[6]. Coarse particulate matter air quality in East Asia: implications for fine particulate nitrate

Distributions and trends of coarse PM concentrations over China and South Korea during 2015-2020

Abstract. Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by difference between PM₁₀ and PM_2.5. Coarse PM concentrations in 2015 averaged 52 μg m^-3 in the North China Plain (NCP) and 23 μg m^-3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM₁₀. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21% from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM_2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the KORUS-AQ campaign over the SMA in May-June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations show that decreasing anthropogenic coarse PM over 2015-2019 directly increases PM_2.5 nitrate in summer, offsetting half the effect of other emission controls, while in winter it increases the sensitivity of PM_2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the flat wintertime PM_2.5 nitrate trends observed in the NCP and the SMA despite decreases in nitrogen oxides and ammonia emissions. The continuing decrease of coarse PM from abating fugitive dust pollution will require more stringent nitrogen oxides and ammonia emission controls to successfully decrease PM_2.5 nitrate.

Publication: Zhai et al., ACP, 2023

[5]. Control of particulate nitrate air pollution in China

PM_2.5 and nitrate trends in Beijing

Abstract. The concentration of fine particulate matter (PM_2.5) across China has decreased by 30-50% over 2013-2018 due to stringent emission controls. However, the nitrate component of PM_2.5 has not responded effectively to decreasing emissions of nitrogen oxides and has actually increased during winter haze pollution events in the North China Plain. Here we show that the GEOS-Chem atmospheric chemistry model successfully simulates the nitrate concentrations and trends. We find that winter mean nitrate would have increased over 2013-2018 were it not for favorable meteorology. The principal cause of this nitrate increase is weaker deposition. The fraction of total inorganic nitrate as particulate nitrate instead of gaseous nitric acid over the North China Plain in winter increased from 90% in 2013 to 98% in 2017, as emissions of nitrogen oxides and sulfur dioxide decreased while ammonia emissions remained high. This small increase in the particulate fraction greatly slows down deposition of total inorganic nitrate and hence drives the particulate nitrate increase. Our results suggest that decreasing ammonia emissions would decrease particulate nitrate by driving faster deposition of total inorganic nitrate. Decreasing nitrogen oxide emissions is less effective because it drives faster oxidation of nitrogen oxides and slower deposition of total inorganic nitrate.

Publication: Zhai et al., Nature Geoscience, 2021 (Hot paper - top 0.1% papers in Geoscience!)

[4]. Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM_2.5): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations

Abstract. Geostationary satellite measurements of aerosol optical depth (AOD) over East Asia from the Geostationary Ocean Color Imager (GOCI) and Advanced Himawari Imager (AHI) instruments can augment surface monitoring of fine particulate matter (PM_2.5) air quality, but this requires better understanding of the AOD–PM_2.5 relationship. Here we use the GEOS-Chem chemical transport model to analyze the critical variables determining the AOD–PM_2.5 relationship over East Asia by simulation of observations from satellite, aircraft, and ground-based datasets. This includes the detailed vertical aerosol profiling over South Korea from the KORUS-AQ aircraft campaign (May–June 2016) with concurrent ground-based PM_2.5 composition, PM₁₀, and AERONET AOD measurements. The KORUS-AQ data show that 550 nm AOD is mainly contributed by sulfate–nitrate–ammonium (SNA) and organic aerosols in the planetary boundary layer (PBL), despite large dust concentrations in the free troposphere, reflecting the optically effective size and high hygroscopicity of the PBL aerosols. We updated SNA and organic aerosol size distributions in GEOS-Chem to represent aerosol optical properties over East Asia by using in situ measurements of particle size distributions from KORUS-AQ. We find that SNA and organic aerosols over East Asia have larger size (number median radius of 0.11 μm with geometric standard deviation of 1.4) and 20% larger mass extinction efficiency as compared to aerosols over North America (default setting in GEOS-Chem). Although GEOS-Chem is successful in reproducing the KORUS-AQ vertical profiles of aerosol mass, its ability to link AOD to PM_2.5 is limited by under-accounting of coarse PM and by a large overestimate of nighttime PM_2.5 nitrate. The GOCI–AHI AOD data over East Asia in different seasons show agreement with AERONET AODs and a spatial distribution consistent with surface PM_2.5 network data. The AOD observations over North China show a summer maximum and winter minimum, opposite in phase to surface PM_2.5. This is due to low PBL depths compounded by high residential coal emissions in winter and high relative humidity (RH) in summer. Seasonality of AOD and PM_2.5 over South Korea is much weaker, reflecting weaker variation in PBL depth and lack of residential coal emissions.

Publication: Zhai et al., ACP, 2021.

[3]. PM_2.5 trends in China, 2013-2018: contributions from anthropogenic emissions and meteorology

Observations of PM_2.5 pollution in China from the extensive MEE network established in 2013 show 30%-50% decreases during 2013-2018 driven by emission controls with complicating influences from meteorology. Here we used a stepwise multiple linear regression (MLR) meteorological model to investigate and separate contributions from anthropogenic emissions and meteorology to these 6-year trends. We find that 88% of the PM_2.5 decrease in the original data is attributed to emission controls.

Publication: Zhai et al., ACP, 2019 (Hot paper - top 0.1% in geoscience.).

[2]. Development and application of the adjoint of an atmospheric chemistry model GRAPES-CUACE

We developed the adjoint version of the atmospheric chemical modeling system GRAPES–CUACE (Global-Regional Assimilation and Prediction System coupled with the CMA Unified Atmospheric Chemistry Environment). The GRAPES-CUACE adjoint model was then used in detection of emission sources of PM_2.5 pollution in Beijing.

Publication: Zhai et al., ACP, 2018; An and Zhai et al., GMD, 2016.

[1]. Effective control of PM_2.5 pollution in Beijing: Lagrangian model (FLEXPART) tracking and Eulerian model (CMAQ) assessment     

Earlier and joint emission control schemes over sensitive emission regions identified by FLEXPART can assure larger improvements of overall PM_2.5 air quality.

Publication: Zhai et al., Atmospheric Environment, 2015; Zhai et al., CES (中国环境科学), 2014; Zhai et al., CES (中国环境科学), 2015.