growth while simultaneously committing to an ambitious emis-sion reduction goal.


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4Kenya’sNationallyDeterminedContributionobjectivesandapproaches

Box 21

To achieve this ambitious goal, Kenya has already implemented several policy measures to limit climate change. These include policies to indirectly price carbon dioxide by taxing older and hence fuel-inefficient vehicles and by limiting the age of vehicles that can be imported to a maximum of eight years. Kenya has also integrated climate change into its national planning process and established, in cooperation with the World Bank, what are called Climate Innovation Centers, which have had a positive impact through various climate-change-related investment projects (Kaudia, 2015).

Kenya’scarbondioxideabatementpotentialbysectorFigure 44

2010 2015 2020 2025 20300

1,000

1,500

500

2,000

2,500

3,000

Emis

sion

Mto

n CO

2eq

Reference case projection

Reduction below reference case:

Low-crabon pathway

-15% -41% -59% -69%

Kaudia (2015) reports that reducing the rate of deforestation by way of large-scale tree planting would be the least-cost solution to tackle climate change in Kenya and other low-income countries. As shown in Figure 44, Kenya’s forestry sector clearly has the biggest CO2 abatement potential. This cost-effective solution would preserve or even increase natural carbon sinks and thus contribute to reducing the country’s emissions. Kau-dia (2015) therefore recommends that low-income countries that rely on natural capital to develop their green growth strategy should mainly focus on environmental and natural resource management policies

Source: Kaudia (2015) based on data from Government of Kenya (2012).

Source: Author’s elaboration based on Kaudia (2015).

Shortsummary

Section 4 reviewed the international climate change policy architecture. It discussed the past 25 years of inter-national climate change policy that started with the adoption of the United Nations Framework Convention on Climate Change (UNFCCC) in 1992. The section showed that climate change policy has been shaped by the principle of common but differentiated responsibilities. It also showed that over past years, climate change policy shifted from a top-down approach – the Kyoto Protocol – towards a mixed approach upon which the Paris Agreement relies. This latter approach combines bottom-up nationally determined contributions – i.e. national commitments to reduce greenhouse gas emissions – with top-down procedures for reporting and synthesis of nationally determined contributions by the UNFCCC Secretariat.

ForestryElectricity

TransportationEnergy demand

AgricultureIndrustrial process

Waste


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1. Describethetwofundamentaloptionsavailabletolimitclimatechange.

2. Listpolicyinstrumentscapableofreducingatmosphericgreenhousegasconcentrations.

3. Comparecarbontaxestocarboncapandtradesystemsanddiscusstheirrelativeadvantagesanddisad-vantages.

4. Whatarecarboncaptureandstoragetechnologies?

5. Comparesolargeoengineeringtocarbongeoengineering.Whatarethefundamentaldifferences?

6. Discusstheobjectives,costs,risks,unknowns,andcollectiveactionprospectsof:

• Substantialreductionsoftheflowofcarbondioxideemissionsreachingtheatmosphere • Carbongeoengineering • Solargeoengineering

7. Discusstheimportanceofclimatechangeadaptationprojectsforyourcountry.Findexamplesofplannedorimplementedclimatechangeadaptationprojects.

8. IdentifythefundamentaldifferencebetweentheParisAgreementandpriorinternationalclimatechangeagreements.

9. Definetheconceptofcommonbutdifferentiatedresponsibilities.Whyis thisconceptofcentral impor-tancetomanydevelopingcountries?

10. Gotohttp://unfccc.int/focus/indc_portal/items/8766.php anddownloadtheINDCofyourcountry.Discusstheobjectivesandapproachesofyourcountry’sINDC.

11. Whatarethechallengesandopportunitiesforclimatechangepoliciesindevelopingcountries?


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4

SelectedadditionalreadingmaterialBarrett S, Carraro C, and de Melo J, eds. (2015). Towards a Workable and Effective Climate Regime. CEPR Press and Ferdi. London.

Stern S (2015). Why Are We Waiting? The Logic, Urgency, and Promise of Tackling Climate Change. MIT Press. Cambridge, MA.

OECD (2012). Energy and Climate Policy Bending the Technological Trajectory. Organisation for Economic Co-operation and Development Publishing. Paris.

UNFCCC (2007). Impacts, Vulnerabilities and Adaptation in Developing Countries. United Nations Framework Convention on Climate Change Secretariat. Bonn.

ANNEX 2

Someusefuldatabases

Database Description Link

Organisation for Economic Co-operation and Development database on instru-ments used for environmental policy and natural resources management

This data catalogue contains informa-tion on climate change policies of different countries. The database can be searched by policy category (taxes/fees/charges, tradable permits, deposit-re-fund systems, environmental subsidies, and voluntary approaches), environ-mental domain, country, and sector.

http://www2.oecd.org/ecoinst/queries/

ECOLEX database This data catalogue contains treaties, Conference of the Parties decisions, leg-islation, court decisions, and literature related to various environmental issues, including climate change.

http://www.ecolex.org/

World Trade Organization (WTO) envi-ronmental database

This data catalogue covers environ-ment-related notifications submitted by World Trade Organization (WTO) members and environmental measures and policies mentioned in the Trade Policy Reviews of WTO members.

https://www.wto.org/english/tratop_e/envir_e/envdb_e.htm

United Nations Framework Convention on Climate Change Intended Nationally Determined Contributions (INDC) portal

This data catalogue contains submitted INDCs of different countries.

http://unfccc.int/focus/indc_portal/items/8766.php

ANNEX 1


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