Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
doi:10.5194/acp-2016-954
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
02 Nov 2016
Review status
A revision of this discussion paper was accepted for the journal Atmospheric Chemistry and Physics (ACP) and is expected to appear here in due course.
Strong influence of 2000–2050 climate change on particulate matter in the United States: Results from a new statistical model
Lu Shen1, Loretta J. Mickley1, and Lee T. Murray2 1School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
2Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY 14627, USA
Abstract. We use a statistical model to investigate the effect of 2000–2050 climate change on fine particulate matter (PM2.5) air quality across the contiguous United States. By applying observed relationships of PM2.5 and meteorology to the IPCC Coupled Model Intercomparision Project Phase 5 (CMIP5) archives, we bypass many of the uncertainties inherent in chemistry-climate models. Our approach uses both the relationships between PM2.5 and local meteorology as well as the synoptic circulation patterns, defined as the Singular Value Decomposition (SVD) pattern of the spatial correlations between PM2.5 and meteorological variables in the surrounding region. Using an ensemble of 17 GCMs under the RCP4.5 scenario, we project an increase of ~ 1 μg m−3 in annual mean PM2.5 in the eastern US and a decrease of 0.3–1.2 μg m−3 in the Intermountain West by the 2050s, assuming present-day anthropogenic sources of PM2.5. Mean summertime PM2.5 increases as much as 2–3 μg m−3 in the eastern United States due to faster oxidation rates and greater mass of organic carbon from biogenic emissions. Mean wintertime PM2.5 decreases by 0.3–3 μg m−3 over most regions in United States, likely due to the volatilization of ammonium nitrate. Our approach provides an efficient method to calculate the climate penalty or benefit on air quality across a range of models and scenarios. We find that current atmospheric chemistry models may underestimate or even fail to capture the strongly positive sensitivity of monthly mean PM2.5 to temperature in the eastern United States in summer, and may underestimate future changes in PM2.5 in a warmer climate. In GEOS-Chem, the underestimate in monthly mean PM2.5-temperature relationship in the East in summer is likely caused by overly strong negative sensitivity of monthly mean low cloud fraction to temperature in the assimilated meteorology (~ −0.04 K−1), compared to the weak sensitivity implied by satellite observations (±0.01 K−1). The strong negative dependence of low cloud cover on temperature, in turn, causes the modeled rates of sulfate aqueous oxidation to diminish too rapidly as temperatures rise, leading to the underestimate of sulfate-temperature slopes, especially in the South. Our work underscores the importance of evaluating the sensitivity of PM2.5 to its key controlling meteorological variables in climate-chemistry models on multiple timescales before they are applied to project future air quality.

Citation: Shen, L., Mickley, L. J., and Murray, L. T.: Strong influence of 2000–2050 climate change on particulate matter in the United States: Results from a new statistical model, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2016-954, in review, 2016.
Lu Shen et al.
Lu Shen et al.

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Short summary
We introduce a new method to characterize the influence of atmospheric circulation on surface PM2.5 concentrations. Applying our statistical model to climate projections, we find a strong influence of 2000–2050 climate change on PM2.5 air quality in the United States. We find that current atmospheric chemistry models may underestimate the strong positive sensitivity of PM2.5 to temperature in the eastern United States in summer, and so may underestimate PM2.5 changes in a warmer climate.
We introduce a new method to characterize the influence of atmospheric circulation on surface...
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