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
Institution: Duke University
EPA Project Officer: Leinbach, Alan
Project Period: June 1, 2012 through May 31, 2015 (Extended to May 31, 2016)
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 , Global Climate Change , Water and Watersheds , Climate Change , Air , Water
Atmospheric systems are strongly affected by extreme weather events (EWEs). Previous studies have demonstrated large sensitivities of air quality to EWEs. The overarching goal of this project is to develop EWE-based air quality projections with explicit uncertainty estimates. The specific objectives are to: (l) quantify the occurrence of EWEs and characterize the duration, frequency, magnitude, and spatial-temporal scales of EWEs based on historical meteorological data; (2) quantify the effects of EWEs on air quality using observations in the past decades; (3) investigate the mechanisms through which air quality is affected by EWEs and quantify how future emission changes will affect the sensitivity of air quality to EWEs; ( 4) project the impact of climate change on air quality due to changes in EWEs using an ensemble of climate simulation results; (5) provide EWE-based ensemble seasonal air quality forecasts for Georgia and collaborate with the Georgia Environmental Protection Division (EPD) to explore effective air quality management practices using mid- to long-term air quality forecasts. The key hypotheses to be tested include: (l) the impacts of EWEs vary significantly by region, season, and type; (2) EWE episodes provide testing cases that will target different aspects of CMAQ model formulations and can be used to improve the CMAQ model; (3) CMAQ model simulations will in turn facilitate the mechanistic understanding of the impacts of EWEs on air quality derived from the multivariate canonical correlation analysis; (4) the EWE-based air quality forecasts can be effectively used with ensemble climate or seasonal forecasts to provide mid- to long-term air quality projections and to explicitly estimate uncertainties due to the EWE prediction uncertainties.
We develop a comprehensive approach to understand how EWEs affect air quality in the United States, including historical analysis of over 30 years of high resolution meteorological reanalysis data and surface ozone observations and over 10 years of PM2.5 mass and speciation measurements, and using a combination of multivariate canonical correlation analysis and an ensemble CMAQ simulations of EWE episodes. The CMAQ simulations will be applied to examine the sensitivity of EWE air quality impacts to emission changes. We will provide climate projections of air quality based the IPCC AR5/CMIP5 multi-model high-resolution ensemble and seasonal forecast for air quality in Georgia based on the NCEP CFSv2 40-member ensemble.
This research will improve the fundamental understanding of EWEs and their impacts on air quality. The ensemble climate projections for air quality will link air quality projections directly to climate model outputs used by the IPCC assessment report. Furthermore, we will provide explicit uncertainty estimates for the projections such that stakeholders can carry out risk-benefit analysis. We will also provide seasonal air quality forecast products and know-how to Georgia EPD such that regional state groups can have the capability of producing and utilizing mid- to longer-term air quality forecasts in their planning and management activities.
Publications and Presentations:Publications have been submitted on this project: View all 5 publications for this project
Supplemental Keywords:air quality projection, climate change, uncertainty
Progress and Final Reports:2012 Progress Report
2013 Progress Report
2014 Progress Report