Grantee Research Project Results
2017 Progress Report: Quantifying Risks from Changing U.S. PM2.5 Distributions Due to Climate Variability and Warming with Large Multi-Model Ensembles and High-Resolution Downscaling
EPA Grant Number: R835878Title: Quantifying Risks from Changing U.S. PM2.5 Distributions Due to Climate Variability and Warming with Large Multi-Model Ensembles and High-Resolution Downscaling
Investigators: Fiore, Arlene M , West, Jason
Institution: Lamont Doherty Earth Observatory of Columbia University , University of North Carolina at Chapel Hill
EPA Project Officer: Chung, Serena
Project Period: January 1, 2016 through December 31, 2018 (Extended to December 31, 2020)
Project Period Covered by this Report: January 1, 2017 through December 31,2017
Project Amount: $788,625
RFA: Particulate Matter and Related Pollutants in a Changing World (2014) RFA Text | Recipients Lists
Research Category: Air , Climate Change
Objective:
The overarching goal of our project is to quantify changes in air pollution meteorology and the resulting fine particulate matter (PM2.5) distributions in U.S. surface air in order to estimate time-evolving air pollution risks over the next 5 decades. We will quantify: (a) changing meteorological hazards conducive to air pollution episodes and their relationships with regional PM2.5; (b) impacts of climate variability versus warming on PM2.5; and (c) the time frame for the emergence of an anthropogenic warming signal. We will examine regional vulnerabilities of PM2.5 to changing meteorological hazards, such as changing anthropogenic emissions and climate feedbacks from “natural” emissions (wildfires, biogenic secondary organic aerosol). For specific U.S. regions, we propose to estimate time-evolving regional PM2.5 risks (statistics relevant for policy and health impacts) from the changes in regional hazards and vulnerabilities (risk = hazard * vulnerability).
Progress Summary:
We are selecting years from the global chemistry-climate model (GFDL CM3) for conducting new simulations to generate boundary conditions used to downscale with WRF-CMAQ. We have successfully downscaled meteorology from the GFDL CM3 with the WRF meteorological model for a first test case. We are working to document our approach for rapid screening of large volumes of data generated by chemistry-climate models to characterize projected changes in the frequency and duration of PM2.5 pollution events. We are examining the role of changing PM2.5 (aerosols) and precursors in contributing to changes in air stagnation events in the GFDL CM3 model, and we continue to evaluate model meteorology and PM2.5 and their connections with observations. With a set of sensitivity simulations for 2004–2012 in the GEOS-Chem model, we examined variability in background ozone, its contribution on days with average versus high observed ozone levels and the sources contributing most on days when the model is biased high.
Future Activities:
We will continue to apply statistical methods to quantify changes in frequency and duration of PM2.5 in multiple chemistry-climate model scenarios. We will continue downscaling selected years from the global models to the United States at high spatial resolution using WRF, SMOKE and CMAQ. We will probe more deeply the relationships between known modes of climate variability (e.g., ENSO) and U.S. PM2.5 levels. We will analyze natural versus anthropogenic (including international pollution) influences on PM2.5 and regional haze over the United States. Wherever possible with available observations, we will continue to evaluate simulated air pollutant levels and their relationships with meteorological and climatic conditions.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
| Other project views: | All 39 publications | 10 publications in selected types | All 10 journal articles |
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Lin M, Horowitz LW, Payton R, Fiore AM, Tonnesen G. US surface ozone trends and extremes from 1980 to 2014: quantifying the roles of rising Asian emissions, domestic controls, wildfires, and climate. Atmospheric Chemistry and Physics 2017;17(4):2943-2970. |
R835878 (2016) R835878 (2017) R835878 (2018) R835878 (2019) R835878 (Final) R835875 (2017) R835875 (2019) |
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Mascioli NR, Previdi M, Fiore AM, Ting M. Timing and seasonality of the United States 'warming hole'. Environmental Research Letters 2017;12(3):034008 (10 pp.). |
R835878 (2016) R835878 (2017) R835878 (2018) R835878 (2019) R835878 (Final) R835206 (Final) |
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Supplemental Keywords:
modeling, climate models, global change, climate variability, risk, health effects, visibility, aerosol, decision-making, sustainable air and water managementRelevant Websites:
http://blog.ldeo.columbia.edu/atmoschem/ Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.