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Li Y, Wang T, Wang Q, Li M, Qu Y, Wu H, Fan J, Shao M, Xie M. Deciphering the seasonal dynamics of multifaceted aerosol-ozone interplay: Implications for air quality management in Eastern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174327. [PMID: 38955271 DOI: 10.1016/j.scitotenv.2024.174327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 06/14/2024] [Accepted: 06/25/2024] [Indexed: 07/04/2024]
Abstract
We employed an enhanced WRF-Chem to investigate the discrete mechanisms of aerosol-radiation-feedback (ARF), extinction-photochemistry (AEP), and heterogeneous-reactions (AHR) across different seasons in eastern China, aiming to assess the synergistic effects arising from the simultaneous operation of multiple processes on O3 and PM2.5. Our findings demonstrated that ARF fostered the accumulation of pollutants and moisture, initiating two distinct feedback mechanisms concerning O3. The elevation in the NO/NO2 ratio amplified O3 consumption. Increased near-surface moisture diminished upper-level cloud formation, thereby enhancing photolysis rates and O3 photochemical production. The pronounced impact of heightened NO/NO2 on O3 led to a decrease of 0.1-2.7 ppb. When decoupled from ARF, AEP led to a more significant reduction in photolysis rates, resulting in declines in both O3 and PM2.5, except for an anomalous increase observed in summer, with O3 increasing by 1.6 ppb and PM2.5 by 2.5 μg m-3. The heterogeneous absorption of hydroxides in spring, autumn, and winter predominantly governed the AHR-induced variation of O3, leading to a decrease in O3 by 0.7-1 ppb. Conversely, O3 variations in summer were primarily dictated by O3-sensitive chemistry, with heterogeneous absorption of NOy catalyzing a decrease of 2.4 ppb in O3. Furthermore, AHR accentuated PM2.5 by facilitating the formation of fine sulfates and ammonium while impeding nitrate formation. In summer, the collective impact of ARF, AEP, and AHR (ALL) led to a substantial reduction of 6.2 ppb in O3, alleviating the secondary oxidation of PM2.5 and leading to a decrease of 0.3 μg m-3 in PM2.5. Conversely, albeit aerosol substantially depleted O3 by 0.4-4 ppb through their interactions except for summer, aerosol feedback on PM2.5 was more pronounced, resulting in a significant increase of 1.7-6.1 μg m-3 in PM2.5. Our study underscored the seasonal disparities in the ramifications of multifaceted aerosol-ozone interplay on air quality.
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Affiliation(s)
- Yasong Li
- School of the Environment, Nanjing University, Nanjing 210023, China
| | - Tijian Wang
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
| | - Qin'geng Wang
- School of the Environment, Nanjing University, Nanjing 210023, China
| | - Mengmeng Li
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Yawei Qu
- College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing 211112, China
| | - Hao Wu
- Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing, China
| | - Jiachen Fan
- School of the Environment, Nanjing University, Nanjing 210023, China
| | - Min Shao
- School of Environment, Nanjing Normal University, Nanjing 210046, China
| | - Min Xie
- School of Environment, Nanjing Normal University, Nanjing 210046, China
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Cui Y, Hua J, He Q, Guo L, Wang Y, Wang X. Comparison of three source apportionment methods based on observed and initial HCHO in Taiyuan, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171828. [PMID: 38521281 DOI: 10.1016/j.scitotenv.2024.171828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 02/11/2024] [Accepted: 03/18/2024] [Indexed: 03/25/2024]
Abstract
Identifying the sources of formaldehyde (HCHO) is key to reducing the pollution of HCHO and ozone (O3) on the ground level. Using the same datasets applied to the positive matrix factorization (PMF) model by (Hua et al., 2023), the initial concentrations of HCHO were estimated using the photochemical age and the sources of observed and initial HCHO were apportioned based on multiple linear regression (MLR) and photochemical age-based parameterization (PCAP) methods. These results suggest that the source of the initial HCHO can better reflect its contribution. The secondary formation contributed to 49.3-69.1 % of initial HCHO at four sites in Taiyuan based on MLR, which was higher (7.4-36.2 %) than the contributions of secondary formation from observed HCHO. The HCHO was mainly affected by anthropogenic secondary (10.8-34.4 %) and background sources (17.4-78.7 %) based on the PCAP method. We compared the results of the HCHO sources from the MLR, PCAP, and PMF models under photochemical loss. There was good agreement among the emission ratios of acetylene-based HCHO obtained by the different methods at the four sites. The correlation analysis of different source apportionment methods illustrated that primary emissions from the PCAP and the MLR model had the greatest correlation (0.22-0.60). Secondary formations from the PMF and MLR models showed good correlations at all four sites, with R values ranging from 0.42 to 0.83. The HCHO peak of diurnal variation simulated by MLR appeared late compared to the other methods, and the difference in daily variation of HCHO from the PMF model was significantly higher than that of PCAP and MLR. The overlapping conclusions of different source apportionment methods should be considered and used to guide efforts to improve air quality.
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Affiliation(s)
- Yang Cui
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China.
| | - Jingya Hua
- Department of Atmospheric Science, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Qiusheng He
- Department of Materials Environmental Engineering, Shanxi Polytechnic College, Taiyuan 237016, China.
| | - Lili Guo
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
| | - Yonghong Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
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He L, Duan Y, Zhang Y, Yu Q, Huo J, Chen J, Cui H, Li Y, Ma W. Effects of VOC emissions from chemical industrial parks on regional O 3-PM 2.5 compound pollution in the Yangtze River Delta. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167503. [PMID: 37788769 DOI: 10.1016/j.scitotenv.2023.167503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 09/28/2023] [Accepted: 09/28/2023] [Indexed: 10/05/2023]
Abstract
Ozone (O3) and fine particulate matter (PM2.5) compound pollution has emerged as a primary form of air pollution in Chinese urban. Volatile organic compounds (VOCs), as common precursors of O3 and PM2.5, play a significant role in air pollution control. Chemical industrial parks (CIPs) are crucial emission sources of VOCs and have garnered significant attention. This study focused on 142 CIPs located in the Yangtze River Delta (YRD) to investigate the characteristics of VOC emissions from CIPs and their impact on O3-PM2.5 compound pollution, considering the enhanced atmospheric oxidation capacity (AOC). The Comprehensive Air Quality Model with Extensions (CAMx) model was employed for this analysis. The results show that VOC emissions from CIPs contributed significantly to regional O3 and secondary organic aerosol (SOA), accounting for 17.1 % and 18.18 % of the anthropogenic sources, respectively. Regions exhibiting the highest contributions were located along the Hangzhou Bay. Compared with 2014, an elevation in the contribution of VOC emissions from CIPs to the annual average concentrations of MDA8 O3 and SOA in the YRD in 2017 by 0.069 μg/m3 and 0.007 μg/m3, respectively. During episodes of compound pollution, the concentration of atmospheric oxidant (HOx + NO3) was 28.65 % higher than during clean days, and significant positive correlations were observed between hydrogen oxygen radicals (HOx) and maximum daily 8-h average (MDA8 O3) as well as between HOx and SOA, exhibiting correlation coefficients of 0.86 and 0.48, respectively. Effective control measures for VOC emissions, particularly from the pharmaceutical and petrochemical industry parks located along Hangzhou Bay, are essential in curtailing the production rate of HOx and in regulating AOC levels in the YRD. Maintaining the daily average HOx concentration below 10 ppt would be a valuable strategy in achieving coordinated control of O3 and SOA, thus aiding in the alleviation of O3-PM2.5 compound pollution in the YRD.
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Affiliation(s)
- Li He
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Yusen Duan
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Yan Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China; Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China; Shanghai Institute of Eco-Chongming (SIEC), Shanghai 200062, China
| | - Qi Yu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Juntao Huo
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Jia Chen
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Huxiong Cui
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Yuewu Li
- Shanghai Environmental Monitoring Center, Shanghai 200235, China
| | - Weichun Ma
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China; Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China; Shanghai Institute of Eco-Chongming (SIEC), Shanghai 200062, China.
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Wang X, Zhang S, Yan H, Ma Z, Zhang Y, Luo H, Yang X. Association of exposure to ozone and fine particulate matter with ovarian reserve among women with infertility. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 340:122845. [PMID: 37926414 DOI: 10.1016/j.envpol.2023.122845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 10/28/2023] [Accepted: 10/30/2023] [Indexed: 11/07/2023]
Abstract
Evidence linking diminished ovarian reserve, a significant cause of female infertility, and exposure to particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5) or O3 exposure remains a critical knowledge gap in female fertility. This study investigated the association between ambient PM2.5, O3 pollution, and anti-Müllerian hormone (AMH), a sensitive marker of ovarian reserve, in reproductive-aged Chinese women. We enrolled 2212 women with spontaneous menstrual cycles who underwent AMH measurements at a reproductive medicine center between 2018 and 2021. The daily mean concentrations of outdoor PM2.5 and O3 were estimated using a validated spatiotemporal model, followed by matching the participants' residential addresses. Three exposure periods were designed according to AMH expression patterns during follicle development. A generalized linear model was used to investigate changes in AMH associated with air pollution. The results showed a mean AMH level of 3.47 ± 2.61 ng/mL. During the six months from primary to early antral follicle stage (Period 1), each 10 μg/m3 increase in PM2.5 and O3 exposure was associated with AMH changes of -0.21 (95% confidence interval [CI]: -0.48, 0.06) ng/mL and -0.31 (95% CI: -0.50, -0.12) ng/mL, respectively. Further analyses indicated that the reduced ovarian reserve measured by AMH level was only significantly associated with PM2.5 exposure during follicle development from the primary to preantral follicle stage (Period 2) but was significantly associated with O3 exposure during Periods 1, 2, and 3. These observations were robust in the dual-pollutant model considering co-exposure to PM2.5 and O3. The results indicated an inverse association between ovarian reserve and ambient O3 exposure and suggested distinct susceptibility windows for O3 and PM2.5 for reduced ovarian reserve. These findings highlight the need to control ambient air pollution to reduce invisible risks to women's fertility, especially at high O3 concentrations.
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Affiliation(s)
- Xinyan Wang
- Center for Reproductive Medicine, Tianjin Central Hospital of Obstetrics and Gynecology, Maternal Hospital of Nankai University, Tianjin Key Laboratory of Human Development and Reproductive Regulation, No. 156 Nankai Third Road, Tianjin 300100, China
| | - Shuai Zhang
- Center for Reproductive Medicine, Tianjin Central Hospital of Obstetrics and Gynecology, Maternal Hospital of Nankai University, Tianjin Key Laboratory of Human Development and Reproductive Regulation, No. 156 Nankai Third Road, Tianjin 300100, China
| | - Huihui Yan
- Center for Reproductive Medicine, Tianjin Central Hospital of Obstetrics and Gynecology, Maternal Hospital of Nankai University, Tianjin Key Laboratory of Human Development and Reproductive Regulation, No. 156 Nankai Third Road, Tianjin 300100, China
| | - Zhao Ma
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China
| | - Yunshan Zhang
- Center for Reproductive Medicine, Tianjin Central Hospital of Obstetrics and Gynecology, Maternal Hospital of Nankai University, Tianjin Key Laboratory of Human Development and Reproductive Regulation, No. 156 Nankai Third Road, Tianjin 300100, China
| | - Haining Luo
- Center for Reproductive Medicine, Tianjin Central Hospital of Obstetrics and Gynecology, Maternal Hospital of Nankai University, Tianjin Key Laboratory of Human Development and Reproductive Regulation, No. 156 Nankai Third Road, Tianjin 300100, China.
| | - Xueli Yang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin 300070, China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, China
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Zhang Q, Wang Y, Liu M, Zheng M, Yuan L, Liu J, Tao S, Wang X. Wintertime Formation of Large Sulfate Particles in China and Implications for Human Health. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:20010-20023. [PMID: 37909663 DOI: 10.1021/acs.est.3c05645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2023]
Abstract
Outdoor air pollution causes millions of premature deaths annually worldwide. Sulfate is a major component of particulate pollution. Winter sulfate observations in China show both high concentrations and an accumulation mode with a modal size >1 μm. However, we find that this observed size distribution cannot be simulated using classical gaseous and aqueous phase formation (CSF) or proposed aerosol-processing formation (APF) mechanisms. Specifically, the CSF simulation underestimates sulfate concentrations by 76% over megacities in China and predicts particle size distributions with a modal size of ∼0.35 μm, significantly smaller than observations. Although incorporating the APF mechanism in the atmospheric chemical model notably improves sulfate concentration simulation with reasonable parameters, the simulated sulfate particle size distribution remains similar to that using the CSF mechanism. We further conduct theoretical analyses and show that particles with diameters <0.3 μm grow rapidly (2-3 s) to 1 μm through the condensation of sulfuric acid in fresh high-temperature exhaust plumes, referred to as in-source formation (ISF). An ISF sulfate source equivalent to 15% of sulfur emissions from fossil fuel combustion largely explains both observed size distributions and mass concentrations of sulfate particles. The findings imply that ISF is a major source of wintertime micron-sized sulfate in China and underscore the importance of considering the size distribution of aerosols for accurately assessing the impacts of inorganic aerosols on radiative forcing and human health.
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Affiliation(s)
- Qianru Zhang
- Ministry of Education Laboratory of Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Yuhang Wang
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Maodian Liu
- Ministry of Education Laboratory of Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
- School of the Environment, Yale University, New Haven, Connecticut 06511, United States
| | - Mingming Zheng
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- School of Chemical and Environmental Engineering, Wuhan Polytechnic University, Wuhan 430023, China
| | - Lianxin Yuan
- Hubei Environmental Monitoring Center, Wuhan 430072, China
| | - Junfeng Liu
- Ministry of Education Laboratory of Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Shu Tao
- Ministry of Education Laboratory of Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Xuejun Wang
- Ministry of Education Laboratory of Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
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Van Do T, Vuong QT, Tong A, Song CK, Choi SD. Roles of ambient temperature and relative humidity on the relationship between fine particulate matter and gaseous pollutants in the largest industrial city of Ulsan, South Korea. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:96926-96937. [PMID: 37584799 DOI: 10.1007/s11356-023-29036-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 07/25/2023] [Indexed: 08/17/2023]
Abstract
Although meteorological conditions play a significant role in air pollution, research on their effects on the relationship between air pollutants is limited. In this study, trends of six criteria air pollutants were investigated from 15 air quality monitoring stations (AQMSs) in Ulsan, a multi-industrial city in South Korea, during 2015-2019. Unlike CO and O3, SO2, NO2, PM10, and PM2.5 showed statistically significant decreasing trends over the period. The companion relationship between PM2.5 and gaseous pollutants was evaluated by their correlations [R (PM2.5-GPs)]. R (PM2.5-NO2) was relatively high at almost all AQMSs, whereas high R (PM2.5-SO2) was observed near the petrochemical industrial complex, suggesting a great influence of local emissions (vehicles and industries). R (PM2.5-CO) and the standardized regression coefficients of CO obtained from the multiple linear regression model were the highest, indicating that combustion processes may significantly contribute to PM2.5. The effect of temperature (T) was more apparent on R (PM2.5-GPs) than that of relative humidity, with significant values under T > 15 °C. Moreover, R (PM2.5-O3) was positive at the T range of 12-18 °C, suggesting that reducing GPs emitted by industrial facilities during May-June may control PM2.5 and O3 in Ulsan. The methodology demonstrated in this study can be further used for a better understanding of the influences of environmental factors on the secondary PM2.5 formation from gaseous precursors and the R (PM2.5-O3).
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Affiliation(s)
- Tien Van Do
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Quang Tran Vuong
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Anh Tong
- Department of Computer Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Chang-Keun Song
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Sung-Deuk Choi
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea.
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Qu Y, Wang T, Yuan C, Wu H, Gao L, Huang C, Li Y, Li M, Xie M. The underlying mechanisms of PM 2.5 and O 3 synergistic pollution in East China: Photochemical and heterogeneous interactions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 873:162434. [PMID: 36841413 DOI: 10.1016/j.scitotenv.2023.162434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 02/16/2023] [Accepted: 02/20/2023] [Indexed: 06/18/2023]
Abstract
The rapid development of Chinese cities is accompanied by air pollution. Although the implementation of air pollution control strategies in recent years has alleviated PM2.5 pollution, O3 pollution and the synergistic pollution of PM2.5 and O3 have become more serious. To understand the underlying chemical interaction mechanisms between PM2.5 and O3, we applied the modified Weather Research and Forecasting model with Chemistry (WRF-Chem) to study the effects of aerosol-photolysis feedback and heterogeneous reactions on the two pollutants and revealed the contribution of different mechanisms in different seasons and regions in Yangtze River Delta (YRD) in eastern China. We found that, through the aerosol-photolysis feedback, PM2.5 decreased the surface photolysis rates JNO2 and JO1D, resulting in a decrease in O3 concentration in the VOC-sensitive area and a slight increase in the NOx-sensitive area. The heterogeneous reactions reduced O3 concentration in the YRD in spring, autumn and winter by consuming HxOy. While in summer, the heterogeneous absorption of NOx decreased O3 in the NOx-sensitive areas and increased O3 in the VOC-sensitive areas. Heterogeneous reactions also promoted the secondary formation of fine sulfate and nitrate aerosols, especially in winter. Through the combined effect of two chemical processes, PM2.5 can lead to a decrease in O3 concentration of -3.3 ppb (-7.6 %), -2.2 ppb (-4.0 %), -2.9 ppb (-6.3 %), and - 5.9 ppb (-18.7 %), in spring, summer, autumn and winter in YRD. Therefore, if the PM2.5 concentration decreases, the weakening effect of PM2.5 on the ozone concentration will be reduced, resulting in the aggravation of ozone pollution. This study is important for understanding the synergistic pollution mechanism and provides a scientific basis for the coordinated control of urban air pollution.
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Affiliation(s)
- Yawei Qu
- College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing 211169, China; Key Laboratory of Meteorological Disaster (KLME), Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Tijian Wang
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
| | - Cheng Yuan
- Key Laboratory of Meteorological Disaster (KLME), Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China; Emergency Management College, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Hao Wu
- Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210041, China.
| | - Libo Gao
- Jiangsu Meteorological Observatory, Nanjing 210041, China.
| | - Congwu Huang
- Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China.
| | - Yasong Li
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
| | - Mengmeng Li
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
| | - Min Xie
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
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Ren Y, Guan X, Zhang Q, Li L, Tao C, Ren S, Wang Q, Wang W. A machine learning-based study on the impact of COVID-19 on three kinds of pollution in Beijing-Tianjin-Hebei region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 884:163190. [PMID: 37061051 PMCID: PMC10102532 DOI: 10.1016/j.scitotenv.2023.163190] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 03/25/2023] [Accepted: 03/27/2023] [Indexed: 05/07/2023]
Abstract
Large-scale restrictions on anthropogenic activities in China in 2020 due to the Corona Virus Disease 2019 (COVID-19) indirectly led to improvements in air quality. Previous studies have paid little attention to the changes in nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3) concentrations at different levels of anthropogenic activity limitation and their interactions. In this study, machine learning models were used to simulate the concentrations of three pollutants during periods of different levels of lockdown, and compare them with observations during the same period. The results show that the difference between the simulated and observed values of NO2 concentrations varies at different stages of the lockdown. Variation between simulated and observed O3 and PM2.5 concentrations were less distinct at different stages of lockdowns. During the most severe period of the lockdowns, NO2 concentrations decreased significantly with a maximum decrease of 65.28 %, and O3 concentrations increased with a maximum increase of 75.69 %. During the first two weeks of the lockdown, the titration reaction in the atmosphere was disrupted due to the rapid decrease in NO2 concentrations, leading to the redistribution of Ox (NO2 + O3) in the atmosphere and eventually to the production of O3 and secondary PM2.5. The effect of traffic restrictions on the reduction of NO2 concentrations is significant. However, it is also important to consider the increase in O3 due to the constant volatile organic compounds (VOCs) and the decrease in NOx (NO+NO2). Traffic restrictions had a limited effect on improving PM2.5 pollution, so other beneficial measures were needed to sustainably reduce particulate matter pollution. Research on COVID-19 could provide new insights into future clean air action.
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Affiliation(s)
- Yuchao Ren
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Xu Guan
- Shandong Academy for Environmental Planning, Jinan 250101, PR China.
| | - Qingzhu Zhang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China.
| | - Lei Li
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Chenliang Tao
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Shilong Ren
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Qiao Wang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
| | - Wenxing Wang
- Big Data Research Center for Ecology and Environment, Environment Research Institute, Shandong University, Qingdao 266003, PR China
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Han L, Qin T, Sun Z, Ren H, Zhao N, An X, Wang Z. Influence of Urbanization on the Spatial Distribution of Associations Between Air Pollution and Mortality in Beijing, China. GEOHEALTH 2023; 7:e2022GH000749. [PMID: 36925585 PMCID: PMC10013134 DOI: 10.1029/2022gh000749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/06/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
This study investigated the influence of urbanization on the intra-city spatial distribution of associations between air pollution and mortality in Beijing, China. First, we utilized the generalized additive model to establish the exposure-response associations of PM2.5, O3, with nonaccidental and cardiorespiratory mortality between urban and suburban areas. Second, we assessed district-specific air pollution-related mortality and analyzed how these associations were affected by the degree of urbanization. Finally, we analyzed the changes in air pollution-related mortality before and after the enforcement of the Air Pollution Prevention and Control Action Plan (referred to as the Action Plan). The effect estimates of PM2.5 for nonaccidental mortality were 0.20% (95% CI: 0.12-0.28) in urban areas and 0.46% (95% CI: 0.35-0.58) in suburban areas per 10 μg/m3 increase in PM2.5 concentrations. The corresponding estimates of O3 were 0.13% (95% CI: -0.04-0.29) in urban areas and 0.34% (95% CI: 0.12-0.56) in suburban areas per 10 μg/m3 increase in O3 concentrations; however, the difference between the estimates of O3 in urban and suburban areas was not statistically significant. The district-specific results suggested that the estimated risks increased along with urban vulnerability levels for the effects of PM2.5. Implementing the Action Plan reduced the mortality risks of PM2.5, but the risks of O3 increased in some districts. However, the difference in the estimates between the pre- and post-emission reductions was not statistically significant. Our study indicated that populations living in less urbanized areas are more vulnerable to the adverse effects of air pollution in Beijing, particularly for PM2.5.
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Affiliation(s)
- Ling Han
- State Key Laboratory for Infectious Disease Prevention and ControlNational Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijingChina
| | - Tian Qin
- State Key Laboratory for Infectious Disease Prevention and ControlNational Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijingChina
| | - Zhaobin Sun
- Institute of Urban MeteorologyChina Meteorological AdministrationBeijingChina
- Joint International Research Laboratory of Atmospheric and Earth System SciencesSchool of Atmospheric SciencesNanjing UniversityNanjingChina
- China Meteorological Administration Urban Meteorology Key LaboratoryBeijingChina
| | - Hongyu Ren
- State Key Laboratory for Infectious Disease Prevention and ControlNational Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijingChina
| | - Na Zhao
- State Key Laboratory for Infectious Disease Prevention and ControlNational Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijingChina
| | - Xingqin An
- Institute of Atmospheric CompositionChinese Academy of Meteorological SciencesBeijingChina
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMAChinese Academy of Meteorological SciencesBeijingChina
| | - Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk AssessmentChinese Research Academy of Environmental SciencesBeijingChina
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10
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Liang M, Han Z, Li J, Sun Y, Liang L, Li Y. Radiative effects and feedbacks of anthropogenic aerosols on boundary layer meteorology and fine particulate matter during the COVID-19 lockdown over China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 862:160767. [PMID: 36493835 PMCID: PMC9726208 DOI: 10.1016/j.scitotenv.2022.160767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 11/19/2022] [Accepted: 12/04/2022] [Indexed: 06/17/2023]
Abstract
The COVID-19 epidemic has exerted significant impacts on human health, social and economic activities, air quality and atmospheric chemistry, and potentially on climate change. In this study, an online coupled regional climate-chemistry-aerosol model (RIEMS-Chem) was applied to explore the direct, indirect, and feedback effects of anthropogenic aerosols on radiation, boundary layer meteorology, and fine particulate matter during the COVID-19 lockdown period from 23 January to 8 April 2020 over China. Model performance was validated against a variety of observations for meteorological variables, PM2.5 and its chemical components, aerosol optical properties, as well as shortwave radiation flux, which demonstrated that RIEMS-Chem was able to reproduce the spatial distribution and temporal variation of the above variables reasonably well. During the study period, direct radiative effect (DRE) of anthropogenic aerosols was stronger than indirect radiative effect (IRE) in most regions north of the Yangtze River, whereas IRE dominated over DRE in the Yangtze River regions and South China. In North China, DRE induced larger changes in meteorology and PM2.5 than those induced by IRE, whereas in South China, the changes by IRE were remarkably larger than those by DRE. Emission reduction alone during the COVID-19 lockdown reduced PM2.5 concentration by approximately 32 % on average over East China. As a result, DRE at the surface was weakened by 15 %, whereas IRE changed little over East China, leading to a decrease in total radiative effect (TRE) by approximately 7 % in terms of domain average. The DRE-induced changes in meteorology and PM2.5 were weakened due to emission reduction, whereas the IRE-induced changes were almost the same between the cases with and without emission reductions. By aerosol radiative and feedback effects, the COVID-19 emission reductions resulted in 0.06 °C and 0.04 °C surface warming, 1.6 and 4.0 μg m-3 PM2.5 decrease, 0.4 and 1.3 mm precipitation increase during the lockdown period in 2020 in terms of domain average over North China and South China, respectively, whereas the lockdown caused negligible changes on average over East Asia.
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Affiliation(s)
- Mingjie Liang
- Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhiwei Han
- Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Jiawei Li
- Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Lin Liang
- Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yue Li
- Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
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11
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Jia C, Tong S, Zhang X, Li F, Zhang W, Li W, Wang Z, Zhang G, Tang G, Liu Z, Ge M. Atmospheric oxidizing capacity in autumn Beijing: Analysis of the O 3 and PM 2.5 episodes based on observation-based model. J Environ Sci (China) 2023; 124:557-569. [PMID: 36182163 DOI: 10.1016/j.jes.2021.11.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 11/14/2021] [Accepted: 11/15/2021] [Indexed: 06/16/2023]
Abstract
Atmospheric oxidizing capacity (AOC) is the fundamental driving factors of chemistry process (e.g., the formation of ozone (O3) and secondary organic aerosols (SOA)) in the troposphere. However, accurate quantification of AOC still remains uncertainty. In this study, a comprehensive field campaign was conducted during autumn 2019 in downtown of Beijing, where O3 and PM2.5 episodes had been experienced successively. The observation-based model (OBM) is used to quantify the AOC at O3 and PM2.5 episodes. The strong intensity of AOC is found at O3 and PM2.5 episodes, and hydroxyl radical (OH) is the dominating daytime oxidant for both episodes. The photolysis of O3 is main source of OH at O3 episode; the photolysis of nitrous acid (HONO) and formaldehyde (HCHO) plays important role in OH formation at PM2.5 episode. The radicals loss routines vary according to precursor pollutants, resulting in different types of air pollution. O3 budgets and sensitivity analysis indicates that O3 production is transition regime (both VOC and NOx-limited) at O3 episode. The heterogeneous reaction of hydroperoxy radicals (HO2) on aerosol surfaces has significant influence on OH and O3 production rates. The HO2 uptake coefficient (γHO2) is the determining factor and required accurate measurement in real atmospheric environment. Our findings could provide the important bases for coordinated control of PM2.5 and O3 pollution.
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Affiliation(s)
- Chenhui Jia
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Shengrui Tong
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.
| | - Xinran Zhang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fangjie Li
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; College of Chemistry, Liaoning University, Shenyang 110036, China
| | - Wenqian Zhang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Weiran Li
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhen Wang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Gen Zhang
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry of CMA, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Guiqian Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Zirui Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Maofa Ge
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
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12
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Liu C, Liang J, Li Y, Shi K. Fractal analysis of impact of PM 2.5 on surface O 3 sensitivity regime based on field observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:160136. [PMID: 36375545 DOI: 10.1016/j.scitotenv.2022.160136] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 06/16/2023]
Abstract
Properties of PM2.5 that can change aerosol chemistry and photolysis rates have great impacts on O3 sensitivity regime, further affecting the production rate of surface O3. However, responses of O3 sensitivity regime to changes in PM2.5 levels are difficult to be accurately determined, due to the complexity and nonlinearity of atmospheric chemistry. Here, based on long-term time series (2016-2020) of air quality variables in north and south Taiwan, fractal analysis along with Pearson correlation analysis are used to directly reveal the impacts of PM2.5 on O3 sensitivity regime in real atmosphere, by capturing the nonlinear dynamic relations among air pollutants. Great regional and seasonal difference in impacts of PM2.5 on O3 sensitivity regime may be ascribed to meteorological factors, PM2.5 components and levels of SO2, NO, NO2, etc. For north Taiwan, increased PM2.5 level can enhance the sensitivity of O3 formation to VOC in spring and summer, whereas the opposite effect can be observed in winter. But for south Taiwan, the influence of PM2.5 on O3 sensitivity regime is not statistically significant, excluding spring. Furthermore, feasibility and availability of fractal analysis is tested by simulations with Empirical Kinetics Modeling Approach (EKMA). The results demonstrate the capability of fractal analysis to identify the impacts of PM2.5 on O3 sensitivity regime in real atmosphere, which can provide suggestions for PM2.5-O3 coordinated control strategies in regions suffering combined air pollution.
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Affiliation(s)
- Chunqiong Liu
- College of Environmental Sciences and Engineering, China West Normal University, Nanchong, Sichuan, China; Key Laboratory of Nanchong City of Ecological Environment Protection and Pollution Prevention in Jialing River Basin, China West Normal University, Nanchong, China; College of Biology and Environmental Sciences, Jishou University, Jishou, Hunan, China
| | - Juan Liang
- College of Architecture & Environment, Sichuan University, Chengdu, China
| | - Youping Li
- College of Environmental Sciences and Engineering, China West Normal University, Nanchong, Sichuan, China; Key Laboratory of Nanchong City of Ecological Environment Protection and Pollution Prevention in Jialing River Basin, China West Normal University, Nanchong, China
| | - Kai Shi
- College of Environmental Sciences and Engineering, China West Normal University, Nanchong, Sichuan, China; Key Laboratory of Nanchong City of Ecological Environment Protection and Pollution Prevention in Jialing River Basin, China West Normal University, Nanchong, China.
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13
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Gao J, Li Y, Xie Z, Wang L, Hu B, Bao F. Which aerosol type dominate the impact of aerosols on ozone via changing photolysis rates? THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 854:158580. [PMID: 36075440 DOI: 10.1016/j.scitotenv.2022.158580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/01/2022] [Accepted: 09/03/2022] [Indexed: 06/15/2023]
Abstract
The impact of aerosols on ozone via influencing photolysis rates is a combined effect of absorbing aerosols (AA) and scattering aerosols (SA). However, AA and SA show different optical properties and influence photolysis rates differently, which then cause different impacts on ozone. Till now, the dominate factor is disconfirmed, which is largely due to the impact of SA on ozone not reaching to a consistent conclusion. In this study, the WRF-Chem model was implemented to simulate the air pollutants over the North China Plain (NCP). The impacts of AA and SA on ozone via influencing photolysis rates were quantitatively isolated and analyzed. Our results also demonstrated the decreasing effect of AA on ozone within planet boundary layer (PBL) which is consistent with the conclusions of previous studies. But for SA, it decreased the ozone chemical contribution (CHEM) near surface but increased which in the upper layers of PBL, that enlarge the ozone vertical gradients. In this case, more vertical exchanges of ozone would occur with the effect of vertical mixing motion of atmosphere, then the opposite CHEM variations were counteracted with each other and finally led to very slight changes in ozone within PBL. Thus, it can be summarized that AA dominate this impact of aerosols on ozone. Reducing AA could cause a general increase in ozone (ΔO3) over the NCP. Based on the aerosol levels of this case, ΔO3 would be seen over 86 % of the areas in the NCP when reducing AA by 3/4 and ΔO3 was more significant in the megacities. Our study highlights the different relationships between ozone and aerosol types, which suggests that more attentions should be paid on aerosol types, especially AA, when making the synergetic control strategy of aerosols and ozone in China.
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Affiliation(s)
- Jinhui Gao
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China; Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China
| | - Ying Li
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China.
| | - Zhouqing Xie
- Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei, China
| | - Lili Wang
- State Key Laboratory of Atmosphere Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Bo Hu
- State Key Laboratory of Atmosphere Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Fangwen Bao
- Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen, China; Center for the Oceanic and Atmospheric Science at SUSTech (COAST), Southern University of Science and Technology, Shenzhen, China
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14
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Gajski G, Gerić M, Pehnec G, Matković K, Rinkovec J, Jakovljević I, Godec R, Žužul S, Bešlić I, Cvitković A, Wild P, Guseva Canu I, Hopf NB. Associating Air Pollution with Cytokinesis-Block Micronucleus Assay Parameters in Lymphocytes of the General Population in Zagreb (Croatia). Int J Mol Sci 2022; 23:ijms231710083. [PMID: 36077482 PMCID: PMC9455971 DOI: 10.3390/ijms231710083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/23/2022] [Accepted: 09/01/2022] [Indexed: 11/19/2022] Open
Abstract
Air pollution is recognized as one of the most serious public health issues worldwide and was declared to be a leading environmental cause of cancer deaths. At the same time, the cytokinesis-block micronucleus (CBMN) assay serves as a cancer predictive method that is extensively used in human biomonitoring for populations exposed to environmental contamination. The objective of this cross-sectional study is two-fold: to evaluate genomic instability in a sample (N = 130) of healthy, general population residents from Zagreb (Croatia), chronically exposed to different levels of air pollution, and to relate them to air pollution levels in the period from 2011 to 2015. Measured frequencies of CBMN assay parameters were in agreement with the baseline data for the general population of Croatia. Air pollution exposure was based on four factors obtained from a factor analysis of all exposure data obtained for the examined period. Based on the statistical results, we did not observe a significant positive association between any of the CBMN assay parameters tested and measured air pollution parameters for designated time windows, except for benzo(a)pyrene (B[a]P) that showed significant negative association. Our results show that measured air pollution parameters are largely below the regulatory limits, except for B[a]P, and as such, they do not affect CBMN assay parameters’ frequency. Nevertheless, as air pollution is identified as a major health threat, it is necessary to conduct prospective studies investigating the effect of air pollution on genome integrity and human health.
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Affiliation(s)
- Goran Gajski
- Mutagenesis Unit, Institute for Medical Research and Occupational Health, 10000 Zagreb, Croatia
- Correspondence: ; Tel.: +385-1468-2500
| | - Marko Gerić
- Mutagenesis Unit, Institute for Medical Research and Occupational Health, 10000 Zagreb, Croatia
| | - Gordana Pehnec
- Environmental Hygiene Unit, Institute for Medical Research and Occupational Health, 10000 Zagreb, Croatia
| | - Katarina Matković
- Mutagenesis Unit, Institute for Medical Research and Occupational Health, 10000 Zagreb, Croatia
| | - Jasmina Rinkovec
- Environmental Hygiene Unit, Institute for Medical Research and Occupational Health, 10000 Zagreb, Croatia
| | - Ivana Jakovljević
- Environmental Hygiene Unit, Institute for Medical Research and Occupational Health, 10000 Zagreb, Croatia
| | - Ranka Godec
- Environmental Hygiene Unit, Institute for Medical Research and Occupational Health, 10000 Zagreb, Croatia
| | - Silva Žužul
- Environmental Hygiene Unit, Institute for Medical Research and Occupational Health, 10000 Zagreb, Croatia
| | - Ivan Bešlić
- Environmental Hygiene Unit, Institute for Medical Research and Occupational Health, 10000 Zagreb, Croatia
| | - Ante Cvitković
- Teaching Institute of Public Health Brod-Posavina County, 35000 Slavonski Brod, Croatia
- Faculty of Dental Medicine and Health, J. J. Strossmayer University of Osijek, 31000 Osijek, Croatia
- Faculty of Medicine, J. J. Strossmayer University of Osijek, 31000 Osijek, Croatia
| | - Pascal Wild
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1011 Lausanne, Switzerland
- PW Statistical Consulting, 54520 Laxou, France
| | - Irina Guseva Canu
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1011 Lausanne, Switzerland
| | - Nancy B. Hopf
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, 1011 Lausanne, Switzerland
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15
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Sha T, Ma X, Wang J, Tian R, Zhao J, Cao F, Zhang YL. Improvement of inorganic aerosol component in PM 2.5 by constraining aqueous-phase formation of sulfate in cloud with satellite retrievals: WRF-Chem simulations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 804:150229. [PMID: 34798748 DOI: 10.1016/j.scitotenv.2021.150229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 08/18/2021] [Accepted: 09/05/2021] [Indexed: 06/13/2023]
Abstract
High concentrations of PM2.5 in China have caused severe visibility degradation and health problems. However, it is still challenging to accurately predict PM2.5 and its chemical components in numerical models. In this study, we compared the inorganic aerosol components of PM2.5 (sulfate, nitrate, and ammonium (SNA)) simulated by the Weather Research and Forecasting model fully coupled with chemistry (WRF-Chem) model with in-situ data in a heavy haze-fog event during November 2018 in Nanjing, China. Comparisons show that the model underestimates sulfate concentrations by 81% and fails to reproduce the significant increase of sulfate from early morning to noon, which corresponds to the timing of fog dissipation that suggests the model underestimates the aqueous-phase formation of sulfate in clouds. In addition, the model overestimates both nitrate and ammonium concentrations by 184% and 57%, respectively. These overestimates contribute to the simulated SNA being 77.2% higher than observed. However, cloud water content is also underestimated which is a pathway for important aqueous-phase reactions. Therefore, we constrained the simulated cloud water content based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Liquid Water Path observations. Results show that the simulation with MODIS-corrected cloud water content increases the sulfate by a factor of 3, decreases the Normalized Mean Bias (NMB) by 53.5%, and reproduces its diurnal cycle with the peak concentration occurring at noon. The improved sulfate simulation also improves the simulation of nitrate, which decreases the simulated nitrate bias by 134%. Although the simulated ammonium is still higher than the observations, corrected cloud water content leads to a decrease of the modelled bias in SNA from 77.2% to 14.1%. The strong sensitivity of simulated SNA concentration to the cloud water content provides an explanation for the simulated SNA bias. Hence, uncertainties in cloud water content can contribute to model biases in simulating SNA which are less frequently explored from a process-level perspective and can be reduced by constraining the model with satellite observations.
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Affiliation(s)
- Tong Sha
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xiaoyan Ma
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Jun Wang
- Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, University of Iowa, Iowa City, Iowa 52242, United States
| | - Rong Tian
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Jianqi Zhao
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Fang Cao
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change and Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Yan-Lin Zhang
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change and Key Laboratory Meteorological Disaster, Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
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16
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Vuong QT, Park MK, Do TV, Thang PQ, Choi SD. Driving factors to air pollutant reductions during the implementation of intensive controlling policies in 2020 in Ulsan, South Korea. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 292:118380. [PMID: 34666098 DOI: 10.1016/j.envpol.2021.118380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 10/13/2021] [Accepted: 10/14/2021] [Indexed: 06/13/2023]
Abstract
Evaluation for the controlling policy's effectiveness to mitigate criteria air pollutants (CAPs) in South Korea during December 1, 2019-March 31, 2020 is difficult because of its coincidence with the COVID-19 social distancing. In this study, we differentiated the influence of three major driving factors (intensive controlling policy by the government, meteorological conditions, and social distancing) to the CAP variation in Ulsan, the largest industrial city in South Korea. In 2013-2019, the concentrations of PM2.5 (2015-2019), PM10, SO2, and NO2 decreased by 6.7, 1.6, 4.2, and 3.3%/year, respectively, whereas the O3 concentration slightly increased by 0.7%/year. Trend analysis was used to predict the CAP concentrations before (January 1-February 21) and during (February 22-March 31) the social distancing in 2020. The difference between the measured and predicted concentrations was designated as the contribution of the three factors. The controlling policy was the most important driver of the CAP reductions. In particular, its contributions were 94.1% (January 1-February 21) and 87.4% (February 22-March 31) to the PM2.5 decrease. The change in meteorological conditions considerably affected the CAP reductions, with the highest contributions of 35.2% (January 1-February 21) and 39.2% (February 22-March 31) to the O3 decrease. On February 22-March 31, the effects of social distancing were 1.6, 0.6, 1.3, and 1.4% to the reduction of SO2, NO2, PM10, and PM2.5, respectively. Overall, a decrease in the CAP concentrations was apparent during January-March 2020 in Ulsan primarily due to the intensive controlling policies, not by the COVID-19 social distancing.
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Affiliation(s)
- Quang Tran Vuong
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Min-Kyu Park
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Tien Van Do
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Phan Quang Thang
- Institute of Environmental Technology (IET), Vietnam Academy of Science and Technology (VAST), 18 Hoang Quoc Viet, Cau Giay, Hanoi, Viet Nam
| | - Sung-Deuk Choi
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea.
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17
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Yumin L, Shiyuan L, Ling H, Ziyi L, Yonghui Z, Li L, Yangjun W, Kangjuan L. The casual effects of COVID-19 lockdown on air quality and short-term health impacts in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 290:117988. [PMID: 34428699 PMCID: PMC8377358 DOI: 10.1016/j.envpol.2021.117988] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 06/21/2021] [Accepted: 08/14/2021] [Indexed: 05/12/2023]
Abstract
The outbreak of coronavirus (COVID-19) has forced China to lockdown many cities and restrict transportation, industrial, and social activities. This provides a great opportunity to look at the impacts of pandemic quarantine on air quality and premature death due to exposure to air pollution. In this study, we applied the difference-in-differences (DID) model to quantify the casual impacts of COVID-19 lockdown on air quality at 278 cities across China. A widely used exposure-response function was further utilized to estimate the short-term health impacts associated with changes in PM2.5 due to lockdown. Results show that lockdown has caused drastic reduction in air pollution level in terms of all criteria pollutants except ozone. On average, concentrations of PM2.5, PM10, NO2, SO2 and CO are estimated to drop by 14.3 μg/m3, 22.2 μg/m3, 17.7 μg/m3, 2.9 μg/m3, and 0.18 mg/m3 as the result of lockdown. Cities with more confirmed cases of COVID-19 are related to stronger responses in air quality, despite that similar lockdown measures were implemented by the local governments. The improvement of air quality caused by COVID-19 lockdown in northern cities is found to be smaller than that of southern cities. Avoided premature death associated with PM2.5 exposures over the 278 cities was estimated to be 50.8 thousand. Our results re-emphasize the effectiveness of emission controls on air quality and associated health impacts. The high cost of lockdown, still high level of air pollution during lockdown and smaller effects in northern cities implies that source-specific mitigation policies are needed for continuous and sustainable reduction of air pollution.
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Affiliation(s)
- Li Yumin
- SILC Business School, Shanghai University, Shanghai, 201800, China
| | - Li Shiyuan
- SILC Business School, Shanghai University, Shanghai, 201800, China
| | - Huang Ling
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, 200444, China.
| | - Liu Ziyi
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, 200444, China
| | - Zhu Yonghui
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, 200444, China
| | - Li Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, 200444, China
| | - Wang Yangjun
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, 200444, China
| | - Lv Kangjuan
- SILC Business School, Shanghai University, Shanghai, 201800, China
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Tian R, Ma X, Sha T, Pan X, Wang Z. Exploring dust heterogeneous chemistry over China: Insights from field observation and GEOS-Chem simulation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 798:149307. [PMID: 34375256 DOI: 10.1016/j.scitotenv.2021.149307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 06/25/2021] [Accepted: 07/23/2021] [Indexed: 06/13/2023]
Abstract
Dust heterogeneous chemistry plays an important role in tropospheric chemistry, but its parameterization in numerical models is often quite simplified, which hampers accurate prediction of particulate matter and its chemical component. In this study, we investigate the evolution of dust heterogeneous chemical process and its potential impacts on gaseous and aerosol components during a dust pollution episode from March 27 to April 2, 2015 over North China. Based on field measurements, the significant role of relative humidity (RH) in dust heterogeneous chemistry is found and a RH-dependent parameterization for uptake coefficients of HNO3 and SO2 is incorporated in GEOS-Chem to reproduce the dust heterogeneous chemical process. During the study period, observed dust sulfate (DSO4) and dust nitrate (DNIT) exhibit maximum concentrations of 9.1 and 22.8 μg m-3 respectively, accompanied by high RH and gaseous precursor concentrations. DSO4 concentrations are positively related to RH. The observed dust sulfate oxidation ratio (DSOR) is elevated evidently with increased RH, especially when RH is higher than ~40%, implying that enhanced RH could promote heterogeneous oxidation of SO2 to DSO4. Model simulation shows that when incorporating the RH-dependent parameterization, DNIT and DSO4 are generally well captured and the model performance of total sulfate oxidation ratio (TSOR) and total nitrate oxidation ratio (TNOR) are improved. High contribution of DNIT and DSO4 are found to be located over the regions close to source areas (>60%) and downwind regions (>40%), respectively. Sensitivity results show that SO2 and HNO3 reduce by 2-24 μg m-3 and 1-18 μg m-3 when considering dust heterogeneous impacts, thus leading to reduction in non-dust sulfate and non-dust nitrate concentrations. As a result, simulated NH3 increases and ammonium reduces by more than 20%. Our study indicates that the contribution of heterogeneous reactions to sulfate formation is 20-30% over North China.
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Affiliation(s)
- Rong Tian
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xiaoyan Ma
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Tong Sha
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xiaole Pan
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), Beijing 100029, China
| | - Zhe Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), Beijing 100029, China
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Huang Z, Sha Q, Zhu M, Xu Y, Yu F, Liu H, Zhou W, Zhang X, Zhang X, Rao S, Jiang F, Liu J, Zheng J. Status and quality evaluation of precursor emission inventories for PM<sub>2.5</sub> and ozone in China. CHINESE SCIENCE BULLETIN-CHINESE 2021. [DOI: 10.1360/tb-2021-0783] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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20
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Shao M, Wang W, Yuan B, Parrish DD, Li X, Lu K, Wu L, Wang X, Mo Z, Yang S, Peng Y, Kuang Y, Chen W, Hu M, Zeng L, Su H, Cheng Y, Zheng J, Zhang Y. Quantifying the role of PM 2.5 dropping in variations of ground-level ozone: Inter-comparison between Beijing and Los Angeles. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 788:147712. [PMID: 34134364 DOI: 10.1016/j.scitotenv.2021.147712] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 04/13/2021] [Accepted: 05/09/2021] [Indexed: 06/12/2023]
Abstract
In recent decade the ambient fine particle (PM2.5) levels have shown a trend of distinct dropping in China, while ground-level ozone concentrations have been increasing in Beijing and many other Chinese mega-cities. The variation pattern in Los Angeles was markedly different, with PM2.5 and ozone decreasing together over past decades. In this study, we utilize observation-based methods to establish the parametric relationship between PM2.5 concentration and key aerosol physical properties (including aerosol optical depth and aerosol surface concentration), and an observation-based 1-D photochemical model to quantify the response of PM2.5 decline in enhancing ground-level ozone pollution over a large PM2.5 concentration range (10-120 μg m-3). We find that the significance of ozone enhancement due to PM2.5 dropping depends on both the PM2.5 levels and optical properties of particles. Ozone formation increased by 37% in 2006-2016 due to PM2.5 dropping in Beijing, while it becomes less important (7%) as PM2.5 reaches below 40 μg/m3, similar to Los Angeles since 1980s. Therefore, the two cities show the convergence of air pollutant characteristics. Hence a control strategy prioritizing reactive volatile organic compound abatement is projected to yield simultaneous ozone and PM2.5 reductions in Beijing, as experienced in Los Angeles.
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Affiliation(s)
- Min Shao
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, China; College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Wenjie Wang
- College of Environmental Sciences and Engineering, Peking University, Beijing, China; Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
| | - Bin Yuan
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, China.
| | - David D Parrish
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, China
| | - Xin Li
- College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Keding Lu
- College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Luolin Wu
- School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
| | - Xuemei Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, China.
| | - Ziwei Mo
- School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
| | - Suxia Yang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, China
| | - Yuwen Peng
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, China
| | - Ye Kuang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, China
| | - Weihua Chen
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, China
| | - Min Hu
- College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Limin Zeng
- College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Hang Su
- Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
| | - Yafang Cheng
- Multiphase Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany; Minerva Research Group, Max Planck Institute for Chemistry, Mainz, Germany
| | - Junyu Zheng
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou, China
| | - Yuanhang Zhang
- College of Environmental Sciences and Engineering, Peking University, Beijing, China
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21
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Zhou Y, Gong S, Zhou C, Zhang L, He J, Wang Y, Ji D, Feng J, Mo J, Ke H. A new parameterization of uptake coefficients for heterogeneous reactions on multi-component atmospheric aerosols. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 781:146372. [PMID: 33784528 DOI: 10.1016/j.scitotenv.2021.146372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/03/2021] [Accepted: 03/05/2021] [Indexed: 06/12/2023]
Abstract
Based on laboratory studies and field observations, a new parameterization of uptake coefficients for heterogeneous reactions on multi-component aerosols is developed in this work. The equivalent ratio (ER) of inorganic aerosol is used to establish the quantitative relationship between the heterogeneous uptake coefficients and the composition of aerosols. Incorporating the new ER-dependent scheme, the WRF-CUACE model has been applied to simulate sulfate mass concentrations during December 2017 in the Beijing-Tianjin-Hebei region and evaluate the role of aerosol chemical components played in the sulfate formation. Simulated temporal variations and magnitudes of sulfate show good agreement with the observations by using this new scheme. From clean to polluted cases, although both dominant cations and anions increase significantly, the equivalent ratio decreases gradually and is closer to unity, representing the variation of aerosol compositions, which inhibits the heterogeneous uptake of SO2, with the uptake coefficient decreasing from 1 × 10-4 to 5.3 × 10-5. Based on this phenomenon, a self-limitation process for heterogeneous reactions with the increasing secondary inorganic aerosol from clean to polluted cases is proposed.
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Affiliation(s)
- Yike Zhou
- Climate and Weather Disasters Collaborative Innovation Center, Nanjing University of Information Science & Technology, Nanjing 210044, China; State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Sunling Gong
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Chunhong Zhou
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Lei Zhang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Jianjun He
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Dongsheng Ji
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Jianing Feng
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Jingyue Mo
- Climate and Weather Disasters Collaborative Innovation Center, Nanjing University of Information Science & Technology, Nanjing 210044, China; State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Huabing Ke
- Climate and Weather Disasters Collaborative Innovation Center, Nanjing University of Information Science & Technology, Nanjing 210044, China; State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
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22
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Evaluation and Bias Correction of the Secondary Inorganic Aerosol Modeling over North China Plain in Autumn and Winter. ATMOSPHERE 2021. [DOI: 10.3390/atmos12050578] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Secondary inorganic aerosol (SIA) is the key driving factor of fine-particle explosive growth (FPEG) events, which are frequently observed in North China Plain. However, the SIA simulations remain highly uncertain over East Asia. To further investigate this issue, SIA modeling over North China Plain with the 15 km resolution Nested Air Quality Prediction Model System (NAQPMS) was performed from October 2017 to March 2018. Surface observations of SIA at 28 sites were obtained to evaluate the model, which confirmed the biases in the SIA modeling. To identify the source of these biases and reduce them, uncertainty analysis was performed by evaluating the heterogeneous chemical reactions in the model and conducting sensitivity tests on the different reactions. The results suggest that the omission of the SO2 heterogeneous chemical reaction involving anthropogenic aerosols in the model is probably the key reason for the systematic underestimation of sulfate during the winter season. The uptake coefficient of the “renoxification” reaction is a key source of uncertainty in nitrate simulations, and it is likely to be overestimated by the NAQPMS. Consideration of the SO2 heterogeneous reaction involving anthropogenic aerosols and optimization of the uptake coefficient of the “renoxification” reaction in the model suitably reproduced the temporal and spatial variations in sulfate, nitrate and ammonium over North China Plain. The biases in the simulations of sulfate, nitrate, ammonium, and particulate matter smaller than 2.5 μm (PM2.5) were reduced by 84.2%, 54.8%, 81.8%, and 80.9%, respectively. The results of this study provide a reference for the reduction in the model bias of SIA and PM2.5 and improvement of the simulation of heterogeneous chemical processes.
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23
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Shen H, Liu Y, Zhao M, Li J, Zhang Y, Yang J, Jiang Y, Chen T, Chen M, Huang X, Li C, Guo D, Sun X, Xue L, Wang W. Significance of carbonyl compounds to photochemical ozone formation in a coastal city (Shantou) in eastern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 764:144031. [PMID: 33387762 DOI: 10.1016/j.scitotenv.2020.144031] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 11/17/2020] [Accepted: 11/18/2020] [Indexed: 06/12/2023]
Abstract
Carbonyl compounds are ubiquitous in the troposphere, yet their contributions to ambient ozone (O3) formation have rarely been quantified in China. To better understand their roles in O3 pollution, a field campaign was conducted at an urban site of Shantou, a coastal city in eastern China, during 7th-29th October 2019. Seven carbonyls were quantified (average ± standard deviation: 14.42 ± 3.05 ppbv), among which formaldehyde (4.12 ± 1.02 ppbv), acetaldehyde (1.57 ± 0.30 ppbv), acetone (7.55 ± 2.10 ppbv), and methyl ethyl ketone (0.94 ± 0.28 ppbv) were the most abundant species. Relative incremental reactivity (RIR) analysis indicated that O3 formation in Shantou was VOC-limited, specifically most sensitive to carbonyls, and formaldehyde showed the largest RIR values in terms of individual species. Budgets of O3 and ROx (OH, HO2, and RO2) radicals were elucidated with a chemical box model. Carbonyls played a vital role in both the primary formation and recycling of the ROx; more than 80% of the primary source of HO2 and RO2 came from photolysis of formaldehyde and other oxygenated VOCs. Zero-out sensitivity studies showed that the seven measured carbonyls accounted for 37% of the peak net O3 production rate, mainly by affecting the concentrations of HO2 and RO2. These results highlight the significance of carbonyls, especially formaldehyde, to photochemical O3 formation, and carbonyls should be paid more attention to mitigate the worsening O3 pollution in China.
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Affiliation(s)
- Hengqing Shen
- Environment Research Institute, Shandong University, Qingdao, Shandong 266237, China
| | - Yuhong Liu
- Environment Research Institute, Shandong University, Qingdao, Shandong 266237, China
| | - Min Zhao
- Environment Research Institute, Shandong University, Qingdao, Shandong 266237, China
| | - Juan Li
- Shantou Environmental Protection Monitoring Station, Shantou 515041, China.
| | - Yingnan Zhang
- Environment Research Institute, Shandong University, Qingdao, Shandong 266237, China
| | - Juan Yang
- Environment Research Institute, Shandong University, Qingdao, Shandong 266237, China
| | - Ying Jiang
- Environment Research Institute, Shandong University, Qingdao, Shandong 266237, China
| | - Tianshu Chen
- Environment Research Institute, Shandong University, Qingdao, Shandong 266237, China
| | - Miao Chen
- Shantou Environmental Protection Monitoring Station, Shantou 515041, China
| | - Xianbing Huang
- Shantou Environmental Protection Monitoring Station, Shantou 515041, China
| | - Chengliu Li
- Shenzhen OnePoint Environmental Consultant Co., Ltd, Shenzhen 518000, China
| | - Danling Guo
- Shenzhen OnePoint Environmental Consultant Co., Ltd, Shenzhen 518000, China
| | - Xiaoyan Sun
- Jinan Environmental Monitoring Center Station, Ji'nan, Shandong 250014, China
| | - Likun Xue
- Environment Research Institute, Shandong University, Qingdao, Shandong 266237, China.
| | - Wenxing Wang
- Environment Research Institute, Shandong University, Qingdao, Shandong 266237, China
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24
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Yang W, Chen H, Wu J, Wang W, Zheng J, Chen D, Li J, Tang X, Wang Z, Zhu L, Wang W. Characteristics of the source apportionment of primary and secondary inorganic PM 2.5 in the Pearl River Delta region during 2015 by numerical modeling. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 267:115418. [PMID: 33254647 DOI: 10.1016/j.envpol.2020.115418] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Revised: 07/16/2020] [Accepted: 08/10/2020] [Indexed: 06/12/2023]
Abstract
Fine particulate matter (PM2.5) contains both primary and secondary components, and their source apportionment characteristics in the Pearl River Delta (PRD) region during 2015 were compared by applying an air quality model coupled with an on-line tracer-tagged module. The results of contributions from different source regions to primary PM2.5 (PPM2.5) and secondary inorganic PM2.5 (SIPM2.5) in four selected cities show that the effect of regional transport on the SIPM2.5 level is stronger than that on the PPM2.5 level in the PRD region. For both Guangzhou city and the average of the entire PRD region, the industrial (25-40%) and transportation (20-25%) sectors are major sources of PPM2.5 and SIPM2.5. However, the residential sector contributes approximately 25% to the PPM2.5 level, mainly from residential biomass burning, but accounts for only approximately 10% of the SIPM2.5 level. The relative importance of each sector to the contributions from local and regional transport indicates that industrial emissions appear to lead to regional air pollution, while the transportation emissions seem to mainly affect the local and surrounding areas. Considering the impact of regional contributions to air quality, efforts made to reduce emissions in each city could not only improve the local air quality but also benefit downstream regions. To further decrease the PM2.5 level, the local government of each city in the PRD region should not only continue to strengthen the control of local emissions, such as those from transportation and residential biomass burning, but also increase their focus on regional joint prevention and control strategies with upstream area (such as northern Guangdong Province, and Jiangxi, Fujian and Hunan provinces).
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Affiliation(s)
- Wenyi Yang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
| | - Huansheng Chen
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China.
| | - Jianbin Wu
- Clear Technology Co., Ltd., Beijing, 100029, China
| | - Wending Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Junyu Zheng
- Institute of Environmental and Climate Research, Jinan University, Guangzhou, 510632, China
| | - Duohong Chen
- Guangdong Environmental Monitoring Center, Guangzhou, 510308, China
| | - Jie Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiao Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
| | - Zifa Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lili Zhu
- China National Environmental Monitoring Center, Beijing, 100012, China
| | - Wei Wang
- China National Environmental Monitoring Center, Beijing, 100012, China
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Miyazaki K, Bowman K, Sekiya T, Jiang Z, Chen X, Eskes H, Ru M, Zhang Y, Shindell D. Air Quality Response in China Linked to the 2019 Novel Coronavirus (COVID-19) Lockdown. GEOPHYSICAL RESEARCH LETTERS 2020; 47:e2020GL089252. [PMID: 33173248 PMCID: PMC7646019 DOI: 10.1029/2020gl089252] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 08/21/2020] [Accepted: 09/08/2020] [Indexed: 05/20/2023]
Abstract
Efforts to stem the spread of COVID-19 in China hinged on severe restrictions to human movement starting 23 January 2020 in Wuhan and subsequently to other provinces. Here, we quantify the ancillary impacts on air pollution and human health using inverse emissions estimates based on multiple satellite observations. We find that Chinese NOx emissions were reduced by 36% from early January to mid-February, with more than 80% of reductions occurring after their respective lockdown in most provinces. The reduced precursor emissions increased surface ozone by up to 16 ppb over northern China but decreased PM2.5 by up to 23 μg m-3 nationwide. Changes in human exposure are associated with about 2,100 more ozone-related and at least 60,000 fewer PM2.5-related morbidity incidences, primarily from asthma cases, thereby augmenting efforts to reduce hospital admissions and alleviate negative impacts from potential delayed treatments.
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Affiliation(s)
- K. Miyazaki
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - K. Bowman
- Jet Propulsion LaboratoryCalifornia Institute of TechnologyPasadenaCAUSA
| | - T. Sekiya
- Japan Agency for Marine‐Earth Science and TechnologyYokohamaJapan
| | - Z. Jiang
- School of Earth and Space SciencesUniversity of Science and Technology of ChinaHefeiChina
| | - X. Chen
- School of Earth and Space SciencesUniversity of Science and Technology of ChinaHefeiChina
| | - H. Eskes
- Royal Netherlands Meteorological Institute (KNMI)De Biltthe Netherlands
| | - M. Ru
- Nicholas School of the EnvironmentDuke UniversityDurhamNCUSA
| | - Y. Zhang
- Nicholas School of the EnvironmentDuke UniversityDurhamNCUSA
| | - D. Shindell
- Nicholas School of the EnvironmentDuke UniversityDurhamNCUSA
- Porter School of the Environment and Earth SciencesTel Aviv UniversityTel AvivIsrael
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Wang H, Chai S, Tang X, Zhou B, Bian J, Vömel H, Yu K, Wang W. Verification of satellite ozone/temperature profile products and ozone effective height/temperature over Kunming, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 661:35-47. [PMID: 30665130 DOI: 10.1016/j.scitotenv.2019.01.145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 12/28/2018] [Accepted: 01/13/2019] [Indexed: 06/09/2023]
Abstract
Ozonesonde data from November 2013 to April 2015 over Kunming, China are used to verify ozone and temperature profile retrievals from two spaceborne instruments, the version 4.2 product from the Microwave Limb Sounder (MLS) on the NASA Aura satellite and the version 6.0 product from the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua satellite. We calculated and compared the ozone effective height Heff and effective temperature Teff, which are two important parameters in ground-based total ozone retrieval through the use of various profile datasets. This is used to verify the accuracy of the operative values (Heff(0) = 23 km, Teff(0) = -46.3 °C (or -45 °C)) from the World Meteorological Organization. The results show that the deviation of MLS and AIRS ozone profiles from ozone sounding data has significant oscillation and scatter in the upper troposphere and lower stratosphere. The average difference of MLS at 82.5 hPa is (80.5 ± 65.1) %, and that of AIRS at 70 and 100 hPa are (105.6 ± 74.9) % and (107.0 ± 67.8) %, respectively. The two satellite temperature profiles have differences within ±3 °C and can effectively describe the vertical distribution and variation of temperature. When calculating the Heff and Teff, upper stratospheric data missing from the sounding data must be filled in by the satellite profile data; otherwise the calculated results will show large errors of 3.2 km and 3.3 °C. The Heff and Teff at Kunming are respectively 24.36 to 25.51 km and -48.3 to -43.6 °C. The operational Heff and Teff used at Kunming ozone observation station clearly do not conform to the actual situation and must be corrected.
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Affiliation(s)
- Haoyue Wang
- Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Fudan University, Shanghai, China; Department of Atmosphere Science, Yunnan University, Kunming, China
| | - Suying Chai
- Department of Atmosphere Science, Yunnan University, Kunming, China; Yunan Institute of Environmental Science, Kunming, China
| | - Xiao Tang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Beijing, China
| | - Bin Zhou
- Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Fudan University, Shanghai, China; Shanghai Institute of Eco-Chongming (SIEC), No. 3663 Northern Zhongshan Road, Shanghai, China.
| | - Jianchun Bian
- Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Holger Vömel
- Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
| | - Ke Yu
- Meteorological Information Center of Yunnan Province, Kunming, China
| | - Weiguo Wang
- Department of Atmosphere Science, Yunnan University, Kunming, China.
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27
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Abstract
Aerosol mixing state significantly affects concentrations of cloud condensation nuclei (CCN), wet removal rates, thermodynamic properties, heterogeneous chemistry, and aerosol optical properties, with implications for human health and climate. Over the last two decades, significant research effort has gone into finding computationally-efficient methods for representing the most important aspects of aerosol mixing state in air pollution, weather prediction, and climate models. In this review, we summarize the interactions between mixing-state and aerosol hygroscopicity, optical properties, equilibrium thermodynamics and heterogeneous chemistry. We focus on the effects of simplified assumptions of aerosol mixing state on CCN concentrations, wet deposition, and aerosol absorption. We also summarize previous approaches for representing aerosol mixing state in atmospheric models, and we make recommendations regarding the representation of aerosol mixing state in future modelling studies.
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28
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Li K, Jacob DJ, Liao H, Shen L, Zhang Q, Bates KH. Anthropogenic drivers of 2013-2017 trends in summer surface ozone in China. Proc Natl Acad Sci U S A 2019; 116:422-427. [PMID: 30598435 PMCID: PMC6329973 DOI: 10.1073/pnas.1812168116] [Citation(s) in RCA: 513] [Impact Index Per Article: 102.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Observations of surface ozone available from ∼1,000 sites across China for the past 5 years (2013-2017) show severe summertime pollution and regionally variable trends. We resolve the effect of meteorological variability on the ozone trends by using a multiple linear regression model. The residual of this regression shows increasing ozone trends of 1-3 ppbv a-1 in megacity clusters of eastern China that we attribute to changes in anthropogenic emissions. By contrast, ozone decreased in some areas of southern China. Anthropogenic NOx emissions in China are estimated to have decreased by 21% during 2013-2017, whereas volatile organic compounds (VOCs) emissions changed little. Decreasing NOx would increase ozone under the VOC-limited conditions thought to prevail in urban China while decreasing ozone under rural NOx-limited conditions. However, simulations with the Goddard Earth Observing System Chemical Transport Model (GEOS-Chem) indicate that a more important factor for ozone trends in the North China Plain is the ∼40% decrease of fine particulate matter (PM2.5) over the 2013-2017 period, slowing down the aerosol sink of hydroperoxy (HO2) radicals and thus stimulating ozone production.
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Affiliation(s)
- Ke Li
- Harvard-NUIST Joint Laboratory for Air Quality and Climate, Nanjing University of Information Science and Technology, 210044 Nanjing, China
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
| | - Daniel J Jacob
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138;
| | - Hong Liao
- Harvard-NUIST Joint Laboratory for Air Quality and Climate, Nanjing University of Information Science and Technology, 210044 Nanjing, China;
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, 210044 Nanjing, China
| | - Lu Shen
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
| | - Qiang Zhang
- Department of Earth System Science, Tsinghua University, 100084 Beijing, China
| | - Kelvin H Bates
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
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Zhang Y, Tong S, Ge M, Jing B, Hou S, Tan F, Chen Y, Guo Y, Wu L. The influence of relative humidity on the heterogeneous oxidation of sulfur dioxide by ozone on calcium carbonate particles. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 633:1253-1262. [PMID: 29758878 DOI: 10.1016/j.scitotenv.2018.03.288] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 03/22/2018] [Accepted: 03/23/2018] [Indexed: 06/08/2023]
Abstract
Heterogeneous reactions of SO2 and O3 with CaCO3 particles were investigated at a series of relative humidity (RH, 1% to 90%) and 298K using a diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). The uptake coefficients of SO2 on CaCO3 at different RHs were obtained for the first time. Our results proved that high RH could substantially promote the formation of sulfate, for which the highest concentration (80% RH and reaction time of 200min) and highest formation rate in stable stage (85% RH) were 14 times and 43 times that at 1% RH, respectively. The surface products, increment of concentration and formation rate of sulfate changed with RH which were due to the surface adsorbed water (SAW) on the particles. SAW could increase the reactive sites on the particles and thus accelerate the conversion of SO2 into sulfite, and sulfite could be oxidized rapidly. Liquid-like water layers formed on the particle surface could enhance the ion mobility and promote the aggregation of CaSO4 hydrates, which could expose more reactive sites and result in additional adsorption of SO2. Piecewise equations of uptake coefficient with RH were given and could be referred by model simulation. The results are of importance in understanding the explosive growth of sulfate during severe haze episodes accompanied with high RH.
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Affiliation(s)
- Ying Zhang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Shengrui Tong
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China.
| | - Maofa Ge
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China; CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China.
| | - Bo Jing
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China
| | - Siqi Hou
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Fang Tan
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Yi Chen
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Yucong Guo
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, PR China
| | - Lingyan Wu
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, PR China
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