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Future Air Quality in Representative Concentration Pathway Scenarios:Relationships Between Economic
Wellbeing and Air Quality
J. Jason WestSteven J. Smith, Joint Global Change Research
InstituteLouisa Emmons, NCAR
Larry W. Horowitz, GFDL
The UNC
Climate, Health and Air Quality Lab
What Will Future Air Quality Be?
• The IPCC Special Report on Emissions Scenarios (SRES, 2000) projected high growth of air pollutant emissions, in future scenarios.
Modeled monthly mean ozone increase in 2100 (SRES A2 scenario), relative to 2000 – average of 10 global models (Prather et al., 2003).
Will A Richer World Put Up With Air Pollution?
Environmental Kuznets Curves: Richer countries are expected to be more willing to devote resources for environmental protection
Ausubel and Waggoner, 2009
Income per Capita
Env
ironm
enta
l Im
pact
• Integrated Assessment Models assume that emission controls increase with income.
• However, pollutant concentrations, should be more closely related to incomes.
Smith et al., 2009
ObjectiveEvaluate one RCP scenario for its consistency across regions in terms of air quality, by using
a global chemical transport model in the scenario development process.- Analyze the relationships between income and air quality, rather than emissions controls.- Use an iterative process of creating scenario and simulating global air quality.
New scenarios for use in IPCC AR5 = Representative Concentration Pathway (RCP) Scenarios
Use MOZART (versions 2 and 4) for global simulations of future air quality.
RCP Scenarios
We will use MOZART to model the RCP4.5 scenario.
RCP8.5>8.5 W/m2 in 2100, Rising
MESSAGE model, IIASA, Austria
RCP6~6 W/m2 at stabilization after 2100Stabilization without exceeding target
AIM model, NIES, Japan
RCP4.5~4.5 W/m2 at stabilization after 2100Stabilization without exceeding target
MiniCAM model, PNNL, USA
RCP3-PD<3 W/m2 in 2100peak & decline stabilization
IMAGE model, PBL, Netherlands
RCP scenarios named for their radiative forcings in 2100.
• MOZART-2 is used to model RCP4.5 scenario in 2005, 2050 and 2095, based on gridded emissions outputs of MiniCAM.
• Resolution: T42, 2.8°x2.8° with 34 vertical levels.• Meteorology: MACCM3 simulated global meteorology for the
present.• VOC speciation: from POET global emissions.• Seasonal distributions of emissions: from RETRO global
emissions.• Natural emissions: from base MOZART-2 simulation
(Horowitz et al., 2003).• PM2.5 = SO4 + NO3 + NH4 + EC + OCx1.5• Methane is fixed globally at estimated future concentrations.• This version of MOZART-2 has been evaluated extensively
against measurements, but not for these base emissions.
MOZART-2 setup
Results: Second IterationAnnual average PM2.5
2050 2095
2005
World Regions
Results – PM2.5 by region
Mean PM2.5 for the consecutive 3 month period with highest PM2.5 in each region.
0
5
10
15
20
25
30
35
2000 2020 2040 2060 2080 2100
Max
Sea
sona
l PM
(ug/
m3)
Year
Max Seasonal PM Levels
NothingEuropeMiddleEastSouthAmericaAustraliaFormerSovietEast ChinaIndia, etc.SoutheastAsiaNorthAfricaJapanMexicoSouthernEuropeSouthern-Cent AfricaEasternUSGlobal
0
5
10
15
20
25
30
35
0 20 40 60
Max
Sea
sona
l PM
(ug/
m3)
Income (1000s MER$/cap)
Max Seasonal PM Levels
EuropeMiddleEastSouthAmericaAustraliaFormerSovietEast ChinaIndia, etc.SoutheastAsiaNorthAfricaJapanMexicoSouthernEuropeSouthern-Cent AfricaEasternUSGlobal
Results: Second Iteration Annual average ozone
2050 2095
2005
Results – Ozone by region
Mean ozone for the consecutive 3 month period with highest ozone in each region.
20
30
40
50
60
2000 2020 2040 2060 2080 2100
Max
Sea
sona
l O3
(ppm
)
Year
Max Seasonal O3 Levels
NothingEuropeMiddleEastSouthAmericaAustraliaFormerSovietEast ChinaIndia, etc.SoutheastAsiaNorthAfricaJapanMexicoSouthernEuropeSouthern-Cent AfricaEasternUSGlobal20
30
40
50
60
0 20 40 60
Max
Sea
sona
l O3
(ppm
)
Income (1000s MER $/cap)
Max Seasonal O3 Levels
EuropeMiddleEastSouthAmericaAustraliaFormerSovietEast ChinaIndia, etc.SoutheastAsiaNorthAfricaJapanMexicoSouthernEuropeSouthern-Cent AfricaEasternUSGlobal
• We’ve shown how atmospheric modeling can be used in the scenario development process.
• By adjusting emission controls, future PM2.5 concentrations were made to yield reasonably consistent relationships with projected future incomes, among world regions.
• Ozone was found to be harder to adjust using a region’s own emission controls, because of the influence of background and foreign sources.
Preliminary Conclusions
Next Steps• Convert to MOZART-4 and evaluate model against
measurements for base emissions.• Simulate final RCP4.5 scenario, and other RCP
scenarios.• Evaluate simulating under future climate conditions.