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Liu P, Dong J, Song H, Zheng Y, Shen X, Wang C, Wang Y, Yang D. Response of fine particulate matter and ozone concentrations to meteorology and anthropogenic precursors over the "2+26" cities of northern China. CHEMOSPHERE 2024; 352:141439. [PMID: 38342145 DOI: 10.1016/j.chemosphere.2024.141439] [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: 07/18/2023] [Revised: 02/02/2024] [Accepted: 02/09/2024] [Indexed: 02/13/2024]
Abstract
Analyzing the influencing factors of fine particulate matter and ozone formation and identifying the coupling relationship between the two are the basis for implementing the synergistic pollutants control. However, the current research on the synergistic relationship between the two still needs to be further explored. Using the Geodetector model, we analyzed the effects of meteorology and emissions on fine particulate matter and ozone concentrations over the "2 + 26" cities at multiple timescales, and also explored the coupling relationship between the two pollutants. Fine particulate matter concentrations showed overall decreasing trends on inter-season and inter-annual scale from 2015 to 2021, whereas ozone concentrations showed overall increasing trends. While ozone concentrations displayed an inverted U-shaped distribution from month to month, fine particulate matter concentrations displayed a U-shaped fluctuation. On inter-annual scale, climatic factors, with planet boundary layer height as the main determinant, have higher effects for both pollutants than human precursors. In summer and autumn, sunshine duration had the most influence on fine particulate matter, while planet boundary layer height was the greatest factor in winter. Fine particulate matter is the leading impacting factor on ozone concentrations in summer, and there were positive associations between them on both annual and seasonal scale. The impact of nitrogen oxides and volatile organic compounds for both pollutants concentrations varied significantly between seasons. The two pollutants concentration were enhanced by the interactions between the various components. On inter-annual scale, interactions between the planet boundary layer height and other factors dominated the concentrations of the two pollutants, whereas in summer, interactions between fine particulate matter and other factors dominated the concentrations of ozone. The study has implications for the treatment of atmospheric pollution in China and other nations and can serve as an important reference for the creation of integrated atmospheric pollution regulation policies over the "2 + 26" cities.
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Affiliation(s)
- Pengfei Liu
- Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, 475004, China; College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China; Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China.
| | - Junwu Dong
- Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, 475004, China; College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China; College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China.
| | - Hongquan Song
- College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China; Institute of Urban Big Data, College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China; Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, 475004, China.
| | - Yiwen Zheng
- College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China; Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, 475004, China.
| | - Xiaoyu Shen
- Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, 475004, China.
| | - Chaokun Wang
- College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China; Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, 475004, China.
| | - Yansong Wang
- College of Geography and Environmental Science, Henan University, Kaifeng, 475004, China; Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng, 475004, China.
| | - Dongyang Yang
- Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, 475004, China.
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Sun Q, Liu J, Yang Y, Chen Y, Liu D, Ye F, Dong B, Zhang Q. Association of residential land cover and wheezing among children and adolescents: A cross-sectional study in five provinces of China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 343:123191. [PMID: 38135141 DOI: 10.1016/j.envpol.2023.123191] [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: 07/07/2023] [Revised: 12/11/2023] [Accepted: 12/17/2023] [Indexed: 12/24/2023]
Abstract
The association between residential land cover (RLC) and wheezing remains poorly understood. This study aimed to investigate the association between RLC and wheezing in childhood and adolescence. A cross-sectional survey was conducted among children and adolescents in five provinces of China. Land cover data were obtained from the Cross-Resolution Land-Cover mapping framework based on noisy label learning, classifying land cover into five categories: cropland, forest, grass/shrubland, wetland, and impervious. Generalized linear mixed models were employed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the risk of wheezing. Mediation analysis was employed to investigate whether ambient particulate matter (PM2.5) acts as a mediator in the association between RLC and wheezing. A total of 12,875 participants were included in the study, comprising 318 patients and 12,557 controls. Cropland500m was significantly associated with decreased odds of wheezing (OR: 0.929, 95% CI: 0.879-0.982), while impervious surfaces500m significantly was associated with increased odds of wheezing (OR: 1.056, 95% CI: 1.019-1.096) in all participants. In the stratified analysis, significant differences were found in the main outcomes between the adolescence group (age ≥10 years) and the childhood group (age <10 years) (Pinteraction < 0.05), while no significant differences were observed between the southern and northern regions, or between male and female respondents. Mediation analysis revealed that PM2.5 partially mediated the association between cropland500m and impervious surfaces500m with wheezing. RLC plays a significant role in wheezing during childhood and adolescence, with cropland offering protection and impervious surfaces posing a heightened risk.
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Affiliation(s)
- Qi Sun
- National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Jing Liu
- National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Yang Yang
- National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Yuanmei Chen
- National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Die Liu
- National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Fang Ye
- National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China
| | - Bin Dong
- Institute of Child and Adolescent Health of Peking University, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Qi Zhang
- National Center for Respiratory Medicine, State Key Laboratory of Respiratory Health and Multimorbidity, National Clinical Research Center for Respiratory Diseases, Institute of Respiratory Medicine, Chinese Academy of Medical Sciences, Department of Pediatrics, China-Japan Friendship Hospital, Beijing, China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
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Sharma A, Srivastava S, Mitra D, Singh RP. Spatiotemporal distribution of air pollutants during a heat wave-induced forest fire event in Uttarakhand. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:110133-110160. [PMID: 37779123 DOI: 10.1007/s11356-023-29906-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 09/12/2023] [Indexed: 10/03/2023]
Abstract
Prevailing dry conditions and rainfall deficit during the spring season in North India led to heat wave conditions which resulted in widespread and intense forest fire events in the Himalayan state of Uttarakhand during April 16-30, 2022. A total of 7589 active fires were detected by VIIRS during the second half of April 2022 compared to 1558 during the first half. The TROPOMI observed total column values of CO and NO2 increased by 4.4% and 11.7%, respectively during April 16-30, 2022 with respect to April 1-15, 2022. A noticeable increase in surface level concentration of trace gases was also observed at Dehradun. In situ measurements of CO, NOx, and O3 during April 16-30, 2022 show an increase of 133, 35, and 6% compared to previous year observations during the same period. Weather Research and Forecasting model with chemistry (WRF-Chem) is utilized to quantitatively estimate the contribution of this event on the distribution of air pollutants over this state. The model results were evaluated against ERA5 reanalysis, upper air soundings, and TROPOMI-retrieved total column density (TCD) of CO, NO2, and O3. Two simulations with (Fire) and without (NoFire) biomass burning emissions input were performed to quantify the contribution of forest fires to the concentration of trace gases and particulates. The CO, NO2, and O3 emitted/produced from forest fire over Uttarakhand during April 2022 contributed approximately 39.95, 35.73, and 9.97% to the surface concentration of respective gas. In the case of aerosols, it was around 71.20, 71.44, and 33.62% for PM2.5, PM10, and BC respectively. The vertical profile analysis of pollutants revealed that extreme forest fire events can perturb the distribution of air pollutants from the surface up to 450 hPa.
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