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Future Air Quality in Representative Concentration Pathway Scenarios: Relationships Between Economic Wellbeing and Air Quality. J. Jason West Steven J. Smith, Joint Global Change Research Institute Louisa Emmons, NCAR Larry W. Horowitz, GFDL The UNC Climate, Health and Air Quality Lab.
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Future Air Quality in Representative Concentration Pathway Scenarios: Relationships Between Economic Wellbeing and Air Quality J. Jason West Steven J. Smith, Joint Global Change Research Institute Louisa 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 Environmental Impact Income per Capita Ausubel and Waggoner, 2009
Integrated Assessment Models assume that emission controls increase with income. • However, pollutant concentrations, should be more closely related to incomes. Smith et al., 2009
Objective Evaluate 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 RCP scenarios named for their radiativeforcings in 2100. We will use MOZART to model the RCP4.5 scenario.
MOZART-2 setup • 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.
Results: Second IterationAnnual average PM2.5 2005 2095 2050
Results – PM2.5 by region Mean PM2.5 for the consecutive 3 month period with highest PM2.5 in each region.
Results: Second Iteration Annual average ozone 2005 2095 2050
Results – Ozone by region Mean ozone for the consecutive 3 month period with highest ozone in each region.
Preliminary Conclusions • 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. 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.