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Observations by Ground-Based MAX-DOAS of the Vertical Characters of Winter Pollution and the Influencing Factors of HONO Generation in Shanghai, China. REMOTE SENSING 2021. [DOI: 10.3390/rs13173518] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Analyzing vertical distribution characters of air pollutants is conducive to study the mechanisms under polluted atmospheric conditions. Nitrous acid (HONO) is a kind of crucial species in photochemical cycles. Exploring the influence and sources of HONO in air pollution at different altitudes offers some insights into the research of tropospheric oxidation chemistry processes. Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements were conducted in Shanghai, China, from December 2017 to March 2018 to investigate vertical distributions and diurnal variations of trace gases (NO2, HONO, HCHO, SO2, and water vapor) and aerosol extinction coefficient in the boundary layer. Aerosol and NO2 showed decreasing profile exponentially, SO2 and HCHO concentrations were observed relatively high values in the middle layer. SO2 was caused by industrial emissions, while HCHO was from secondary sources. As for HONO, below 0.82 km, the heterogeneous reactions of NO2 impacted on forming HONO, while in the upper layers, vertical diffusion might be the dominant source. The contribution of OH production from HONO photolysis at different altitudes was mainly controlled by the concentration of HONO. MAX-DOAS measurements characterize the vertical structure of air pollutants in Shanghai and provide further understanding for HONO formation, which can help deploy advanced measurement platforms of regional air pollution over eastern China.
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Sánchez-Balseca J, Pérez-Foguet A. Spatio-temporal air pollution modelling using a compositional approach. Heliyon 2020; 6:e04794. [PMID: 32984572 PMCID: PMC7495062 DOI: 10.1016/j.heliyon.2020.e04794] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/26/2020] [Accepted: 08/24/2020] [Indexed: 01/04/2023] Open
Abstract
Air pollutant data are compositional in character because they describe quantitatively the parts of a whole (atmospheric composition). However, it is common to use air pollutant concentrations in statistical models without considering this characteristic of the data and, therefore, without control of common statistical problems, such as spurious correlations and subcompositional incoherence. This paper now proposes a daily multivariate spatio-temporal model with a compositional approach. The air pollution spatio-temporal model is based on a dynamic linear modelling framework with Bayesian inference. The novel modelling methodology was applied in an urban area for carbon monoxide (CO, mg·m-3), sulfur dioxide (SO2, μg·m-3), ozone (O3, μg·m-3), nitrogen dioxide (NO2, μg·m-3), and particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5, μg·m-3). The proposal complemented and improved the conventional approach in air pollution modelling. The main improvements come from a fast multivariate data description, high spatial-correlation, and adequate modelling of air pollutants with high variability.
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Affiliation(s)
- Joseph Sánchez-Balseca
- Research Group on Engineering Sciences and Global Development (EScGD), Civil and Environmental Engineering Department, Universitat Politècnica de Catalunya – BarcelonaTech (UPC), Spain
| | - Agustí Pérez-Foguet
- Research Group on Engineering Sciences and Global Development (EScGD), Civil and Environmental Engineering Department, Universitat Politècnica de Catalunya – BarcelonaTech (UPC), Spain
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Wu R, Song X, Chen D, Zhong L, Huang X, Bai Y, Hu W, Ye S, Xu H, Feng B, Wang T, Zhu Y, Fang J, Liu S, Chen J, Wang X, Zhang Y, Huang W. Health benefit of air quality improvement in Guangzhou, China: Results from a long time-series analysis (2006-2016). ENVIRONMENT INTERNATIONAL 2019; 126:552-559. [PMID: 30852442 DOI: 10.1016/j.envint.2019.02.064] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2018] [Revised: 02/25/2019] [Accepted: 02/25/2019] [Indexed: 05/22/2023]
Abstract
Numerous epidemiologic studies on adverse health effects of air pollution have been well documented; however, assessment on health benefits of air quality improvement from air pollution control measures has been limited in developing countries. We assessed the mortality benefits associated with air pollution improvement over 11 years in Guangzhou, China (2006-2016). A time series analysis with Generalized additive Poisson models was used to estimate mortality effects of ozone (O3) and nitrogen dioxide (NO2), adjusting for time trend, day of week, public holiday, temperature and relative humidity. We further estimated the changes in mortality burden of O3 and NO2, including attributable fraction (AF, in %) and attributable mortality (AM, in number of death) during study period. We lastly estimated mortality effects during the 2010 Asian Games (November 12 to December 18, 2010) compared to a baseline period consisting of 4-week before and 4-week after the game. During the study period, average annual concentrations of NO2 decreased from 42.3 μg/m3 in 2006 to 33.8 μg/m3 in 2016; while O3 levels remained stable over time. We observed significant increases in mortality of O3 and NO2, with approximately linear exposure-response relationships. In specific, each increase of 10 μg/m3 in O3 and NO2 at 2 prior days was associated with increases of 0.60% (95% confidence interval (CI): 0.47, 0.74) and 1.89% (95%CI: 1.49, 2.29) in total mortality, respectively. We further estimated that AF on total mortality attributed to NO2 decreased from 1.38% (95%CI: 1.09, 1.68) in 2006-2010 to 0.43% (95%CI: 0.34, 0.52) in 2011-2016, corresponding to AM on total mortality of 2496 deaths (95%CI: 1964, 3033) to 1073 deaths (95%CI: 846, 1301). During the 2010 Asian Games, we observed decrease in total mortality of 9.3% (95%CI: -15.0, -3.2) in comparison with that observed in the baseline period. Similar mortality benefits in cardiovascular diseases were also observed. Our results showed reduced mortality burden from air pollution improvement in Guangzhou in recent years, which provide strong rationale for continuing to reduce air pollution through comprehensive and rigorous air quality management in the area.
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Affiliation(s)
- Rongshan Wu
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China
| | - Xiaoming Song
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China
| | - Duohong Chen
- Environmental Monitoring Center of Guangdong Province, Guangzhou, Guangdong Province, China
| | - Liuju Zhong
- Guangdong Polytechnic of Environmental Protection Engineering, Foshan, Guangdong Province, China.
| | - Xiaoliang Huang
- Government Affairs Service Center of Health Department of Guangdong Province, China
| | - Yingchen Bai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Wei Hu
- Government Affairs Service Center of Health Department of Guangdong Province, China
| | - Siqi Ye
- Environmental Monitoring Center of Guangdong Province, Guangzhou, Guangdong Province, China
| | - Hongbing Xu
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China
| | - Baihuan Feng
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China
| | - Tong Wang
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China
| | - Yutong Zhu
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China
| | - Jiakun Fang
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China
| | - Shuo Liu
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China
| | - Jie Chen
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China
| | - Xuemei Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong Province, China
| | - Yuanhang Zhang
- Department of Environmental Sciences, Peking University College of Environmental Science and Engineering, Beijing, China
| | - Wei Huang
- Department of Occupational and Environmental Health, Peking University School of Public Health, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University Institute of Environmental Medicine, Beijing, China.
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