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Salehi M, Almasi Hashiani A, Karimi B, Mirhoseini SH. Estimation of health-related and economic impacts of PM2.5 in Arak, Iran, using BenMAP-CE. PLoS One 2023; 18:e0295676. [PMID: 38127954 PMCID: PMC10734986 DOI: 10.1371/journal.pone.0295676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023] Open
Abstract
Ambient air quality is one of the most critical threats to human health. In this study, the health and economic benefits of reducing PM2.5 were estimated in the city of Arak during the period of 2017-2019. The concentration data were obtained from the Environmental Protection Organization of Central Province, while the demographic data were obtained from the website of the Iran Statistics Center. The number of premature deaths from all causes, ischemic heart disease, chronic obstructive pulmonary disease, and lung cancer, attributable to PM2.5 pollution was estimated using the Environmental Benefits Mapping and Analysis Program-Comprehensive Version (BenMAP_CE) to limit the guidelines of the World Health Organization. The results showed that improving air quality in 2017, 2018, and 2019 in Arak could prevent the deaths of 729, 654, and 460 people, respectively. The number of years of life lost (YLL) in 2017, 2018, and 2019 was 11383, 10362, and 7260 years, respectively. The total annual economic benefits of reducing the PM2.5 concentration in Arak under the proposed scenarios in 2017, 2018, and 2019 were estimated to be 309,225,507, 262,868,727, and 182,224,053 USD, respectively, using the statistical life method (VSL). Based on the results of this study, there are significant health and economic benefits to reducing PM2.5 concentrations in Arak City. Therefore, planning and adopting control policies to reduce air pollution in this city are necessary.
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Affiliation(s)
- Maryam Salehi
- Department of Environmental Health Engineering, School of Health, Arak University of Medical Sciences, Arak, Iran
| | - Amir Almasi Hashiani
- Department of Epidemiology, School of Health, Arak University of Medical Sciences, Arak, Iran
| | - Behrooz Karimi
- Department of Environmental Health Engineering, School of Health, Arak University of Medical Sciences, Arak, Iran
| | - Seyed Hamed Mirhoseini
- Department of Environmental Health Engineering, School of Health, Arak University of Medical Sciences, Arak, Iran
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2
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Camilleri SF, Kerr GH, Anenberg SC, Horton DE. All-Cause NO 2-Attributable Mortality Burden and Associated Racial and Ethnic Disparities in the United States. Environ Sci Technol Lett 2023; 10:1159-1164. [PMID: 38106529 PMCID: PMC10720462 DOI: 10.1021/acs.estlett.3c00500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 10/19/2023] [Accepted: 10/23/2023] [Indexed: 12/19/2023]
Abstract
Nitrogen dioxide (NO2) is a regulated pollutant that is associated with numerous health impacts. Recent advances in epidemiology indicate high confidence linking NO2 exposure with increased mortality, an association that recent studies suggest persists even at concentrations below regulatory thresholds. While large disparities in NO2 exposure among population subgroups have been reported, U.S. NO2-attributable mortality rates and their disparities remain unquantified. Here we provide the first estimate of NO2-attributable all-cause mortality across the contiguous U.S. (CONUS) at the census tract-level. We leverage fine-scale, satellite-informed, land use regression model NO2 concentrations and census tract-level baseline mortality data to characterize the associated disparities among different racial/ethnic subgroups. Across CONUS, we estimate that the NO2-attributable all-cause mortality is ∼170,850 (95% confidence interval: 43,970, 251,330) premature deaths yr-1 with large variability across census tracts and within individual cities. Additionally, we find that higher NO2 concentrations and underlying susceptibilities for predominately Black communities lead to NO2-attributable mortality rates that are ∼47% higher compared to CONUS-wide average rates. Our results highlight the substantial U.S. NO2 mortality burden, particularly in marginalized communities, and motivate adoption of more stringent standards to protect public health.
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Affiliation(s)
- Sara F Camilleri
- Department
of Earth and Planetary Sciences, Northwestern
University, Evanston, Illinois 60208, United States
| | - Gaige Hunter Kerr
- Department
of Environmental and Occupational Health, The George Washington University, Washington, DC 20052, United States
| | - Susan C Anenberg
- Department
of Environmental and Occupational Health, The George Washington University, Washington, DC 20052, United States
| | - Daniel E Horton
- Department
of Earth and Planetary Sciences, Northwestern
University, Evanston, Illinois 60208, United States
- Trienens
Institute for Sustainability and Energy, Northwestern University, Evanston, Illinois 60208, United States
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3
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Tsai SS, Yang CY. Health benefits of reducing ambient levels of fine particulate matter: a mortality impact assessment in Taiwan. J Toxicol Environ Health A 2023; 86:653-660. [PMID: 37489027 DOI: 10.1080/15287394.2023.2233985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
While numerous studies have found a relationship between long-term exposure to airborne fine particulate matter (PM2.5) and higher risk of death, few investigations examined the contribution that a reduction of exposure to ambient PM2.5 levels might exert on mortality rates. This study aimed to collect data on changes in annual average ambient levels of PM2.5 from 2006 to 2020 and consequent health impact in public health in 65 municipalities in Taiwan. Avoidable premature mortality was used here as an indicator of adverse health impact or health benefits. Annual PM2.5 levels were averaged for the years 2006, 2010, and 2020. In accordance with World Health Organization (WHO) methodology, differences were estimated in the number of deaths attributed to ambient PM2.5 exposure which were derived from concentration-response data from prior epidemiological studies. PM2.5 concentrations were found to have been decreased markedly throughout Taiwan over the two-decade study. As the PM2.5 concentrations fell, so was the health burden as evidenced by number of deaths concomitantly reduced from 22.4% in 2006 to 8.47% in 2020. Data demonstrated that reducing annual mean levels of PM2.5 to PM10 ug/m3 was associated with decrease in the total burden of mortality, with a 2.22-13.18% fall in estimated number of PM2.5-related deaths between 2006 and 2020. Based upon these results, these declines in ambient PM2.5 levels were correlated with significant improvement in public health (health benefits) and diminished number of deaths in Taiwan.
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Affiliation(s)
- Shang-Shyue Tsai
- Department of Healthcare Administration, I-Shou University, Kaohsiung, Taiwan
| | - Chun-Yuh Yang
- Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
- National Institute of Environmental Health Sciences, National Health Research Institute, Miaoli, Taiwan
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4
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Wang J, Gao A, Li S, Liu Y, Zhao W, Wang P, Zhang H. Regional joint PM 2.5-O 3 control policy benefits further air quality improvement and human health protection in Beijing-Tianjin-Hebei and its surrounding areas. J Environ Sci (China) 2023; 130:75-84. [PMID: 37032044 DOI: 10.1016/j.jes.2022.06.036] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 06/12/2022] [Accepted: 06/25/2022] [Indexed: 06/19/2023]
Abstract
Beijing-Tianjin-Hebei and its surrounding areas (hereinafter referred to as "2+26" cities) are one of the most severe air pollution areas in China. The fine particulate matter (PM2.5) and surface ozone (O3) pollution have aroused a significant concern on the national scale. In this study, we analyzed the pollution characteristics of PM2.5 and O3 in "2+26" cities, and then estimated the health burden and economic loss before and after the implementation of the joint PM2.5-O3 control policy. During 2017-2019, PM2.5 concentration reduced by 19% while the maximum daily 8 hr average (MDA8) O3 stayed stable in "2+26" cities. Spatially, PM2.5 pollution in the south-central area and O3 pollution in the central region were more severe than anywhere else. With the reduction in PM2.5 concentration, premature deaths from PM2.5 decreased by 18% from 2017 to 2019. In contrast, premature deaths from O3 increased by 5%. Noticeably, the huge potential health benefits can be gained after the implementation of a joint PM2.5-O3 control policy. The premature deaths attributed to PM2.5 and O3 would be reduced by 91.6% and 89.1%, and the avoidable economic loss would be 60.8 billion Chinese Yuan (CNY), and 68.4 billion CNY in 2035 compared with that in 2019, respectively. Therefore, it is of significance to implement the joint PM2.5-O3 control policy for improving public health and economic development.
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Affiliation(s)
- Junyi Wang
- Hebei GEO University, Hebei Center for Ecological and Environmental Geology Research, Hebei Province Key Laboratory of Sustained Utilization and Development of Water Resources, Hebei Province Collaborative Innovation Center for Sustainable Utilization of Water Resources and Optimization of Industrial Structure, Shijiazhuang 050031, China
| | - Aifang Gao
- Hebei GEO University, Hebei Center for Ecological and Environmental Geology Research, Hebei Province Key Laboratory of Sustained Utilization and Development of Water Resources, Hebei Province Collaborative Innovation Center for Sustainable Utilization of Water Resources and Optimization of Industrial Structure, Shijiazhuang 050031, China.
| | - Shaorong Li
- Hebei GEO University, Hebei Center for Ecological and Environmental Geology Research, Hebei Province Key Laboratory of Sustained Utilization and Development of Water Resources, Hebei Province Collaborative Innovation Center for Sustainable Utilization of Water Resources and Optimization of Industrial Structure, Shijiazhuang 050031, China
| | - Yuehua Liu
- Hebei GEO University, Hebei Center for Ecological and Environmental Geology Research, Hebei Province Key Laboratory of Sustained Utilization and Development of Water Resources, Hebei Province Collaborative Innovation Center for Sustainable Utilization of Water Resources and Optimization of Industrial Structure, Shijiazhuang 050031, China
| | - Weifeng Zhao
- Hebei Provincial Academy of Environmental Science, Shijiazhuang 050037, China
| | - Peng Wang
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai 200438, China; Shanghai Qi Zhi Institute, Shanghai 200232, China; IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China.
| | - Hongliang Zhang
- IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China; Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China; Institute of Eco-Chongming (SIEC), Shanghai 200062, China
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5
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Chen B, Wang Y, Huang J, Zhao L, Chen R, Song Z, Hu J. Estimation of near-surface ozone concentration and analysis of main weather situation in China based on machine learning model and Himawari-8 TOAR data. Sci Total Environ 2023; 864:160928. [PMID: 36539084 DOI: 10.1016/j.scitotenv.2022.160928] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 11/21/2022] [Accepted: 12/10/2022] [Indexed: 06/17/2023]
Abstract
Ozone (O3) is an important greenhouse gas in the atmosphere. Stratospheric ozone protects human beings, but high near-surface ozone concentrations threaten environment and human health. Owing to the uneven distribution of ground-monitoring stations and the low time resolution of polar orbiting satellites, it is difficult to accurately evaluate the refinement and synergistic pollution of near-surface ozone in China. Besides, atmospheric circulation patterns also affect ozone concentrations greatly. In this study, a new generation of geostationary satellite is used to estimate the hourly near-surface ozone concentration with a spatial resolution of 0.05°. First, the Pearson correlation coefficient and maximum information coefficient were used to study the correlation between the top of atmospheric radiation (TOAR) of Himawari-8 satellite and O3 concentration; seven TOAR channels were selected. Second, based on an interpretable deep learning model, the hourly ozone concentration in China from September 2015 to August 2021 was obtained using the TOAR-O3 model. Finally, the self-organizing map method was used to determine six major summer weather circulation patterns in China. The results showed that (1) the near-surface O3 concentration can be accurately estimated; the R2 (RMSE: μg/m3) values of the daily, monthly, and annual tenfold cross validation results were 0.91 (12.74), 0.97 (5.64), and 0.98 (1.75), respectively. The feature importance of the model showed that the temperature, TOAR, and boundary layer height contributed 38 %, 22 %, and 13 %, respectively. (2) The O3 concentration showed obvious spatiotemporal difference and gradually increased from 10:00 to 15:00 (Beijing time) every day. In most areas of China, O3 concentration had increased significantly. (3) The O3 concentration in northern China was the highest under the circulation pattern of the Meiyu front over the Yangtze River Delta, while in southern China, it was the highest under the circulation pattern of the northeast cold vortex controlling most of China.
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Affiliation(s)
- Bin Chen
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China.
| | - Yixuan Wang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Jianping Huang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Lin Zhao
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Ruming Chen
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Zhihao Song
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
| | - Jiashun Hu
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou 730000, China
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6
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Gauthier-Manuel H, Bernard N, Boilleaut M, Giraudoux P, Pujol S, Mauny F. Spatialized temporal dynamics of daily ozone concentrations: Identification of the main spatial differences. Environ Int 2023; 173:107859. [PMID: 36898173 DOI: 10.1016/j.envint.2023.107859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 02/14/2023] [Accepted: 02/27/2023] [Indexed: 06/18/2023]
Abstract
Ground-level ozone (O3) is one of the most worrisome air pollutants regarding environmental and health impacts. There is a need for a deeper understanding of its spatial and temporal dynamics. Models are needed to provide continuous temporal and spatial coverage in ozone concentration data with a fine resolution. However, the simultaneous influence of each determinant of ozone dynamics, their spatial and temporal variations, and their interaction make the resulting dynamics of O3 concentrations difficult to understand. This study aimed to i) identify different classes of temporal dynamics of O3 at daily and 9 km2 resolution over a long-term period of 12 years, ii) identify the potential determinants of these dynamics and, iii) explore the spatial distribution of the potential classes of temporal dynamics on a spatial continuum and over about 1000 km2. Thus, 126 time series of 12-year daily ozone concentrations were classified using dynamic time warping (DTW) and hierarchical clustering (study area centered on Besançon, eastern France). The different temporal dynamics obtained differed on elevation, ozone levels, proportions of urbanized and vegetated surfaces. We identified different daily ozone temporal dynamics, spatially structured, that overlapped areas called urban, suburban and rural. Urbanization, elevation and vegetation acted as determinants simultaneously. Individually, elevation and vegetated surface were positively correlated with O3 concentrations (r = 0.84 and r = 0.41, respectively), while the proportion of urbanized area was negatively correlated with O3 (r = -0.39). An increasing ozone concentration gradient was observed from urban to rural areas and was reinforced by the elevation gradient. Rural areas were both subject to higher ozone levels (p < 0.001), least monitoring and lower predictability. We identified main determinants of the temporal dynamics of ozone concentrations. The joint influence of determinants was also synthesized. This study proposed a systematic, and reproducible way to build exposure area mapping.
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Affiliation(s)
- Honorine Gauthier-Manuel
- Chrono-environnement UMR 6249, CNRS, Université de Franche-Comté, F-25000 Besançon, France; Unité de méthodologie en recherche clinique, épidémiologie et santé publique (uMETh), Inserm CIC 1431, Centre Hospitalier Universitaire de Besançon, 25030, Besançon Cedex, France.
| | - Nadine Bernard
- Chrono-environnement UMR 6249, CNRS, Université de Franche-Comté, F-25000 Besançon, France; Centre National de La Recherche Scientifique, UMR 6049, Laboratoire ThéMA, Université de Bourgogne Franche-Comté, 25000 Besançon, France
| | | | - Patrick Giraudoux
- Chrono-environnement UMR 6249, CNRS, Université de Franche-Comté, F-25000 Besançon, France
| | - Sophie Pujol
- Chrono-environnement UMR 6249, CNRS, Université de Franche-Comté, F-25000 Besançon, France; Unité de méthodologie en recherche clinique, épidémiologie et santé publique (uMETh), Inserm CIC 1431, Centre Hospitalier Universitaire de Besançon, 25030, Besançon Cedex, France
| | - Frédéric Mauny
- Chrono-environnement UMR 6249, CNRS, Université de Franche-Comté, F-25000 Besançon, France; Unité de méthodologie en recherche clinique, épidémiologie et santé publique (uMETh), Inserm CIC 1431, Centre Hospitalier Universitaire de Besançon, 25030, Besançon Cedex, France
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7
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Wang X, Liu X, Wang L, Dong Z, Han X. Analysis of the Temporal Distribution Characteristics of PM2.5 Concentration and Risk Evaluation of Its Inhalation Exposure. Environ Sci Pollut Res Int 2022; 29:71460-71473. [PMID: 35595906 DOI: 10.1007/s11356-022-20511-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 04/25/2022] [Indexed: 06/15/2023]
Abstract
PM2.5 poses a threat to human health. It is important to evaluate the potential risk of PM2.5 inhalation exposure when people are located in different spatiotemporal activity locations. In this study, the PM2.5 concentration was detected by the atmospheric cruise monitoring system (ACMS), a new detection technology used for city-wide PM2.5 concentration monitoring. People were divided into eight categories of five typical activity patterns, including rest (R), sedentary behavior (SB), light physical activity (LPA), moderate physical activity (MPA), and vigorous physical activity (VPA). The PM2.5 inhalation exposure risk was then estimated for these typical activities. The research results showed that the time sequence data of the ACMS had a similar tendency to change as those of the traditional air quality monitoring stations (AQMS). Although both passed the stationarity test, the relative error (RE) of the monthly average PM2.5 concentration between the ACMS and AQMS was 7.5-14%. RE was usually lower when the individual air quality index (IAQI) of PM2.5 was higher. Otherwise, RE was higher. The research results also showed that PM2.5 exposure was positively correlated with PM2.5 concentration, respiration rate, and human activity patterns. Because adults had a higher monthly average potential exposure (MAPE) than minors and that males had a higher MAPE than females. The potential exposure generated by LPA and MPA reached 50.76% of the total potential exposure (TPE). VPA brought about a 14.7% increase in the TPE. The research findings are helpful to understand the temporal distribution characteristics of PM2.5 concentrations and guide the potential risk evaluation of PM2.5 inhalation exposure.
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Affiliation(s)
- Xiaoxia Wang
- School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou, 510006, Guangdong, People's Republic of China
| | - Xuezhen Liu
- Cangzhou Air Pollution Control Center, Cangzhou, 061000, Hebei, People's Republic of China
| | - Luqi Wang
- School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou, 510006, Guangdong, People's Republic of China.
| | - Zhongzhen Dong
- Rizhao City Ecological Environmental Protection Service Center, Rizhao, 276800, Shandong, People's Republic of China
| | - Xiaowei Han
- School of basic medicine, Weifang Medical University, Weifang, 261053, Shandong, People's Republic of China.
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8
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Safari Z, Fouladi-Fard R, Vahedian M, Mahmoudian MH, Rahbar A, Fiore M. Health impact assessment and evaluation of economic costs attributed to PM 2.5 air pollution using BenMAP-CE. Int J Biometeorol 2022; 66:1891-1902. [PMID: 35852660 PMCID: PMC9295116 DOI: 10.1007/s00484-022-02330-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Revised: 07/02/2022] [Accepted: 07/06/2022] [Indexed: 06/01/2023]
Abstract
Air pollution is considered the most prominent public health. Economically, air pollution imposes additional costs on governments. This study aimed to quantify health effects and associated economic values of reducing PM2.5 air pollution using BenMAP-CE in Qom in 2019. The air quality data were acquired from Qom Province Environmental Protection Agency, and the population data were collected from Qom Province Management and Planning Organization website. The number of deaths due to Stroke, Chronic Obstructive Pulmonary Disease, Lung Cancer, and Ischemic Heart Disease attributable to PM2.5 were estimated using BenMAP-CE based on two control scenarios, 2.4 and 10 μg/m3, known as scenarios I and II, respectively. The associated economic effect of premature deaths was assessed by value of a statistical life (VSL) approach. The annual average of PM2.5 concentration was found to be 16.32 μg/m3 (SD: 9.93). A total of 4694.5 and 2475.94 premature deaths in scenarios I and II were found to be attributable to PM2.5 in overall, respectively. The total associated cost was calculated to be 855.91 and 451.40 million USD in scenarios I and II, respectively. The total years of life lost due to PM2.5 exposure in 2019 was 158,657.06 and 78,351.51 in scenarios I and II, respectively. The results of both health and economic assessment indicate the importance of solving the air pollution problem in Qom, as well as other big cities in Iran. The elimination of limitations, such as insufficient local data, should be regarded in future studies.
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Affiliation(s)
- Zahra Safari
- Research Center for Environmental Pollutants, Department of Environmental Health Engineering, Faculty of Health, Qom University of Medical Sciences, Qom, 3715614566 Iran
- Student Research Committee, Qom University of Medical Sciences, Qom, 3715614566 Iran
| | - Reza Fouladi-Fard
- Research Center for Environmental Pollutants, Department of Environmental Health Engineering, Faculty of Health, Qom University of Medical Sciences, Qom, 3715614566 Iran
| | - Mostafa Vahedian
- Research Center for Environmental Pollutants, Department of Environmental Health Engineering, Faculty of Health, Qom University of Medical Sciences, Qom, 3715614566 Iran
| | - Mohammad Hassan Mahmoudian
- Research Center for Environmental Pollutants, Department of Environmental Health Engineering, Faculty of Health, Qom University of Medical Sciences, Qom, 3715614566 Iran
| | - Ahmad Rahbar
- Department of Public Health, School of Health, Qom University of Medical Sciences, Qom, 3715614566 Iran
| | - Maria Fiore
- Department of Medical, Surgical and Advanced Technologies “G.F. Ingrassia”, University of Catania, 87-95123 Catania, Italy
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McDermott-Levy R, Scolio M, Shakya KM, Moore CH. Factors That Influence Climate Change-Related Mortality in the United States: An Integrative Review. Int J Environ Res Public Health 2021; 18:ijerph18158220. [PMID: 34360518 PMCID: PMC8345936 DOI: 10.3390/ijerph18158220] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/23/2021] [Accepted: 07/29/2021] [Indexed: 12/02/2022]
Abstract
Global atmospheric warming leads to climate change that results in a cascade of events affecting human mortality directly and indirectly. The factors that influence climate change-related mortality within the peer-reviewed literature were examined using Whittemore and Knafl’s framework for an integrative review. Ninety-eight articles were included in the review from three databases—PubMed, Web of Science, and Scopus—with literature filtered by date, country, and keywords. Articles included in the review address human mortality related to climate change. The review yielded two broad themes in the literature that addressed the factors that influence climate change-related mortality. The broad themes are environmental changes, and social and demographic factors. The meteorological impacts of climate change yield a complex cascade of environmental and weather events that affect ambient temperatures, air quality, drought, wildfires, precipitation, and vector-, food-, and water-borne pathogens. The identified social and demographic factors were related to the social determinants of health. The environmental changes from climate change amplify the existing health determinants that influence mortality within the United States. Mortality data, national weather and natural disaster data, electronic medical records, and health care provider use of International Classification of Disease (ICD) 10 codes must be linked to identify climate change events to capture the full extent of climate change upon population health.
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Affiliation(s)
- Ruth McDermott-Levy
- M. Louise Fitzpatrick College of Nursing, Villanova University, Villanova, PA 19085, USA
- Correspondence:
| | - Madeline Scolio
- Department of Geography and the Environment, Villanova University, Villanova, PA 19085, USA; (M.S.); (K.M.S.)
| | - Kabindra M. Shakya
- Department of Geography and the Environment, Villanova University, Villanova, PA 19085, USA; (M.S.); (K.M.S.)
| | - Caroline H. Moore
- Georgia Baptist College of Nursing, Mercer University, Atlanta, GA 30341, USA;
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10
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Qi C, Shang L, Yang W, Huang L, Yang L, Xin J, Wang S, Yue J, Zeng L, Chung MC. Maternal exposure to O 3 and NO 2 may increase the risk of newborn congenital hypothyroidism: a national data-based analysis in China. Environ Sci Pollut Res Int 2021; 28:34621-34629. [PMID: 33655476 PMCID: PMC8275538 DOI: 10.1007/s11356-021-13083-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 02/17/2021] [Indexed: 06/12/2023]
Abstract
Maternal exposure to air pollution during pregnancy is associated with adverse outcomes in the offspring, but limited studies focused on the impacts of gaseous air pollution on newborn congenital hypothyroidism (CH). Therefore, a national data-based analysis was conducted to explore the association between maternal exposure to gaseous air pollution and the incidence of CH in China. Annual average exposure levels of SO2, NO2, CO, and O3 from January 1, 2014, to December 30, 2014, were acquired from the Chinese Air Quality Online Monitoring and Analysis Platform. The annual incidence of newborn CH from October 1, 2014, to September 30, 2015, was collected from the Chinese Maternal and Child Health Surveillance Network. Temperature and toxic metal in wastewater in 2014 were also collected as covariates. Maternal exposure to O3 and NO2 in 1 μg/m3 level increment was positively associated with newborn CH, with an OR of 1.055 (95% CI 1.011, 1.102) and 1.097 (95% CI 1.019, 1.182) after adjusting for covariates completely. Compared with the lowest level of O3, maternal exposure to the 4th quartile of O3 was positively associated with newborn CH (OR 1.393, 95% CI 1.081, 1.794) after adjusting for covariates completely. And the 3rd and 4th quartiles of NO2 were associated positively with CH (OR 1.576, 95% CI 1.025, 2.424, and OR 1.553, 95% CI 0.999, 2.414, respectively) compared with the lowest level of NO2. By fitting the ROC curve, 93.688 μg/m3 in O3 might be used as cutoff to predict the incidence of newborn CH in China.
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Affiliation(s)
- Cuifang Qi
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277, West Yanta Road, Xi’an,, Shaanxi 710061 People’s Republic of China
| | - Li Shang
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277, West Yanta Road, Xi’an,, Shaanxi 710061 People’s Republic of China
- School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an,, Shaanxi 710061 People’s Republic of China
| | - Wenfang Yang
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277, West Yanta Road, Xi’an,, Shaanxi 710061 People’s Republic of China
| | - Liyan Huang
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277, West Yanta Road, Xi’an,, Shaanxi 710061 People’s Republic of China
- School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an,, Shaanxi 710061 People’s Republic of China
| | - Liren Yang
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277, West Yanta Road, Xi’an,, Shaanxi 710061 People’s Republic of China
- School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an,, Shaanxi 710061 People’s Republic of China
| | - Juan Xin
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277, West Yanta Road, Xi’an,, Shaanxi 710061 People’s Republic of China
- School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an,, Shaanxi 710061 People’s Republic of China
| | - Shanshan Wang
- School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an,, Shaanxi 710061 People’s Republic of China
| | - Jie Yue
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277, West Yanta Road, Xi’an,, Shaanxi 710061 People’s Republic of China
| | - Lingxia Zeng
- School of Public Health, Xi’an Jiaotong University Health Science Center, Xi’an,, Shaanxi 710061 People’s Republic of China
| | - Mei Chun Chung
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277, West Yanta Road, Xi’an,, Shaanxi 710061 People’s Republic of China
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA USA
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Liu J, Yin H, Tang X, Zhu T, Zhang Q, Liu Z, Tang X, Yi H. Transition in air pollution, disease burden and health cost in China: A comparative study of long-term and short-term exposure. Environ Pollut 2021; 277:116770. [PMID: 33640815 DOI: 10.1016/j.envpol.2021.116770] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 01/13/2021] [Accepted: 02/13/2021] [Indexed: 05/22/2023]
Abstract
Ambient air pollution is one of the leading environmental risk factors to human health, largely offsetting economic growth. This study evaluated health burden and cost associated with the short-term and long-term exposure of major air pollutants (fine particulate matter [PM2.5] and ozone [O3]) during 2013-2018. We developed a database of gridded daily and annual PM2.5 and O3 exposure in China at 15 km × 15 km resolution. Then, we estimated the age- and cause-specific premature deaths and quantified related health damage with an age-adjusted value of statistical life (VSL) measure. The health cost estimated in this study captured direct cost, indirect cost and intangible cost of the premature death attributable to ambient PM2.5 and O3. We found that the national premature deaths attributable to long-term and short-term exposure to PM2.5 decreased by 15% and 59%, whereas the national premature deaths attributable to long-term and short-term exposure to O3 increased by 36% and 94%. Despite a 15% reduction of attributable deaths, the health cost attributable to long-term exposure to PM2.5 did not change significantly as a result of GDP growth and population aging. On the other hand, the long-term O3 related health cost in 2018 doubled that in 2013. Our study suggests that while premature deaths fell as a result of China's clean air actions, the health costs of air pollution remained high. The growing trends of O3 highlighted the needs for strategies to reduce both PM2.5 and O3 emissions, for the sake of public health and social well-being in China.
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Affiliation(s)
- Jun Liu
- Department of Environmental Engineering, School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China; Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, PR China; Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, PR China
| | - Hao Yin
- School of Population and Public Health, The University of British Columbia, Vancouver BC, Canada; Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, PR China; Energy and Resources Group, University of California, Berkeley, CA, USA
| | - Xiao Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China.
| | - Tong Zhu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, PR China
| | - Zhu Liu
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, 100084, PR China
| | - XiaoLong Tang
- Department of Environmental Engineering, School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China; Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, PR China
| | - HongHong Yi
- Department of Environmental Engineering, School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China; Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, PR China.
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Zhao N, Li B, Li H, Li G, Wu R, Hong Q, Mperejekumana P, Liu S, Zhou Y, Ahmad R, Ibrahim Zayan AM, Pemberton-Pigott C, Dong R. The potential co-benefits for health, economy and climate by substituting raw coal with waste cooking oil as a winter heating fuel in rural households of northern China. Environ Res 2021; 194:110683. [PMID: 33450236 DOI: 10.1016/j.envres.2020.110683] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 11/15/2020] [Accepted: 12/23/2020] [Indexed: 06/12/2023]
Abstract
The toxic emissions from coal combustion associated with domestic winter heating requirements are an important public health issue. Waste cooking oil (WCO) holds promise as a means of reducing pollutant emissions thereby improving human health with the co-benefit of decreasing climate-forcing gas emissions by avoiding the combustion of mineral coal. With an annual production of ~2.17 Mt of WCO in Northern China, it could be used to meet the winter heating demand of ~3.25 million rural households, offsetting ~9.83 Mt of raw coal consumption. Through the adoption of coal-to-WCO shift in rural regions of 15 provinces, approximately 15.0%, 15.6%, 15.9% and 13.7%, respectively of CO, PM2.5, SO2 and NOX emissions would be eliminated. It is estimated that such a change would remove the respective contributions of these pollutants to the premature deaths of respectively, 63,400, 29,300, 173,00 and 31,300 rural residents. Such a positive health impact on the labor cohort would reduce the loss of labor supply and work time, as well as producing billions of RMB in economic benefits. WCO-based heating technology has the same effect on the reduction of GWC100 value as other modern energy carriers while also being cheaper and sustainable, long term. Reducing household emissions by substituting raw coal with green energy is a vital strategy to support pathways for sustainable environment design. The results of this work for the coal-to-WCO shift can reinforce the support for coal phase-out in China.
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Affiliation(s)
- Nan Zhao
- Bioenergy and Environment Science & Technology Laboratory, College of Engineering, China Agricultural University, Beijing, 100083, China; Key Laboratory of Clean Production and Utilization of Renewable Energy, Ministry of Agriculture and Rural Affairs, China, Beijing, 100083, China; National Center for International Research of BioEnergy Science and Technology, Ministry of Science and Technology, Beijing, 100083, China
| | - Bowen Li
- Bioenergy and Environment Science & Technology Laboratory, College of Engineering, China Agricultural University, Beijing, 100083, China; Key Laboratory of Clean Production and Utilization of Renewable Energy, Ministry of Agriculture and Rural Affairs, China, Beijing, 100083, China; National Center for International Research of BioEnergy Science and Technology, Ministry of Science and Technology, Beijing, 100083, China
| | - Huan Li
- Bioenergy and Environment Science & Technology Laboratory, College of Engineering, China Agricultural University, Beijing, 100083, China; Key Laboratory of Clean Production and Utilization of Renewable Energy, Ministry of Agriculture and Rural Affairs, China, Beijing, 100083, China; National Center for International Research of BioEnergy Science and Technology, Ministry of Science and Technology, Beijing, 100083, China
| | - Gang Li
- School of Material Science and Mechanical Engineering, Beijing Technology and Business University, Beijing, 100048, China; Key Laboratory of Processing and Quality Evaluation Technology of Green Plastics of China National Light Industry Council, Beijing Technology and Business University, Beijing, 100048, China.
| | - Rucong Wu
- Bioenergy and Environment Science & Technology Laboratory, College of Engineering, China Agricultural University, Beijing, 100083, China; Key Laboratory of Clean Production and Utilization of Renewable Energy, Ministry of Agriculture and Rural Affairs, China, Beijing, 100083, China; National Center for International Research of BioEnergy Science and Technology, Ministry of Science and Technology, Beijing, 100083, China
| | - Quan Hong
- Bioenergy and Environment Science & Technology Laboratory, College of Engineering, China Agricultural University, Beijing, 100083, China; Key Laboratory of Clean Production and Utilization of Renewable Energy, Ministry of Agriculture and Rural Affairs, China, Beijing, 100083, China; National Center for International Research of BioEnergy Science and Technology, Ministry of Science and Technology, Beijing, 100083, China
| | - Philbert Mperejekumana
- Bioenergy and Environment Science & Technology Laboratory, College of Engineering, China Agricultural University, Beijing, 100083, China; Key Laboratory of Clean Production and Utilization of Renewable Energy, Ministry of Agriculture and Rural Affairs, China, Beijing, 100083, China; National Center for International Research of BioEnergy Science and Technology, Ministry of Science and Technology, Beijing, 100083, China
| | - Shan Liu
- Bioenergy and Environment Science & Technology Laboratory, College of Engineering, China Agricultural University, Beijing, 100083, China; Key Laboratory of Technology and Model for Cyclic Utilization from Agricultural Resources, Ministry of Agriculture and Rural Affairs, Beijing, 100125, China.
| | - Yuguang Zhou
- Bioenergy and Environment Science & Technology Laboratory, College of Engineering, China Agricultural University, Beijing, 100083, China; Key Laboratory of Clean Production and Utilization of Renewable Energy, Ministry of Agriculture and Rural Affairs, China, Beijing, 100083, China; National Center for International Research of BioEnergy Science and Technology, Ministry of Science and Technology, Beijing, 100083, China
| | - Riaz Ahmad
- Key Laboratory of Clean Production and Utilization of Renewable Energy, Ministry of Agriculture and Rural Affairs, China, Beijing, 100083, China
| | - Ali Mohammed Ibrahim Zayan
- Department of Agricultural Engineering, Faculty of Agriculture, Omdurman Islamic University, Omdurman Province, Khartoum State, 11111, Sudan
| | - Crispin Pemberton-Pigott
- National Center for International Research of BioEnergy Science and Technology, Ministry of Science and Technology, Beijing, 100083, China; School of Geo- and Spatial Sciences, Private Bag X6001, North-West University, 2520, Potchefstroom, South Africa
| | - Renjie Dong
- Key Laboratory of Clean Production and Utilization of Renewable Energy, Ministry of Agriculture and Rural Affairs, China, Beijing, 100083, China; National Center for International Research of BioEnergy Science and Technology, Ministry of Science and Technology, Beijing, 100083, China; Yantai Institute, China Agricultural University, No. 2006 Binhai Zhonglu, Laishan District, Yantai, Shandong Province, 264670, China
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Abstract
IMPORTANCE Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 μm (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood. OBJECTIVE To model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios. DESIGN, SETTING, AND PARTICIPANTS This modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020. MAIN OUTCOMES AND MEASURES The main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets. RESULTS The projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21 000 (95% CI, 14 000-28 000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15 000 (95% CI, 10 000-20 000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions. CONCLUSIONS AND RELEVANCE These findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.
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Affiliation(s)
- Neal L. Fann
- Office of Air Quality Planning and Standards, Office of Air and Radiation, US Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Christopher G. Nolte
- Center for Environmental Measurement and Modeling, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Marcus C. Sarofim
- Office of Atmospheric Programs, Office of Air and Radiation, US Environmental Protection Agency, Washington District of Columbia
| | - Jeremy Martinich
- Office of Atmospheric Programs, Office of Air and Radiation, US Environmental Protection Agency, Washington District of Columbia
| | - Nicholas J. Nassikas
- Department of Pulmonary, Critical Care, and Sleep Medicine, Alpert School of Medicine, Brown University, Providence, Rhode Island
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Zhang Y, Yang P, Gao Y, Leung RL, Bell ML. Health and economic impacts of air pollution induced by weather extremes over the continental U.S. Environ Int 2020; 143:105921. [PMID: 32623223 DOI: 10.1016/j.envint.2020.105921] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2019] [Revised: 06/14/2020] [Accepted: 06/19/2020] [Indexed: 06/11/2023]
Abstract
Extreme weather events may enhance ozone (O3) and fine particulate matter (PM2.5) pollution, causing additional adverse health effects. This work aims to evaluate the health and associated economic impacts of changes in air quality induced by heat wave, stagnation, and compound extremes under the Representative Concentration Pathways (RCP) 4.5 and 8.5 climate scenarios. The Environmental Benefits Mapping and Analysis Program-Community Edition is applied to estimate health and related economic impacts of changes in surface O3 and PM2.5 levels due to heat wave, stagnation, and compound extremes over the continental U.S. during past (i.e., 2001-2010) and future (i.e., 2046-2055) decades under the two RCP scenarios. Under the past and future decades, the weather extremes-induced concentration increases may lead to several tens to hundreds O3-related deaths and several hundreds to over ten thousands PM2.5-related deaths annually. High mortalities and morbidities are estimated for populated urban areas with strong spatial heterogeneities. The estimated annual costs for these O3 and PM2.5 related health outcomes are $5.5-12.5 and $48.6-140.7 billion U.S. dollar for mortalities, and $8.9-97.8 and $19.5-112.5 million for morbidities, respectively. Of the extreme events, the estimated O3- and PM2.5-related mortality and morbidity attributed to stagnation are the highest, followed by heat wave or compound extremes. Large increases in heat wave and compound extreme events in the future decade dominate changes in mortality during these two extreme events, whereas population growth dominates changes in mortality during stagnation that is projected to occur less frequently. Projected reductions of anthropogenic emissions under bothRCP scenarios compensate for the increased mortality due to increasedoccurrence for heat wave and compound extremes in the future. These results suggest a need to further reduce air pollutant emissions during weather extremes to minimize the adverse impacts of weather extremes on air quality and human health.
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Affiliation(s)
- Yang Zhang
- Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA; Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA.
| | - Peilin Yang
- Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Yang Gao
- Key Laboratory of Marine Environment and Ecology, Ministry of Education of China, Ocean University of China, Qingdao, Shandong 266100, China
| | - Ruby L Leung
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Michelle L Bell
- School of Forestry & Environmental Studies, Yale University, New Haven, CT 06511, USA
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Wang X, Zou C, Wang L. Analysis on the Temporal Distribution Characteristics of Air Pollution and Its Impact on Human Health under the Noticeable Variation of Residents' Travel Behavior: A Case of Guangzhou, China. Int J Environ Res Public Health 2020; 17:E4947. [PMID: 32659942 DOI: 10.3390/ijerph17144947] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Accepted: 07/07/2020] [Indexed: 12/14/2022]
Abstract
During the large-scale outbreak of COVID-19 in China, the Chinese government adopted multiple measures to prevent the epidemic. The consequence was that a sudden variation in residents' travel behavior took place. In order to better evaluate the temporal distribution of air pollution, and to effectively explore the influence of human activities on air quality, especially under the special situation, this study was conducted based on the real data from a case city in China from this new perspective. Two case scenarios were constructed, in which the research before the changes of residents' travel behavior was taken as case one, and the research after the changes in residents' travel behavior as case two. The hourly real-time concentrations of PM2.5, PM10, SO2, NO2, CO and O3 that have passed the augmented Dickey-Fuller (ADF) test were employed as a data source. A series of detailed studies have been carried out using the correlation method, entropy weight method and the Air Quality Index (AQI) calculation method. Additionally, the research found that the decrease rate of NO2 concentration is 61.05%, and the decrease rate of PM10 concentration is 53.68%. On the contrary, the average concentration of O3 has increased significantly, and its growth rate has reached to 9.82%. Although the air quality in the first week with fewer travels was in the excellent category, and chief pollutant (CP), as well as excessive pollutant (EP), were not found, as traffic volume increased, it became worse in the second and third weeks. In addition to that, special attention should still be paid to the development trend of O3, as its average hourly concentration has increased. The findings of this study will have some guiding significance for the study of air pollution prevention, cleaner production, and indoor environmental safety issues, especially for the study of abnormal traffic environments where residents' travel behaviors have changed significantly.
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Liu P, Song H, Wang T, Wang F, Li X, Miao C, Zhao H. Effects of meteorological conditions and anthropogenic precursors on ground-level ozone concentrations in Chinese cities. Environ Pollut 2020; 262:114366. [PMID: 32443214 DOI: 10.1016/j.envpol.2020.114366] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 02/29/2020] [Accepted: 03/10/2020] [Indexed: 06/11/2023]
Abstract
Ground-level ozone pollution has negative impacts on human health and vegetation and has increased rapidly across China. Various factors are implicated in the formation of ozone (e.g., meteorological factors, anthropogenic emissions), but their relative individual impact and the impact of interactions between these factors remains unclear. This study quantified the influence of specific meteorological conditions and anthropogenic precursor emissions and their interactions on ozone concentrations in Chinese cities using the geographic detector model (GeoDetector). Results revealed that the impacts of meteorological and anthropogenic factors and their interactions on ozone concentrations varied significantly at different spatial and temporal scales. Temperature was the dominant driver at the annual time scale, explaining 40% (q = 0.4) of the ground-level ozone concentration. Anthropogenic precursors and meteorological conditions had comparable effects on ozone concentrations in summer and winter in northern China. Interactions between all the factors can enhance effects. The interaction between meteorological factors and anthropogenic precursors had the strongest impact in summer. The results can be used to enhance our understanding of ozone pollution, to improve ozone prediction models, and to formulate pollution control measures.
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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, 475001, China; Institute of Urban Big Data, College of Environment and Planning, Henan University, Kaifeng, Henan, 475004, China
| | - Hongquan Song
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, Henan, 475004, China; Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Henan University, Kaifeng, Henan, 475004, China; Institute of Urban Big Data, College of Environment and Planning, Henan University, Kaifeng, Henan, 475004, China.
| | - Tuanhui Wang
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, Henan, 475004, China; Institute of Urban Big Data, College of Environment and Planning, Henan University, Kaifeng, Henan, 475004, China
| | - Feng Wang
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, Henan, 475004, China; Institute of Urban Big Data, College of Environment and Planning, Henan University, Kaifeng, Henan, 475004, China
| | - Xiaoyang Li
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, Henan, 475004, China; Institute of Urban Big Data, College of Environment and Planning, Henan University, Kaifeng, Henan, 475004, China
| | - Changhong Miao
- Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, 475001, China
| | - Haipeng Zhao
- Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, Henan, 475004, China; Institute of Urban Big Data, College of Environment and Planning, Henan University, Kaifeng, Henan, 475004, China
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Chen K, Vicedo-Cabrera AM, Dubrow R. Projections of Ambient Temperature- and Air Pollution-Related Mortality Burden Under Combined Climate Change and Population Aging Scenarios: a Review. Curr Environ Health Rep 2020; 7:243-255. [PMID: 32542573 DOI: 10.1007/s40572-020-00281-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
PURPOSE OF REVIEW Climate change will affect mortality associated with both ambient temperature and air pollution. Because older adults have elevated vulnerability to both non-optimal ambient temperature (heat and cold) and air pollution, population aging can amplify future population vulnerability to these stressors through increasing the number of vulnerable older adults. We aimed to review recent evidence on projections of temperature- or air pollution-related mortality burden (i.e., number of deaths) under combined climate change and population aging scenarios, with a focus on evaluating the role of population aging in assessing these health impacts of climate change. We included studies published between 2014 and 2019 with age-specific population projections. RECENT FINDINGS We reviewed 16 temperature projection studies and 15 air pollution projection studies. Nine of the temperature studies and four of the air pollution studies took population aging into account by performing age-stratified analyses that utilized age-specific relationships between temperature or air pollution exposures and mortality (i.e., age-specific exposure-response functions (ERFs)). Population aging amplifies the projected mortality burden of temperature and air pollution under a warming climate. Compared with a constant population scenario, population aging scenarios lead to less reduction or even increases in cold-related mortality burden, resulting in substantial net increases in future overall (heat and cold) temperature-related mortality burden. There is strong evidence suggesting that to accurately assess the future temperature- and air pollution-related mortality burden of climate change, investigators need to account for the amplifying effect of population aging. Thus, all future studies should incorporate age-specific population size projections and age-specific ERFs into their analyses. These studies would benefit from refinement of age-specific ERF estimates.
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Affiliation(s)
- Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA. .,Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA.
| | - Ana Maria Vicedo-Cabrera
- Institute of Social and Preventive Medicine, University of Bern, 43 Mittelstrasse, 3012, Bern, Switzerland.,Oeschger Center for Climate Change Research, University of Bern, 4 Hochschulstrasse, 3012, Bern, Switzerland
| | - Robert Dubrow
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA.,Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA
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