Grantee Research Project Results
2018 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, 2018 through December 31,2018
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 PM2.5 distributions in U.S. surface air, in order to estimate time- evolving air pollution risks over the next five 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 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 completed our selection of eight years from the GFDL CM3 chemistry-climate model for new simulations to generate boundary conditions for downscaling with WRF-CMAQ, and have now begun the downscaling process.
We are placing the meteorology for downscaled years in the context of decadal average conditions in the global model. We examined the influence of climate variability on relationships between ENSO and U.S. PM2.5 determined from short observational records. We are documenting 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. With a set of sensitivity simulations for 2004-2012 in the GEOS-Chem model, we examined variability in background ozone and its contribution on days with average versus high observed ozone levels, and the sources contributing most on days when the model is biased high. We are now extending our analysis of these simulations to regional haze.
Future Activities:
We will continue refining and documenting our methodology for applying statistical methods to quantify changes in frequency and duration of PM2.5 in multiple chemistry- climate model scenarios. We are downscaling selected years from a global model to the U.S.A. at high spatial resolution using WRF, SMOKE, and CMAQ. We will finish documenting our analysis of relationships between ENSO and U.S. PM2.5 levels, noting some challenges to discerning robust relationships in short observational records. We are analyzing natural versus anthropogenic (including international pollution) influences on PM2.5 and regional haze over the
U.S.A. Wherever possible with available observations, we continue to evaluate simulated air pollutant levels and their relationships with meteorological and climatic conditions.
Journal Articles on this Report : 7 Displayed | Download in RIS Format
Other project views: | All 39 publications | 10 publications in selected types | All 10 journal articles |
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Type | Citation | ||
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Guo JJ, Fiore AM, Murray LT, Jaffe DA, Schnell JL, Moore T, Milly GP. Average versus high surface ozone levels over the continental USA:model bias, background influences, and interannual variability. Atmospheric Chemistry and Physics 2018;18:12123-12140. |
R835878 (2018) R835878 (2019) R835878 (Final) |
Exit Exit |
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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) |
Exit Exit Exit |
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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) |
Exit Exit |
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Westervelt DM, Horowitz LW, Naik V, Tai APK, Fiore AM, Mauzerall DL. Quantifying PM2.5-meteorology sensitivities in a global climate model. Atmospheric Environment 2016;142:43-56. |
R835878 (2016) R835878 (2018) R835878 (2019) R835878 (Final) R835206 (Final) |
Exit Exit Exit |
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Zhang Y, Cooper OR, Gaudel A, Thompson AM, Nedelec P, Ogino S-Y, West JJ. Tropospheric ozone change from 1980 to 2010 dominated by equatorward redistribution of emissions. Nature Geoscience 2016;9(12):875-879. |
R835878 (2016) R835878 (2018) R835878 (2019) R835878 (Final) R834285 (Final) |
Exit Exit |
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Chen K, Fiore AM, Chen R, Jiang L, Jones B, Schneider A, Peters A, Bi J, Kan H, Kinney PL. Future ozone-related acute excess mortality under climate and population change scenarios in China:a modeling study. PLoS Medicine 2018;15(7):e1002598 |
R835878 (2018) R835878 (2019) R835878 (Final) R835206 (Final) |
Exit Exit |
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Rieder HE, Fiore AM, Clifton OE, Correa G, Horowitz LW, Naik V. Combining model projections with site-level observations to estimate changes in distributions and seasonality of ozone in surface air over the USA. Atmospheric Environment 2018;193:302-315. |
R835878 (2018) R835878 (2019) R835878 (Final) R835206 (Final) |
Exit Exit |
Supplemental Keywords:
modeling, climate models, global change, climate variability, risk, health effects, visibility, aerosol, decision-making, sustainable air and water managementRelevant Websites:
Fiore Atmospheric Chemistry Group 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.