Effects of future climate and land cover changes on biogenic emissions and air quality in the US

Biogenic volatile organic compounds (BVOCs) emitted from vegetations are highly reactive in the atmosphere and contribute to ozone and secondary organic aerosol formation. Climate change influences vegetation distributions and emissions of BVOCs and thereby affects air quality. As part of a comprehensive investigation of the effects of global change on regional air quality in the US, this study examines the effects of future climate and land cover changes on emissions of BVOCs into the atmosphere and air quality in the US. The mesoscale WRF (Weather Research and Forecasting) model is applied at hemispheric (220 km grid cells) and continental US (36 km grid cells) scales for current (1995-2004) and future (2045-2054) decades to downscale climate results from the ECHAM5 global climate model for IPCC SRES scenario A1B. The MEGAN (Model of Emissions of Gases and Aerosols from Nature) model is driven by WRF meteorological results to predict biogenic emissions of VOCs and NOx. MEGAN accounts for vegetation species distributions and environmental factors such as temperature and light. Current decade vegetation distributions are derived from satellite observations. Future vegetation distributions are predicted from MAPSS (Mapped Atmosphere-Plant-Soil System) and the land cover model of IMAGE 2.0 (Integrated Model to Assess the Global Environment). Future land cover changes include the expansion of croplands so that land management changes can also be examined. The CMAQ (Community Multiscale Air Quality Modeling) chemical transport model is used to simulate O3 and aerosol concentrations using current- and future-decade biogenic emissions but with anthropogenic emissions held constant at current-decade levels. Results showing the changes in US air quality due to climate- and landuse-driven changes in biogenic emissions will be presented. These results are compared to previous simulations derived from the IPCC SRES scenario A1 scenario with the PCM (Parallel Climate Model) global model.