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Li Y, Geng Y, Hu X, Yin X. Seasonal differences in sources and formation processes of PM 2.5 nitrate in an urban environment of North China. J Environ Sci (China) 2022; 120:94-104. [PMID: 35623777 DOI: 10.1016/j.jes.2021.08.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 07/11/2021] [Accepted: 08/11/2021] [Indexed: 06/15/2023]
Abstract
Nitrate (NO3-) has been the dominant ion of secondary inorganic aerosols (SIAs) in PM2.5 in North China. Tracking the formation mechanisms and sources of particulate nitrate are vital to mitigate air pollution. In this study, PM2.5 samples in winter (January 2020) and in summer (June 2020) were collected in Jiaozuo, China, and water-soluble ions and (δ15N, δ18O)-NO3- were analyzed. The results showed that the increase of NO3- concentrations was the most remarkable with increasing PM2.5 pollution level. δ18O-NO3- values for winter samples (82.7‰ to 103.9‰) were close to calculated δ18O-HNO3 (103‰ ± 0.8‰) values by N2O5 pathway, while δ18O-NO3- values (67.8‰ to 85.7‰) for summer samples were close to calculated δ18O-HNO3 values (61‰ ± 0.8‰) by OH oxidation pathway, suggesting that PM2.5 nitrate is largely from N2O5 pathway in winter, while is largely from OH pathway in summer. Averaged fractional contributions of PN2O5+H2O were 70% and 39% in winter and summer sampling periods, respectively, those of POH were 30% and 61%, respectively. Higher δ15N-NO3- values for winter samples (3.0‰ to 14.4‰) than those for summer samples (-3.7‰ to 8.6‰) might be due to more contributions from coal combustion in winter. Coal combustion (31% ± 9%, 25% ± 9% in winter and summer, respectively) and biomass burning (30% ± 12%, 36% ± 12% in winter and summer, respectively) were the main sources using Bayesian mixing model. These results provided clear evidence of particulate nitrate formation and sources under different PM2.5 levels, and aided in reducing atmospheric nitrate in urban environments.
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Affiliation(s)
- Yanli Li
- Institute of Resources and Environment, Henan Polytechnic University, Jiaozuo 454000, China.
| | - Yaping Geng
- Institute of Resources and Environment, Henan Polytechnic University, Jiaozuo 454000, China
| | - Xiaomian Hu
- Institute of Resources and Environment, Henan Polytechnic University, Jiaozuo 454000, China
| | - Xijie Yin
- Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361000, China
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Numerical Simulation of Topography Impact on Transport and Source Apportionment on PM2.5 in a Polluted City in Fenwei Plain. ATMOSPHERE 2022. [DOI: 10.3390/atmos13020233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The unique energy structure, high intensity of coal production, and complex terrain, make Fenwei Plain a highly polluted region in China. In this study, we characterized the transport characteristic and sources of PM2.5 (the fraction of particulate matter ≤ 2.5 μm) in Sanmenxia, a polluted city in canyon terrain. The results showed that special topography in Sanmenxia had an important role in the transport of particulates. Sanmenxia is located between two northeast-southwest facing mountains, showing a special local circulation. The local circulation was dominated by a downslope wind at nighttime, while the cross−mountain airflow and zonal wind were dominant during the daytime in the canyon terrain. PM2.5 accumulated near Sanmenxia with the influence of downslope, zonal wind, and topography. The main regional transport paths could be summarized into an eastern path, a northern path, and a western path during the severe haze episodes. The PM2.5 source apportionment revealed by an on-line tracer-tagged of the Nested Air Quality Prediction Model System (NAQPMS) showed that the main regional sources of Sanmenxia were Yuncheng, Sanmenxia, and Weinan. The contribution to PM2.5 concentration in Sanmenxia was 39%, 25%, and 11%, respectively. The northern path had the most important impact on Sanmenxia. The results can provide scientific basis for the establishment of severe haze control in Sanmenxia and regional joint control.
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Wang Q, Li J, Yang J, Chen Y, Li Y, Li S, Xie C, Chen C, Wang L, Wang L, Wang W, Tong S, Sun Y. Seasonal characterization of aerosol composition and sources in a polluted city in Central China. CHEMOSPHERE 2020; 258:127310. [PMID: 32947673 DOI: 10.1016/j.chemosphere.2020.127310] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 05/28/2020] [Accepted: 06/01/2020] [Indexed: 06/11/2023]
Abstract
We characterized the aerosol composition and sources of particulate matter (PM) in Sanmenxia, a polluted city located in the Fen-Wei Plain region of Central China. The PM2.5 concentration decreased by 18% from 72 μg m-3 in 2014 to 59 μg m-3 in 2019. All chemical species presented pronounced seasonal variations, with their highest concentrations in winter due to enhanced emissions and the frequent stagnant meteorological conditions. Nitrate was the major fraction of PM2.5 during all seasons (35-41%) except summer (25%), while sulfate was a dominant species in summer (29%) compared to other seasons (16-18%) from July 2018 to June 2019. The detailed analysis of a wintertime severe haze episode that lasted for approximately half a month demonstrated that secondary aerosols, including secondary organic aerosol, sulfate, nitrate, and ammonium, contributed 89% to non-refractory PM1 (NR-PM1), indicating the remarkable role of secondary aerosol formation in air pollution in Sanmenxia. Positive matrix factorization analysis further showed considerably enhanced low-volatility oxygenated organic aerosol (OA) and hydrocarbon-like OA during severe haze episodes, while significant contributions in semi-volatile oxygenated OA and coal combustion OA during clean periods. Severe pollution events in the city were generally associated with air masses from the southwest, and we also found that aerosol species, especially secondary aerosol species, showed distinct forenoon increases that were caused by the subsidence of air pollutants aloft. Our results highlight that future air quality improvement would benefit substantially from a more efficient control of gaseous precursors, particularly the NOx emissions from industry and vehicle emissions.
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Affiliation(s)
- Qingqing Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; University of Chinese Academy of Sciences, Beijing, 100049, 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; University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Jinxing Yang
- Sanmenxia Environmental Monitoring Station, Sanmenxia, 472400, China
| | - Yong Chen
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yanyu Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shiyao Li
- 3 Clear Technology Co., Ltd, Beijing, 100029, China
| | - Conghui Xie
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Chun Chen
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lingling Wang
- Henan Environmental Monitoring Center Station, Zhengzhou, 450000, China
| | - Lin Wang
- Sanmenxia Environmental Monitoring Station, Sanmenxia, 472400, China
| | - Weigang Wang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences (BNLMS), 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, Beijing National Laboratory for Molecular Sciences (BNLMS), CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, 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; 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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