Earth and Atmospheric Sciences, Department of


Date of this Version

Spring 3-24-2016


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Earth and Atmospheric Sciences, Under the Supervision of Professor Jun Wang. Lincoln, Nebraska: March, 2016

Copyright © Chase Calkins 2016

Final journal revisions will be in Atmospheric Environment


The last decade has seen frequent occurrences of severe air pollution episodes of high concentration in SO2 during winters in the North China Plain (NCP). Using satellite data from the Ozone Monitoring Instrument (OMI), chemistry transport model (GEOS-Chem) simulations, and National Center for Environmental Predication (NCEP) meteorological reanalyzes, this study examines meteorological and synoptic conditions associated with these air pollution episodes during winters of 2006-2015. OMI-based data suggest a large decrease (~30% in area average) of emission since 2010. Statistical analyzes show that meteorological conditions associated with the top 10% of OMI-based high days are found in average to be controlled by high pressure systems with 2 m s-1 lower wind speeds, slightly warmer, 1-2 °C, temperatures and 10-20% higher relative humidities from the surface to 850 hPa. Numerical experiments with GOES-Chem nested grid simulations at 0.5°´0.667° resolution are conducted for winters of 2009 as a control year, and 2012 and 2013 as years for sensitivity analysis. The experiments reveal that year-to-year winter change of columnar SO2 amount and distribution in first order is linearly proportional to the change of SO2 emission, regardless of the differences in meteorological conditions. In contrast, the surface SO2 amount and distribution exhibit highly non-linear relationships with respect to the emission and stronger dependence on meteorological conditions. Longer data records of atmospheric SO2 from space combined with meteorological reanalyzes are needed to further study the climatology of air pollution and the variations in air pollution events in the context of climate change.

Adviser: Jun Wang