Influence of 2000–2050 climate change on particulate matter in the United States: results from a new statistical model

Abstract

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 some 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 19 global climate models (GCMs) under the RCP4.5 scenario, we project an increase of 0.4–1.4 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 aerosols from biogenic emissions. Mean wintertime PM2. 5 decreases by 0.3–3 µg m−3 over most regions in the United States, likely due to the volatilization of ammonium nitrate. Our approach provides an efficient method to calculate the potential climate penalty 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 they 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.

Synoptic meteorological modes of variability for fine particulate matter (PM<sub>2.5</sub>) air quality in major metropolitan regions of China

“…Tai et al (2012a) showed that cold fronts associated with midlatitude cyclone passages and maritime inflows were the major ventilation mechanisms of PM 2.5 in the US. Shen et al (2017) further showed that variability of PM 2.5 over the US explained by both local meteorology and synoptic factors (43%) are in average about 10% higher than solely using local 20 meteorology (34%). In Asia, Chen et al (2008) demonstrated that synoptic high-pressure systems in northern Mongolia associated with cold fronts facilitate the dispersion of air pollutants over northern China, whereas a surface high centered on BTH favors accumulation.…”

“…We finally construct a statistical model using annual median synoptic frequency and annual mean local meteorology to project 2000-2050 PM 2.5 changes, given present-day and future climate simulations by an ensemble of climate 10 models. This study represents an advancement over that of Tai et al (2012a, b) in terms of methodology by considering the joint effects of synoptic frequency and local meteorology, and is on a par with the work of Shen et al (2017), who focused on the US instead. Our work represents the first attempt to apply these methods to China air quality in an effort to derive a statistical projection of future PM 2.5 concentrations based on historical PM 2.5 -meteorology relationships.…”

“…For example, Zhang et al (2016) showed using GEOS-Chem that cold surge occurrences over northern China attribute to about half of the variability of total PM 2.5 . Several modeling 10 studies have examined the effects of historical (Fu et al, 2016) and future (Jiang et al, 2013) changes in emissions and climate (i.e., long-term changes in weather statistics) on PM 2.5 air quality in East Asia, but large uncertainty remains due to the complex PM 2.5 -meteorology interactions (Jiang et al, 2013;Shen et al, 2017;Tai et al, 2012b). Such poor understanding stems mainly from the diverse sensitivities of different PM 2.5 chemical components to meteorological changes, and from the strong coupling of PM 2.…”

“…Higher temperature also increases the emissions of biogenic VOCsfrom vegetation, especially in southern China where high-emitting broadleaf evergreen trees are prevalent (Ding et al, 2012;Zhang and Cao., 2015). Higher temperature favors the volatilization of nitrate, ammonium and semivolatile organics by shifting the gas-aerosol phase equilibria toward the gas phase (Jiang et al, 2013;Shen et al, 2017), thereby decreasing these components. Depending on the region, an increase in relative humidity (RH) may enhance the production of hydroxyl (OH) radical and hydrogen 5 peroxide (H 2 O 2 ), which promotes SO 2 oxidization and increases the uptake of semivolatile components including nitrate and organics (Seinfeld and Pandis, 2016).…”

“…Different classification schemes for a wide range of synoptic circulation patterns have been researched extensively (Huth et al, 2008), and used worldwide to evaluate 15 pollution-meteorology interactions (e.g., McGregor and Bamzelis, 1995;Shahgedanva et al, 1998;Shen et al, 2017;Tai et al, 2012a;. Tai et al (2012a) showed that cold fronts associated with midlatitude cyclone passages and maritime inflows were the major ventilation mechanisms of PM 2.5 in the US.…”