2012 Progress Report: Air Quality Impacts of Extreme Weather Events: Historical Analysis and Future ProjectionEPA Grant Number: R835204
Title: Air Quality Impacts of Extreme Weather Events: Historical Analysis and Future Projection
Investigators: Wang, Yuhang , Deng, Yi , Zhang, Henian
Current Investigators: Wang, Yuhang , Deng, Yi , Loadholt, Jay , Park, Taewon , Song, Yongjia , Zeng, Tao , Zhang, Henian , Zhang, Yuzhong , Zou, Yufei
Institution: Georgia Institute of Technology
Current Institution: Georgia Institute of Technology , Georgia Environmental Protection Division
EPA Project Officer: Chung, Serena
Project Period: June 1, 2012 through May 31, 2015 (Extended to May 31, 2016)
Project Period Covered by this Report: June 1, 2012 through May 31,2013
Project Amount: $749,859
RFA: Extreme Event Impacts on Air Quality and Water Quality with a Changing Global Climate (2011) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Water Quality , Climate Change , Air , Water
Atmospheric systems are strongly affected by extreme weather events (EWEs). Previous studies have demonstrated large sensitivities of air quality to the variability in atmospheric systems. The primary objective of this project is to characterize and understand the links between air quality extremes and regional weather/climate systems such that EWE-based air quality projections with explicit uncertainty estimates can be developed.
In the first year of the project, we focused our effort on analyzing historical air quality (ozone and PM2.5) and weather/climate data. An emphasis was placed on understanding the characteristics of extreme ozone and PM2.5 events and how they relate to extreme meteorological events such as heat wave and drought. Indices for heat wave and drought previously developed in climate research were adopted and modified to suit the needs of air quality research. Statistical characterization and correlation analyses were carried out. In order to understand better the regional characteristics of extreme events, cluster analysis was applied to the observed datasets. We also used multivariate empirical orthogonal function analysis to link changes in ozone and PM2.5 with regional climate variability. We have begun to carry out regional and global model simulations and analysis. In regional modeling analysis, we identified extreme ozone episodes to understand the physical, dynamical, and chemical processes contributions and to evaluate the capability of the regional air quality models. We also finished chemistry-climate simulations of ozone and PM2.5 from 1980 to 2013 using the CAM5 model. The modeling results will be analyzed starting later this year.
In the second year of the project, we plan to continue the ongoing statistical data analysis to characterize and understand the links between air quality extremes and regional weather/climate systems. After consolidating research results and further analysis, we expect to write journal papers to publish these results. We will put effort into the analysis of regional and global model simulations. New simulation experiments will be considered in light of the statistical analysis results in order to use the model simulations to examine the relationships we found in the statistical analysis. We will use the model simulations to understand the underlying chemical, physical, and dynamical processes. By evaluating model simulations with the observations, we will also try to understand potential limitations in current regional and global modeling capabilities. Furthermore, we will start exploring statistical and combined statistical and modeling approaches in seasonal/yearly air quality extreme projection.