An explainable integrated optimization methodology for source apportionment of ambient particulate matter components.

Source apportionment of fine particulate matter (PM2.5) components is crucial for air pollution control. Prediction accuracies by the chemical transport model (CTM) significantly affect source apportionment results. Many efforts have been made to improve source apportionment results based on the CTM using mathematical algorithms, but the reasons for uncertainties in source apportionment results are less concerned. Here, an integrated optimization methodology is developed to quantify deviations from emission inventory and chemical mechanism in the model for improving prediction and source apportionment accuracies. Emission deviations of primary aerosols and gaseous pollutants are firstly calculated by an optimization algorithm with observation and receptor model constraints. Emission inventory is then adjusted for a new CTM simulation. Deviations from chemical mechanism for secondary conversions are evaluated by biases between observations and new predictions. Source apportionment results are adjusted according to both emission and chemical mechanism deviations. A winter month in 2016 at the Qingpu supersite in eastern China is selected as a case study. Results show that our integrated optimization methodology can successfully adjust emissions to pull original predictions towards observations. Total deviations of emissions for elemental carbon, organic carbon, primary sulfate, primary nitrate, primary ammonium, sulfur dioxide (SO2), nitrogen oxides (NOx) and ammonia (NH3) are estimated +59.6%, +95.9%, +72.9%, +82.2%, +75.9%, -6.4%, +67.6% and -17.6%, respectively. Also, major directions of deviations from chemical mechanisms can be captured. Deviations from SO2 to secondary sulfate, nitrogen dioxide (NO2) to secondary nitrate and NH3 to secondary ammonium conversions are estimated -77.3%, +27.1% and -38.8%, respectively. Consequently, source apportionment results are significantly improved. This developed methodology provides an efficient way to quantify deviations from emissions and chemical mechanisms to improve source apportionment for air pollution management.

Comprehensive Insights Into O3 Changes During the COVID-19 From O3 Formation Regime and Atmospheric Oxidation Capacity.

Economic activities and the associated emissions have significantly declined during the 2019 novel coronavirus (COVID-19) pandemic, which has created a natural experiment to assess the impact of the emitted precursor control policy on ozone (O3) pollution. In this study, we utilized comprehensive satellite, ground-level observations, and source-oriented chemical transport modeling to investigate the O3 variations during the COVID-19 pandemic in China. Here, we found that the significant elevated O3 in the North China Plain (40%) and Yangtze River Delta (35%) were mainly attributed to the enhanced atmospheric oxidation capacity (AOC) in these regions, associated with the meteorology and emission reduction during lockdown. Besides, O3 formation regimes shifted from VOC-limited regimes to NOx-limited and transition regimes with the decline of NOx during lockdown. We suggest that future O3 control policies should comprehensively consider the effects of AOC on the O3 elevation and coordinated regulations of the O3 precursor emissions.

The aggravated short-term PM2.5-related health risk due to atmospheric transport in the Yangtze River Delta.

Severe fine particulate matter (PM2.5) pollution and the associated health risks remain pressing issues in the Yangtze River Delta (YRD), although significant efforts have been made locally, such as the Clean Air Action since 2013. Regional transport is an important contributor to high PM2.5 levels during haze episodes in the YRD, but its impact on human health is rarely analyzed. In this study, we evaluate the short-term PM2.5-related health risks and associated economic losses due to different source regions by estimating daily mortality based on model results in the YRD. The results show that regional transport induces significant health risks in the YRD during haze days, contributing over 60% of daily premature mortality in Shanghai and Nanjing (major cities in the YRD). Moreover, in Hangzhou and Jiaxing, regional transport's contribution can be as high as 70%. The total daily mean economic loss in the YRD is estimated as 526.8 million Chinese Yuan (approximately 81.4 million U.S. dollar) in winter of 2015 and 2016, accounting for 1.4% of the daily averaged gross domestic product (GDP) of the YRD. Emission control (in accordance with the 13th Five-year Energy Conservation and Emission Reduction Plan) is an effective way to reduce health risks in the YRD, reducing premature deaths during haze days by 12-33%. More stringent emission control measures are suggested for further reduce PM2.5-related health risks.

Enhanced atmospheric oxidation capacity and associated ozone increases during COVID-19 lockdown in the Yangtze River Delta.

Aggressive air pollution control in China since 2013 has achieved sharp decreases in fine particulate matter (PM2.5), along with increased ozone (O3) concentrations. Due to the pandemic of coronavirus disease 2019 (COVID-19), China imposed nationwide restriction, leading to large reductions in economic activities and associated emissions. In particular, large decreases were found in nitrogen oxides (NOx) emissions (>50%) from transportation. However, O3 increased in the Yangtze River Delta (YRD), which cannot be fully explained by changes in NOx and volatile organic compound (VOCs) emissions. In this study, the Community Multi-scale Air Quality model was used to investigate O3 increase in the YRD. Our results show a significant increase of atmospheric oxidation capacity (AOC) indicated by enhanced oxidants levels (up to +25%) especially in southern Jiangsu, Shanghai and northern Zhejiang, inducing the elevated O3 during lockdown. Moreover, net P(HOx) of 0.4 to 1.6 ppb h-1 during lockdown (Case 2) was larger than the case without lockdown (Case 1), mainly resulting in the enhanced AOC and higher O3 production rate (+12%). This comprehensive analysis improves our understanding on AOC and associated O3 formation, which helps to design effective strategies to control O3.

Responses of decline in air pollution and recovery associated with COVID-19 lockdown in the Pearl River Delta.

The Guangdong government implemented lockdown measures on January 23, 2020, to ease the spread of the coronavirus disease 2019 (COVID-19). These measures prohibit a series of human activities and lead to a great reduction in anthropogenic emissions. Starting on February 20, all companies resumed work and production, and emissions gradually recovered. To investigate the response of air pollutants in the Pearl River Delta (PRD) to the emission reduction and recovery related to COVID-19 lockdown, we used the Community Multi-scale Air Quality (CMAQ) model to estimate the changes in air pollutants, including three periods: Period I (January 10 to January 22, 2020), Period II (January 23 to February 19, 2020), Period III (February 20 to March 9, 2020). During Period II, under the concurrent influence of emissions and meteorology, air quality improved significantly with PM2.5, NO2, and SO2 decreased by 52%, 67%, and 25%, respectively. O3 had no obvious changes in most cities, which mainly due to the synergetic effects of emissions and meteorology. In Period III, with the recovery of emissions and the changes in meteorology, the increase of secondary components was faster than that of primary PM2.5 (PPM), which indicated that changes in PPM concentration were more sensitive to emissions reduction. O3 concentration increased as emission and temperature rising. Our findings elucidate that more effective emission control strategies should be implemented in PRD to alleviate the increasingly serious pollution situation.

Insights into source origins and formation mechanisms of nitrate during winter haze episodes in the Yangtze River Delta.

Nitrate became the most significant component of secondary inorganic aerosols (SNA, the sum of sulfate, nitrate and ammonium ions) as the emissions of sulfur dioxide (SO2) have been greatly reduced in China in recent years. In the Yangtze River Delta (YRD), nitrate could contribute 56% of SNA and 34% of total PM2.5 during haze episodes. In this study, a modified Community Multiscale Air Quality (CMAQ) model was used to provide a comprehensive understanding of nitrate source and formation under severe pollution during winter 2015 and 2016. Three haze episodes (HEP1, HEP2 and HEP3) and one clean episode (CEP) were selected to investigate the emission sector and regional contributions to nitrate at six environmental monitoring sites in the YRD. Source apportionment results showed that industry (35%), transportation (32%) and power (28%) sectors were the important sources of nitrate during haze episodes. Regional transport (60-98%) was responsible for the high nitrate concentrations in the YRD. During haze episodes, the high ozone production (PO3) rate (up to 700 ppb/h) and hydroxyl radicals (OH) removal rate (up to 9 ppb/h) were observed in the daytime indicating the important atmospheric oxidation capacity in the YRD. Also, the nitrogen oxidation ratio (NOR) analysis elucidated that daytime photochemistry played an important role in nitrate formation and the heterogeneous chemistry enhanced the high nitrate at night. Results from emission scenario analysis demonstrated that averaged nitrate concentration in Shanghai decreased by 18% during haze episodes under emission reductions of 20% NOx, NH3 and VOC in the YRD, and Shandong, Shanxi, Henan and Hebei provinces. Emission reduction on the regional scale (one city and its surrounding areas) is an efficient strategy to reduce nitrate concentration in the YRD.

Source apportionment and regional transport of anthropogenic secondary organic aerosol during winter pollution periods in the Yangtze River Delta, China.

Since the concentrations of primary particles and secondary inorganic aerosol components have been reduced significantly due to stringent emission controls, quantifying the source contributions and regional transport of secondary organic aerosol (SOA) is critical to further improve air quality in eastern China. In this study, the Community Multiscale Air Quality (CMAQ) model coupled with the updated SAPRC-11 photochemical mechanism and a revised SOA module was applied to investigate the emission sector and regional contributions to SOA in winter 2015 (January 5-26, 2015) and 2016 (December 20, 2015-January 20, 2016) in the Yangtze River Delta (YRD). The model is generally capable of reproducing the observed SOA concentrations at the Qingpu Supersite in Shanghai. The observed and predicted SOA concentrations are 6.4 µg/m3 and 6.9 µg/m3 in winter 2015, and 5.7 µg/m3 and 9.6 µg/m3 in winter 2016. The mean fraction bias (MFB) of the hourly SOA predictions is 0.22 and 0.32, respectively. High SOA concentrations in the wintertime of YRD are mainly due to aromatic compounds and dicarbonyls (glyoxal and methylglyoxal), which, on average, account for 43% and 53% of total SOA, respectively. The average contributions of industrial, residential, and transportation sectors in the YRD region during the entire simulation periods are 61%, 22%, and 17%, respectively. At the Qingpu Supersite in Shanghai, the industrial sector contributes to as much as 65% of total SOA in the heavy pollution episode of 2016. The contributions from transportation and residential sectors are 16% and 17%, respectively, during the same episode. The industry emissions from the Jiangsu, Zhejiang, and Shanghai are major contributors to the SOA at the Qingpu supersite during the heavy-polluted episodes, accounting for 31%, 19%, and 14% of the total predicted SOA. This study represents the first detailed regional modeling study of source region contributions to SOA in the YRD region and the detailed analyses of SOA in two winters months complement the previous SOA source apportionment studies focusing on seasonal average contributions.