A13D-3196:
Inter-annual variability of air pollutants over East Asia: an integrated analysis using satellite, lidar and numerical model.

Monday, 15 December 2014
Keiya Yumimoto1, Itsushi Uno2, Masatoshi Kuribayashi2, Kazuyuki Miyazaki3 and Tomoaki Nishizawa4, (1)Meteorological Research Institute, Ibaraki, Japan, (2)Kyushu University, Fukuoka, Japan, (3)JAMSTEC Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan, (4)National Institute for Environmental Studies, Tsukuba, Japan
Abstract:
Air quality in East Asia has a drastic temporal and spatial variability. The rapid economic growth in the last three decades enhanced the increase of anthropogenic emission of air pollutions, and caused deterioration of the air quality in both source and downwind regions. The unprecedented heavy PM­2.5 pollution over the central China in January 2013 records the maximum PM2.5 concentration of 996 μg/m3 and raised critical environmental issues (e.g., mortality, human health, social activity and trans-boundary transport, etc.). Recently, efforts to reduce anthropogenic emissions (e.g., emission regulations and improvements of emission factors and removal efficiencies) decelerate their growth rates. In fact, Asian SO2 emission is estimated to be reducing from 2007 [Kurokawa et al., 2013]. However, growth rates other pollutant emissions (e.g., NOx and PM10) still remain in high.

To understand the life cycle of pollutants (emission, transport, reaction and deposition) and their temporal and spatial variation, an integrated analysis using observation and numerical model (chemical transport model; CTM) is useful. In this study, we installed a comprehensive observation operator system, which converts model results into observed variables, into the GEOS-Chem CTM. A long-term (2005–2013) full-chemistry simulation over East Asia was performed, and simulation results are translated to tropospheric NO2 and SO2 columns and vertical profiles of aerosol extinction coefficient equivalent to satellite measurements and in-situ lidar network observations. Combining CTM and observations, and integrating analyses of aerosols over the downwind region and their precursors over the source region will provide important insights into temporal and spatial variation of air pollutants over East Asia.