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A changing climate: impacts on human exposures to O3 using an integrated modeling methodology
Dionisio, K., Chris Nolte, T. Spero, S. Graham, N. Caraway, K. Foley, AND K. Isaacs. A changing climate: impacts on human exposures to O3 using an integrated modeling methodology. 2016 Annual International Society of Exposure Science Meeting, Utrecht, N/A, NETHERLANDS, October 09 - 13, 2016.
Presented at 2016 Annual ISES Meeting held in Utrecht, The Netherlands, from 9-13 October 2016.
Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposures due to these impacts was developed by linking climate, air quality, land-use, and human exposure models. This methodology was then applied to characterize changes in predicted human exposures to O3 under multiple future scenarios. Regional climate projections for the U.S. were developed by downscaling global circulation model (GCM) scenarios for three of the Intergovernmental Panel on Climate Change’s (IPCC’s) Representative Concentration Pathways (RCPs) using the Weather Research and Forecasting (WRF) model. The regional climate results were in turn used to generate air quality (concentration) projections using the Community Multiscale Air Quality (CMAQ) model. For each of the climate change scenarios, future U.S. census-tract level population distributions from the Integrated Climate and Land Use Scenarios (ICLUS) model for four future scenarios based on the IPCC’s Special Report on Emissions Scenarios (SRES) storylines were used. These climate, air quality, and population projections were used as inputs to EPA’s Air Pollutants Exposure (APEX) model for 12 U.S. cities. Probability density functions show changes in the population distribution of 8 h maximum daily O3 exposure by age, gender, and city for each of the three future climate scenarios. Of the 12 cities analyzed, some cities see an increase in the number of exceedances (e.g., Los Angeles), while others see a decrease (e.g., Chicago). In contrast, results show that there is minimal change in exposure distributions across future population scenarios. Thus we expect the change in ambient air quality concentrations in future climate scenarios to have a greater impact on future exposure distributions than potential scenarios of population change.