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Xu L, Wang B, Wang Y, Zhang H, Xu D, Zhao Y, Zhao K. Characterization and Source Apportionment Analysis of PM 2.5 and Ozone Pollution over Fenwei Plain, China: Insights from PM 2.5 Component and VOC Observations. TOXICS 2025; 13:123. [PMID: 39997938 PMCID: PMC11862001 DOI: 10.3390/toxics13020123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2025] [Revised: 01/30/2025] [Accepted: 01/30/2025] [Indexed: 02/26/2025]
Abstract
PM2.5 and volatile organic compounds (VOCs) have been identified as the primary air pollutants affecting the Fenwei Plain (FWP), necessitating urgent measures to improve its air quality. To gain a deeper understanding of the formation mechanisms of these pollutants, this study employed various methods such as HYSPLIT, PCT, and PMF for analysis. Our results indicate that the FWP is primarily impacted by PM2.5 from the southern Shaanxi air mass and the northwestern air mass during winter. In contrast, during summer, it is mainly influenced by O3 originating from the southern air mass. Specifically, high-pressure fronts are the dominant weather pattern affecting PM2.5 pollution in the FWP, while high-pressure backs predominately O3 pollution. Regarding the sources of PM2.5, secondary nitrates, vehicle exhausts, and secondary sulfates are major contributors. As for volatile organic compounds, liquefied petroleum gas sources, vehicle exhausts, solvent usage, and industrial emissions are the primary sources. This study holds crucial scientific significance in enhancing the regional joint prevention and control mechanism for PM2.5 and O3 pollution, and it provides scientific support for formulating effective strategies for air pollution prevention and control.
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Affiliation(s)
- Litian Xu
- Yunnan Key Laboratory of Meteorological Disasters and Climate Resources in the Greater Mekong Subregion, Yunnan University, Kunming 650091, China
| | - Bo Wang
- Xianyang Environmental Monitoring Station, Xianyang 712000, China
| | - Ying Wang
- Xianyang Meteorological Bureau, Xianyang 712000, China
| | - Huipeng Zhang
- Xianyang Environmental Monitoring Station, Xianyang 712000, China
| | - Danni Xu
- Yunnan Key Laboratory of Meteorological Disasters and Climate Resources in the Greater Mekong Subregion, Yunnan University, Kunming 650091, China
- Xianyang Environmental Monitoring Station, Xianyang 712000, China
- Information School, Yunnan University of Finance and Economics, Kunming 650221, China
| | - Yibing Zhao
- Xianyang Meteorological Bureau, Xianyang 712000, China
| | - Kaihui Zhao
- Yunnan Key Laboratory of Meteorological Disasters and Climate Resources in the Greater Mekong Subregion, Yunnan University, Kunming 650091, China
- Xianyang Environmental Monitoring Station, Xianyang 712000, China
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Wang S, Tian R, Yan J, Hu J, Xu S, Zhao S, Zhang M, Dai S, Yang H, Zhang X. Decadal Response of Atmospheric Inorganic Nitrogen Dry Deposition into Offshore Areas to Policy Controls and Environmental Significance. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2025; 59:689-698. [PMID: 39723963 DOI: 10.1021/acs.est.4c12063] [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: 12/28/2024]
Abstract
Accurately assessing the dry deposition fluxes of inorganic nitrogen aerosol (aerosol-IN) is crucial for mitigating the ecological damage caused by excessive nitrogen in oceanic equilibria. We developed a dry deposition model to assess the dry deposition fluxes of aerosol-IN into Chinese offshore areas over a decade, with the range of 2.81 × 106-1.89 × 107 g N km-2 year-1. Our findings showed a clear decline in the dry deposition fluxes of aerosol-IN following the implementation of environmental laws and policies. Promoting cleaner production, using new energy vehicles, the rational use of nitrogenous fertilizers, and standardized straw burning will all reduce pollution caused by excessive nitrogen deposition. High ratios of dry deposit to river transport nitrogen (0.48-17.89) indicate aerosol-IN is a significant source of inorganic nitrogen in Chinese offshore areas. The implementation of the policy has significantly reduced aerosol-IN deposition into the ocean, but its contribution remained substantial and should be considered when protecting the Chinese marine ecological environment.
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Affiliation(s)
- Shanshan Wang
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, MNR, Xiamen 361001, China
- Third Institute of Oceanography, Ministry of Natural Resources of China, Xiamen 361001, China
| | - Rong Tian
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, MNR, Xiamen 361001, China
- Third Institute of Oceanography, Ministry of Natural Resources of China, Xiamen 361001, China
| | - Jinpei Yan
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, MNR, Xiamen 361001, China
- Third Institute of Oceanography, Ministry of Natural Resources of China, Xiamen 361001, China
| | - Jiehua Hu
- Xiamen Ocean Vocational College, Xiamen 361100, China
| | - Suqing Xu
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, MNR, Xiamen 361001, China
- Third Institute of Oceanography, Ministry of Natural Resources of China, Xiamen 361001, China
| | - Shuhui Zhao
- School of Tourism, Taishan University, Tai'an 271021, China
| | - Miming Zhang
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, MNR, Xiamen 361001, China
- Third Institute of Oceanography, Ministry of Natural Resources of China, Xiamen 361001, China
| | - Siying Dai
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, MNR, Xiamen 361001, China
- Third Institute of Oceanography, Ministry of Natural Resources of China, Xiamen 361001, China
| | - Hang Yang
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, MNR, Xiamen 361001, China
- Third Institute of Oceanography, Ministry of Natural Resources of China, Xiamen 361001, China
| | - Xiaoke Zhang
- Key Laboratory of Global Change and Marine Atmospheric Chemistry, MNR, Xiamen 361001, China
- Third Institute of Oceanography, Ministry of Natural Resources of China, Xiamen 361001, China
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Luo Z, Feng C, Yang J, Dai Q, Dai T, Zhang Y, Liang D, Feng Y. Assessing emission-driven changes in health risk of source-specific PM 2.5-bound heavy metals by adjusting meteorological covariates. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 927:172038. [PMID: 38552967 DOI: 10.1016/j.scitotenv.2024.172038] [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: 01/03/2024] [Revised: 03/05/2024] [Accepted: 03/26/2024] [Indexed: 04/15/2024]
Abstract
Heavy metals (HMs) in PM2.5 gain much attention for their toxicity and carcinogenic risk. This study evaluates the health risks of PM2.5-bound HMs, focusing on how meteorological conditions affect these risks against the backdrop of PM2.5 reduction trends in China. By applying a receptor model with a meteorological normalization technique, followed by health risk assessment, this work reveals emission-driven changes in health risk of source-specific HMs in the outskirt of Tianjin during the implementation of China' second Clean Air Action (2018-2020). Sources of PM2.5-bound HMs were identified, with significant contributions from vehicular emissions (on average, 33.4 %), coal combustion (26.3 %), biomass burning (14.1 %), dust (11.7 %), industrial boilers (9.7 %), and shipping emission and sea salt (4.7 %). The source-specific emission-driven health risk can be enlarged or dwarfed by the changing meteorological conditions over time, demonstrating that the actual risks from these source emissions for a given time period may be higher or smaller than those estimated by traditional assessments. Meteorology contributed on average 56.1 % to the interannual changes in source-specific carcinogenic risk of HMs from 2018 to 2019, and 5.6 % from 2019 to 2020. For the source-specific noncarcinogenic risk changes, the contributions were 38.3 % and 46.4 % for the respective periods. Meteorology exerts a more profound impact on daily risk (short-term trends) than on annual risk (long-term trends). Such meteorological impacts differ among emission sources in both sign and magnitude. Reduced health risks of HMs were largely from targeted regulatory measures on sources. Therefore, the meteorological covariates should be considered to better evaluate the health benefits attributable to pollution control measures in health risk assessment frameworks.
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Affiliation(s)
- Zhongwei Luo
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Chengliang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Jingyi Yang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China; Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
| | - Tianjiao Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China; Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Danni Liang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China; Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
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Liu J, Ma T, Chen J, Peng X, Zhang Y, Wang Y, Peng J, Shi G, Wei Y, Gao J. Insights into PM 2.5 pollution of four small and medium-sized cities in Chinese representative regions: Chemical compositions, sources and health risks. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170620. [PMID: 38320696 DOI: 10.1016/j.scitotenv.2024.170620] [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: 10/23/2023] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 02/09/2024]
Abstract
Fine particles (PM2.5) pollution is still a severe issue in some cities in China, where the chemical characteristics of PM2.5 remain unclear due to limited studies there. Herein, we focused on PM2.5 pollution in small and medium-sized cities in key urban agglomerations and conducted a comprehensive study on the PM2.5 chemical characteristics, sources, and health risks. In the autumn and winter of 2019-2020, PM2.5 samples were collected simultaneously in four small and medium-sized cities in four key regions: Dingzhou (Beijing-Tianjin-Hebei region), Weinan (Fenwei Plain region), Fukang (Northern Slope of the Tianshan Mountain region), and Bozhou (Yangtze River Delta region). The results showed that secondary inorganic ions (43.1 %-67.0 %) and organic matter (OM, 8.6 %-36.4 %) were the main components of PM2.5 in all the cities. Specifically, Fukang with the most severe PM2.5 pollution had the highest proportion of SO42- (31.2 %), while the dominant components in other cities were NO3- and OM. The Multilinear Engine 2 (ME2) analysis identified five sources of PM2.5 in these cities. Coal combustion contributed most to PM2.5 in Fukang, but secondary sources in other cities. Combined with chemical characteristics and ME2 analysis, it was preliminarily determined that the primary emission of coal combustion had an important contribution to high SO42- in Fukang. Potential source contribution function (PSCF) analysis results showed that regional transport played an important role in PM2.5 in Dingzhou, Weinan and Bozhou, while PM2.5 in Fukang was mainly affected by short-range transport from surrounding areas. Finally, the health risk assessment indicated Mn was the dominant contributor to the total non-carcinogenic risks and Cr had higher carcinogenic risks in all cities. The findings provide a scientific basis for formulating more effective abatement strategies for PM2.5 pollution.
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Affiliation(s)
- Jiayuan Liu
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Tong Ma
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Jianhua Chen
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xing Peng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Yuechong Zhang
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yali Wang
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jianfei Peng
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Guoliang Shi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Yuting Wei
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Jian Gao
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
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Wang J, Gao J, Che F, Wang Y, Lin P, Zhang Y. Dramatic changes in aerosol composition during the 2016-2020 heating seasons in Beijing-Tianjin-Hebei region and its surrounding areas: The role of primary pollutants and secondary aerosol formation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 849:157621. [PMID: 35901889 DOI: 10.1016/j.scitotenv.2022.157621] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 07/19/2022] [Accepted: 07/20/2022] [Indexed: 06/15/2023]
Abstract
With the implementation of a series of air pollution mitigation strategies during the past decade, great air quality improvements have been observed in the BTH region. Despite of significant decreases in gaseous pollutants, such as SO2 and NO2, the enhancement of secondary aerosol formation was observed. NO3- has surpassed SO42- and OM to become the dominant PM2.5 component. We find that the reduction of POC mainly dominated the decreasing trend of OC. As for secondary inorganic components, the key processes or factors controlling the spatial-temporal variation characteristics were different. The areas with large SO42- concentrations corresponded well to those with high SO2 concentrations, while the synchronized NO3- better followed spatial patterns in O3 than NO2. From 2016 to 2020, the response of SO42- to SO2 was close to a linear function, while the reaction of NO3- to the decrease of NO2 displayed nonlinear behavior. Such different relationships indicated that SO42- was predominantly controlled by SO2, while NO3- was not only related to NO2 but also determined by the secondary conversion process. The ratios of SO42-, NO3-, NH4+, and OC to EC between 2016 and 2020 were generally higher than 1 in typical BTH cities, and the ratio of NO3- to EC was exceptionally high, with a range reaching up to 200 %. Besides, this ratio coincided well with the enhancement of Ox, indicating the potential role of Ox to secondary NO3- formation. The diurnal cycle of NO3-, O3, and NO2 concentration change rate indicated that the relative increase of O3 during nighttime may offset the effectiveness of NOX emission reduction. This study provided observational evidence of enhanced secondary NO3- formation with the rising trend of atmospheric oxidation and emphasized the importance of nighttime chemistry for NO3- formation in the BTH region.
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Affiliation(s)
- Jiaqi Wang
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jian Gao
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Fei Che
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yali Wang
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Pengchuan Lin
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yuechong Zhang
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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