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Khoshakhlagh AH, Mohammadzadeh M, Gruszecka-Kosowska A, Oikonomou E. Burden of cardiovascular disease attributed to air pollution: a systematic review. Global Health 2024; 20:37. [PMID: 38702798 PMCID: PMC11069222 DOI: 10.1186/s12992-024-01040-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 04/19/2024] [Indexed: 05/06/2024] Open
Abstract
BACKGROUND Cardiovascular diseases (CVDs) are estimated to be the leading cause of global death. Air pollution is the biggest environmental threat to public health worldwide. It is considered a potentially modifiable environmental risk factor for CVDs because it can be prevented by adopting the right national and international policies. The present study was conducted to synthesize the results of existing studies on the burden of CVDs attributed to air pollution, namely prevalence, hospitalization, disability, mortality, and cost characteristics. METHODS A systematic search was performed in the Scopus, PubMed, and Web of Science databases to identify studies, without time limitations, up to June 13, 2023. Exclusion criteria included prenatal exposure, exposure to indoor air pollution, review studies, conferences, books, letters to editors, and animal and laboratory studies. The quality of the articles was evaluated based on the Agency for Healthcare Research and Quality Assessment Form, the Newcastle-Ottawa Scale, and Drummond Criteria using a self-established scale. The articles that achieved categories A and B were included in the study. RESULTS Of the 566 studies obtained, based on the inclusion/exclusion criteria, 92 studies were defined as eligible in the present systematic review. The results of these investigations supported that chronic exposure to various concentrations of air pollutants, increased the prevalence, hospitalization, disability, mortality, and costs of CVDs attributed to air pollution, even at relatively low levels. According to the results, the main pollutant investigated closely associated with hypertension was PM2.5. Furthermore, the global DALY related to stroke during 2016-2019 has increased by 1.8 times and hospitalization related to CVDs in 2023 has increased by 8.5 times compared to 2014. CONCLUSION Ambient air pollution is an underestimated but significant and modifiable contributor to CVDs burden and public health costs. This should not only be considered an environmental problem but also as an important risk factor for a significant increase in CVD cases and mortality. The findings of the systematic review highlighted the opportunity to apply more preventive measures in the public health sector to reduce the footprint of CVDs in human society.
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Affiliation(s)
- Amir Hossein Khoshakhlagh
- Department of Occupational Health Engineering, School of Health, Kashan University of Medical Sciences, Kashan, Iran
| | - Mahdiyeh Mohammadzadeh
- Department of Health in Emergencies and Disasters, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
- Climate Change and Health Research Center (CCHRC), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran.
| | - Agnieszka Gruszecka-Kosowska
- AGH University of Krakow, Faculty of Geology, Geophysics and Environmental Protection, Department of Environmental Protection, al. A. Mickiewicza 30, 30-059, Krakow, Poland
| | - Evangelos Oikonomou
- Department of Cardiology, 'Sotiria' General Hospital, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
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Liu J, Ye Z, Christensen JH, Dong S, Geels C, Brandt J, Nenes A, Yuan Y, Im U. Impact of anthropogenic emission control in reducing future PM 2.5 concentrations and the related oxidative potential across different regions of China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170638. [PMID: 38316299 DOI: 10.1016/j.scitotenv.2024.170638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/29/2024] [Accepted: 01/31/2024] [Indexed: 02/07/2024]
Abstract
Affected by both future anthropogenic emissions and climate change, future prediction of PM2.5 and its Oxidative Potential (OP) distribution is a significant challenge, especially in developing countries like China. To overcome this challenge, we estimated historical and future PM2.5 concentrations and associated OP using the Danish Eulerian Hemispheric Model (DEHM) system with meteorological input from WRF weather forecast model. Considering different future socio-economic pathways and emission scenario assumptions, we quantified how the contribution from various anthropogenic emission sectors will change under these scenarios. Results show that compared to the CESM_SSP2-4.5_CLE scenario (based on moderate radiative forcing and Current Legislation Emission), the CESM_SSP1-2.6_MFR scenario (based on sustainability development and Maximum Feasible Reductions) is projected to yield greater environmental and health benefits in the future. Under the CESM_SSP1-2.6_MFR scenario, annual average PM2.5 concentrations (OP) are expected to decrease to 30 (0.8 nmolmin-1m-3) in almost all regions by 2030, which will be 65 % (67 %) lower than that in 2010. From a long-term perspective, it is anticipated that OP in the Fen-Wei Plain region will experience the maximum reduction (82.6 %) from 2010 to 2049. Largely benefiting from the effective control of PM2.5 in the region, it has decreased by 82.1 %. Crucially, once emission reduction measures reach a certain level (in 2040), further reductions become less significant. This study also emphasized the significant role of secondary aerosol formation and biomass-burning sources in influencing OP during both historical and future periods. In different scenarios, the reduction range of OP from 2010 to 2049 is estimated to be between 71 % and 85 % by controlling precursor emissions involved in secondary aerosol formation and emissions from biomass burning. Results indicate that strengthening the control of anthropogenic emissions in various regions are key to achieving air quality targets and safeguarding human health in the future.
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Affiliation(s)
- Jiemei Liu
- Key Laboratory of Aerospace Thermophysics, Ministry of Industry and Information Technology, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China; Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Zhuyun Ye
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Jesper H Christensen
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Shikui Dong
- Key Laboratory of Aerospace Thermophysics, Ministry of Industry and Information Technology, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China
| | - Camilla Geels
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Jørgen Brandt
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Athanasios Nenes
- Laboratory of Atmospheric Processes and Their Impacts, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Center for the Study of Air Quality and Climate Change, Foundation for Research and Technology Hellas (FORTH), Thessaloniki, Greece
| | - Yuan Yuan
- Key Laboratory of Aerospace Thermophysics, Ministry of Industry and Information Technology, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China.
| | - Ulas Im
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark.
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Liao Q, Li Z, Li Y, Dai X, Kang N, Niu Y, Tao Y. Specific analysis of PM 2.5-attributed disease burden in typical areas of Northwest China. Front Public Health 2023; 11:1338305. [PMID: 38192558 PMCID: PMC10771959 DOI: 10.3389/fpubh.2023.1338305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 11/24/2023] [Indexed: 01/10/2024] Open
Abstract
Background Frequent air pollution events in Northwest China pose a serious threat to human health. However, there is a lack of specific differences assessment in PM2.5-related disease burden. Therefore, we aimed to estimate the PM2.5-related premature deaths and health economic losses in this typical northwest region, taking into account disease-specific, age-specific, and region-specific factors. Methods We utilized the WRF-Chem model to simulate and analyze the characteristics and exposure levels of PM2.5 pollution in Gansu Province, a typical region of Northwest China. Subsequently, we estimated the premature mortality and health economic losses associated with PM2.5 by combining the Global Exposure Mortality Model (GEMM) and the Value of a Statistical Life (VSL). Results The results suggested that the PM2.5 concentrations in Gansu Province in 2019 varied spatially, with a decrease from north to south. The number of non-accidental deaths attributable to PM2.5 pollution was estimated to be 14,224 (95% CI: 11,716-16,689), accounting for 8.6% of the total number of deaths. The PM2.5-related health economic loss amounted to 28.66 (95% CI: 23.61-33.63) billion yuan, equivalent to 3.3% of the regional gross domestic product (GDP) in 2019. Ischemic heart disease (IHD) and stroke were the leading causes of PM2.5-attributed deaths, contributing to 50.6% of the total. Older adult individuals aged 60 and above accounted for over 80% of all age-related disease deaths. Lanzhou had a higher number of attributable deaths and health economic losses compared to other regions. Although the number of PM2.5-attributed deaths was lower in the Hexi Corridor region, the per capita health economic loss was higher. Conclusion Gansu Province exhibits distinct regional characteristics in terms of PM2.5 pollution as well as disease- and age-specific health burdens. This highlights the significance of implementing tailored measures that are specific to local conditions to mitigate the health risks and economic ramifications associated with PM2.5 pollution.
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Affiliation(s)
- Qin Liao
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - Zhenglei Li
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - Yong Li
- Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Xuan Dai
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - Ning Kang
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - Yibo Niu
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
| | - Yan Tao
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
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Zheng W, Chu J, Bambrick H, Wang N, Mengersen K, Guo X, Hu W. Impact of environmental factors on diabetes mortality: A comparison between inland and coastal areas. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166335. [PMID: 37591381 DOI: 10.1016/j.scitotenv.2023.166335] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/02/2023] [Accepted: 08/14/2023] [Indexed: 08/19/2023]
Abstract
BACKGROUND Diabetes mortality varies between coastal and inland areas in Shandong Province, China. However, evidence about the reasons for this disparity is limited. We assume that distinct environmental conditions may contribute to the disparities in diabetes mortality patterns between coastal and inland areas. METHOD Qingdao and Jinan were selected as typical coastal and inland cities in Shandong Province, respectively, with similar socioeconomic but different environmental characteristics. Data on diabetes deaths and environmental factors (i.e., temperature, relative humidity and air pollution particles with a diameter of 2.5 μm or less (PM2.5)) were collected from 2013 to 2020. Spatial kriging methods were used to estimate the aggregated diabetes mortality at the city level. A distributed lag non-linear model (DLNM) was used to quantify the possible cumulative and non-cumulative associations between environmental factors and diabetes mortality by age, sex and location. RESULTS In the coastal city (Qingdao), the maximum cumulative relative risks (RRs) of temperature and PM2.5 associated with diabetes deaths were 2.54 (95 % confidence interval (CI): 1.25-5.15), and 1.17 (95 % CI: 1.01-1.37) respectively, at lag 1 week. In the inland city (Jinan), only temperature exhibited significant cumulative associations with diabetes deaths (RR = 1.54, 95 % CI: 1.07-2.23 at 29 °C). Lower relative humidity (22 %-45 %) had a lag-specific association with diabetes deaths in inland areas at lag 3 weeks (RR = 1.33, 95 % CI: 1.03-1.70 at 22 %). CONCLUSION Despite the lower PM2.5 concentrations in the coastal location, diabetes mortality exhibited stronger links to environmental variables in the coastal city than in the inland city. These findings suggest that the control of air pollution could decrease the mortality burden of diabetes, even in the region with relatively good air quality. Additionally, the spatial estimation method is recommended to identify associations between environmental factors and diseases in studies with limited data.
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Affiliation(s)
- Wenxiu Zheng
- Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Jie Chu
- Shandong Center for Disease Control and Prevention, Academy of Preventive Medicine, Shandong University, Jinan, Shandong, China
| | - Hilary Bambrick
- Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia; National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Ning Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Kerrie Mengersen
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Xiaolei Guo
- Shandong Center for Disease Control and Prevention, Academy of Preventive Medicine, Shandong University, Jinan, Shandong, China.
| | - Wenbiao Hu
- Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia.
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Guo B, Gao Q, Pei L, Guo T, Wang Y, Wu H, Zhang W, Chen M. Exploring the association of PM 2.5 with lung cancer incidence under different climate zones and socioeconomic conditions from 2006 to 2016 in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:126165-126177. [PMID: 38008841 DOI: 10.1007/s11356-023-31138-8] [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: 08/04/2023] [Accepted: 11/16/2023] [Indexed: 11/28/2023]
Abstract
Air pollution generated by urbanization and industrialization poses a significant negative impact on public health. Particularly, fine particulate matter (PM2.5) has become one of the leading causes of lung cancer mortality worldwide. The relationship between air pollutants and lung cancer has aroused global widespread concerns. Currently, the spatial agglomeration dynamic of lung cancer incidence (LCI) has been seldom discussed, and the spatial heterogeneity of lung cancer's influential factors has been ignored. Moreover, it is still unclear whether different socioeconomic levels and climate zones exhibit modification effects on the relationship between PM2.5 and LCI. In the present work, spatial autocorrelation was adopted to reveal the spatial aggregation dynamic of LCI, the emerging hot spot analysis was introduced to indicate the hot spot changes of LCI, and the geographically and temporally weighted regression (GTWR) model was used to determine the affecting factors of LCI and their spatial heterogeneity. Then, the modification effects of PM2.5 on the LCI under different socioeconomic levels and climatic zones were explored. Some findings were obtained. The LCI demonstrated a significant spatial autocorrelation, and the hot spots of LCI were mainly concentrated in eastern China. The affecting factors of LCI revealed an obvious spatial heterogeneity. PM2.5 concentration, nighttime light data, 2 m temperature, and 10 m u-component of wind represented significant positive effects on LCI, while education-related POI exhibited significant negative effects on LCI. The LCI in areas with low urbanization rates, low education levels, and extreme climate conditions was more easily affected by PM2.5 than in other areas. The results can provide a scientific basis for the prevention and control of lung cancer and related epidemics.
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Affiliation(s)
- Bin Guo
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China.
| | - Qian Gao
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China
| | - Lin Pei
- School of Exercise and Health Sciences, Xi'an Physical Education University, Xi'an, 710068, Shaanxi, China
| | - Tengyue Guo
- Department of Geological Engineering, Qinghai University, Xining, 810016, Qinghai, China
| | - Yan Wang
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China
| | - Haojie Wu
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China
| | - Wencai Zhang
- College of Land Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Miaoyi Chen
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China
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Zhang Y, Yang Y, Chen J, Shi M. Spatiotemporal heterogeneity of the relationships between PM 2.5 concentrations and their drivers in China's coastal ports. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 345:118698. [PMID: 37536139 DOI: 10.1016/j.jenvman.2023.118698] [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: 02/20/2023] [Revised: 07/22/2023] [Accepted: 07/26/2023] [Indexed: 08/05/2023]
Abstract
PM2.5 is one of the primary air pollutants that affect air quality and threat human health in the port areas. To prevent and control air pollution, it is essential to understand the spatiotemporal distributions of PM2.5 concentrations and their key drivers in ports. 19 coastal ports of China are selected to examine the spatiotemporal distributions of PM2.5 concentrations during 2013-2020. The annual average PM2.5 concentration decreases from 61.03 μg/m3 to 30.17 μg/m3, with an average decrease rate of 51.57%. Significant spatial autocorrelation exists among PM2.5 concentrations of ports. The result of the geographically and temporally weighted regression (GTWR) model shows significant spatiotemporal heterogeneity in the effects of meteorological and socioeconomic factors on PM2.5 concentrations. The effects of boundary layer height on PM2.5 concentrations are found to be negative in most ports, with a stronger effect found in the Pearl River Delta, Yangtze River Delta and some ports of the Bohai Rim Area. The total precipitation shows negative effects on PM2.5 concentrations, with the strongest effect found in ports of the Southeast Coast. The effects of surface pressure on PM2.5 concentrations are positive, with stronger effects found in Beibu Gulf Port and Zhanjiang Port. The effects of wind speed on PM2.5 concentrations generally increase from south to north. Cargo throughput shows strong and positive effects on PM2.5 concentrations in ports of Bohai Rim Area; the positive effects found in Beibu Gulf Port increased from 2013 to 2018 and decreased since 2019. The positive effects of GDP and nighttime light on PM2.5 concentrations gradually decrease and turn negative from south to north. Understandings obtained from this study can potentially support the prevention and control of air pollution in China's coastal ports.
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Affiliation(s)
- Yang Zhang
- College of Transport and Communications, Shanghai Maritime University, Shanghai, 201306, China
| | - Yuanyuan Yang
- College of Transport and Communications, Shanghai Maritime University, Shanghai, 201306, China
| | - Jihong Chen
- College of Management, Shenzhen University, Shenzhen, 518073, China; Shenzhen International Maritime Institute, Shenzhen, 518081, China; Business School, Xi'an International University, Xi'an, 710077, China.
| | - Meiyu Shi
- College of Transport and Communications, Shanghai Maritime University, Shanghai, 201306, China
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Masoud AA. Spatio-temporal patterns and trends of the air pollution integrating MERRA-2 and in situ air quality data over Egypt (2013-2021). AIR QUALITY, ATMOSPHERE, & HEALTH 2023; 16:1-28. [PMID: 37359392 PMCID: PMC10195670 DOI: 10.1007/s11869-023-01357-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 04/06/2023] [Indexed: 06/28/2023]
Abstract
For best-informed decision-making to improve climate change adaptation and reduce present and future air pollution health hazards, it is essential to identify major trends in spatiotemporal air quality patterns of common air contaminants. This study examined the patterns and trends of SO2, NO2, CO, O3, and particulate matter (PM) air pollutants over 91 monitoring stations in Egypt during 93 months in the August (2013)-April (2021) period. In situ data with their monthly, seasonal, and yearly spatial trends are defined and used to validate the counterpart satellite reanalysis MERRA-2 data. The Mann-Kendall test characterized the seasonal monotonic trends and their Sen's slope, and annual change rate for both data series. Regression analysis of MERRA-2 against in situ concentrations of SO2 and PM10 revealed underestimation with RMSE values of 13.38 g m-3 and 69.46 g m-3, respectively. Local plumes with variable magnitudes characterized distinct industrial places clarified by patterns of in situ pollutants. As a result of the COVID-19 lockdown, the in situ air pollutants showed a considerable regional decline in the yearly average in 2020 compared to the years before. The in situ air pollutants showed annual trends far more significant than those seen in the MERRA-2 data. The shortcomings of the few and spatiotemporal discontinuities of the in situ contaminants are addressed by MERRA-2 air quality products. The in situ data made trends and magnitudes clear that were hidden in their MERRA-2 counterparts. The results clarified air pollution patterns, trends, and spatial variability over Egypt that are essential for climate risk management and for reducing environmental/health concerns. Supplementary Information The online version contains supplementary material available at 10.1007/s11869-023-01357-6.
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Affiliation(s)
- Alaa A. Masoud
- Remote Sensing Laboratory, Geology Department, Faculty of Science, Tanta University, Tanta, 31527 Egypt
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Gu Y, Henze DK, Nawaz MO, Cao H, Wagner UJ. Sources of PM 2.5-Associated Health Risks in Europe and Corresponding Emission-Induced Changes During 2005-2015. GEOHEALTH 2023; 7:e2022GH000767. [PMID: 36949891 PMCID: PMC10027220 DOI: 10.1029/2022gh000767] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 03/03/2023] [Accepted: 03/07/2023] [Indexed: 06/18/2023]
Abstract
We present a newly developed approach to characterize the sources of fine particulate matter (PM2.5)-related premature deaths in Europe using the chemical transport model GEOS-Chem and its adjoint. The contributions of emissions from each individual country, species, and sector are quantified and mapped out at km scale. In 2015, total PM2.5-related premature death is estimated to be 449,813 (257,846-722,138) in Europe, 59.0% of which were contributed by domestic anthropogenic emissions. The anthropogenic emissions of nitrogen oxides, ammonia, and organic carbon contributed most to the PM2.5-related health damages, making up 29.6%, 23.2%, and 16.8%, respectively of all domestic anthropogenic contributions. Residential, agricultural, and ground transport emissions are calculated to be the largest three sectoral sources of PM2.5-related health risks, accounting for 23.5%, 23.0%, and 19.4%, respectively, of total anthropogenic contributions within Europe. After excluding the influence of extra-regional sources, we find eastern European countries suffered from more premature deaths than their emissions caused; in contrast, the emissions from some central and western European regions contributed premature deaths exceeding three times the number of deaths that occurred locally. During 2005-2015, the first decade of PM2.5 regulation in Europe, emission controls reduced PM2.5-related health damages in nearly all European countries, resulting in 63,538 (46,092-91,082) fewer PM2.5-related premature deaths. However, our calculation suggests that efforts to reduce air pollution from key sectors in some countries can be offset by the lag in control of emissions in others. International cooperation is therefore vitally important for tackling air pollution and reducing corresponding detrimental effects on public health.
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Affiliation(s)
- Yixuan Gu
- Department of Mechanical EngineeringUniversity of Colorado BoulderBoulderCOUSA
- Department of EconomicsUniversity of MannheimMannheimGermany
| | - Daven K. Henze
- Department of Mechanical EngineeringUniversity of Colorado BoulderBoulderCOUSA
| | - M. Omar Nawaz
- Department of Mechanical EngineeringUniversity of Colorado BoulderBoulderCOUSA
| | - Hansen Cao
- Department of ChemistryUniversity of YorkYorkUK
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Yuan Y, Zhang X, Zhao J, Shen F, Nie D, Wang B, Wang L, Xing M, Hegglin MI. Characteristics, health risks, and premature mortality attributable to ambient air pollutants in four functional areas in Jining, China. Front Public Health 2023; 11:1075262. [PMID: 36741959 PMCID: PMC9893643 DOI: 10.3389/fpubh.2023.1075262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 01/03/2023] [Indexed: 01/20/2023] Open
Abstract
Air pollution is one of the leading causes for global deaths and understanding pollutant emission sources is key to successful mitigation policies. Air quality data in the urban, suburban, industrial, and rural areas (UA, SA, IA, and RA) of Jining, Shandong Province in China, were collected to compare the characteristics and associated health risks. The average concentrations of PM2.5, PM10, SO2, NO2, and CO show differences of -3.87, -16.67, -19.24, -15.74, and -8.37% between 2017 and 2018. On the contrary, O3 concentrations increased by 4.50%. The four functional areas exhibited the same seasonal variations and diurnal patterns in air pollutants, with the highest exposure excess risks (ERs) resulting from O3. More frequent ER days occurred within the 25-30°C, but much larger ERs are found within the 0-5°C temperature range, attributed to higher O3 pollution in summer and more severe PM pollution in winter. The premature deaths attributable to six air pollutants can be calculated in 2017 and 2018, respectively. Investigations on the potential source show that the ER of O3 (r of 0.86) had the tightest association with the total ER. The bivariate polar plots indicated that the highest health-based air quality index (HAQI) in IA influences the HAQI in UA and SA by pollution transport, and thus can be regarded as the major pollutant emission source in Jining. The above results indicate that urgent measures should be taken to reduce O3 pollution taking into account the characteristics of the prevalent ozone formation regime, especially in IA in Jining.
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Affiliation(s)
- Yue Yuan
- Jining Meteorological Bureau, Shandong, China
| | - Xi Zhang
- Jining Meteorological Bureau, Shandong, China
| | | | - Fuzhen Shen
- Institute of Energy and Climate Research, IEK-7: Stratosphere, Forschungszentrum Jülich, Jülich, Germany,Department of Meteorology, University of Reading, Reading, United Kingdom,*Correspondence: Fuzhen Shen ✉
| | - Dongyang Nie
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Bing Wang
- Henley Business School, University of Reading, Reading, United Kingdom
| | - Lei Wang
- Jining Bureau of Ecology and Environment, Shandong, China
| | - Mengyue Xing
- Business School, Dalian University of Foreign Languages, Liaoning, China
| | - Michaela I. Hegglin
- Institute of Energy and Climate Research, IEK-7: Stratosphere, Forschungszentrum Jülich, Jülich, Germany,Department of Meteorology, University of Reading, Reading, United Kingdom,Michaela I. Hegglin ✉
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Vinnikov D, Rapisarda V, Babanov S, Vitale E, Strizhakov L, Romanova Z, Mukatova I. High levels of indoor fine particulate matter during the cold season in Almaty prompt urgent public health action. PLoS One 2023; 18:e0285477. [PMID: 37141317 PMCID: PMC10159184 DOI: 10.1371/journal.pone.0285477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 04/22/2023] [Indexed: 05/06/2023] Open
Abstract
INTRODUCTION Almaty is the largest city of Kazakhstan with extreme air pollution, mostly in the cold season, but little is known whether staying indoors could lessen the exposure. The aim was to quantitatively characterize indoor fine PM levels and to verify the contribution of ambient pollution to it in a polluted city like Almaty. METHODS We collected forty-six 24-hour 15-min average samples of the ambient air and a similar number of paired indoor samples (total 92 samples). Predictors of both ambient and indoor PM2.5 mass concentrations in mg/m3, including ambient concentration, precipitation, minimal daily temperature and humidity, along with the indoor/outdoor (I/O) ratio were tested in the adjusted regression models at eight 15-min lags. RESULTS Ambient air PM2.5 15-min average mass concentrations were highly variable and ranged from 0.001 to 0.694 mg/m3 (geometric mean (GM) 0.090, geometric standard deviation (GSD) 2.285). Snowing was the strongest predictor of lower ambient PM2.5 24-hour mass concentrations (median 0.053 vs 0.135 mg/m3 (p<0.001)). Indoor mean 15-min PM2.5 concentrations ranged from 0.002 to 0.228 mg/m3 (GM 0.034, GSD 2.254). In adjusted models, outdoor PM2.5 concentration explained 0.58 of all variability of the indoor concentration with a 75-min delay (R2 0.67 at lag8 on snowing days). Median I/O ranged from 0.386 (IQR 0.264 to 0.532) at lag0 to 0.442 (IQR 0.339 to 0.584) at lag8. CONCLUSION During the cold season when fossil fuel is burnt for heating, the population in Almaty is exposed to very high fine PM levels even indoors. Urgent public health action is needed.
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Affiliation(s)
- Denis Vinnikov
- Occupational Health Risks Laboratory, RUDN University, Moscow, Russian Federation
- Environmental Health Laboratory, al-Farabi Kazakh National University, Almaty, Kazakhstan
| | - Venerando Rapisarda
- Occupational Medicine, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Sergey Babanov
- Department of Clinical Pharmacology and Occupational Disease, Samara State Medical University, Samara, Russian Federation
| | - Ermanno Vitale
- Occupational Medicine, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Leonid Strizhakov
- Department of Internal, Occupational Diseases and Rheumatology, Sechenov First Moscow State Medical University, Moscow, Russian Federation
- Laboratory of Workers' Reproductive Health Disorders Prevention, Izmerov Research Institute of Occupational Health, Moscow, Russian Federation
- Department of Internal Diseases, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Zhanna Romanova
- Department of Epidemiology, Biostatistics and Evidence-Based Medicine, al-Farabi Kazakh National University, Almaty, Kazakhstan
| | - Irina Mukatova
- Department of Internal Diseases with Courses of Nephrology, Hematology, Allergology, and Immunology, Astana Medical University, Astana, Kazakhstan
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Zhang Y, Zhou R, Hu D, Chen J, Xu L. Modelling driving factors of PM 2.5 concentrations in port cities of the Yangtze River Delta. MARINE POLLUTION BULLETIN 2022; 184:114131. [PMID: 36150225 DOI: 10.1016/j.marpolbul.2022.114131] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 06/16/2023]
Abstract
PM2.5 is one of the major air pollutants in port cities of the Yangtze River Delta (YRD) of China. Understanding the driving factors of PM2.5 is essential to guide air pollution prevention and control. We selected 17 major port cities in YRD to study the driving factors of PM2.5 in 2019 and 2020. Generalized Additive Models were built to model the non-linear effects of single, multiple and interactions of driving factors on the variations of PM2.5. NO2, SO2 and the day of year are most strongly associated with the variation of PM2.5 concentration when used alone. Anthropogenic emissions play complicated roles in regulating PM2.5 concentration. Although the effect of cargo throughput (CT) on PM2.5 concentration is non-monotonic, higher PM2.5 levels are found to be associated with higher levels of SO2 and CT. This work can potentially provide a scientific basis for formulating PM2.5 prevention and control policies in the region.
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Affiliation(s)
- Yang Zhang
- College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
| | - Rui Zhou
- College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
| | - Daoxian Hu
- Shenzhen International Maritime Institute, Shenzhen 518081, China; Hyde (Guangzhou) International Logistics Group Co., LTD, Guangzhou 510665, China.
| | - Jihong Chen
- Shenzhen International Maritime Institute, Shenzhen 518081, China; College of Management, Shenzhen University, Shenzhen 518073, China; Commercial College, Xi'an International University, Xi'an 710077, China.
| | - Lang Xu
- College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
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Wu M, Xing Q, Duan H, Qin G, Sang N. Suppression of NADPH oxidase 4 inhibits PM 2.5-induced cardiac fibrosis through ROS-P38 MAPK pathway. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 837:155558. [PMID: 35504386 DOI: 10.1016/j.scitotenv.2022.155558] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/14/2022] [Accepted: 04/23/2022] [Indexed: 06/14/2023]
Abstract
Fine particulate matter (PM2.5) has been consistently linked to cardiovascular diseases, and cardiac fibrosis plays a crucial role in the occurrence and development of heart diseases. It is reported that NOX4-dependent redox signaling are responsible for TGFβ-mediated profibrotic responses. The current study was designed to explore the possible mechanisms of cardiac fibrosis by PM2.5 both in vitro and in vivo. Female C57BL/6 mice received PM2.5 (3 mg/kg b.w.) exposure with/without NOX4 inhibitor (apocynin, 25 mg/kg b.w.) or ROS scavenger (NALC, 50 mg/kg b.w.), every other day, for 4 weeks. H9C2 cells were incubated with PM2.5 (3 μg/mL) with/without 5 mM NALC, TGFβ inhibitor (SB431542, 10 μM), or siRNA-NOX4 for 24 h. The results demonstrated that PM2.5 induced evident collagen deposition and elevated expression of fibrosis biomarkers (Col1a1 & Col3a1). Significant systemic inflammatory response and cardiac oxidative stress were triggered by PM2.5. PM2.5 increased the protein expression of TGFβ1, NOX4, and P38 MAPK. Notably, the increased effects of PM2.5 could be suppressed by SB431542, siRNA-NOX4 in vitro or apocynin in vivo, and NALC. The reverse verification experiments further supported the involvement of the TGFβ/NOX4/ROS/P38 MAPK signaling pathway in the myocardial fibrosis induced by PM2.5. In summary, the current study provided evidence that PM2.5 challenge led to cardiac fibrosis through oxidative stress, systemic inflammation, and subsequent TGFβ/NOX4/ROS/P38 MAPK pathway and may offer new therapeutic targets in cardiac fibrosis.
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Affiliation(s)
- Meiqiong Wu
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China; Department of Children and Adolescences Health, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030001, PR China.
| | - Qisong Xing
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
| | - Huiling Duan
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China
| | - Guohua Qin
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China.
| | - Nan Sang
- College of Environment and Resource, Research Center of Environment and Health, Shanxi University, Taiyuan, Shanxi 030006, PR China.
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