Project Deliverable Project Number: Project Acronym: Project Title: 604068 MORE Real-time Monitoring and Optimization of Resource Ef- ficiency in Integrated Processing Plants Instrument: Thematic Priority COLLABORATIVE PROJECT NMP Title D6.7 Impact Assessment Due Date: Actual Submission Date: M40 (February 2017) M41 (March 6 th , 2017) Start date of project: Duration: November 1 st , 2013 40 months Organisation name of lead contractor for this deliverable: Document version: Inno TSD 1.0 Dissemination level ( Project co-funded by the European Commission within the Seventh Framework Programme) PU Public X PP Restricted to other programme participants (including the Commission) RE Restricted to a group defined by the consortium (including the Commission) CO Confidential, only for members of the consortium (including the Commission)
Transcript
Project Deliverable
Project Number: Project Acronym: Project Title:
604068 MORE Real-time Monitoring and Optimization of Resource Ef-
ficiency in Integrated Processing Plants
Instrument: Thematic Priority
COLLABORATIVE PROJECT NMP
Title
D6.7 Impact Assessment
Due Date: Actual Submission Date:
M40 (February 2017) M41 (March 6th, 2017)
Start date of project: Duration:
November 1st, 2013 40 months
Organisation name of lead contractor for this deliverable: Document version:
Inno TSD 1.0
Dissemination level ( Project co-funded by the European Commission within the Seventh Framework Programme)
PU Public X
PP Restricted to other programme participants (including the Commission)
RE Restricted to a group defined by the consortium (including the Commission)
CO Confidential, only for members of the consortium (including the Commission)
604068 D6.7 Impact Assessment p.2
Abstract:
The report assesses the impact of applying the MORE approach in industry, which aims to measure, mon-
itor and improve resource efficiency in the process industries during plant operations in real time by opti-
mizing the way in which a plant or a unit is operated. The environmental, economic and managerial impact
assessment analysis is undertaken through the implementation of MORE in 4 industrial companies. The
generalisation analysis estimates the potential impact of the broad application of the MORE approach to
other plants or companies on a European level, assuming that 25-50% of the chemical companies in Europe
can take up the resource efficiency monitoring and improvement methods directly from MORE. Overall,
the analysis proves that there is a potential to improve resource efficiency in terms of materials and energy
consumption and financial costs, and that the MORE approach can be transferred to similar companies
within the same sectors across Europe.
Disclaimer THIS DOCUMENT IS PROVIDED "AS IS" WITH NO WARRANTIES WHATSOEVER, INCLUDING ANY WARRANTY
OF MERCHANTABILITY, NONINFRINGEMENT, FITNESS FOR ANY PARTICULAR PURPOSE, OR ANY WARRANTY
OTHERWISE ARISING OUT OF ANY PROPOSAL, SPECIFICATION OR SAMPLE. Any liability, including liability for
infringement of any proprietary rights, relating to use of information in this document is disclaimed. No li-
cense, express or implied, by estoppels or otherwise, to any intellectual property rights are granted herein.
The members of the project MORE do not accept any liability for actions or omissions of MORE members or
third parties and disclaims any obligation to enforce the use of this document. This document is subject to
change without notice.
Keywords:
Impact assessment, logical framework, life cycle assessment, generalisation
Authors (organisations): Sophie Vallet Chevillard (inno), Marjukka Kujanpää (VTT), Eva Fadil (inno)
Reviewed by: Stefan Krämer (INEOS), Sebastian Engell (TUDO)
604068 D6.7 Impact Assessment p.3
Revision History The following table describes the main changes done in the document since it was created.
Revision Date Description Author (Organisation)
V0.1 17/05/2016 Document creation, table of content Sophie Vallet Chevillard
V0.2 05/07/2016 Section concept and methodology Sophie Vallet Chevillard,
Marjukka Kujanpaa
V0.3 20/01/2016 Section impact assessment Sophie Vallet Chevillard,
Marjukka Kujanpaa
V0.4 20/12/2016 Section process industry and generalisation Eva Fadil, Marjukka Kujanpaa
V0.5 06/02/2017 Draft of the comprehensive document Sophie Vallet Chevillard, Eva
Fadil
V0.6 12/02/2017 Revision of executive summary and recom-
mendations
Sebastian Engell
V1.0 28/02/2017 Finalisation of the entire report Eva Fadil, Sophie Vallet Chevil-
lard
604068 D6.7 Impact Assessment p.4
Table of Content
1.EXECUTIVE SUMMARY 8
2.INTRODUCTION 12
3.THE PROCESS INDUSTRY IN EUROPE 15
3.1.The process industry in general ........................................................ 15
3.2.The chemical industry ...................................................................... 15
3.2.1. The chemical industry production and market ....................................................... 15
3.2.2. The value chain of the chemical industry – and relation to the 4 MORE use cases 18
3.2.3. The structure of the EU chemical industry ............................................................. 19
3.2.4. Energy and raw material use of the chemical industry .......................................... 20
3.2.5. The EU chemical industry’s environmental performance ...................................... 24
3.2.6. The relevance of optimisation ................................................................................ 25
3.3.Example from another process industry sector: European pulp and paper
industry26
4.IMPACT ASSESSMENT 28
4.1.Concepts and methodology .............................................................. 28
4.1.1. Dimensions and scope of the impact assessment .................................................. 28
Figure 17. Greenhouse gas emission decrease is about 5 kg CO2eq/ t treated diesel. .................................. 37
Figure 18: The reduction of greenhouse gas emissions is clearly the most meaningful improvement when
looking at the environmental impacts of cooling tower optimisation ............................................................ 41
Figure 20: Greenhouse gas emissions from the BASF process. ....................................................................... 46
Figure 22: Methodology of the MORE impact generalisation ......................................................................... 55
604068 D6.7 Impact Assessment p.7
List of Abbreviations
AN: Acrylonitrile
BAT: Best Available Techniques
BPT: Best Practice Technology
BREF: Reference Document
CO2eq: Carbon Dioxide Equivalents
DCS: Decision Control System
DMC: Multivariable Controller
DSS: Decision Support System
GDP: Gross Domestic Product
ISP: Industrial Stakeholder Panel
KPI: Key Performance Indicator
LCI: Life Cycle Inventory
LCA: Life Cycle Assessment
N2O: Nitrous Oxide
NMVOC: Non-Methane Volatile Organic Compounds
LCI: Life Cycle Inventory
LCIA: The Life Cycle Impact Assessment
MPC: Model Predictive Controller
NAMUR: User Association of Automation Technology in Process Industries
PAT: Process Analytical Technology
REACH: Restriction of Chemicals Regulation
REI: Resource Efficiency Indicator
SEC: Specific Energy Consumption
SPIRE: Sustainable Process Industry through Resource and Energy Efficiency Association
TOE: Tons of Oil Equivalent
VOC: Volatile Organic Compound
604068 D6.7 Impact Assessment p.8
1. Executive summary
The MORE project aims to measure, monitor and improve resource efficiency in the process industries during
plant operations in real time by optimizing the way in which a plant or a unit is operated. This analysis report
assesses the impact of applying the MORE approach in the four industrial companies (the plants of the “case
studies”) involved in the project and the potential impact of generalizing this approach to other plants or
companies on a European level.
The purpose of the impact assessment is to evaluate the economic, environmental and managerial impact
of using REI in the chemical and process industries for four case studies, a refinery (Petronor, Spain), a pet-
rochemical site (INEOS in Köln, Germany), a global supplier of specialty chemical products and nutritional
ingredients based on renewable raw materials (BASF PCN, Germany) and a plant producing viscose fibers
(Lenzing AG, Austria). The generalisation analysis estimates the potential impact of the broad application of
the MORE approach in Europe.
The analysis of the impact of the four MORE case studies and of the generalisation potential was placed in
the context of the overall European process industries and more specifically the chemical industry. An
overview of key data with regards to the markets, the production and the resources of the chemical industry,
as well as in particular economic and environmental challenges, is presented in this report.
The four cases represent a good coverage of the value chain of this very diverse industry sector. However,
even though the MORE cases can be considered as “standard” examples of companies of the chemical indus-
try, it should be noted that the application of resource efficiency measures in industrial processes can en-
counter quite disparate issues: chemical companies in Europe operate on different levels with regards to
optimization, some have already applied optimization and model-based control of plant operations whereas
others have not applied any measures yet. This means that the generalisation potential needs to be taken
with care: it is assumed in this analysis that 25-50% of the chemical companies in Europe can take up the
resource efficiency monitoring and improvement methods from MORE directly, while in the remaining cases
either much of the potential has already been realized or the state of plant instrumentation and automation
is insufficient for their application in the short term and first some modernization of the plants is needed.
Impact assessment:
The impact assessment methodology combined several tools to deal with the environmental impact assess-
ment and the economic impact assessment: The environmental impact assessment was conducted based on
the Life Cycle Assessment (LCA) methodology, while the economic impact assessment combined quantitative
and qualitative approaches to measure the gains of optimization and the changes resulting from the project.
In terms of the approach to data collection, environmental and economic impacts were assessed by compar-
ing the situation “before” and “after” the REIs have been defined and displayed to operators or used in
model-based optimization and control schemes.
Impacts assessment main findings:
For Petronor (Muskiz, Spain, Repsol group), the second biggest oil refinery in Spain, the economic gain from
the implementation of MORE is estimated to be between 1.000.000 to 5.000.000 €/y which corresponds to
the target of 3-5% of cost savings. It also had an impact on reducing greenhouse gas emissions by about
3,5%., as for the same amount of hydrotreated diesel less hydrogen is needed. Regarding the impacts on
604068 D6.7 Impact Assessment p.9
operational and management decisions, the implementation of the REIs impacts the company mainly at the
operational level by taking profit of the two new tools developed in the MORE project. Furthermore, oppor-
tunities to spread the approach in other plants of the company have been identified and can be achieved
within a 2-year horizon.
The integrated petrochemical site of INEOS in Cologne, Germany is a major producer of base chemicals. In
this case, the implementation of the MORE approach is still under way and will continue after the project,
especially regarding the implementation of new dashboards for the visualization of REIs in different plants.
Only an estimation of impacts can therefore be given at this stage. The example shows a considerable poten-
tial for economic and environmental improvements. Regarding the environmental impact, the reduction in
indirect greenhouse gas emissions (through electricity savings) could reach 16 400-32 900 t CO2eq less emit-
ted per year. Beyond the MORE project, INEOS has a strong interest in investing further in energy efficiency
improvement measures and in spreading the results of the MORE project more widely in the company.
BASF is a global supplier of specialty chemical products and nutritional ingredients based on renewa-
ble raw materials. Overall, the implementation of REIs did not lead to the expected result, mostly due
to technical difficulties encountered. The implementation of REIs could produce potential economic
impacts, but further investigations and investments are required. Regarding the environmental foot-
print, the impact so far is small as the MORE technology could be applied only to a small part of the
process under consideration. However, the gain in knowledge provides a basis to continue the inves-
tigation in other plants.
The Lenzing site is a reference factory around the world for producing man-made cellulose fibres. Overall,
the economic impact of all optimisation measures using MORE approaches in savings of steam consumption
could lead to economic benefits of 575 000 to 825 000 € per year. There is also coupled to a significant effect
on climate change, by reducing direct CO2 emissions from site by about 0,3%. Further investments will be
made beyond the project in energy efficiency and it is planned to spread the MORE approach in other plants
of the company (in China and Indonesia) and in others application areas, increasing the savings.
Generalisation:
The objective of the MORE generalisation analysis was to find out if and how significant impacts can
be reached by implementing the MORE approach on a wider level in the European chemical industry
and in other sectors of the process industry. Regarding the generalisation methodology, the process
of generalising from the data gathered during the Impact Assessment was done with regards to several
aspects: generalisation to comparable processes or products, generalisation with respect to compara-
ble equipment or technology, and generalisation of the general approach of MORE.
The methodology was based on a five steps approach: desk research on relevant background data on chem-
ical processes and industry data in Europe (e.g. production capacities, etc.), set up of hypotheses on how the
MORE impact assessment of the case studies can be cast into general terms, so that it can be generalised to
a broader range of cases, collection of real impact data from the “after the project” analysis, and application
of the generalisation to other plants or other sites within the same company, or to other companies on Eu-
ropean level.
604068 D6.7 Impact Assessment p.10
Main findings of the generalisation:
For PETRONOR, on the basis of the available impact assessment data, two generalisation hypotheses
could be applied on the internal level (the Repsol Group) and on European level, one with regards to
energy resources and environmental impact, one with regards to economic values:
1. Increased diesel production with the same amount of hydrogen: if this was applied to all EU refin-
eries the potential production increase was 2.8-5.6M tons of Diesel fuel per year in the EU.
2. Cost saving: the generalisation potential in economic terms is at least 25-125 and at best 50-250M €/y in
the EU.
For INEOS: Within the MORE project several plants have been in the focus for which different technologies
of MORE have been applied: an AN (Acrylonitrile) plant, a cracker and a cooling tower. INEOS in Köln being a
highly integrated site, the impact assessment data could only partly be translated into generalisation figures.
The generalisation analysis has shown that at least 25% of the large scale continuous base chemical plants in
Europe could reach an overall energy efficiency improvement of 2% by fully implementing the MORE meth-
ods as operator advisory systems. INEOS estimates an improvement potential on site of 1.5% variable gross
margin increase in their crackers, a potential 2.5% energy savings in their cooling towers and a 1.25-2.5%
energy savings in their AN plants.
For BASF: Specialty chemicals are produced usually in small volumes but represent 28% of the European
chemical sales. Quantitative impacts on European level are difficult to estimate and the uncertainty is too
high for giving recommendations and for estimates on possible savings and efficiency improvements.
For LENZING: The generalisation analysis has shown that there is potential for impact beyond the individual
plants addressed in the MORE project on two levels:
1. Energy and steam saving: Due to an optimised process, less energy (fossil fuels) is needed for the same
amount of product. This results in a saving of steam in the evaporation process, thus leading to natural
gas savings and to cost and CO2 emission savings. The optimisation potential amounts to about 36-
72kt/year and potential energy savings of 2,5-5 MJ/year, as well as 0,35-0,7Mio Nm3 natural gas saving
per year in Europe.
2. On the basis of the reductions in energy and steam consumption displayed above, the savings potential
amounts to 23.5K-47K€/year for smaller structures in Europe.
As a conclusion, there is a significant potential for improving resource efficiency in terms of materials and
energy consumption and financial costs, both within the companies involved in the MORE project and as-
sessed in the case studies, and in similar companies within the same sectors across Europe.
Several recommendations are provided to policymakers in order to support the process of wider implemen-
tation of resource efficiency solutions in the European process industry:
The human operators have and will have for a long period of time a significant influence on the op-
eration of plants in the process industries. Therefore, the support and the acceptance of the intro-
duction of new tools and technologies by the operators is key to success. Collaboration between
human operators and computer-based tools should be addressed prominently in further research
projects.
604068 D6.7 Impact Assessment p.11
While the technology level in large chemical plants generally is high and many opportunities for re-
source efficiency improvement have already been seized, many smaller plants exist which have not
reached this level. As the engineering workforce in such plants usually is small, external support is
needed and measures should first address low hanging fruit.
Digitalisation of industry is a prominent topic in research and innovation at the moment. In MORE,
we have encountered that the lack of reliable and precise measurements of flows of materials and
of energy in the process industries which is a basic ingredient for digitalisation is a major obstacle to
the use of the available data.
It was noticed that data with regards to production data of the chemical industry is dispersed over
many publications and difficult to access, so the development of reference publications is encour-
aged.
Further progress in energy and resource efficiency requires significant investments. Such invest-
ments will only be made if there is a stable regulatory framework. Conditions are needed so that the
risk that is incurred for longer payback periods is reduced. Otherwise, the potential of the available
technologies cannot be realised.
604068 D6.7 Impact Assessment p.12
2. Introduction
The MORE approach
The MORE approach is to measure and monitor resource efficiency during operations, in real time, and to
improve it by optimizing or improving the way in which a plant or a unit is operated. Towards reaching this
goal, indicators (so-called resource efficiency indicators or REI) have been defined that provide meaningful
information about the resource efficiency over short periods of time like hours or days, and new analytical
measurements have been screened and tested. The REI are the means to measure the resource efficiency,
but MORE is more than the REI and their visualization. The improvement of the operation can also be based
on the measurement of indirect indicators or other variables, and it can be implemented as algorithms (real-
time optimization or control schemes), not necessarily directly using REI, but derived from an analysis of the
effects of the operating policy on the resource efficiency.
Impact Assessment
The objective of the impact assessment activities is to evaluate the economic and environmental impact of
using REI in chemical and process industries, validate their interest in terms of industries’ performance, esti-
mate the application potential in a mid-term and finally estimate the suitability of the proposed technologies
for a broad application in Europe.
Figure 1: Objectives of the impact assessment
The results presented in this report detail the work undertaken on four complementary directions:
- The measure of the environmental impacts in the four industrial cases that implemented MORE ap-
proaches during the project. The assessment used the life cycle analysis methodology and compared
the environmental performance on relevant factors (reduction of CO2, reduction of energy used, etc.)
before and after the implementation of MORE;
- The measure of the economic impacts in the four cases observed along the project or calculated
from the reduction potential of production costs due to better optimisation of industrial processes;
- The analysis of changes induced by the implementation and use of REI in the company at the various
levels of decisions of the companies (plant operation, plant management, strategic management)
- The generalisation of MORE results to find out if and how significant impacts could be reached by
implementing the MORE approach on a wider level in the European chemical industry or other sec-
tors of the process industry.
Cas
e st
ud
ies
Evaluate the environmental and economic impacts of the use of REI
Ind
ust
ries Estimate the
medium term application potential
Sect
ors Estimate the
suitability of the technologies for a broad application in EU.
604068 D6.7 Impact Assessment p.13
This report is complementary to the technical assessment of the development and implementation of MORE
approaches reported in the deliverable D5.2.
Impact and limits of the impact assessment
It should be noticed that MORE is a research project. The approaches developed and implemented during
the project are at an experimental stage and tested in specific (and limited) industrial processes and/or
plants. Assessing the impacts includes necessarily prospective analyses at this stage as creating concrete and
tangible impacts will take time for the majority of the cases. Furthermore, the high complexity and interde-
pendence inside the companies between the plants or processes where MORE is applied and the rest of the
plants, as well dependence on external conditions (e.g. the price of energy) and global competition, is hard
to grasp in totality at this stage.
Nevertheless, the exercise of impact assessment shows an interest in enlarging the technical validation un-
dertaken in the project and highlighting the overall paths towards the long term expected impacts in terms
of competitiveness and environmental performance both at company and European level.
Generalisation of impact and its limits
On the basis of the Impact assessment, it was one of the objectives of MORE to find out if and how significant
impacts could be reached by implementing the MORE approach on a wider level in the European chemical
industry or other sectors of the process industry. This is what is called “generalisation” of findings to other
sites within a company or to other companies or “extrapolation” on another sector (for easier reading it has
been decided to speak of “generalisation” overall in this report). Indeed, impact generalisation – or upscale
of the impact assessment – can be done on several levels: from units to plants; from plants to sites, from
sites to companies, from companies to an industrial sector in the EU and eventually to the whole of the
process industry. The more similar the plants in a sector are, the more reliable is the generalisation, when
significantly different sectors are considered, the results can be only rough estimates.
However, a number of barriers, influencing factors and prerequisites exist for generalisation:
The data from the case studies after the implementation of the MORE approach and therefore stem-
ming impact assessment results need to be available in a non-confidential way to be able to proceed
with the generalisation
Adequate mindset, equipment and technological state in other companies/industries are a prereq-
uisite to implement the same kind of improvements and be comparable for impact/generalisation
Energy price is a trigger
Content of the report
Before assessing and generalising impacts on the European level, it is important to provide first a short over-
view of the process industry in Europe and more specifically of the chemical industry. Chapter 3 is meant to
provide the baseline data from this industry that will serve as a measure of comparison.
Then the report aims at assessing the environmental and economic impacts the MORE approach used within
the four industrial companies involved in the MORE project in chapter 4.
Chapter 5 concludes the main assets of the impact assessments and gives an overview of impact elements in
the four MORE cases that are suitable for generalisation.
604068 D6.7 Impact Assessment p.14
Chapter 6 provides an analysis of the generalisation within Petronor, INEOS, BASF and Lenzing, answering to
the question “what are the hypotheses for generalisation, i.e. what impact with regards to the economic and
environmental efficiency improvements can be estimated if the approach was applied to other similar pro-
cesses or technologies within the companies or on European level within the same sector”. The hypotheses
used for the generalisation of the case studies data are set taking for comparison the baseline data displayed
in chapter 3.
Chapter 7 aims at providing policy recommendations on the basis of the analysed data from the impact as-
sessment and the potential impact displayed in the generalisation exercise.
604068 D6.7 Impact Assessment p.15
3. The process industry in Europe
3.1. The process industry in general
The process industry is a wide industrial concept, comprising several different industrial sectors. The biggest
industrial sectors in the process industry are chemical, metal, pulp and paper, cement, food and pharmaceu-
tical industries. The process industry could be defined as “industry that processes resources into other prod-
ucts”.
An alliance of eight European process industry sectors (chemicals, cement, ceramics, engineering, minerals
and ore, non-ferrous metals, steel and water) launched a new initiative called Sustainable Process Industry
through Resource and Energy Efficiency (SPIRE)1. Sectors in SPIRE form a major basis for manufacturing in
Europe, representing 20% of the total European industry in terms of turnover and employment. The sectors
include more than 450 000 enterprises, over 6.8 million employees and more than 1600 billion € turnover.
The main goals of SPIRE are to reduce fossil energy intensity to up to 30% from current levels and to reduce
non-renewable, primary raw material intensity to up to 20% from current levels.2 SPIRE underlines that whole
value chains need to be considered when assessing the improvements to see the impacts along the whole
life cycle and to demonstrate total sustainability performance and improvements.
3.2. The chemical industry
3.2.1. The chemical industry production and market
The chemical industry is an important sector of the process industry: world chemicals turnover was valued
at 3,232 billion € in 2014 with a 2.6% global sales growth in comparison to 2013. However, the close to 10%
growth rate of precedent years has considerably shrunk. The EU chemical industry ranks second after Asia,
along with the US, in total sales. Indeed, the EU countries have contributed to world chemicals sales by 17%
(20% together with non-EU European countries, corresponding to 649 billion €) in 2014.3 Despite having
grown in absolute terms, the EU share of the global demand has declined. In addition, the European demand
has grown more slowly than the world average. Figure 2 shows the sales increase in comparison to the global
market share of EU chemical industries. 4
1 The European Commission. Sustainable Process Industry (SPIRE). http://ec.europa.eu/research/industrial_technolo-
gies/sustainable-process-industry_en.html 2 SPIRE Roadmap, p.5-6. https://www.spire2030.eu/sites/default/files/pressoffice/spire-roadmap.pdf 3 Cefic, The European Chemical Industry. Facts & Figures 2016, p.4, 6 4 Cefic, The European Chemical Industry. Facts & Figures 2016, p.6-7
604068 D6.7 Impact Assessment p.16
Figure 2: Chemical industry sales (source: Cefic)
Twelve out of the top 30 major chemicals producing countries are European, but with Asia, notably China,
bringing more and more competition to the market, the chemical industry in Europe clearly faces economic
challenges. In addition, China plans an ambitious industrial policy strategy the “13th Five-Year Plan” which
aims at taking its chemical industry to the next stage of development – taking the lead. In addition, the main
markets of EU chemical companies are Europe and North America where low growth is forecasted, in
comparison to the emerging countries. 5
5 Cefic, The European Chemical Industry. Facts & Figures 2016, p.5, 7
604068 D6.7 Impact Assessment p.17
The chemical industry in
Europe is quite heterogeneous
and three main broad product
areas can be considered as
outputs: base chemicals
(covering petrochemicals and
their polymer derivatives along
with basic inorganics), specialty
chemicals and consumer
chemicals. Base chemicals
represented 59.6%, specialty
chemicals made up 27.8% and
consumer chemicals make up
12.6% of the total EU chemical
sales in 2014. The specialty
chemicals group is the most
heterogeneous with regards to
products, applications, production
processes and business structures.
Figure 3 presents the sectoral
breakdown of the EU chemical industry.6
Growth rates of the production in the
EU chemical sector are currently not
at their best: indeed, during the
period 2004-2014, the average
production growth rate was 0.4%
with a strong decline after the 2009
economic and financial crisis and
recovery trend since 2010 which
however has not reached its pre-
crisis level. Chemical output grew by
0.3% in 2015 compared to 2014.7
Sector-wise, only the specialty
chemicals and consumer chemicals
sectors have known positive growth
in 2014, whereas the petrochemicals
production remains in negative
state (see figure 4).
6 Cefic, Landscape of the European Chemical Industry, 03/2014, p.9 and Cefic, The European Chemical Industry. Facts &
Figures 2016, p.8 7 Cefic, The European Chemical Industry. Facts & Figures 2016, p.22
Figure 3: Breakdown of the chemical industry sales per product areas
(source: Cefic)
Figure 4: Chemical sector growth rates (source: Cefic)
604068 D6.7 Impact Assessment p.18
As an example, production figures for different chemical products in Western Europe (EU15 + Norway) are
as follows (2014)8:
Ethylene: 19,279Kt
Propylene: 14,485Kt
Butadiene: 1,991Kt
In 2014, Western European ethylene consumption decreased very slightly to 19,068Kt compared to 2013. At
the same time ethylene production (19,279Kt) increased by 4.09%, whilst capacity (23,378Kt) decreased by
2% compared to 2013 (23,862Kt).
In 2014 Western European propylene consumption was almost stable with 14,357Kt/y.
The same goes for propylene production from refinery with 4,400Kt.9
In 2014, Western European benzene consumption (7,534Kt/y) decreased by 100 Kt versus 2013, whilst pro-
duction decreased by 2.4%. Pyrolisis gasoline remains the first source of supply with 54.3% of the total, refor-
matted-based production representing 28.7% and on-purpose and coal-based production representing 17%.
3.2.2. The value chain of the chemical industry – and relation to the 4 MORE use
cases
10 Figure 5: Value chain of the chemical industry (source: Cefic)
figures also available for a number of aromatics under the same source 9 Petrochemical products, http://www.petrochemistry.eu/about-petrochemistry/products.html?filter_id=18 10 Cefic, José Mosquera, Competitiveness of the EU Chemical Industry, a Key sector in the Refining Value Chain, 11/2013,
ers.html, 2016 12 Centre for Process Innovation (CPI), European chemical clusters move up a gear, 02/2012, p.2, http://www.uk-cpi.com/news/european-chemical-clusters-move-up-a-gear/
The EU's crude refining capacity currently represents 778 million tonnes per year (or 15.5 million
barrels per day), equivalent to 18% of total global capacity; there are refineries in 22 Member States with
the exceptions of Cyprus, Estonia, Latvia, Luxembourg, Malta, and Slovenia.13
Already in 2012 the future of some sites (crackers) was questionned in the light of the global competition,
however many sites could be renewed/expanded thanks to the return of investment in new projects after
the financial crisis. A number of companies take advantages of the economies of scales achieved in chemical
industrial parks. “Sites within clusters which comprise groups of separate sites, have tended to enjoy more
competitive advantages because of a multiplicity of chemical plants and owners, ranging from feedstock and
commodity producers to fine and technologically advanced specialty chemical businesses.”14 Such clusters
are centred around a production center for basic feedstock supplies or close to main European ports which
facilitates logistcs considerably.15
With regards to employment, the EU chemical industry counted 1.2 million total staff in 2014 with about
three times higher additional indirect jobs generated. The direct employment has seen an annual average
decrease of 1.7% between 1997-2014, accounting for a total decrease of 25% within this period. Labor cost
per employee in the EU chemical industry was 44% higher in 2014 compared to 2002 16, not taking into
account inflation adjustment.
The chemical industry is linked to a large variety of other industrial sectors; indeed, nearly two thirds of EU
chemicals are supplied to the EU industrial sector. The contribution of the chemical industry to the EU gross
domestic product (GDP) is 1.1%, out of the 15% of total industry contribution.17
3.2.4. Energy and raw material use of the chemical industry
The chemical industry worldwide accounts for more than 30% of the global industrial energy use (including feedstocks). On the basis of a variety of sources, the specific energy consumption (SEC) per world region has been calcu-
lated by EIA for the five most important processes (leading to the production of nine chemicals and account-
ing for half of the sector’s energy use including electricity), i.e. steam cracking, and the production of ammo-
nia, methanol, chlorine (incl. sodium hydroxide) and soda ash; results can be seen in the table of figure 7
(data from 2006). “System boundaries of the values refer to direct fuel use consumed per ton of product
13 European Commission, Energy infrastructure priorities for 2020 and beyond - A Blueprint for an integrated European
energy network, Commission staff working paper on refining and the supply of petroleum products in the EU, http://eur-
lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52010SC1398&from=EN, 2010 14 Centre for Process Innovation (CPI), European chemical clusters move up a gear, 02/2012, p.2-3, http://www.uk-
cpi.com/news/european-chemical-clusters-move-up-a-gear/ 15 Centre for Process Innovation (CPI), European chemical clusters move up a gear, 02/2012, p.3, http://www.uk-
cpi.com/news/european-chemical-clusters-move-up-a-gear/ 16 Cefic, The European Chemical Industry. Facts & Figures 2016, p.31, 33 17 Cefic, Landscape of the European Chemical Industry, 03/2014, p.6
associated with the entire chemical processes covering both chemical conversion and downstream pro-
cessing. Energy use of processes outside the chemical production processes, e.g. mining and extraction of
materials, plastic waste management, are outside the system boundaries.”18
Figure 7: Specific Energy Consumption (SEC) per country for the production of key chemicals (source: EIA)
With regards to Europe, the chemical and petrochemical sector correspond to about 19% of the industry energy consumption, according to Eurostat (June 2016, see figure 8)19. The following tables provide an over-view:
Consumption of the energy branch ktoe
+ Oil and Natural Gas extraction plants 7 699
+ Oil refineries (Petroleum Refineries) 42 477
Final energy consumption ktoe
+ Industry 274 769
Iron & steel industry 51 085
Chemical and Petrochemical industry 52 612
Non-ferrous metal industry 8 948
Non-metallic Minerals (Glass, pottery & building mat. Industry) 33 998
Transport Equipment 7 874
18 EIA, Potential of best practice technology to improve energy efficiency in the global chemical and petrochemical sec-
tor, ENERGY. September 2011, DOI: 10.1016/j.energy.2011.05.019, p.5783 19 Eurostat, 2014 Energy Balances, June 2016 edition, ec.europa.eu/eurostat/documents/38154/4956218/Energy-Bal-
Figure 8: Energy consumption in Europe (source: Eurostat)
The raw material used in the EU chemical industry mainly
comprises refining products (68%), natural gas (21%), Re-
newables (9%) and coal (1%) (data of 2011 for EU-28, see
figure 9).20
Cracker Feedstocks in Europe account for 60,000kt/yr, of which 68% are naphtha and condensates (data of 2014,
see figure 10).21 The EU chemical industry has developed an important
means of improving efficiency and cost-competitiveness of its sites: the European chemical sites count
among the most integrated chemical complexes in the world.22
20 Cefic, José Mosquera, Competitiveness of the EU Chemical Industry, a Key sector in the Refining Value Chain, 11/2013,
p.7-8 21 http://www.petrochemistry.eu/about-petrochemistry/facts-and-figures.html 22 Centre for Process Innovation (CPI), European chemical clusters move up a gear, 02/2012, p.2, http://www.uk-
Energy use and transformation is a major issue in the chemical industry and its optimization thus an im-portant topic. “The chemical industry transforms energy and raw materials into products required by other industrial sectors as well as by final con-sumers. The cost of energy and raw ma-terials is a major factor in determining the competitiveness of the EU chemical industry on the global market. In 2013, the fuel and power consump-tion of the EU chemical industry, includ-ing pharmaceuticals, amounted to 51.5 million tons of oil equivalent (TOE). The EU chemical industry, including phar-maceuticals, significantly reduced its fuel and power consumption during the period from 1990 to 2013. The amount of energy consumed in 2013 was 24% less than in 1990, according to Euro-pean Commission data. Most of the feedstock used in the chem-
ical industry is stored in products and
can be recycled.23 Figure 11 shows the
types of energy used in the EU chemical in-
dustry.24
It can be noted that between 1990 and 2013, the chemical industry in EU has reduced its fuel and power
consumption by 16 million tons of oil equivalent and its gas consumption by 8 million tons of oil equivalent.25
The chemical industry is an energy-intensive industry. Nevertheless, due to intensive efforts on energy effi-
ciency, the fuel and power energy consumption per unit of production (energy intensity) has already been
reduced by 55.4% until 2013 in comparison to 1990 (data on the chemical industry including pharmaceuti-
cals). This is a considerable improvement and good performance when comparing with the EU manufacturing
sector overall.26
Even though the EU chemical industry has recovered from the economic and financial crisis of 2009 with
regards to production and sales figures, it needs to take into account any possibilities for further improve-
ment through optimisation of processes, as it is competing globally. The recent extraction of shale gas in the
US creates a clear competitive disadvantage to the European chemical and manufacturing industries and it
23 Cefic, The European Chemical Industry. Facts & Figures 2016, p.37 24 NB: Cefic and other sources count both incoming energy flows and feedstock as “energy”, whereas in the MORE
approach feedstock is counted as raw material. When speaking about improvement in energy efficiency in MORE, feed-
stock is thus excluded. 25 Cefic, The European Chemical Industry. Facts & Figures 2016, p.38 26 Cefic, The European Chemical Industry. Facts & Figures 2016, p.40, 41
Figure 11: Energy use in the EU chemical industry (source:
Cefic)
604068 D6.7 Impact Assessment p.24
can be expected that other world regions having access to shale gas potentially follow the US example and
exploit such benefits in the future.27
3.2.5. The EU chemical industry’s environmental performance
The greenhouse gas emissions from European chemical industry have been decreased remarkably over the
past 25 years. This is mainly because of the decrease in nitrous oxide (N2O) emissions. In year 2014 European
chemical industry’s greenhouse gas emissions totalled to 131,6 million tonnes of CO2 equivalents28. This
equals to about 3% of the total European greenhouse gas emissions, that were 4419,2 million tons of CO2
equivalents in the year 201429. Figure 12 shows that the greenhouse gas emissions have decreased while
production has increased within the last 25 years.
Figure 12: Greenhouse gas emissions in comparison to the production rate in the European chemical industry (source:
Cefic 2016).
Development of cleaner and safer technologies, putting effort on waste recycling processes and also in de-
veloping new products has not only enabled the greenhouse gas reductions but also other environmental
impacts have clearly decreased over the past 25 years. The intensity of non-methane volatile organic com-
pounds (NMVOC) emissions has nearly halved over the past 10 years30 and the intensity of acidifying emis-
sions, such as sulphur dioxide and nitrous oxides, has decreased ca. 37% over the past 10 years31.
In order to steer the environmental actions in the chemical industry, regulatory and voluntary frameworks
have been set up and implemented throughout the industry. The most comprehensive regulatory framework
27 Cefic, The European Chemical Industry. Facts & Figures 2016, p.5 28 Cefic, The European Chemical Industry. Facts & Figures 2016, p.50 29 Eurostat, http://ec.europa.eu/eurostat/statistics-explained/index.php/Greenhouse_gas_emission_statistics 30 Cefic, The European Chemical Industry. Facts & Figures 2016, p.55 31 Cefic, The European Chemical Industry. Facts & Figures 2016, p.54
604068 D6.7 Impact Assessment p.25
including also environmental aspects is the Registration, Evaluation and Authorization and Restriction of
Chemicals Regulation (REACH) that was launched in 2007 in Europe32. From the voluntary framework, Re-
sponsible Care, a global initiative for continuous improvement in health, safety and environmental perfor-
mance, is an important programme that also obliges the European chemical industry to continuously improve
its environmental performance33.
3.2.6. The relevance of optimisation
The SPIRE Roadmap shows that the whole chemical industry “loses” approximately 40% of the used energy
and utilizes approximately 60%. It also states that physical changes are required to improve this figure;
strongly energy integrated plants will present a better value.34
The EIA study “Potential of best practice technology to improve energy efficiency in the global chemical and
petrochemical sector”, indicates the worldwide energy efficiency improvement potentials for the chemical
and petrochemical sector to be approximately 18% and 21% for 2004 and 2005 respectively, if best practice
technology (BPT) was applied. BPT is defined as “best practice technologies that are currently in use at indus-
trial scale and [that] are therefore, by definition, economically viable”. The study provides an analysis for a
number of countries worldwide, e.g. it shows the total improvement potential with available technology for
some European countries, gathered through two different approaches, Top-Down calculation and Bottom-
Up-Calculation, the latter being based on the potentials with regards to the difference between the average
current specific energy consumption (SEC) and the BPT of each process, no use of energy statistics as in the
top-down approach, with the production rate unchanged. The potential for energy efficiency improvement
is indicated as follows:
- Germany: between 1.5% vs 12.5%
- Benelux: -5% vs +10.2%
- France: 11.3% vs 10.1%
- Italy: 10.5% vs 11.5%35
Besides high energy prices and scarcity of raw material, the regulatory environment puts additional pressure
on the EU chemical industry: indeed, according to the results of the evaluation of the cumulative costs, re-
cently undertaken by the European Commission, the total cost of legislation for the EU chemical industries
32 Cefic, The European Chemical Industry. Governmental Initiatives and Regulations. 2017. http://www.cefic.org/Regu-
latory-Framework/Governmental-Initiatives-and-Regulations1/ 33 Cefic, The European Chemical Industry. The chemical industry’s commitment to sustainability. 2017.
http://www.cefic.org/Responsible-Care/ 34 A.SPIRE, SPIRE Roadmap, p. 34 35 EIA, Potential of best practice technology to improve energy efficiency in the global chemical and petrochemical sec-
tor, ENERGY. September 2011, DOI: 10.1016/j.energy.2011.05.019, p.5780
604068 D6.7 Impact Assessment p.26
amounted to €10 billion per year on average from 2004-2014. Main cost elements are regulations on indus-
trial emissions (33%), chemicals (30%) and workers’ safety (24%). Increasing costs are expected with regards
to stricter emission limit values and energy efficiency objectives as well as carbon footprint reduction.36
3.3. Example from another process industry sector: European pulp and
paper industry
The pulp and paper industry is part of the larger industrial segment of forest industry. Existing alongside the
pulp and paper industry, are e.g. saw mills and the wood-based panels industry, wood construction and the
carpentry industry. New products, like biofuels, biochemicals and biopolymers from the forest are being de-
veloped. Traditional forest industry products may be enhanced with smart features or they may be produced
using new methods.
The paper industry has put a lot of effort into energy efficiency over the recent years. Energy efficiency is
seen as an important aspect to ensure competitiveness while costs for energy are rising. Energy is produced
with an efficient co-generation technology (CHP) and energy efficiency improvements have led to decreased
energy usage while production rates have not decreased37.
The Confederation of European Paper Industries (CEPI) represents approximately 510 pulp, paper and board
producing companies across Europe. It represents 93% of the European pulp and paper industry in terms of
production. The pulp and paper industry has a turnover of 79 billion euros38.
Like the chemical industry, the European pulp and paper industry has decreased its environmental impacts
over the 25 years while the production rate has increased39.
36 The Cumulative Cost Assessment, CCA, has been undertaken under the REFIT programme by the European Commis-
sion. Cefic, The European Chemical Industry. Facts & Figures 2016, p.26-27 37 The Confederation of European Paper Industries (CEPI). Sustainability report 2013, p.47-49. http://www.cepi-sus-
tainability.eu/uploads/FIN_Full%20version_sustainability%20report_LOW%20WEB.pdf 38 The Confederation of European Paper Industries (CEPI). Key Statistics 2015, p.3. http://www.cepi.org/sys-
tem/files/public/documents/publications/statistics/2016/FINALKeyStatistics2015web.pdf 39 The Confederation of European Paper Industries (CEPI). Key Statistics 2015, p.28
Figure 13: Environmental impacts in comparison to the production (source: CEPI, Key statistics 2016)
The pulp and paper sector typically controls its environmental impacts carefully. The focus is on air and water emission levels as well as on other waste streams (sludge from the process) and their handling. In recent decades, many steps have been taken to improve process or site-level environmental performance in areas such as reduction of water discharges, improvement of waste streams handling (e.g. sludge treatment plants) and reduction of air emissions (e.g. sulphur emissions).
Economics is also a strong motivator, for example sludge streams from the process incur costs, especially if landfilling is needed. The sludge may also be burned to provide energy or it may be used in various products, depending on the sludge quality and source. Fossil fuel based CO2 emissions also lead to costs due to emission trading; these emission trading costs will play a more important role in the future40.
According to the European Commission, the pulp and paper industry can combat with increased competition and pressure to further decrease the environmental impacts by continuous resource and energy efficiency improvements41.
40 MORE 2016. D1.5 Description of generally applicable and sector-specific indicators for the process industries, with
two feasibility studies 41 The European Commission. Growth; Internal Market, Industry, Entrepreneurship and SMEs; Pulp and Paper.
The impact assessment aimed at assessing the economic and environmental performance resulting from the project. A conceptual approach and a specific methodology have been defined to structure the evaluation, by taking care of encompassing the point of view and interests of both the European Commission and SPIRE PPP, as the funders of the project, and the industrial partners involved in the project case studies, having their own expectations of the project.
The generic question of the impact assessment is the following:
“What are the costs and impacts associated with the implementation of the REI-based approach?”
In concrete terms, the objective is to provide an understanding and estimation of the results of MORE devel-opments related to:
- Environmental impacts (Savings of energy and/or raw material estimated per ton of products; Re-duction of green emission and waste at process and plant level)
- Economic returns for the companies at plant level and an estimation of possible impacts on their overall performance
- Changes induced by the use of REIs and conditions for successful implementation (e.g. cost of invest-ment beyond the European funding) and the identification of possible obstacles and factors to spread success stories.
In this section, we introduce the dimensions and scope of analysis (§4.1.1), the evaluation framework (§ 0) and the methodological approach (§ 4.1.3).
4.1.1. Dimensions and scope of the impact assessment
We considered industry’s expected impacts as a starting point to build a reference framework for impact assessment. The particularity of the MORE project is that it involves people from strategic management to operators. We undertook several interviews with each partner covering different opinions to find out the drivers to use REIs.
Why using REI: drivers for the industrials.
Based on the interviews, we identify four categories of drivers to deal with resource efficiency in companies:
- Economic interest: The first driver is economical; the European chemical and processing in-dustries face extensive worldwide competition especially with countries in America and in Asia, even inside the companies themselves. Furthermore, these industries are hardly dependent on the price of the energy which varies significantly from one country to another and in time 42. Thus, the overall strategy of these companies is to reduce the cost of production as much as possible by reducing the consumption of raw materials and energy;
- Performance of processes: the second driver deals with optimising the overall performance of production processes to improve both the quality of the production and its efficiency, and therefore improve the overall yield. But having access to real time information leads also to
42 As expressed by interviewed people in different companies.
604068 D6.7 Impact Assessment p.29
new expectations regarding a better understanding of the process (e.g. through more precise models, new analytic tools in real time or online, etc.). It is expected that the increase of knowledge can drive to new possibilities of innovation. In fact, energy efficiency has been a topic addressed by industries for several years and the most obvious optimisations have al-ready been done. Reaching the last remaining percentage of possible improvement requires more in depth knowledge of the processes and their interdependencies with other processes.
Moreover, companies must react to the evolution of standards and regulations that oblige companies to report and monitor their actions to decrease their emissions of greenhouse gas. Companies expect that a project like MORE increases their “readiness” to comply easily (and in advance compared to their competitors) with future standards and regulations.
- Environmental interest: in parallel with the economic interest, companies also need to reduce their overall environmental impact. The EU legislation requires member states and the com-panies operating in the EU to meet the requirements set to them. Chemical industries in Eu-rope are often located in dense urban areas, and face pressure from public authorities and citizens to decrease pollution and other harmful effects.
- Marketing: last but not least, chemical companies work also to improve their reputation and expect to build marketing arguments by being proactive in tackling environmental challenges.
These four objectives are not independent from each other. Furthermore, their importance is per-ceived and considered differently inside the companies depending on an operating or strategic level.
From managers to operators: dealing with various interests
The particularity of the MORE project is that it not only focuses on developing new methods, tech-niques and tools but is really connected to the daily work in chemical and processing industries. The REIs developed in the project concern the different organisation hierarchy levels of the industrial com-panies from operating levels to business and strategic levels. Those levels shall be considered in the analysis of the impact as the expectations (and thus expected impacts) don’t deal with the same di-mensions.
We identify five successive levels for impacts: three inside the companies, where we distinguish the operating level, the managing level and the strategic level; but there is also an interest to understand to what extent the REIs can be spread at European level to other comparable companies; and how the analysis should take into account the entire value chain, including upstream and downstream pro-cesses (e.g. raw material acquisition, energy production and use phase).
The Figure 14 summarises the different levels taken into account in the analysis and the specific focus in each of them.
LEVEL OF ANALYSIS SPECIFIC FOCUS
Operating level Understanding of what is improved and how by the use and visualization of REI
by operators (local optimization)
Management level Understanding of what is improved and how in terms of decisions regarding re-
source management to improve efficiency
604068 D6.7 Impact Assessment p.30
Strategic level Understanding of how real time monitoring impacts the overall strategy at com-
pany level to improve efficiency and identifying possible side effects (e.g. contra-
diction between local and global optimisation)
At EU sector level Identification of the key success factors and impediments to spread the imple-
mentation and use of REI across industries.
At “Value Chain”
level
Understanding of the impacts along the whole value chain including upstream and
downstream processes (e.g. raw material acquisition, energy production).
Figure 14: level of analysis
4.1.2. Evaluation framework
In this section, we introduce the conceptual framework developed to support the evaluation and the specific
tools for data collection. It constitutes a key step for the industries involved in the case studies to estimate
how the REIs helped to manage and improve the processes and energy management at plant level and what
was gained in terms of performance at company level.
The evaluation framework consists of:
- The logical framework that aims to make explicit the cause-effect relationships from the inputs
(what is delivered by the project) to the expected impacts. It serves as a basis to explicit the
hypothesis of the production of impacts.
- The evaluation questions and their corresponding criteria, that aim at defining the specific
questions for the evaluation of the impacts. They serve as a basis to define criteria and indica-
tors by identifying the information to be collected. The strategy to collect information (ques-
tionnaire, interview guidelines, database, etc.) derived from this framework.
Logical framework
The diagram below (Figure 15) represents the logical framework of the project, linking the “activities”, per-
formed in the project (namely the definition and use of REI) and the expected impacts as they have been
identified by the industrials partners.
604068 D6.7 Impact Assessment p.31
Figure 15: logical framework of use of REI
The diagram emphasises the different levels of impacts: plant level (operating and managing level), company
level (strategic level) and finally sector level. The analysis will focus at plant and company level, starting from
the use cases and will then be extrapolated at sectoral level.
Evaluative questions
Formally, the impact assessment aims at answering the following question:
“What are the costs and impacts associated with the implementation of the REI-based approach?”
Based on the logical framework, we structure the evaluation framework around three dimensions formulated
in formal questions (Figure 16):
1. The environmental impacts of REI implementation at plant and company level
2. The economic impacts of REI implementation at plant and company level
3. The changes induced by the use of REI at operation, management and decision level and the condi-
tions of replicability for other plants and sectors.
604068 D6.7 Impact Assessment p.32
Evaluative questions
Q1: To what extent the REIs improved the environmental performance at plant and company level?
Q2: To what extent the use of REI increased economic performance at plant and at company level?
Q3: To what extent the use of REI changed and improved the operation, management and decision process
at plant and company level?
Figure 16: evaluative questions
Criteria and indicators
For each question, we defined a set of criteria and indicators to answer the questions.
The table X illustrates the two selected criteria and their associated indicators for the first question
“to what extent the REIs improved the environmental performance at plant and company level?” and
the comprehensive table for the three questions is provided in annex 1.
Q1: To what extent the REIs improved the environmental performance at plant and company level?
Criteria Indicators
1. Has the environmental perfor-
mance improved through the use
of REI?
- Decreased direct emissions to air and water
- Decreased use of resources
- Decreased electricity consumption
- Decreased use of heat
- Changes in raw materials
- Decreased amounts of waste
2. Is the environmental perfor-
mance at company level concord-
ant with plant level?
- Overall environmental performance has improved
- Is there an overall reduction in environmental impacts or are
some impacts lower, some higher than before REI implementa-
tion?
- No shifting between plants (e.g. due to interconnections less in-
ternal energy produced in plant A leads to increased external en-
ergy supply at plant B)
4.1.3. Methodological approach
The impact assessment combines several tools to deal with the environmental impact assessment and the
economic impact assessment:
- The environmental impact assessment is conducted based on the Life Cycle Assessment (LCA) meth-
odology
- The economic impact assessment combines quantitative and qualitative approaches to measure the
gains and the changes resulting from the project.
604068 D6.7 Impact Assessment p.33
Principles of Life Cycle Assessment
LCA analyses the environmental aspects and potential impacts across the product life cycle from cradle to
grave, including raw material acquisition, production, use, end-of-life treatment, recycling, and final disposal,
by examining the physical chains of material flows (ISO 14040:2006). However, as the MORE project concen-
trates on resource efficiency improvements at industrial plants, only cradle-to-gate processes are included
in the assessment, meaning that all the life cycle phases after the plant are excluded from the scope.
LCA is divided in four phases: (1) the goal and scope definition phase, (2) inventory analysis, (3) impact as-
sessment and (4) interpretation.
ISO 14040 -standard addresses some requirements for carrying out an LCA. The goal definition phase deter-
mines the goal of a study; the intended application, the reasons behind the study, the intended audience and
if the results are intended to be used in comparative assertions in public. The scope includes information
about the studied product system, the functions of product system, the functional unit, the system boundary,
the allocation procedures, data requirements, assumptions, limitations, initial data quality requirements and
type of critical review. (ISO 14040:2006).
Life cycle inventory (LCI) phase gives information about the inputs from the environment to the system and
about the outputs to the environment from the studied system. Data for each unit process can be classified
as follows:
- Energy inputs, raw material inputs, ancillary inputs and other physical inputs;
- Products, co-products and waste
- Emissions to air, discharges to water and soil, and
- Other environmental aspects.
After gathering the data, information is related to unit processes and to the reference flow of the functional
unit. (ISO 14040:2006).
In this report, none of this information is disclosed to public as it is considered confidential. The results pro-
vide information about the gained resource efficiency improvements but exact figures are not given. How-
ever, all the calculations are based on real, plant-specific data if not otherwise stated.
In the life cycle impact assessment (LCIA) phase, the significance of potential environmental impacts is eval-
uated using the LCI results. LCIA involves associating inventory data with specific environmental impact cat-
egories and category indicators (ISO 14040:2006). The life cycle impact assessment (LCIA) phase was per-
formed by applying the ReCiPe Midpoint method for Europe43. ReCiPe 2008 methods were selected as pre-
ferred choice because they cover all impact categories in a consistent way. ReCiPe is an LCIA method, which
offers results at both the midpoint and endpoint level. The midpoint-level assessment is used in this study,
emissions and extractions of natural resources are converted into impact category indicator results for im-
pact categories such as acidification, climate change and eutrophication. All the categories that show changes
43 Goedkoop M.J., Heijungs R, Huijbregts M., De Schryver A., Struijs J., Van Zelm R, ReCiPe 2008, A life cycle impact
assessment method which comprises harmonised category indicators at the midpoint and the endpoint level; First edi-
tion Report I: Characterisation; 6 January 2009, http://www.lcia-recipe.net
NB: the presentation of the impacts generated in each industrial partner follows the three evaluation ques-tions: environmental impact assessment, economic impact assessment and changes in the operation, man-agement and decision process. The context of each case and the interest in the MORE approach has been shortly summarize to allow a standalone reading of the report and make it accessible to a wider audience. The analyses provided are complementary to the technical evaluation of the project results (D5.2), that es-pecially addresses the extent of implementation of MORE activities.
4.2.1. PETRONOR
Context of the case, impact expectations and implementations of MORE approach
Petronor is an oil refinery where hydrogen produced on the site is used as a raw material for hy-drodesulfurization units (HDS) (consumer plants) in the integrated site. The H2 network has been cho-sen to apply the MORE approach to optimize hydrogen production it constitutes an importa nt cost of the refinery.
The main interest for Petronor in the project is to improve the management of its H2 network (and by this controlling and improving the economic return of H2 production). But operating the H2 network faces a high level of complexity due to the variety of parameters to control and a high degree of interaction between them. Two scenarios are taken into account in the optimisation problem:
- Scenario 1: when the H2 production availability is greater than the demand of the consumer plants, the expectation is to reduce it to the minimum. This situation will mean that the minimum H2 is purged to the fuel gas header and burnt in heaters.
- Scenario 2: when the maximum capacity of H2 production is less than the demand, it is necessary to reduce the H2 consumption of the consumer plants to keep the material balance in the network. The expectation is to decrease the production to the minimum possible in the consumer plants taking into account the priority of H2 needs in those units.
Implementations of MORE approach in Petronor were:
- The implementation of REIs in the multivariable controller (DMC) operating and optimizing in real time the H2 network,
- The development of a theoretical model to calculate the optimal network distribution imple-mented in an offline optimizer.
The expected target of Petronor was an improvement of 3-5% in the efficiency of the hydrogen network that corresponds to a saving of 1-5M€/year.
Environmental impact assessment
Data for natural gas and Spanish grid electricity are from Ecoinvent 3.3. database45. Data for hydrogen production and diesel hydrotreatment are sourced directly from Petronor.
The improvement includes the two scenarios: - Regarding the first scenario, a reduction of 2500Nm3/h of the H2 flow to the fuel gas header was
observed. The reduction of H2 production induces that less H2 is burned at fuel gas headers. Due to the increase in H2 burned in headers, natural gas flow to the headers needed to be increased to
45 Ecoinvent 3.3. LCI database. Modules market for natural gas, high pressure and market for electricity, medium voltage,
Spain. www.ecoinvent.org
604068 D6.7 Impact Assessment p.36
cover the energy production needs. However, the overall need for natural gas decreased by 1,4% because natural gas is used in hydrogen production and due to the decreased H2 production, con-sumption of natural gas was decreased too.
- Regarding the second scenario, the increase in the quantity of liquid feeds is estimated at 25m3/h.
Environmental impacts are not separately calculated for reduced H2 production as it is just part of the hydrogen network. The demand of hydrogen in consumer plants determines the need for hydrogen and when looking at the hydrogen in the two scenarios the following can be concluded:
- Scenario 1: less hydrogen is produced because there is no excess hydrogen to the headers anymore
- Scenario 2: maximum amount of hydrogen is produced to cover the needs at consumer plants. Hydrogen is not burnt in headers because all is needed at consumer plants.
Thus, it can be concluded that maximum resource efficiency improvement is the improvement gained with scenario 2 because when scenario 2 is valid, scenario 1 is valid too and if scenario 2 is not valid, scenario 1 is anyway valid but the impact is smaller than the impact of the scenario 2. Thus, only the impacts from Scenario 2 are reported as it shows the maximum potential for environmental improve-ments at Petronor.
In Scenario2 the main goal was to be able to treat more diesel with the same amount of hydrogen. This goal was successfully met and the diesel production increased by circa 30490 kg per hour which corresponds to 5,6% increase in diesel treatment . At the same time greenhouse gas emissions that are caused by diesel treatment process increased too, totalling to 1712 kg CO2eq increase per hour. The increase in greenhouse gas emissions is due to the increased diesel treatment (direct emissions at the site), increased electricity consumption (indirect emissions from electricity production) and in-creased natural gas combustion (indirect emissions from natural gas supply chain, e.g. leakages in pipelines). Diesel production is not included in the scope of the study, only the diesel hydrotreatment process.
However, if the change is related to the produced amount of diesel, then one can see a saving in produced hydrogen. With the same amount of hydrogen, more diesel can be treated which means that for the same amount of hydrotreated diesel less hydrogen is needed . From resource efficiency point of view this is a relevant approach as more is produced with less. When results of the environ-mental impact assessment are calculated and normalised (Error! Reference source not found.Error! Reference source not found.), the climate change is the most meaningful environmental impact cate-gory. Therefore, this report concentrates on climate impacts and greenhouse gas emissions.
604068 D6.7 Impact Assessment p.37
When looking at the diesel treatment process and using treated diesel as unit of analysis, a reduction of
approximately 5 kg CO2eq. per diesel ton can be realised which corresponds to a reduction of 3,4% in green-
house gas emissions emitted due to the diesel treatment process (diesel production is not included in the
figures). As the amount for diesel treatment per hour is rather high, approximately 578 t per hour, the re-
duction in CO2 will reach circa 3100 kg CO2/hour.
Overall, the reduction in greenhouse gas emissions is about 3,4%.
Figure 17. Greenhouse gas emission decrease is about 5 kg CO2eq/ t treated diesel.
Economic impact assessment
The economic impact ensues directly from the improvement of H2 network efficiency and was esti-
mated by Petronor.
climate change (GWP100) [kg CO2eq]
fossil depletion (FDP) [kg oil eq]
freshwater eutrophication (FEP) [kg P eq]
ionising radiation (IRP HE) [kg U235 eq]
marine eutrophication (MEP) [kg N eq]
metal depletion (MDP) [kg Fe eq]
ozone depletion (ODP inf) [kg CFC-11 eq]
particulate matter formation (PMFP) [kg PM10 eq]
photochemical oxidant formation (POFP) [kg NMVOC]
terrestrial acidification (TAP100) [kg SO2 eq]
-6
-5
-4
-3
-2
-1
0
Diesel treatment Electricity fromgrid
Hydrogenproduction
Natural gas for fuel
kg C
O2
eq
./t
die
sel
604068 D6.7 Impact Assessment p.38
For Scenario 1, when H2 production availability is greater than the demand of the consumer plants, H2 sav-
ings are estimated to about 2500Nm3/h (1955 t/y) that corresponds to a gain of 1 000 000 €/y approxima-
tively
For scenario 2, when H2 production is not able to cover the demand, the potential of increase of HC liquid
feed is estimated at 25m3/h that corresponds to gain of 5 000 000 €/y approximatively.
In total, the estimated potential gain is between 1.000.000 to 5.000.000 €/y which corresponds to the
target of 3-5% of cost savings expected at the beginning of the project. The range is quite large because it
is largely dependent on the total feed rate and its composition. For the last two years, the first scenario (H2
production is greater than the demand) has dominated. Operating in the second scenarios have the potential
to generate more benefits, but the conditions of operation are fixed by the market and the kind of crude
proceed and is not controllable.
The required investments to implement MORE approach are estimated at around 400 000€ including cost of
development (mainly the work required by engineers) and investment in equipment and software. This ap-
pears slight in comparison with the gain of benefit. The return of investment period is estimated to be less
than 1 year.
Overall, it is estimated that the implementation of REI produces a better tangible economic performance
and is convergent with plant and company primary target.
Furthermore, opportunities to spread this approach in other plants of the company have been identified
and could be achieved within a 2-years horizon.
The project is also contributing to maintain business competitiveness of Petronor and thus maintain its ac-
tivities in Europe.
Impacts on process and management decision
MORE project permitted to develop ad-hoc tools for PETRONOR:
- A multivariable controller (DMC) (based on empirical modelling) has been implemented in the con-
trol system (DCS) that operates in closed-loop, and optimizes in real time in the H2 network.
- An off-line optimizer has been developed through a theoretical model and provides results of what
should be the optimal network distribution.
It generates changes in the way operation is done, by automating several operators’ decisions on the H2
network. The two tools (DMC controller and optimizer) are calculating and taking decisions in real time, push-
ing the process against its maximum.
The optimizer is not yet fully implemented, but it should allow the plant and planning technicians to better
monitor the plant and to identify how far they are from the optimum and what to do to reach it, thus capture
the maximum benefit possible. Whereas before the implementation operators and Plant Supervisors took
decisions based on pre-established criteria, these two new tools are going to improve the management of
the network, helping to take faster decisions, in better coordinated-cooperation and based on a process
model.
In terms of acceptance, the DMC controller had a good acceptance of control operators as well as Plant Su-
pervisors. Trainings have been undertaken on the DMC to explain to all control operators how the DMC works
604068 D6.7 Impact Assessment p.39
and how operate it. Overall, they clearly see the added value brought by the real-time dimension that support
them to take decisions in closed loop, and support a better coordination and cooperation among the different
units and control rooms of the H2 network.
Overall, the implementation of REI impacts the company, but mainly at operational level by taking profit
of the two new tools developed in the MORE project.
Next steps, key success factors and limitations
PETRONOR demonstrates a strong interest in the project, the top-level management of the company is aware
of the MORE results and is satisfied with them. Even if MORE will not impact the strategy of the company,
the results are very positive, not only with respect to energy efficiency but also regarding the gain in produc-
tivity.
No limitation was highlighted that limit the extent of the project impact.
4.2.2. INEOS
Context of the case, impact expectations and implementations of MORE approach
The petrochemical site in Cologne, German, operated by INEOS (“INEOS in Köln”), integrates 19 major plants
including a power plant. Continuous optimisation of plants has been done for several years to improve the
yield of the plants and their economic performance. MORE is part of this strategy. The objective of INEOS is
to pursue further process optimisation to achieve a part of potential dormant in improved process opera-
tions.
Four plants are included in the scope of the evaluation in the MORE project:
- Acrylonitrile (AN) plant,
- Isoamylene plant,
- Cooling towers
- Crackers
The implementations of the MORE approach in INEOS were:
- Online naphtha analysis and subsequent cracker data reconciliation and optimization as proof of concept and potential decision support – to be practically implemented in 2017
- Fully developed REI for INEOS site and site wide evaluation and aggregation scheme – theoretical development
- Implementation of REI, Dashboards and aggregation for selected plants (AN, Isoamylene) and site in MATLAB Scripts
- Rudimentary implementation of past and live reporting using MORE REI and MORE principles with integrated deployment platform as decision support – to be continued in 2017
- Prototypical implementation of cooling tower optimisation and multiobjective optimisation as deci-sion support
The implementation differs from a plant to another and is not totally completed except for the AN
plant46.
46 As reported in D5.2
604068 D6.7 Impact Assessment p.40
It is possible that in the long run LCI (life cycle inventory) data could be attached to REIs (and be
included in the dashboard system). This way information about the cradle-to-grave impacts of deci-
sions made can be gained beyond site-level impacts.
Environmental impact assessment
As the implementation is not finalised, assessing environmental impacts is not possible. Nevertheless,
in some cases, estimation of the potential impacts can be calculated from theoretical models and are
provided in this paragraph. In the other cases, where implementations are supposed to change the
operations, environmental impacts cannot be estimated.
Acrylonitrile plant
The MORE approach was fully implemented in the AN plant, including REIs and dashboard. However,
there were other regulatory changes taking place at the same time that affected plant’s energy bal-
ances quite drastically and thus before-after assessment was not possible. Some estimates of the im-
pacts can be given: Up to 5% energy savings by implementation of a full Model Predictive Control ler
(MPC) control solution appears possible, and 1-1.5% by operator advisory only.
Cooling towers
The main goal for the cooling towers was to gain a better understanding of the influence of ambient
conditions to the cooling tower performance. A model was built to be able to simulate and take into
account ambient conditions in cooling optimisation. The model shows promising savings in electricity.
By increasing the cooling temperature, electricity use of the ventilators could be dropped clearly. It
has to be noted that some processes require the coldest possible cooling water and in these cases
electricity use cannot be reduced. Therefore, also the generalisation of the result is difficult but the
savings derived from the model can be used as an indicative example of potential for electricity savings
at cooling towers.
The normalised results calculated for the maximum saving potential (cooling water = 25⁰C) show that
the reduction in electricity consumption has a clear impact on climate change, fossil depletion and
ionising radiation. Climate change and fossil depletion are due to the decrease of the use of fossil fuels
and ionising radiation is mostly due to reduction of nuclear power-related emissions. However, ionis-
ing radiation results are highly dependent on data quality; in this case emissions contributing to this
category in Ecoinvent database include high uncertainty and hence this category can be neglected
from the assessment.
604068 D6.7 Impact Assessment p.41
Figure 18: The reduction of greenhouse gas emissions is clearly the most meaningful improvement when looking at
the environmental impacts of cooling tower optimisation
The electricity consumption of ventilators cover ca. half of the total electricity consumption of cooling towers
and cooling towers consume about 20% of the electricity consumption of the whole site. Hence it can be
stated that the saving potential is very promising. It is estimated that if the model was applied as an opera-
tor advisory, the saving potential would be about 25-50% of the theoretical saving potential. In greenhouse
gas emissions, this would mean 16 400-3 2900t CO2eq less emitted per year. For INEOS, these are indirect
emission changes, nonetheless, to put the number into perspective, this corresponds to circa 0,6%-1,2%47
of the annual direct CO2 emissions from INEOS Cologne site.
Table 1. Theoretical saving potential at cooling towers.
Cooling water temperature Theoretical saving poten-
tial for electricity used in
ventilators
Theoretical saving po-
tential in MWh/a
Reduction in CO2eq
emissions, based on
theoretical saving
potential [t
CO2eq./a]48
20⁰C 9 % 1080 710
22⁰C 15% 1800 1184
25⁰C 20% 2400 1578
It was expected that MORE would make a contribution towards the target of reducing the energy intensity
of the site by 1,5% per year. Without a very detailed analysis of the pure operational influence using the
47 Data for site emissions sourced from E-PRTR database, reporting year 2014. http://prtr.ec.europa.eu/#/facilitylevels 48 CO2 reductions are calculated using Ecoinvent 3.3. database data for German grid electricity (market for electricity,
- To other application areas such as the system “heat recovery-evaporator-crystallization-calcination”
where a rough estimation of saving could reach 200 000€ to 1M€ per year.
The required investments to implement MORE approach are estimated at around 100 000€ for the imple-
mentation of the models in the decision control systems (on which 40 000€ are still required to achieve the
full implementation). This appears very slight in comparison with the gain and in fact, the return of invest-
ment period is estimated at 2,4 months (estimated for the LENZING site).
Overall, it is estimated that the implementation of REI produces a tangible economic performance and
ways for further opportunities both in the plant involved in the case study and wider in the company.
The observed impact is more important than expected at the beginning of the project: whereas overall en-
ergy savings were expected to reach around 1%, current savings are currently of 3% with potential for further
improvement.
The project is also contributing to maintain LENZING activities in Europe as higher energy efficiency leads to
lower production costs and maintain the company competitive in comparison with international competition.
Impacts on process and management decision
MORE project permitted to develop ad-hoc models for LENZING case studies and generates gain of
knowledge about the operation of the plants:
- By identifying new value of optima: therefore, the optimal value of energy now required is around
2.5% lower than the previous value for the evaporator control and 0.5% lower for the cooling tower
control. It is not yet estimated for the other cases.
- By including new parameters in the control system: therefore, the load of evaporators which value
is established by the calculation of its optimal value, or the optimal cleaning time of evaporators are
now included in the decision support system.
Finally, this gain of knowledge results in an overall optimisation of the evaporator park (generating the ob-
served economic and environmental impact), and make possible to operate the plant close to the theoretical
optimum.
Other factors influencing the efficiency are still under exploration, such as the parameters influencing the
success of evaporator cleaning depending of the type of evaporator and type of cleaning.
Regarding the changes induced for the operators, for the evaporator control and the cooling tower, the mod-
els are implemented directly in the distributed control system and do not impact operators. For the evapo-
rator load allocation and evaporators cleanings, the decision support system aims at supporting operators’
work: for the load allocation, whereas the operator take decision solely based on his experience for the mo-
ment, after the full implementation, the decision support system will give him a proposal for an energy effi-
cient load allocation. Nevertheless, it will not replace the decision of operators and they will take in the end
the decision of applying the new load allocation as suggested by the DSS or not, by assessing its relevance
for every evaporator and cycle. For the evaporators cleaning, the number of cleaning will also change and
may impact the operators with additional constraints.
As the DSS isn’t implemented yet, the level of acceptance of operators cannot be assessed. Nevertheless,
interviews with operators reveal that they are curious about the DSS and open minded for improvements.
604068 D6.7 Impact Assessment p.52
Their acceptance could be a hard topic because they actually did not face problems in the operation until
now. They thus don´t really expect the DSS. Moreover, they feel worried about possible additional work they
would need to carry out. A fare balance between process efficiency and conditions of operation would thus
certainly have to be discussed and agreed between managers and operators. The test phase would certainly
be critical, as it is plausible that everything will not work smoothly from the beginning and will generate
additional work to operators. The potential of the DSS should thus be clearly communicated and shared with
operators to foster their acceptance. Training of operators would certainly play also an important role for
the acceptance. Training investments are already planned and are estimated around 5 000€:
- For the supervisors and the operators to work with the DSS Tool for the load allocation. They will get
trained on how the tool works and how to use it properly. Furthermore, a process control engineer
will be trained by TU Dortmund for the MATLAB support of the DSS tool.
- For the evaporator cleanings, training will be required for supervisors on how to use the tool properly
and how to change some inputs.
Overall, the implementation of REI impacts the company, but not all levels of hierarchy are concerned and
involved. Some changes to monitor and operate the plant are resulting of MORE, but not that much as
some parameters are implemented directly in the control system. Changes will impact operators but it is
too early to know to what extent their involvement will be a factor of success or create constraints to reach
the expected level of performance.
Next steps, key success factors and limitations
LENZING demonstrates a strong interest in the project, the top level management of the company is aware
of the MORE results and is highly satisfied with them. Energy and resource efficiency is already one of the
core values at Lenzing and MORE perfectly matches the “Score Ten” company strategy.
Moreover, further investments will be done beyond the project in energy efficiency and it is scheduled to
spread MORE approach in other plants of the company (in China and Indonesia) and in others application
areas, increasing equally the savings.
No limitation was highlighted that limit the extent of the project impact.
604068 D6.7 Impact Assessment p.53
5. Main achievements of the industrial cases and impact ele-
ments suitable for generalisation
5.1.1. Main achievements of the industrial cases
4 cases are complementary and didn’t implement the same things:
o INEOS: the most advanced and comprehensive case in terms of operational implemen-
tation (definition and visualisation of REIs in case studies plants)
o PETRONOR & LENZING: optimization based on theoretical models developed in MORE
and implementation in their own control and decision system
o BASF: test of online analytics system for real time measurements. No concrete imple-
mentation.
The nature and extent of impact vary importantly from a case to another:
o Depending mainly on the degree and complexity of implementation and integration of
REI visualization in existing systems.
o Depending if the implementation concerns only control system (automatic) or also de-
cision system (impacting daily operations of plants)
Main messages:
o Energy efficiency and company competitiveness are closely related. Economic aspect
(meaning the expectations in terms of reduction of cost production) is the main drivers
to explore energy efficiency and optimization.
o In all cases, MORE enables to provide theoretical results on the potential of optimisa-
tion and in some cases, concrete results of savings.
o Savings deals with reduction of energy consumption (gaz, electricity), reduction of raw
material, increase of yield. All result in a reduction of cost production.
o Savings are estimated about 3-5% and corresponds or are upper the primary expecta-
tions.
o In three cases, the project outcomes will be pursued after the end of the project, to
finalize the implementation and/or to spread the approaches in other plants of the
companies.
o In terms of investments, the analyses showed that they are limited, except when new
tools are required (for instance for online analytics measurements), and concern
mainly human resource that must be trained to new systems. They are consistent with
the necessary short period payback required for chemical and process industries.
o Regarding the acceptance for operators, the analyses couldn’t go very far, but it seems
that operators are interested in such approaches. Their acceptance will be considered
on the trade-off between the extent of work these approaches induce, their benefit
and the clarity and usability of the information displayed to them.
Further details on the technical evaluation of the case studies can be found in D5.2.
604068 D6.7 Impact Assessment p.54
5.1.2. Impacts elements suitable for generalisation
The 4 MORE use cases provide a good spectrum of examples of the chemical industry; they represent a re-
finery, a petrochemical site that produces base chemicals from naphtha and natural gas, a site that produces
a large variety of products from natural oils, and a cellulose plant.
Impact elements that are possible sources for the investigation on generalisation to other plants/indus-
tries/sectors, are as follows:
- Raw material consumption: the decrease of the raw material used for industrial processes thanks to
the optimization of processes equals economic gains.
- Energy consumption: facing high competition from countries outside the EU, the reduction of energy
consumption is both an economic goal and marketing goal for companies towards policy makers and
consumers, as well as the general public.
- Water consumption: the reduction of water use in some processes is a main environmental issue.
- Waste water production: reducing waste water can be a main opportunity to improve the efficiency
in industrial processes, thanks to optimised scheduling and re-use of water in different processes.
- Waste production: reducing the waste from production is a main means for both economic savings
and reducing the (negative) environmental impact.
- Greenhouse gas emission and pollution: improving the image of the process industry and notably the
chemical industry depends highly on the (estimated) pollution of the environment that goes with
these industrial processes. Improvement on this indicator is certainly a major aspect for policy mak-
ers and the general public.
- Production cost and product value in Euro: multiplication of data as indicated above with economic
value (€).
- Soft facts (impact on process operations and management decisions): acceptance and change of be-
haviour in the operation process, changes in decision making on operational and plant manager level.
604068 D6.7 Impact Assessment p.55
6. Generalisation
The objective of the MORE generalisation is to find out if and how significant impacts could be reached by
implementing the MORE approach on a wider level in the European chemical industry or other sectors of the
process industry.
6.1. Methodology
The process of generalising from the data gathered through the Impact Assessment can be done with regards
to several aspects: comparison with regards to a comparable process or product, comparison with regards
to a comparable equipment or technology or comparison with regards to the general MORE approach. The
figure below illustrates these different paths.
The result of the MORE work (the outcomes) are represented in the box on the left side. The case studies
have two aspects, technology and process/product. Thus, there are two paths (top and bottom paths), one
via the similarity of the products and processes, e.g. butadiene, one via the similarity of the equipment, e.g.
evaporators, and one on a more abstract level of “relative savings” for the process considered. The whole
case study is generalised more globally, by using the % improvement (this is represented in the middle path,
connecting to the whole case study, not to the individual elements). The actions of measurements, and im-
pact assessments or generalisations are represented by the arrows, giving the result in the first set of boxes
after the case study box. Additional elements such as success factors, acceptance by the operators etc. are
included in the impact assessment and can be generalised roughly in the middle path as well. In some cases,
where impact figures are not specifically available, generalisation is provided as recommendation.
Figure 20: Methodology of the MORE impact generalisation
On this basis, the generalisation exercise has been undertaken in several steps:
1. Desk research studies and data collection and analysis on the process industry in Europe and more
specifically of the chemical industry. Other sectors with comparable processes / technologies have
604068 D6.7 Impact Assessment p.56
been analysed, but discarded as not suitable for generalisation, such as the pulp & paper and sugar
industries.
2. Analysis of the MORE case studies’ generalisation potential. It has been analysed case by case
whether there was potential for internal or external comparison (generalisation) with regards to the
aspects of similarity in processes/technologies and positioning.
3. Data collection from the 4 industry case studies (via a specific generalisation questionnaire)
4. Collection of results from the Impact Assessment
5. Generalisation of 4 MORE cases’ impact on the basis of Impact Assessment data: Comparison on
plant level, company level and the same kind of plants in the EU. Generalisation to other sectors have
proven to be not possible, as the comparison on processes / equipment in other sectors were too
vague.
The following chapter aims at summarizing the aspects of each of the MORE use cases that can be an element
for generalisation, providing generalisation hypotheses and the potential results.
The analysis has however proven that the following statement can be confirmed: “The chemical and petro-
chemical sector poses a special challenge because of its complexity and due to the large number of products
it manufactures. Other factors that make the analysis a challenging task are: lack of publicly available detailed
energy use and energy efficiency data, complex production sites with a high level of (…) integration, a large
diversity of process routes for producing the same product, the very high levels of combined heat and power
that can be attained, and in some cases integration with refineries.”52
Generally speaking, it should be noted that the generalisation potential has been analysed per case as spe-
cifically as possible and generalisation has been done as widely as suitable. It is realistic to say that on EU
level there are some 3-5% of saving potential in all plants through improved process operations alone.
However, this is not applicable to all plants: 50% of the plants already use other, in some cases more sophis-
ticated but also more expensive solutions and in other plants the prerequisites for energy efficiency solutions
are not even given, so we assume that only 25% to 50% of plants are in focus, making 25% the worst-case
estimate.
Also, it has to be taken into account that there can be a trade-off between resource efficiency (use of less
energy or material and reduced costs) and environmental impacts which means that possibly there may be
generalisation potential which would never be realised due to these constraints. More stringent environmen-
tal regulation might lead to lower resource efficiency. As this would be a desired effect, the baseline for
comparison of the current resource efficiency needs to be raised.
6.2. Analyses of the 4 industrial cases
The following is a summary of each case including hypotheses for generalisation that result from the impact
assessment exercise undertaken; main impact elements used for generalisation in the four cases are the raw
material and energy consumption. Some cases can be generalised to other companies in the same sector.
52 EIA, Potential of best practice technology to improve energy efficiency in the global chemical and petrochemical sec-
tor, ENERGY. September 2011, DOI: 10.1016/j.energy.2011.05.019, p.5779
604068 D6.7 Impact Assessment p.57
Other cases can only be generalised to similar processes within the same company or with a high degree of
uncertainty.
6.2.1. Petronor
Impact objective
The MORE implementation at Petronor focuses on the measurement and improvement of the efficiency in
the use of hydrogen (H2) as a raw material in the refinery.
The aim is to conclude in a more efficient H2 network operation, e.g. ensure a 5% improvement in the energy
consumption per kg diesel (H2/kg diesel) or to say it differently to treat more diesel with the same amount of
hydrogen. The latter is taken as basis for the generalisation approach.
Petronor impact generalisation background and potential
Petronor (Muskiz, Spain) is the second biggest oil refinery in Spain and it belongs to the Repsol group. It can
be assumed that the Petronor refinery is a standard refinery with standard procedures. Indeed, the optimi-
sation potential of a refinery depends on the refinery capacity, but the challenges with regards to resource
efficiency are similar in all oil refineries. Every refinery has a hydrogen network.
The following table gives more information about the generalisation potential of the Petronor case:
Hydrogen networks: Amount
within Petronor 1
within Repsol 4 (one per refinery excluding Petronor)
in Spain 8 (excluding Petronor)
in the EU About 114
Comparable structures (e.g. hydrogen networks
anywhere else than in oil refineries)
Not available
Table 4: Petronor generalisation potential
The Petronor case has thus potential for:
- Generalisation within the same company (Repsol group)
- Generalisation to other oil refineries with hydrogen networks in Spain and Europe overall
Generalisation hypotheses and results
On the basis of the available data, two generalisation hypotheses could be applied, one with regards to en-
ergy resources and environmental impact, one with regards to economic values.
604068 D6.7 Impact Assessment p.58
1. Increased diesel production with the same amount of hydrogen:
Every refinery has a hydrogen network. The demand of hydrogen depends on the production volume of the refinery (this is the dominating influence) but also on the crude oil that is processed and the spectrum of products that is produced. It is assumed that Petronor uses a standard type of crude oil that is comparable to other European refineries.
If the amount of diesel produced with the same amount of hydrogen rises, this is considered an improvement impacting positively both resource efficiency and costs. The results of the hypothesis are as follows:
Petronor’s initial diesel production having been 548t/h, an increase of the total diesel production with the same amount of hydrogen according to the impact assessment corresponds to 30,490kg/h - equalling 5.6% improvement
Total diesel production in the refining industry:
Inside Repsol: it can roughly be estimated that the diesel production of Repsol is 2030 t/h. An improvement of 5.6% would equal 113,680kg/h additional diesel production with the same amount of hydrogen.
In Spain: It can very roughly be estimated that the diesel production in Spain corresponds to the diesel production at Petronor / 0.16. This equals 548t/h / 0.16 = 3425t/h diesel production. 5.6% improvement of this amount corresponds to 191,800kg/h. Calculating this optimisation potential only on 25-50% of existing plants, the generalisation potential is 47,950 – 95,900kg/h in the Spanish diesel production with the same amount of hydro-gen.
In the EU: The diesel production amounts to approximately 200M tonnes per year (2015)53. An improvement of 5.6% as in the Petronor case would equal 11.2M tonnes per year additional diesel production with the same amount of hydrogen used. Calculat-ing this optimisation potential only on 25-50% of existing plants, the generalisation po-tential is 2.8-5.6M tonnes per year
2. Cost saving
According to Petronor internal data, the implementation of the MORE approach has resulted in a cost saving as follows: the evaluated hydrogen saving represents between 1-5M €/y. NB: The investment of Petronor is estimated at 400k € with a full return of the investment within a year. On the basis of the production capacity, the potential cost saving can be generalised.
The comparison can thus be done as follows:
Inside Repsol: production capacity is a bit more than 3 times higher than for Petronor (676000 barrels crude per day for the other 4 refineries of Repsol 54); the cost saving po-tential amounts thus to 3.03-15.15M €/y.
In Spain: The refining capacity in Spain is 1,440000 barrels crude oil/day, according to AOP, the Spanish Petroleum Operators Association. excluding Petronor’s capacity this
53 Fuels Europe, Statistical Report 2015, p. 14
604068 D6.7 Impact Assessment p.59
gives 1,220000 barrels crude oil/day in the 8 other refineries in the country. The saving potential in Spain is thus 5.55–27.75M €/y.
In the EU: the ratio of Petronor’s production capacity to the EU-wide capacity is 0.01. The cost saving potential amounts thus to 100-500M €/y. Calculating this optimisation po-tential only on 25-50% of existing plants, the generalisation potential is worst 25-125 or best 50-250M €/y.
6.2.1. INEOS
Impact objective
The objective of the INEOS Cologne site in the MORE project was to optimise the operations in several of its
plants and to ensure the acceptance of these changes by the operating staff.
INEOS impact generalisation background and potential
The integrated petrochemical site in Cologne, Germany, operated by INEOS in Köln is highly integrated which
makes generalisation to other production units difficult. The plants included in MORE are the site overall, the
acrylonitrile (AN) and butadiene plants, cooling towers and crackers. Each of these plants has their unique
role in the integrated petrochemical site and interconnections exist between the example plants and other
plants that are not evaluated in the MORE project. Generalisation of the whole site is not easily possible
because no petrochemical site is fully alike.
A full implementation of the dashboard was finished for the AN plant. Technical changes at the plant that
were made simultaneously but independently of the MORE project changed plant operation from baseline
generation to today, making the assessment of quantitative impacts of MORE difficult. Hence, a specific hy-
pothesis for each plant was used in generalisation.
Generalisation hypothesis and results
INEOS in Köln is a major base chemicals producer. The chemicals are produced in large scale in continuous
and product specific plants. In the crackers, the site feed naphtha and LPG are cracked to receive a large
spectrum of olefins active enough to produce further chemicals and plastics. Typically, they are distinguished
by chain lengths and type. Although all plants are product specific and therefore show completely different
energy and resource efficiency, they are all large scale and continuous. As such, some generalisation hypoth-
eses on plant operation can be made that are supported by experience:
1. In contrast to refineries, it can be safely assumed that 25-50% of base chemicals productions plants
are only manually optimised without methods shown in MORE or the use of advanced techniques,
such as online optimisation and advanced process control. Considering the value chain from refining
to fine chemicals, the percentage decreases from close to 100% in refineries to 75% in crackers and
even lower figures for the downstream processes. As such, these plants would show a similar opti-
misation potential as the plants at the integrated petrochemical site operated by INEOS in Köln.
2. Implementation of Real-Time Optimisation projects and advanced process control projects typically
show an improvement in throughput and energy efficiency of 2-5% dependent on how much effort
had already been spent on optimising the plant before. This figure is both in agreement with expert
604068 D6.7 Impact Assessment p.60
and MORE partner experience55. It is assumed that in large scale and continuous production plants,
5% is the typical best case that can be reached through optimising plant operations.
3. It can be assumed that changes in human behaviour (by using REI in decision support and monitoring)
can realise only a fraction of full scale automatic optimisation. In this generalisation, we assume this
figure to be 40%.
Combining these three assumptions the following conservative hypothesis for the generalisation is derived:
25% of large scale continuous base chemical plants in Europe can reach an overall energy efficiency im-
provement of 2% through fully implementing the MORE methods as advisory systems.
In the following, each of the MORE INEOS case studies and the generalisation potential are discussed briefly.
Acrylonitrile (AN)
INEOS is market leader in AN production in Europe; it has two AN plants in Cologne (Capacity 320 kt/year,
source INEOS website) and one in the United Kingdom. According to the Best Available Techniques (BAT)
reference document (BREF) for large organic chemical plants, there are four AN plants in Europe – three
operated by INEOS and one operated by AnQour (formerly DSM).56
The MORE approach can be applied to other AN plants in Europe.
The production capacity of AN in Europe in 2013 was 1200 kt/year and is about 800 kt/year today. According
to the BREF document, the energy export from AN plants is between 340 – 5700 MJ/t acrylonitrile. If we
estimate that with the MORE approach approximately 25% of the European capacity could gain 2% energy
efficiency improvements by applying MORE approach, this would mean 2040-34200 GJ/year more energy
exported from AN plants to other processes in integrated sites. If this amount of steam would have to be
generated by natural gas, the estimated emission savings would be between 125-2100 t CO2 per year in Eu-
ropean level. It has to be noted that all AN plants are differently integrated into the total sites and therefore
it is difficult to estimate impacts on site energy flows in a generic level. As the extra energy results from an
exothermic reaction, it has to be checked very carefully with an overall analysis that this increased steam
export is not traded with a lower product material yield.
Cooling towers
A cooling tower is a typical unit of a petrochemical site and also an essential part of many industrial processes.
Cooling towers are a major electricity consumer at the petrochemical site operated by INEOS in Köln and thus
continuous optimisation of the electricity consumption is needed.
Cooling towers are used widely outside the petrochemical industry in many industrial sectors. Many different
types of cooling towers exist. Major savings can be expected in forced draft towers with many automated
55 Bauer et al, Economic Assessment of Advanced Process Control - A Survey and Framework, Journal of Process Control,
01/2008 56 The European IPPC Bureau. 2014. Best Available Techniques (BAT) Reference Document in the Large Volume Organic
Chemical Industry, Working draft (1). http://eippcb.jrc.ec.europa.eu/reference/BREF/LVOC042014.pdf
604068 D6.7 Impact Assessment p.61
cells or variable speed drive fans. The operation of a cooling tower is closely dependent on the adjacent
plants and thus the optimal cooling water temperature is different in each case.
Environmental impacts are mostly related to the energy use in cooling. When environmental impacts of cool-
ing and cooling towers are estimated, it is important to include both direct energy consumption (by pumps
and fans) and indirect energy consumption (cooling efficiency in the process where cooling is needed)57.
In the MORE project, the energy use of a cooling tower was optimised both separately and together with a
butadiene plant. Based on MORE results one can argue that cooling tower control that takes into account
ambient conditions helps reduce electricity consumption at the cooling tower by about 10% by increasing
the cooling temperature at 25°C.
Instead of generalising case-specific impacts from cooling towers, a recommendation is given: a 2⁰C increase
in cooling temperature can lead to 6 % of MWh annual savings in cooling tower electricity consumption ac-
cording to Table 1. Considering that a cooling tower is widely used unit throughout the process industry,
savings on European level can be notable.
Any cooling tower needs to be analysed with the adjacent plants.
This has been tested to Butadiene plants with theoretical models. Using the available process models from
the butadiene plant APC controller and the cooling tower model developed in MORE, the dependency could
be modelled and its trade-off could be understood better. Now, the understanding of the dependency needs
to be utilised.
Crackers
A cracker is the central unit of any petrochemical site. There are approximately 40 sites in Europe with crack-
ers58. Steam cracking is the most typical way of producing lower olefins, such as ethylene, propylene, butyl-
ene and butadiene59. The majority of the European steam crackers uses naphtha as feedstock. The most
relevant environmental issues related to steam cracking are carbon dioxide and other combustion gas emis-
sions from the cracking furnaces, dust emissions from cracker tubes, volatile organic compound (VOC) emis-
sions from diffuse sources, emissions to water and hazardous wastes.60
The aim of the MORE project is to run all the furnaces in the best way by implementing an optimisation model
in crackers. An improvement possibility in naphtha cracking is expected through knowing in advance, which
naphtha quality arrives at the furnace. While this might lead to a better product yield, there is little impact
on direct CO2 emissions because if less internal energy is produced at crackers it has to be compensated with
external energy and in the INEOS case that would be with natural gas. Also, the desired products from a
cracker (more ethylene or more propylene, also classed as severity) and the resulting operation has a larger
impact on CO2 that can be noticed through improved operations.
57 The European IPPC Bureau. 2001. Reference Document on the application of Best Available Techniques to Industrial
Cooling Systems 58 http://www.petrochemistry.eu/about-petrochemistry/facts-and-figures/crackers-capacities.html 59 The European IPPC Bureau. 2014. Best Available Techniques (BAT) Reference Document in the Large Volume Organic
Chemical Industry, Working draft (1). http://eippcb.jrc.ec.europa.eu/reference/BREF/LVOC042014.pdf 60 The European IPPC Bureau. 2014. Best Available Techniques (BAT) Reference Document in the Large Volume Organic
Chemical Industry, Working draft (1), p.138. http://eippcb.jrc.ec.europa.eu/reference/BREF/LVOC042014.pdf
604068 D6.7 Impact Assessment p.62
Savings that could theoretically be realized in the Cracker at INEOS in Köln can be generalised with multipli-
cation of n° of crackers in Europe. As these savings are economic in nature, they cannot be disclosed.
6.2.2. BASF
Impact objective
One of the main goals for BASF in MORE project was to gain more knowledge about applicability of custom-ized online analytics and online monitoring for speciality products based on renewable raw materials.
BASF impact generalisation background and potential
BASF Personal Care and Nutrition GmbH (formerly Cognis GmbH) is a global supplier of specialty chemical products and nutritional ingredients based on renewable raw materials. The Düsseldorf site is BASF’s largest production site for personal care products worldwide. Based on natural and renewable raw materials, BASF PCN produces a wide range of ingredients for cosmetics, hair and body care products as well as household and industrial cleansers. These include, for example, surfactants, oil components and care products that in-fluence the sensory properties of creams and lotions.
As the BASF process is confidential and production capacity of the chosen product neither on BASF nor Euro-pean level can be published, a generalisation of impacts is not feasible.
Generalisation hypotheses and results
Speciality chemicals are produced usually in small volumes but represent 28% of the European chemical sales61. The production rates of speciality chemicals in Europe have grown in the past years but competition will increase in future due to lower demand from key industries, producers outside Europe and global eco-nomic situation62.
It can be argued that comparable savings in similar processing steps on other speciality chemicals plants are possible; however, it is not known how many plants perform this specific step and what are the capacities. Therefore, quantitative impacts on European level are difficult to estimate and the uncertainty is too high for giving recommendations or estimates on possible savings and efficiency improvements. On BASF level, gen-eralisation of MORE approach is possible. BASF has other similar plants and it would be possible and even probable to implement similar approaches and technologies in other plants and processes. The feasibility of applying the same approach on other speciality chemicals plants depends on the automation level of each plant. Therefore, not all plants with similar production processes are seen as potential plants for implement-ing MORE approach, only those ones that have similar automation level than the case study plant.
6.2.3. LENZING
Impact objective
The Lenzing site, located in the city of Lenzing, Austria, is a reference factory around the world for producing
man-made cellulose fibres. This site is called LAG. There are very few competitors remaining in Europe and
thus the generalisation potential is a different from other case studies. In the MORE project, energy efficiency
of the evaporators in the spinbath process stage were optimised.
61 Cefic. Facts and Figures 2016, p.8. http://fr.zone-secure.net/13451/186036/#page=8 62 Cefic. Facts and Figures 2016, p.22. http://fr.zone-secure.net/13451/186036/#page=8
604068 D6.7 Impact Assessment p.63
The impact objectives were:
Reduced steam consumption, evaluated through the ratio between GJ steam/ GJ nat gas (Hu) that
should be 0,9 (=90% Boiler efficiency).
Reduced natural gas consumption [Nm3 natural gas/year], [kg CO2/year]
Steam saving directly results in less natural gas input.
Impact generalisation potential and background
This site is the only viscose production site of the Lenzing group within the EU; the only comparable viscose
fibre manufacturer in the EU is Lenzing’s competitor Kelheim fibres. In addition, a number of much smaller
producers exist that correspond to about 25% of the production of Lenzing.63
The following table gives more information about the generalisation potential.
Lenzing generalisation potential Amount
Spinbath evaporators within Lenzing (LAG site): Confidential
Comparable structures inside Lenzing in the EU 0
Comparable structures in Europe 1 large at Kelheim fibres, a number of much
smaller ones
Comparable structures (e.g. evaporators any-
where else than in viscose fibre production)
Not available
Table 5: Lenzing generalisation potential
The Lenzing use case has thus potential for:
- Generalisation to other companies in the same sector
Even though not enough data could be gathered on comparable structures to permit generalisation to other
sectors, it can be noted that the same methodology could be used for any operation including one or more
evaporators.
Generalisation hypotheses and results
63 There are only two viscose staple fiber manufacturers left in Europe: Lenzing AG (262kt/year) and Kelheim Fibers
GmbH (~90kt/year). Other companies using the viscose process (Glanzstoff, ENKA, CORDENKA, Casetech…) to produce viscose filaments (textile, tirecord) or viscose blow films and sponges. The production capacity of a filament plant (5 to 20 kt/year) is much lower than for a staple fiber one. In addition, the process differs more or less depending on the product. It is also difficult to estimate how the recovery plant is working in a filament plant, how many and how big evaporators are used. The estimate of these companies as 25% of LAG is thus very rough.
604068 D6.7 Impact Assessment p.64
On the basis of the available data, two generalisation hypotheses could be applied, one with regards to en-
ergy resources and ecologic impact, one with regards to economic values.
1. Energy and steam saving:
Due to an optimized process, less energy (fossil fuels) is needed for the same amount of product. This results
in a saving of steam in the evaporator process. Steam saving is directly related to natural gas savings leading
to cost and CO2 emission savings.
The results of the hypothesis are as follows: Lenzing total production: 260kt/year viscose fibres
Total savings of production energy or fossil fuel per ton of cellulose fibres: 68 MJ/t
Generalisation:
- Within LAG: the optimization process is already applied to all the evaporators. The energy
saving per ton of cellulose fibres can thus be multiplied with the total production
(260kt/year) which results in savings of 17,68MJ/year. The same applies for the Natural gas
saving due to steam saving: 2,5MioNm3 natural gas saving/year (for the whole Lenzing site).
- Within Europe: Kelheim fibres is the main comparable structure, it corresponds to around
30% of LAG; in addition, smaller companies in the same sector account for about 25% of the
LAG production. Thus, there is a potential for 55/100 of 260kt/year (=143kt/year), corre-
sponding to potential energy savings of 9,72 MJ/year and 1,38Mio Nm3 natural gas sav-
ing/year in Europe’s viscose fibre production. Calculating this optimisation potential only on
25-50% of existing plants, the optimisation potential amounts to about 36-72kt/year and po-
tential energy savings of 2,5-5 MJ/year, as well as 0,35-0,7Mio Nm3 natural gas saving per
year.
2. Cost saving
On the basis of the reductions in energy and steam consumption displayed above, cost savings can equally
be calculated. The generalisation is however done for Lenzing sites beyond LAG, as the cost savings already
calculated take into account investments that were done on the LAG overall, not only one evaporator. Gen-
eralisation to other companies can be done as in the hypothesis 1.
The comparison can thus be done as follows:
The estimated LAG investment for the MORE approach implementation and roll-out to all evapora-
tors accounts to around 75k €. The benefit is an estimated saving of 375k €/year. The reduction of
the production costs is proved to be 1.5 €/t, due to the gas saving.
Generalisation:
- The reduction of total energy costs (thanks to reduced energy use): The optimisation being
already done in evaporators all over the LAG site, savings could be estimated for evaporators
in non-EU based sites. They account to 500k €/year due to energy saving (already realized)
and further 500k€/year expected next year.
604068 D6.7 Impact Assessment p.65
- The reduction of product costs: is proved to be around 1.5 €/t fibre (gas saving), correspond-
ing thus to an overall saving of 375 000€/year for the production of 260kt/year. Applying the
methodology to other areas in the fibre production plant (beyond the MORE project scope)
could give an estimated additional reduction of 200-1000k €/year = 0.77– 3.85 €/t fibre.
- Production compared to other EU structures: Kelheim corresponds to around 30% of LAG
30/100 * 375k €/year roughly 112,500 €/year savings potential. In addition, several other
smaller structures exist with saving potential (possibly 25% of LAG), so some 94 000€/year
saving potential can be estimated for these structures overall. Calculating this optimisation
potential only on 25-50% of existing plants, the savings potential amounts to 23.5K-
47K€/year for the smaller structures.
604068 D6.7 Impact Assessment p.66
7. Conclusions and recommendations for policy makers
On the basis of the generalisation analysis provided above, it becomes obvious that there is significant po-
tential for improved resource efficiency by the use of real-time REIs for operator support and optimization
and control solutions. This can lead to considerable savings with regard to material, energy and costs – both
inside the companies involved in the MORE project and in comparable structures of the same sectors in Eu-
rope and in the process industries in general. As discussed, the figures provided need to be taken with care,
as differences between structures (processes and technologies) may influence the generalisation potential
and the measures cannot be applied to all plants and sites straight away. Nevertheless, the results of the
generalisation of the use cases can be taken as an orientation and point to promising directions for potentials
of resource efficiency improvements in the chemical industry.
From the results of the impact assessment and of the generalisation analysis as well as from background
knowledge and experience of the industrial partners, the following recommendations are provided:
- The Horizon 2020 work programmes comprise already calls that aim at the optimisation of processes
and more resource-efficient production. The impact analysis undertaken by the MORE project
showed that besides the development of computer-based technologies, “human factors” need to be
taken into account. In particular, plant operators have a strong influence on the operation of pro-
cessing plants and this situation is not expected to change quickly. Therefore, the support and the
acceptance of technical solutions by the operators and their training is of key importance. The ac-
ceptance by the operators decides on the success or failure of many technical measures. Therefore,
we recommend to put an emphasis on the interaction of operators with computer-based solutions
in the remaining H2020 work programme. Also, the element of the evaluation of the acceptance and
of the results of the introduction of support tools is not easy and this element should be included in
future H2020 calls.
- Digitalisation of the industry is a prominent topic for the improvement of the competitiveness of the
European industry. The experience of the MORE project shows that connectivity and data integration
is not the main limiting factor in the process industries but that the use of the data is severely im-
peded by the limited quality and the incompleteness of the available measurements. Further ad-
vances in sensing are indispensable for improved plant operations.
- When undertaking the analysis of the generalisation of the impact of the MORE project, it has be-
come clear that data about the production of the chemical industry is dispersed over many sources
and incomplete. In consequence, a large number of sources had to be compared and combined to
provide reliable information about the baseline data and the potential in the different sectors. The
use of a variety of different measures of energy and resource efficiency in the publications renders
providing an overall picture even more difficult. We thus recommend to an adequate body, such as
A.SPIRE as an industry association, to proceed to a sector-by-sector analysis and to publish the results
as a reference report on the state of the process industries. We believe that industry has delivered
all of this data in the past (ETC, BREF, etc.) but the data collection, storage, management and availa-
bility for statistical analysis can be improved.
- There are many regulations imposed on industry in Europe in order to stimulate resource efficient
operations. In comparison to other countries, e.g. the US, the regulatory burden in the EU can be
considered rather high. This is not a problem if the regulations are consistent and stable, as the goals
604068 D6.7 Impact Assessment p.67
of the regulation and of the industry with respect to resource efficiency are similar. A problem, how-
ever, is the frequency of changes in regulations. Further improvements of resource efficiency, espe-
cially for not only improving the operation of the available plants but introducing new plant technol-
ogy requires significant investments. Such investments are only possible if the regulatory environ-
ment is stable, otherwise payback times are required to be short (1-2 years) which will then hinder
potential investment into new plants and new technologies. A volatile regulatory framework is coun-
terproductive for technology development and deployment. The framework conditions need to be
stable to reduce the risk of longer payback periods, thus leading to improved resource efficiency by
measures which are currently economically too risky.
604068 D6.7 Impact Assessment p.68
8. Annex 1: comprehensive evaluation framework
Criteria indicators
Q1: To what extend the REIs improved the environmental performance at plant and at company level?
Qualification of the results The implementation of REI improves importantly the environmental performance and reach the expected target in terms of waste production, energy consumption and resources consumption and open the way to further improve-ments The implementation of REI enables progress on environmental performance, but others actions should be under-taken to make them significant at company level The implementation of REI improves environmental footprint at plant level, but other significant steps are required to extent at a larger scale The implementation of REI does not produce noticeable or sufficient changes in environmental impacts in compar-ison with the expectations
Has the environmental performance im-proved through the use of REI?
- Decreased direct emissions to air and water
- Decreased use of resources
- Decreased electricity consumption - Decreased use of heat
- Changes in raw materials
- Decreased amounts of waste
Is the environmental performance at company level concordant with plant level?
- Overall environmental performance has improved a.k.a. reduction in environmental impacts
- Overall reduction in environmental impacts or are some impacts lower, some higher than before REI implementation?
- No shifting between plants (e.g. less resource-efficient/environ-mental friendly production moved to another plant)
Q2: To what extent the use of REI increased economic performance at plant and at company level?
Qualification of the results
The implementation of REI produces a tangible economic performance and ways for further opportunities in the plant involved in the case study or wider. The implementation of REI produces a better tangible economic performance and is convergent with plant and company expectation or target The implementation of REI produces economic gains but at small scale and below the expectations The implementation of REI is disappointed in terms of economic performance
Are there economic gain produced from the use of REI and decision support sys-tem?
- Cost of implementation
- Conditions prior implementation (and their associated cost)
- Conversion of REI in money
- % of gain realized
604068 D6.7 Impact Assessment p.69
Is the economic performance at com-pany level concordant with plant level?
- Existence of conflicts between REI (local optimity) and KPI at com-pany level (global optimity)
- Nature of conflicts
Does the use of REI improve innovation opportunities and technological im-provements of company
- Identification of opportunities (number, nature, perimeter)
- Estimation of further gain from these innovations
Q3: To what extent the use of REI changed and improved the operation, manage-ment and decision process at plant and company level?
Qualification of the results The implementation of REI impacts the decision making at all levels of the company from strategic to operational and better knowledge have been acquired on the factors that influence resource efficiency The implementation of REI impacts the company, but not all levels of hierarchy are concerned and involved and no noticeable change to monitor performance have been done or are planned The implementation of REI is mainly at operational level and involves very few strategic decision The implementation of REI does not produce noticeable impacts in terms of management and decision making
Does the decision support system enable multicriteria optimisation?
- Number of additional parameters controlled by operators
- Number of additional operations taken by operators
- Identification of new optima to be targeted (Y/N) - New value of the optima
- % of improvement
Are the causes of loose of efficiency iden-tified?
- Factors identified
- Better understanding of the influence of individual parameters/factors
Are correctives actions taken (or planned)?
- Number, nature and extent of corrective actions already taken
- Evolution of procedures in internal document (existence, extent)
- Training of operators to implement corrective actions (existence, number)
- Corrective actions foreseen in the future (nature, timing, extent)
Does REI and dynamic approach provide added value to operators to take deci-sion?
- Evolution of key decisions taken by operators (nature, numbers)
- Level of acceptance of operators
Does the optimisation strategy at com-pany level evolve?
- Evolution of time / constraints for operators
- Relevance of REI and visualization
- Evolution of key decisions taken by managers (nature, numbers)
