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Cao S, Wu D, Liu L, Li S, Zhang S. Decoding the effect of demographic factors on environmental health based on city-level PM 2.5 pollution in China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 349:119380. [PMID: 37922823 DOI: 10.1016/j.jenvman.2023.119380] [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: 04/03/2023] [Revised: 10/13/2023] [Accepted: 10/14/2023] [Indexed: 11/07/2023]
Abstract
Although considerable health effects are gained from air quality improvement action plans implemented in China recently, they may have been amplified or offset due to the complexity and uncertainty of the changing demographic factors. In this study, we developed a framework for analyzing the effects of demographic factors on environmental health effects, focusing on three aspects: population scale, age structure, and spatial distribution. We quantified the above three effects by investigating how the health endpoint changed by the three demographic factors, based on a strategy of counterfactual and step-by-step relaxing hypothesis. We found that the increasing population scale and population aging caused 44,279 to 292,442 premature deaths, which offset the health effect of air quality improvement efforts for China. The change in population spatial distribution, in general, has little impact on the health effects of air quality improvement. Furthermore, the three effects are distributed unevenly across regions, especially the spatial distribution effect. Considering the widespread effect of demographic factors, PM2.5 concentration should be further reduced, and the aged population and mega-cities should be targeted for managing air quality in a cost-effective manner.
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Affiliation(s)
- Shuhui Cao
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China.
| | - Dan Wu
- School of Public Administration, Hainan University, Haikou, 570000, China; Hainan University-UC Davis Joint Research Center on Energy and Transportation, Hainan University, Haikou, 570000, China.
| | - Li Liu
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China; Guangdong Provincial Key Laboratory of Solid Wastes Pollution Control and Recycling, South China University of Technology, Guangzhou, 510006, China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, South China University of Technology, Guangzhou, 510006, China.
| | - Suli Li
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China.
| | - Shiqiu Zhang
- College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
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Li X, Abdullah LC, Sobri S, Syazarudin Md Said M, Aslina Hussain S, Poh Aun T, Hu J. Long-term spatiotemporal evolution and coordinated control of air pollutants in a typical mega-mountain city of Cheng-Yu region under the "dual carbon" goal. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2023; 73:649-678. [PMID: 37449903 DOI: 10.1080/10962247.2023.2232744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 05/31/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023]
Abstract
Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for megacities to formulate relevant air pollution prevention and control measures and achieve carbon neutrality goals. Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain-city in China, environmental problems are complex and sensitive. This research aims to investigate the exceeding standard levels and spatio-temporal evolution of criteria pollutants between 2014 and 2020. The results indicated that PM10, PM2.5, CO and SO2 were decreased significantly by 45.91%, 52.86%, 38.89% and 66.67%, respectively. Conversely, the concentration of pollutant O3 present a fluctuating growth and found a "seesaw" phenomenon between it and PM. Furthermore, PM and O3 are highest in winter and summer, respectively. SO2, NO2, CO, and PM showed a "U-shaped", and O3 showed an inverted "U-shaped" seasonal variation. PM and O3 concentrations are still far behind the WHO, 2021AQGs standards. Significant spatial heterogeneity was observed in air pollution distribution. These results are of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, and formulate a regional carbon peaking roadmap under climate coordination. Besides, it can provide an important platform for exploring air pollution in typical terrain around the world and provide references for related epidemiological research.Implications: Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain city, environmental problems are complex and sensitive. Under the background of the "14th Five-Year Plan", the construction of the "Cheng-Yu Dual-City Economic Circle" and the "Dual-Carbon" goal, this article comprehensively discussed the annual and seasonal excess levels and spatiotemporal evolution of pollutants under the multiple policy and the newest international standards (WHO,2021AQG) backgrounds from 2014 to 2020 in Chongqing. Furthermore, suggestions and measures related to the collaborative management of pollutants were discussed. Finally, limitations and recommendations were also put forward.Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for cities to formulate relevant air pollution control measures and achieve carbon neutrality goals. This study is of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, study and formulate a regional carbon peaking roadmap under climate coordination and an action plan for sustained improvement of air quality.In addition, this research can advanced our understanding of air pollution in complex terrain. Furthermore, it also promote the construction of the China national strategic Cheng-Yu economic circle and build a beautiful west. Moreover, it provides scientific insights for local policymakers to guide smart urban planning, industrial layout, energy structure, and transportation planning to improve air quality throughout the Cheng-Yu region. Finally, this is also conducive to future scientific research in other regions of China, and even megacities with complex terrain in the world.
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Affiliation(s)
- Xiaoju Li
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
- Department of Resource and Environment, Xichang University, Xichang City, Sichuan Province, China
| | - Luqman Chuah Abdullah
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Shafreeza Sobri
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Mohamad Syazarudin Md Said
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Siti Aslina Hussain
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Tan Poh Aun
- SOx NOx Asia Sdn Bhd, Subang Jaya, Selangor, Malaysia
| | - Jinzhao Hu
- Department of Resource and Environment, Xichang University, Xichang City, Sichuan Province, China
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Li X, Abdullah LC, Sobri S, Md Said MS, Hussain SA, Aun TP, Hu J. Long-Term Air Pollution Characteristics and Multi-scale Meteorological Factor Variability Analysis of Mega-mountain Cities in the Chengdu-Chongqing Economic Circle. WATER, AIR, AND SOIL POLLUTION 2023; 234:328. [PMID: 37200574 PMCID: PMC10175934 DOI: 10.1007/s11270-023-06279-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/29/2023] [Indexed: 05/20/2023]
Abstract
Currently, air quality has become central to global environmental policymaking. As a typical mountain megacity in the Cheng-Yu region, the air pollution in Chongqing is unique and sensitive. This study aims to comprehensively investigate the long-term annual, seasonal, and monthly variation characteristics of six major pollutants and seven meteorological parameters. The emission distribution of major pollutants is also discussed. The relationship between pollutants and the multi-scale meteorological conditions was explored. The results indicate that particulate matter (PM), SO2 and NO2 showed a "U-shaped" variation, while O3 showed an "inverted U-shaped" seasonal variation. Industrial emissions accounted for 81.84%, 58% and 80.10% of the total SO2, NOx and dust pollution emissions, respectively. The correlation between PM2.5 and PM10 was strong (R = 0.98). In addition, PM only showed a significant negative correlation with O3. On the contrary, PM showed a significant positive correlation with other gaseous pollutants (SO2, NO2, CO). O3 is only negatively correlated with relative humidity and atmospheric pressure. These findings provide an accurate and effective countermeasure for the coordinated management of air pollution in Cheng-Yu region and the formulation of the regional carbon peaking roadmap. Furthermore, it can improve the prediction accuracy of air pollution under multi-scale meteorological factors, promote effective emission reduction paths and policies in the region, and provide references for related epidemiological research. Graphical abstract Supplementary Information The online version contains supplementary material available at 10.1007/s11270-023-06279-8.
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Affiliation(s)
- Xiaoju Li
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, 43400 UPM Serdang, Selangor Malaysia
- Xichang University, No. 1 Xuefu Road, Anning Town, Xichang City, 615000 Sichuan Province China
| | - Luqman Chuah Abdullah
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, 43400 UPM Serdang, Selangor Malaysia
| | - Shafreeza Sobri
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, 43400 UPM Serdang, Selangor Malaysia
| | - Mohamad Syazarudin Md Said
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, 43400 UPM Serdang, Selangor Malaysia
| | - Siti Aslina Hussain
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, 43400 UPM Serdang, Selangor Malaysia
| | - Tan Poh Aun
- SOx NOx Asia Sdn Bhd, UEP Subang Jaya, 47620 Selangor Darul Ehsan Malaysia
| | - Jinzhao Hu
- Xichang University, No. 1 Xuefu Road, Anning Town, Xichang City, 615000 Sichuan Province China
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Li Y, Xue L, Tao Y, Li Y, Wu Y, Liao Q, Wan J, Bai Y. Exploring the contributions of major emission sources to PM 2.5 and attributable health burdens in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 322:121177. [PMID: 36731741 DOI: 10.1016/j.envpol.2023.121177] [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: 05/15/2022] [Revised: 01/27/2023] [Accepted: 01/29/2023] [Indexed: 06/18/2023]
Abstract
Ambient fine particulate matter (PM2.5) pollution is the principal environmental risk factor for health burdens in China. Identifying the sectoral contributions of pollutant emissions sources on multiple spatiotemporal scales can help in the formulation of specific strategies. In this study, we used sensitivity analysis to explore the specific contributions of seven major emission sources to ambient PM2.5 and attributable premature mortality across mainland China. In 2016, about 60% of China's population lived in areas with PM2.5 concentrations above the Chinese Ambient Air Quality Standard of 35 μg/m3. This percentage was expected to decrease to 35% and 39% if industrial and residential emissions were fully eliminated. In densely populated and highly polluted regions, residential sources contributed about 50% of the PM2.5 exposure in winter, while industrial sources contributed the most (29-51%) in the remaining seasons. The three major sectoral contributors to PM2.5-related deaths were industry (247,000 cases, 35%), residential sources (219,000 cases, 31%), and natural sources (87,000, 12%). The relative contributions of the different sectors varied in the different provinces, with industrial sources making the largest contribution in Shanghai (65%), while residential sources predominated in Heilongjiang (63%), and natural sources dominated in Xinjiang (82%). The contributions of the agricultural (11%), transportation (6%), and power (3%) sources were relatively low in China, but emissions mitigation was still effective in densely populated areas. In conclusion, to effectively alleviate health burdens across China, priority should be given to controlling residential emissions in winter and industrial emissions all year round, taking additional measures to curb emissions from other sources in urban hotspots, and formulating air pollution control strategies tailored to local conditions.
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Affiliation(s)
- Yong Li
- Key Laboratory of Western China's Environmental Systems, Ministry of Education, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China; Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 550025, China
| | - Liyang Xue
- Key Laboratory of Western China's Environmental Systems, Ministry of Education, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China; Gansu Ecological Environment Emergency and Accident Investigation Center, Lanzhou, 730030, China
| | - Yan Tao
- Key Laboratory of Western China's Environmental Systems, Ministry of Education, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
| | - Yidu Li
- Key Laboratory of Western China's Environmental Systems, Ministry of Education, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Yancong Wu
- Key Laboratory of Western China's Environmental Systems, Ministry of Education, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Qin Liao
- Key Laboratory of Western China's Environmental Systems, Ministry of Education, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China; Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Junyi Wan
- School of Natural Science, University of Manchester, Manchester, M13 9PL, United Kingdom
| | - Yun Bai
- School of Management Science and Engineering, Chongqing Technology and Business University, Chongqing, 400067, China
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Tian Y, Jia B, Zhao P, Song D, Huang F, Feng Y. Size distribution, meteorological influence and uncertainty for source-specific risks: PM 2.5 and PM 10-bound PAHs and heavy metals in a Chinese megacity during 2011-2021. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 312:120004. [PMID: 35995293 DOI: 10.1016/j.envpol.2022.120004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 08/15/2022] [Accepted: 08/16/2022] [Indexed: 06/15/2023]
Abstract
This study aims at exploring size distribution, meteorological influence and uncertainty for source-specific risks of atmospheric particulate matter (PM), which can improve risk-mitigation strategies for health protection. Heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) in PM2.5 and PM10 were detected in a Chinese megacity during 2011-2021. A new method named as PMFBMR, which combines the Positive Matrix Factorization, Bootstrapping, Mote Carlo and Risk assessment model, was developed to estimate uncertainty of source-specific risks. It was found that PAH risks concentrated in fine PM, while HMs showed high risks in both fine and coarse PMs. For PM2.5, HQ (non-cancer risk hazard quotient) of gasoline combustion (GC), diesel and heavy oil combustion (DC), coal combustion (CC), industrial source (IS), resuspended dust (RD) and secondary and transport PM (ST) were 0.6, 1.4, 0.9, 1.6, 0.3, and 0.3. ILCR (lifetime cancer risk) of sources were IS (9.2E-05) > DC (2.6E-05) = CC (2.6E-05) > RD (2.2E-05) > GC (1.7E-05) > ST (6.4E-06). PM2.5 from GC, DC, CC and IS caused higher risks than coarse PM, while coarse PM from RD caused higher risks. Source-specific risks were influenced not only by emissions, but also by meteorological condition and dominant toxic components. Risks of GC and DC were usually high during stable weather. Some high risks of CC, IS and RD occurred at strong WS due to transport or wind-blown resuspension. GC and DC risks (influenced by both PAHs and HMs) showed strong relationship with T, while IS and RD risks (dominated by HMs) showed weak link with meteorological conditions. For uncertainty of source-specific risks, HQ and ILCR were sensitive for different variables, because they were dominated by components with different uncertainties. When using source-specific risks for risk-mitigation strategies, the focused toxic components, used toxic values, PM sizes and uncertainty are necessary to be considered.
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Affiliation(s)
- Yingze Tian
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin, 300350, China.
| | - Bin Jia
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Peng Zhao
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Danlin Song
- Chengdu Research Academy of Environmental Sciences, Chengdu, 610015, China
| | - Fengxia Huang
- Chengdu Research Academy of Environmental Sciences, Chengdu, 610015, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin, 300350, China
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