Grantee Research Project Results
Final 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 Amount: $788,625
RFA: Particulate Matter and Related Pollutants in a Changing World (2014) RFA Text | Recipients Lists
Research Category: Air , Climate Change
Objective:
Our overarching goal is to advance understanding of how climate change resulting from rising greenhouse gases will alter risks from PM2.5 and other air pollutants in surface air over the United States (US) in the coming decades. A novel aspect of our analysis is to develop methods that combine the statistical power of global chemistry-climate model ensemble simulations with fine spatial scale dynamical downscaling to estimate time-evolving PM2.5 distributions over different US regions. We quantify changes in meteorology (hazards) conducive to air pollution episodes, and the impacts of climate variability versus warming on US PM2.5 (and ozone). We also consider differences in regional vulnerabilities of air pollution to changing meteorological hazards, which include changing anthropogenic emissions and climate feedbacks from “natural” emissions. From the air pollution distributions we generate over specific US regions, risk-based metrics relevant to public health and welfare (e.g., population-weighted exposure, visibility) are being constructed that reflect the effects of climate change amidst natural (internal) variability.
Conclusions:
We are conducting downscaling of air pollutant concentrations with the WRF and CMAQ models from the global GFDL CM3 chemistry-climate model to the continental US. Doing so, we aim to construct probability distributions of future PM2.5 and of the impact of climate change on PM2.5 in individual grid cells that reflect both the fine spatial resolution (12 km) of the regional model and the natural, internally arising, climate variability from the global model. We have completed meteorological downscaling with the WRF regional meteorological model of eight selected years, and continue to work to downscale air quality using CMAQ. The eight years include four in the present day (2006-2020) and four at mid-Century (2040-2059) under RCP8.5 climate change with air pollutant emissions held constant at current (2005) levels. We are placing the meteorology and PM2.5 for downscaled years in the context of decadal average conditions with a 3-member ensemble of the global GFDL CM3 model (with members differing only in initial conditions) as well as the NCAR CESM model, as the 12-member NCAR ensemble provides a broader context. Knowing where the selected years lie in the full distribution of variability from the global model, we then construct probability distributions of PM2.5 concentrations and of the impacts of climate change on PM2.5 in individual grid cells from the downscaled model. In addition to estimating the effects of climate change on air pollutant concentrations, these results will be extended to estimate probability distributions of future climate change on health impacts and visibility.
We developed and automated an approach using statistical methods (empirical orthogonal function analysis) to quantify changes in the frequency and duration of regional-scale PM2.5 pollution and heat events, using GFDL-CM3 and NCAR-CESM1 initial condition ensemble simulations for the 21st century climate change scenario noted above, in which air pollutant emissions are held at present-day levels. We label high pollution events as falling in the upper quartile defined over the full 2006-2100 simulation. Over the Northeast US, both models robustly show an increase in the frequency of regional-scale high-PM2.5 events that last at least five consecutive days. Our approach should enable future rapid screening of large volumes of data generated by chemistry-climate model ensembles.
With a systematic analysis of temperature trends over the eastern US by season, region, and time period, we found a partial role for anthropogenic aerosols in contributing to the so-called ‘US warming hole’ over the northeastern and southern US in summer (Mascioli et al., 2017). We also found a role for changing PM2.5 (aerosols) and precursors in contributing to changes in air stagnation events in the GFDL CM3 model (Mascioli, 2018). We showed that climate variability complicates unambiguous detection of quantitative relationships between ENSO and PM2.5 (dust) over the South-Central US previously determined from short (1999-2015) observational records (Previdi and Fiore, 2019). We showed that the GFDL-CM3 model generally represents observed eastern U.S. temperature-PM2.5 and wind-PM2.5 relationships, and that these, along with precipitation, are key meteorological drivers of future PM2.5 distributions (Westervelt et al., 2016).
In addition to our work on particulate matter, we showed that a global equatorward shift of ozone precursor emissions dominated the growth in tropospheric ozone from 1980 to 2010, more important than either the global growth in emissions or the growth in methane (Zhang et al., 2016; 2021). We quantified variability in background ozone over the US, and the sources contributing to surface ozone on days with average versus high observed levels, and on days when the model is biased high (Guo et al., 2018) as well as the factors driving observed surface ozone trends (Lin et al., 2017). We used similar approaches to investigate anthropogenic versus natural sources of regional haze. Key findings include that climate warming can increase weather-sensitive emissions that contribute to background levels of smog and haze. We also developed statistical downscaling and bias correction approaches by combining simulated ozone levels under 21st century emission scenarios with observed ozone levels (Chen et al., 2018; Rieder et al., 2018).
Journal Articles on this Report : 10 Displayed | Download in RIS Format
Other project views: | All 39 publications | 10 publications in selected types | All 10 journal articles |
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Fiore AM, Milly GP, Hancock SE, Quiñones L, Bowden JH, Helstrom E, Lamarque J-F, Schnell J, West JJ, Xu Y. Characterizing changes in eastern U.S. pollution events in a warming world. Journal of Geophysical Research:Atmospheres 2022;127:e2021JD035985. doi:10.1029/2021JD035985. |
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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. |
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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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Previdi M, Fiore AM. The Importance of Sampling Variability in Assessments of ENSO‐PM2. 5 Relationships:A Case Study for the South Central United States. Geophysical Research Letters 2019;46(12):6878-84. |
R835878 (2019) R835878 (Final) |
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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) |
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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) |
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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) |
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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) |
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Zhang Y, West JJ, Emmons LK, Flemming J, Jonson JE, Lund MT, Sekiya T, Sudo K, Gaudel A, Chang KL, Nédélec P. Contributions of world regions to the global tropospheric ozone burden change from 1980 to 2010. Geophysical Research Letters 2021 ;48(1):e2020GL089184. |
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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:
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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.
Project Research Results
- 2019 Progress Report
- 2018 Progress Report
- 2017 Progress Report
- 2016 Progress Report
- Original Abstract
10 journal articles for this project