Articles | Volume 16, issue 8
https://doi.org/10.5194/essd-16-3565-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-3565-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Reconstructing long-term (1980–2022) daily ground particulate matter concentrations in India (LongPMInd)
Shuai Wang
Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Mengyuan Zhang
Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Hui Zhao
School of Resources and Environmental Engineering, Jiangsu University of Technology, Changzhou 213001, China
Peng Wang
Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China
Sri Harsha Kota
Department of Civil Engineering, Indian Institute of Technology, Delhi, 110016, India
Qingyan Fu
Shanghai Academy of Environmental Sciences, Shanghai 200003, China
Cong Liu
School of Public Health, Fudan University, Shanghai 200032, China
Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China
Institute of Eco-Chongming (IEC), East China Normal University, Shanghai 200062, China
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Mercury is a persistent toxic pollutant that has equally important anthropogenic and natural sources. This study developed a quantitative method on separating the anthropogenic and natural contributions of total gaseous mercury. The underlying impacts on the sea-air exchange fluxes of mercury are evaluated. The new method developed in this study can be reproducible in other regions and the findings are innovative in the field of mercury sources and biogeochemical cycles.
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Atmos. Chem. Phys., 24, 12943–12962, https://doi.org/10.5194/acp-24-12943-2024, https://doi.org/10.5194/acp-24-12943-2024, 2024
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Zijun Zhang, Weiqi Xu, Yi Zhang, Wei Zhou, Xiangyu Xu, Aodong Du, Yinzhou Zhang, Hongqin Qiao, Ye Kuang, Xiaole Pan, Zifa Wang, Xueling Cheng, Lanzhong Liu, Qingyan Fu, Douglas R. Worsnop, Jie Li, and Yele Sun
Atmos. Chem. Phys., 24, 8473–8488, https://doi.org/10.5194/acp-24-8473-2024, https://doi.org/10.5194/acp-24-8473-2024, 2024
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We investigated aerosol composition and sources and the interaction between secondary organic aerosol (SOA) and clouds at a regional mountain site in southeastern China. Clouds efficiently scavenge more oxidized SOA; however, cloud evaporation leads to the production of less oxidized SOA. The unexpectedly high presence of nitrate in aerosol particles indicates that nitrate formed in polluted areas has undergone interactions with clouds, significantly influencing the regional background site.
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Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
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Song Gao, Yong Yang, Xiao Tong, Linyuan Zhang, Yusen Duan, Guigang Tang, Qiang Wang, Changqing Lin, Qingyan Fu, Lipeng Liu, and Lingning Meng
Atmos. Meas. Tech., 16, 5709–5723, https://doi.org/10.5194/amt-16-5709-2023, https://doi.org/10.5194/amt-16-5709-2023, 2023
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Jianing Dai, Guy P. Brasseur, Mihalis Vrekoussis, Maria Kanakidou, Kun Qu, Yijuan Zhang, Hongliang Zhang, and Tao Wang
Atmos. Chem. Phys., 23, 14127–14158, https://doi.org/10.5194/acp-23-14127-2023, https://doi.org/10.5194/acp-23-14127-2023, 2023
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Da Lu, Hao Li, Mengke Tian, Guochen Wang, Xiaofei Qin, Na Zhao, Juntao Huo, Fan Yang, Yanfen Lin, Jia Chen, Qingyan Fu, Yusen Duan, Xinyi Dong, Congrui Deng, Sabur F. Abdullaev, and Kan Huang
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Qianqian Gao, Shengqiang Zhu, Kaili Zhou, Jinghao Zhai, Shaodong Chen, Qihuang Wang, Shurong Wang, Jin Han, Xiaohui Lu, Hong Chen, Liwu Zhang, Lin Wang, Zimeng Wang, Xin Yang, Qi Ying, Hongliang Zhang, Jianmin Chen, and Xiaofei Wang
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Xiaodong Xie, Jianlin Hu, Momei Qin, Song Guo, Min Hu, Dongsheng Ji, Hongli Wang, Shengrong Lou, Cheng Huang, Chong Liu, Hongliang Zhang, Qi Ying, Hong Liao, and Yuanhang Zhang
Atmos. Chem. Phys., 23, 10563–10578, https://doi.org/10.5194/acp-23-10563-2023, https://doi.org/10.5194/acp-23-10563-2023, 2023
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Meng Wang, Yusen Duan, Zhuozhi Zhang, Qi Yuan, Xinwei Li, Shuwen Han, Juntao Huo, Jia Chen, Yanfen Lin, Qingyan Fu, Tao Wang, Junji Cao, and Shun-cheng Lee
Atmos. Chem. Phys., 23, 10313–10324, https://doi.org/10.5194/acp-23-10313-2023, https://doi.org/10.5194/acp-23-10313-2023, 2023
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Hourly elemental carbon (EC) and NOx were continuously measured for 5 years (2016–2020) at a sampling site near a highway in western Shanghai. We use a machine learning model to rebuild the measured EC and NOx, and a business-as-usual (BAU) scenario was assumed in 2020 and compared with the measured EC and NOx.
Jinlong Ma, Shengqiang Zhu, Siyu Wang, Peng Wang, Jianmin Chen, and Hongliang Zhang
Atmos. Chem. Phys., 23, 4311–4325, https://doi.org/10.5194/acp-23-4311-2023, https://doi.org/10.5194/acp-23-4311-2023, 2023
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An updated version of the CMAQ model with biogenic volatile organic compound (BVOC) emissions from MEGAN was applied to study the impacts of different land cover inputs on O3 and secondary organic aerosol (SOA) in China. The estimated BVOC emissions ranged from 25.42 to 37.39 Tg using different leaf area index (LAI) and land cover (LC) inputs. Those differences further induced differences of 4.8–6.9 ppb in O3 concentrations and differences of 5.3–8.4 µg m−3 in SOA concentrations in China.
Peng Wang, Ruhan Zhang, Shida Sun, Meng Gao, Bo Zheng, Dan Zhang, Yanli Zhang, Gregory R. Carmichael, and Hongliang Zhang
Atmos. Chem. Phys., 23, 2983–2996, https://doi.org/10.5194/acp-23-2983-2023, https://doi.org/10.5194/acp-23-2983-2023, 2023
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In China, the number of vehicles has jumped significantly in the last decade. This caused severe traffic congestion and aggravated air pollution. In this study, we developed a new temporal allocation approach to quantify the impacts of traffic congestion. We found that traffic congestion worsens air quality and the health burden across China, especially in the urban clusters. More effective and comprehensive vehicle emission control policies should be implemented to improve air quality in China.
Yizhen Wu, Juntao Huo, Gan Yang, Yuwei Wang, Lihong Wang, Shijian Wu, Lei Yao, Qingyan Fu, and Lin Wang
Atmos. Chem. Phys., 23, 2997–3014, https://doi.org/10.5194/acp-23-2997-2023, https://doi.org/10.5194/acp-23-2997-2023, 2023
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Based on a field campaign in a suburban area of Shanghai during summer 2021, we calculated formaldehyde (HCHO) production rates from 24 volatile organic compounds (VOCs). In addition, HCHO photolysis, reactions with OH radicals, and dry deposition were considered for the estimation of HCHO loss rates. Our results reveal the key precursors of HCHO and suggest that HCHO wet deposition may be an important loss term on cloudy and rainy days, which needs to be further investigated.
Changqin Yin, Jianming Xu, Wei Gao, Liang Pan, Yixuan Gu, Qingyan Fu, and Fan Yang
Atmos. Chem. Phys., 23, 1329–1343, https://doi.org/10.5194/acp-23-1329-2023, https://doi.org/10.5194/acp-23-1329-2023, 2023
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The particle matter (PM2.5) at the top of the 632 m high Shanghai Tower was found to be higher than the surface from June to October due to unexpected larger PM2.5 levels during early to middle afternoon at Shanghai Tower. We suppose the significant chemical production of secondary species existed in the mid-upper planetary boundary layer. We found a high nitrate concentration at the tower site for both daytime and nighttime in winter, implying efficient gas-phase and heterogeneous formation.
Xiaofei Qin, Shengqian Zhou, Hao Li, Guochen Wang, Cheng Chen, Chengfeng Liu, Xiaohao Wang, Juntao Huo, Yanfen Lin, Jia Chen, Qingyan Fu, Yusen Duan, Kan Huang, and Congrui Deng
Atmos. Chem. Phys., 22, 15851–15865, https://doi.org/10.5194/acp-22-15851-2022, https://doi.org/10.5194/acp-22-15851-2022, 2022
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Using artificial neural network modeling and an explainable analysis approach, natural surface emissions (NSEs) were identified as a main driver of gaseous elemental mercury (GEM) variations during the COVID-19 lockdown. A sharp drop in GEM concentrations due to a significant reduction in anthropogenic emissions may disrupt the surface–air exchange balance of Hg, leading to increases in NSEs. This implies that NSEs may pose challenges to the future control of Hg pollution.
Meng Wang, Yusen Duan, Wei Xu, Qiyuan Wang, Zhuozhi Zhang, Qi Yuan, Xinwei Li, Shuwen Han, Haijie Tong, Juntao Huo, Jia Chen, Shan Gao, Zhongbiao Wu, Long Cui, Yu Huang, Guangli Xiu, Junji Cao, Qingyan Fu, and Shun-cheng Lee
Atmos. Chem. Phys., 22, 12789–12802, https://doi.org/10.5194/acp-22-12789-2022, https://doi.org/10.5194/acp-22-12789-2022, 2022
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In this study, we report the long-term measurement of organic carbon (OC) and elementary carbon (EC) in PM2.5 with hourly time resolution conducted at a regional site in Shanghai from 2016 to 2020. The results from this study provide critical information about the long-term trend of carbonaceous aerosol, in particular secondary OC, in one of the largest megacities in the world and are helpful for developing pollution control measures from a long-term planning perspective.
Han Zang, Yue Zhao, Juntao Huo, Qianbiao Zhao, Qingyan Fu, Yusen Duan, Jingyuan Shao, Cheng Huang, Jingyu An, Likun Xue, Ziyue Li, Chenxi Li, and Huayun Xiao
Atmos. Chem. Phys., 22, 4355–4374, https://doi.org/10.5194/acp-22-4355-2022, https://doi.org/10.5194/acp-22-4355-2022, 2022
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Particulate nitrate plays an important role in wintertime haze pollution in eastern China, yet quantitative constraints on detailed nitrate formation mechanisms remain limited. Here we quantified the contributions of the heterogeneous N2O5 hydrolysis (66 %) and gas-phase OH + NO2 reaction (32 %) to nitrate formation in this region and identified the atmospheric oxidation capacity (i.e., availability of O3 and OH radicals) as the driving factor of nitrate formation from both processes.
Peng Wang, Juanyong Shen, Men Xia, Shida Sun, Yanli Zhang, Hongliang Zhang, and Xinming Wang
Atmos. Chem. Phys., 21, 10347–10356, https://doi.org/10.5194/acp-21-10347-2021, https://doi.org/10.5194/acp-21-10347-2021, 2021
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Ozone (O3) pollution has received extensive attention due to worsening air quality and rising health risks. The Chinese National Day holiday (CNDH), which is associated with intensive commercial and tourist activities, serves as a valuable experiment to evaluate the O3 response during the holiday. We find sharply increasing trends of observed O3 concentrations throughout China during the CNDH, leading to 33 % additional total daily deaths.
Lian Zong, Yuanjian Yang, Meng Gao, Hong Wang, Peng Wang, Hongliang Zhang, Linlin Wang, Guicai Ning, Chao Liu, Yubin Li, and Zhiqiu Gao
Atmos. Chem. Phys., 21, 9105–9124, https://doi.org/10.5194/acp-21-9105-2021, https://doi.org/10.5194/acp-21-9105-2021, 2021
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In recent years, summer O3 pollution over eastern China has become more serious, and it is even the case that surface O3 and PM2.5 pollution can co-occur. However, the synoptic weather pattern (SWP) related to this compound pollution remains unclear. Regional PM2.5 and O3 compound pollution is characterized by various SWPs with different dominant factors. Our findings provide insights into the regional co-occurring high PM2.5 and O3 levels via the effects of certain meteorological factors.
Jinlong Ma, Juanyong Shen, Peng Wang, Shengqiang Zhu, Yu Wang, Pengfei Wang, Gehui Wang, Jianmin Chen, and Hongliang Zhang
Atmos. Chem. Phys., 21, 7343–7355, https://doi.org/10.5194/acp-21-7343-2021, https://doi.org/10.5194/acp-21-7343-2021, 2021
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Due to the reduced anthropogenic emissions during the COVID-19 lockdown, mainly from the transportation and industrial sectors, PM2.5 decreased significantly in the whole Yangtze River Delta (YRD) and its major cities. However, the contributions and relative importance of different source sectors and regions changed differently, indicating that control strategies should be adjusted accordingly for further pollution control.
Kun Zhang, Ling Huang, Qing Li, Juntao Huo, Yusen Duan, Yuhang Wang, Elly Yaluk, Yangjun Wang, Qingyan Fu, and Li Li
Atmos. Chem. Phys., 21, 5905–5917, https://doi.org/10.5194/acp-21-5905-2021, https://doi.org/10.5194/acp-21-5905-2021, 2021
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Recently, high O3 concentrations were frequently observed in rural areas of the Yangtze River Delta (YRD) region under stagnant conditions. Using an online measurement and observation-based model, we investigated the budget of ROx radicals and the influence of isoprene chemistry on O3 formation. Our results underline that isoprene chemistry in the rural atmosphere becomes important with the participation of anthropogenic NOx.
Mengyuan Zhang, Arpit Katiyar, Shengqiang Zhu, Juanyong Shen, Men Xia, Jinlong Ma, Sri Harsha Kota, Peng Wang, and Hongliang Zhang
Atmos. Chem. Phys., 21, 4025–4037, https://doi.org/10.5194/acp-21-4025-2021, https://doi.org/10.5194/acp-21-4025-2021, 2021
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We studied changes in air quality in India induced by the COVID-19 lockdown through both surface observations and the CMAQ model. Our results show that emission reductions improved the air quality across India during the lockdown. On average, the levels of PM2.5 and O3 decreased by 28 % and 15 %, indicating positive effects of lockdown measures. We suggest that more stringent and localized emission control strategies should be implemented in India to mitigate air pollutions.
Junjun Deng, Hao Guo, Hongliang Zhang, Jialei Zhu, Xin Wang, and Pingqing Fu
Atmos. Chem. Phys., 20, 14419–14435, https://doi.org/10.5194/acp-20-14419-2020, https://doi.org/10.5194/acp-20-14419-2020, 2020
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One-year source apportionment of BC aerosols in a coastal city in China was conducted with the light-absorption observation-based method and source-oriented model. Source contributions identified by the two source apportionment methods were compared. Temporal variability, potential sources and transport pathways of BC from fossil fuel and biomass burning were characterized. Significant influence of biomass burning in North and East–Central China on BC in the region was highlighted.
Zhihao Shi, Lin Huang, Jingyi Li, Qi Ying, Hongliang Zhang, and Jianlin Hu
Atmos. Chem. Phys., 20, 13455–13466, https://doi.org/10.5194/acp-20-13455-2020, https://doi.org/10.5194/acp-20-13455-2020, 2020
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Meteorological conditions play important roles in the formation of O3 and PM2.5 pollution in China. O3 is most sensitive to temperature and the sensitivity is dependent on the O3 chemistry formation or loss regime. PM2.5 is negatively sensitive to temperature, wind speed, and planetary boundary layer height and positively sensitive to humidity. The results imply that air quality in certain regions of China is sensitive to climate changes.
Rui Li, Qiongqiong Wang, Xiao He, Shuhui Zhu, Kun Zhang, Yusen Duan, Qingyan Fu, Liping Qiao, Yangjun Wang, Ling Huang, Li Li, and Jian Zhen Yu
Atmos. Chem. Phys., 20, 12047–12061, https://doi.org/10.5194/acp-20-12047-2020, https://doi.org/10.5194/acp-20-12047-2020, 2020
Xiaofei Qin, Leiming Zhang, Guochen Wang, Xiaohao Wang, Qingyan Fu, Jian Xu, Hao Li, Jia Chen, Qianbiao Zhao, Yanfen Lin, Juntao Huo, Fengwen Wang, Kan Huang, and Congrui Deng
Atmos. Chem. Phys., 20, 10985–10996, https://doi.org/10.5194/acp-20-10985-2020, https://doi.org/10.5194/acp-20-10985-2020, 2020
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The uncertainties in mercury emissions are much larger from natural sources than anthropogenic sources. A method was developed to quantify the contributions of natural surface emissions to ambient GEM based on PMF modeling. The annual GEM concentration in eastern China showed a decreasing trend from 2015 to 2018, while the relative contribution of natural surface emissions increased significantly from 41 % in 2015 to 57 % in 2018, gradually surpassing those from anthropogenic sources.
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Short summary
Long-term, open-source, gap-free daily ground-level PM2.5 and PM10 datasets for India (LongPMInd) were reconstructed using a robust machine learning model to support health assessment and air quality management.
Long-term, open-source, gap-free daily ground-level PM2.5 and PM10 datasets for India...
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