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Dong Z, Li S, Jiang Y, Wang S, Xing J, Ding D, Zheng H, Wang H, Huang C, Yin D, Zhao B, Hao J. Health-Oriented Emission Control Strategy of Energy Utilization and Its Co-CO 2 Benefits: A Case Study of the Yangtze River Delta, China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:12320-12329. [PMID: 38973717 DOI: 10.1021/acs.est.3c10693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/09/2024]
Abstract
Reducing air pollutants and CO2 emissions from energy utilization is crucial for achieving the dual objectives of clean air and carbon neutrality in China. Thus, an optimized health-oriented strategy is urgently needed. Herein, by coupling a CO2 and air pollutants emission inventory with response surface models for PM2.5-associated mortality, we shed light on the effectiveness of protecting human health and co-CO2 benefit from reducing fuel-related emissions and generate a health-oriented strategy for the Yangtze River Delta (YRD). Results reveal that oil consumption is the primary contributor to fuel-related PM2.5 pollution and premature deaths in the YRD. Significantly, curtailing fuel consumption in transportation is the most effective measure to alleviate the fuel-related PM2.5 health impact, which also has the greatest cobenefits for CO2 emission reduction on a regional scale. Reducing fuel consumption will achieve substantial health improvements especially in eastern YRD, with nonroad vehicle emission reductions being particularly impactful for health protection, while on-road vehicles present the greatest potential for CO2 reductions. Scenario analysis confirms the importance of mitigating oil consumption in the transportation sector in addressing PM2.5 pollution and climate change.
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Affiliation(s)
- Zhaoxin Dong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shengyue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yueqi Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Dian Ding
- Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, 00014 Helsinki, Finland
| | - Haotian Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of the Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Dejia Yin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Bin Zhao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Jiming Hao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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Xue T, Wang R, Wang M, Wang Y, Tong D, Meng X, Huang C, Ai S, Li F, Cao J, Tong M, Ni X, Liu H, Deng J, Lu H, Wan W, Gong J, Zhang S, Zhu T. Health benefits from the rapid reduction in ambient exposure to air pollutants after China's clean air actions: progress in efficacy and geographic equality. Natl Sci Rev 2024; 11:nwad263. [PMID: 38213522 PMCID: PMC10776362 DOI: 10.1093/nsr/nwad263] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 09/13/2023] [Accepted: 10/08/2023] [Indexed: 01/13/2024] Open
Abstract
Clean air actions (CAAs) in China have been linked to considerable benefits in public health. However, whether the beneficial effects of CAAs are equally distributed geographically is unknown. Using high-resolution maps of the distributions of major air pollutants (fine particulate matter [PM2.5] and ozone [O3]) and population, we aimed to track spatiotemporal changes in health impacts from, and geographic inequality embedded in, the reduced exposures to PM2.5 and O3 from 2013 to 2020. We used a method established by the Global Burden of Diseases Study. By analyzing the changes in loss of life expectancy (LLE) attributable to PM2.5 and O3, we calculated the gain of life expectancy (GLE) to quantify the health benefits of the air-quality improvement. Finally, we assessed the geographic inequality embedded in the GLE using the Gini index (GI). Based on risk assessments of PM2.5 and O3, during the first stage of CAAs (2013 to 2017), the mean GLE was 1.87 months. Half of the sum of the GLE was disproportionally distributed in about one quarter of the population exposed (GI 0.44). During the second stage of CAAs (2017 to 2020), the mean GLE increased to 3.94 months and geographic inequality decreased (GI 0.18). According to our assessments, CAAs were enhanced, from the first to second stages, in terms of not only preventing premature mortality but also ameliorating health inequalities. The enhancements were related to increased sensitivity to the health effects of air pollution and synergic control of PM2.5 and O3 levels. Our findings will contribute to optimizing future CAAs.
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Affiliation(s)
- Tao Xue
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
- Advanced Institute of Information Technology, Peking University, Hangzhou311215, China
| | - Ruohan Wang
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY14214, USA
| | - Yanying Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
| | - Dan Tong
- Department of Earth System Science, Tsinghua University, Beijing100084, China
| | - Xia Meng
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai200433, China
| | - Conghong Huang
- College of Land Management, Nanjing Agricultural University, Nanjing 210095, China
- National & Local Joint Engineering, Research Center for Rural Land Resources Use and Consolidation, Nanjing 210095, China
| | - Siqi Ai
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Fangzhou Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Jingyuan Cao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Mingkun Tong
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Xueqiu Ni
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Hengyi Liu
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Jianyu Deng
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Hong Lu
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health/Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing100191, China
| | - Wei Wan
- Clean Air Asia, Beijing100600, China
| | - Jicheng Gong
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Shiqiu Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
| | - Tong Zhu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing100871, China
- State Environmental Protection Key Laboratory of Atmospheric Exposure, and Health Risk Management and Center for Environment and Health, Peking University, Beijing100871, China
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Xue T, Wang R, Tong M, Kelly FJ, Liu H, Li J, Li P, Qiu X, Gong J, Shang J, Zhu T. Estimating the exposure-response function between long-term ozone exposure and under-5 mortality in 55 low-income and middle-income countries: a retrospective, multicentre, epidemiological study. Lancet Planet Health 2023; 7:e736-e746. [PMID: 37673544 DOI: 10.1016/s2542-5196(23)00165-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 07/02/2023] [Accepted: 07/03/2023] [Indexed: 09/08/2023]
Abstract
BACKGROUND In 2021, WHO suggested new target concentration limits for long-term exposure to ambient ozone. However, the harmful effects of ozone on vulnerable children have not been sufficiently studied. We aimed to evaluate the association between long-term ozone exposure and mortality in children younger than 5 years (hereafter denoted under-5 mortality) in low-income and middle-income countries (LMICs) and to estimate this mortality burden for 97 LMICs. METHODS By combining information from 128 Demographic and Health Surveys, we evaluated the association between the survival status of more than 1·2 million children younger than 5 years from 2457 sampling strata in 55 LMICs and the average peak-season ozone concentration during the life course, using a fixed-effects Cox model. A non-linear exposure-response function was developed by integrating the marginal effects of within-strata variation in exposure. We extrapolated the function obtained from the 55 LMICs to estimate the under-5 mortality burden attributable to ozone exposure in 97 LMICs, in which more than 95% of global deaths in this age group occur. FINDINGS The fixed-effects model showed a robust association between ozone and under-5 mortality. According to the fully adjusted linear model, an increment of 10 ppb in the life-course average peak-season ozone concentration was associated with a 6·4% (95% CI 2·4-10·7) increase in the risk of under-5 mortality. The non-linear exposure-response function showed a sublinear curvature with a threshold, suggesting that the effect of ozone exposure was non-significant at concentrations lower than the first-stage interim target (100 μg/m3) recommended by WHO. Using this function, we estimate that, in 2010, long-term ozone exposure contributed to 153 361 (95% CI 17 077-276 768; 2·3% [0·3-4·1]) deaths of children younger than 5 years in 97 LMICs, which is equivalent to 56·8% of all ozone-related deaths in adults (269 785) in these countries. From 2003 to 2017, the ozone-related under-5 mortality burden decreased in most of the 97 LMICs. INTERPRETATION Long-term exposure to ozone concentrations higher than the WHO first-stage interim target is a risk factor for under-5 mortality, and ozone exposure contributes substantially to mortality in this age group in LMICs. Increased efforts should be made to control ambient ozone pollution as this will lead to positive health benefits. FUNDING Ministry of Science and Technology of the People's Republic of China and China National Natural Science Foundation.
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Affiliation(s)
- Tao Xue
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health, School of Public Health, Peking University Health Science Centre, Beijing, China; Department of Epidemiology and Biostatistics/Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China.
| | - Ruohan Wang
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health, School of Public Health, Peking University Health Science Centre, Beijing, China; Department of Epidemiology and Biostatistics/Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Mingkun Tong
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health, School of Public Health, Peking University Health Science Centre, Beijing, China; Department of Epidemiology and Biostatistics/Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Frank J Kelly
- Environmental Research Group, MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Hengyi Liu
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health, School of Public Health, Peking University Health Science Centre, Beijing, China; Department of Epidemiology and Biostatistics/Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Jiajianghui Li
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health, School of Public Health, Peking University Health Science Centre, Beijing, China; Department of Epidemiology and Biostatistics/Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Pengfei Li
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health, School of Public Health, Peking University Health Science Centre, Beijing, China; Department of Epidemiology and Biostatistics/Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China
| | - Xinghua Qiu
- State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management, Center for Environment and Health, Peking University, Beijing, China; College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Jicheng Gong
- State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management, Center for Environment and Health, Peking University, Beijing, China; College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Jing Shang
- State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management, Center for Environment and Health, Peking University, Beijing, China; College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Tong Zhu
- State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management, Center for Environment and Health, Peking University, Beijing, China; College of Environmental Sciences and Engineering, Peking University, Beijing, China.
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Xie Y, Xu M, Pu J, Pan Y, Liu X, Zhang Y, Xu S. Large-scale renewable energy brings regionally disproportional air quality and health co-benefits in China. iScience 2023; 26:107459. [PMID: 37599826 PMCID: PMC10432202 DOI: 10.1016/j.isci.2023.107459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/06/2023] [Accepted: 07/19/2023] [Indexed: 08/22/2023] Open
Abstract
Developing renewable energy could jointly reduce air pollution, greenhouse gas emissions, and bring air pollution-related health co-benefits. However, the temporal and sub-national distributions of investment costs and human health co-benefits from renewable energy deployment remain unclear. To investigate this gap, we linked multiple models for a more comprehensive assessment of the economic-environmental-health co-benefits of renewable energy development in China. The results show that developing renewable energy can avoid 0.6 million premature mortalities, 151 million morbidities, and 111 million work-loss days in 2050. Meanwhile, the human health and economic co-benefits vary substantially across regions in China. Renewable energy can undoubtedly bring health and economic co-benefits. Nevertheless, the economic benefits lag considerably behind the high initial investment cost, first negative in 2030 (-0.6 trillion Yuan) and then positive in 2050 (2.9 trillion Yuan). Hence, renewable energy deployment strategy must be carefully designed considering the regional disparities.
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Affiliation(s)
- Yang Xie
- School of Economics and Management, Beihang University, Beijing 100191, China
- Laboratory for Low-carbon Intelligent Governance, Beihang University, Beijing 100191, China
| | - Meng Xu
- School of Management, Wuhan Institute of Technology, Wuhan 430205, China
| | - Jinlu Pu
- School of Economics and Management, Beihang University, Beijing 100191, China
| | - Yujie Pan
- College of Environmental Science and Engineering, Peking University, Beijing 100871, China
| | - Xiaorui Liu
- College of Environmental Science and Engineering, Peking University, Beijing 100871, China
| | - Yanxu Zhang
- School of Atmospheric Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Shasha Xu
- College of Environmental Science and Engineering, Peking University, Beijing 100871, China
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Zhu T, Tang M, Gao M, Bi X, Cao J, Che H, Chen J, Ding A, Fu P, Gao J, Gao Y, Ge M, Ge X, Han Z, He H, Huang RJ, Huang X, Liao H, Liu C, Liu H, Liu J, Liu SC, Lu K, Ma Q, Nie W, Shao M, Song Y, Sun Y, Tang X, Wang T, Wang T, Wang W, Wang X, Wang Z, Yin Y, Zhang Q, Zhang W, Zhang Y, Zhang Y, Zhao Y, Zheng M, Zhu B, Zhu J. Recent Progress in Atmospheric Chemistry Research in China: Establishing a Theoretical Framework for the "Air Pollution Complex". ADVANCES IN ATMOSPHERIC SCIENCES 2023; 40:1-23. [PMID: 37359906 PMCID: PMC10140723 DOI: 10.1007/s00376-023-2379-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 03/06/2023] [Accepted: 04/10/2023] [Indexed: 06/28/2023]
Abstract
Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the "air pollution complex" was first proposed by Professor Xiaoyan TANG in 1997. For papers published in 2021 on air pollution (only papers included in the Web of Science Core Collection database were considered), more than 24 000 papers were authored or co-authored by scientists working in China. In this paper, we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years, including studies on (1) sources and emission inventories, (2) atmospheric chemical processes, (3) interactions of air pollution with meteorology, weather and climate, (4) interactions between the biosphere and atmosphere, and (5) data assimilation. The intention was not to provide a complete review of all progress made in the last few years, but rather to serve as a starting point for learning more about atmospheric chemistry research in China. The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established, provided robust scientific support to highly successful air pollution control policies in China, and created great opportunities in education, training, and career development for many graduate students and young scientists. This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances, whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China, to hopefully be addressed over the next few decades.
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Affiliation(s)
- Tong Zhu
- Peking University, Beijing, 100871 China
| | - Mingjin Tang
- Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640 China
| | - Meng Gao
- Hong Kong Baptist University, Hong Kong SAR, China
| | - Xinhui Bi
- Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, 510640 China
| | - Junji Cao
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
| | - Huizheng Che
- Chinese Academy of Meteorological Sciences, Beijing, 100081 China
| | | | - Aijun Ding
- Nanjing University, Nanjing, 210023 China
| | | | - Jian Gao
- Chinese Research Academy of Environmental Sciences, Beijing, 100012 China
| | - Yang Gao
- Ocean University of China, Qingdao, 266100 China
| | - Maofa Ge
- Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 China
| | - Xinlei Ge
- Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Zhiwei Han
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
| | - Hong He
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China
| | - Ru-Jin Huang
- Institute of Earth Environment, Chinese Academy of Sciences, Xi’an, 710061 China
| | - Xin Huang
- Nanjing University, Nanjing, 210023 China
| | - Hong Liao
- Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Cheng Liu
- University of Science and Technology of China, Hefei, 230026 China
| | - Huan Liu
- Tsinghua University, Beijing, 100084 China
| | - Jianguo Liu
- Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
| | | | - Keding Lu
- Peking University, Beijing, 100871 China
| | - Qingxin Ma
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China
| | - Wei Nie
- Nanjing University, Nanjing, 210023 China
| | - Min Shao
- Jinan University, Guangzhou, 510632 China
| | - Yu Song
- Peking University, Beijing, 100871 China
| | - Yele Sun
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
| | - Xiao Tang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
| | - Tao Wang
- Hong Kong Polytechnic University, Hong Kong SAR, China
| | | | - Weigang Wang
- Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 China
| | | | - Zifa Wang
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
| | - Yan Yin
- Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | | | - Weijun Zhang
- Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
| | - Yanlin Zhang
- Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Yunhong Zhang
- Beijing Institute of Technology, Beijing, 100081 China
| | - Yu Zhao
- Nanjing University, Nanjing, 210023 China
| | - Mei Zheng
- Peking University, Beijing, 100871 China
| | - Bin Zhu
- Nanjing University of Information Science and Technology, Nanjing, 210044 China
| | - Jiang Zhu
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029 China
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Li Y, Li B, Liao H, Zhou BB, Wei J, Wang Y, Zang Y, Yang Y, Liu R, Wang X. Changes in PM 2.5-related health burden in China's poverty and non-poverty areas during 2000-2020: A health inequality perspective. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 861:160517. [PMID: 36464040 DOI: 10.1016/j.scitotenv.2022.160517] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/30/2022] [Accepted: 11/22/2022] [Indexed: 06/17/2023]
Abstract
China suffers from severe PM2.5 pollution that has resulted in a huge health burden. Such PM2.5-related health burden has long been suspected to differ between China's poverty-stricken areas (PAs) and non-poverty-stricken areas (NPAs). Yet, evidence-based examination of this long-held belief, which is critical as a barrier of environmental injustice to advancing China's sustainability, is still missing. Here our study shows that the PM2.5 pollution is more serious in China's NPAs than PAs-with their annual averages being respectively 54.83 μg/m3 and 43.63 μg/m3-causing higher premature mortality in the NPAs. Compared to economic inequality, China's total PM2.5-related premature mortality was relatively evenly distributed during 2000-2015 across regions of varying levels of gross domestic product (GDP) per capita but increased slightly in 2015-2020 owing to the dramatic change in age structure. The elderly population increased by 31 %. PM2.5-related premature deaths were more severe for populations of low socioeconomic status, and such environmental health inequalities could be amplified by population aging. Additionally, population migration from China's PAs to developed cities contributed to 638, 779, 303, 954, and 896 premature deaths in 2000, 2005, 2010, 2015, and 2020, respectively. Changes in the age structure (53 %) and PM2.5 concentration (28 %) had the greatest impact on premature deaths, followed by changes in population (12 %) and baseline mortality (8 %). The contribution rate of changes in the age structure and PM2.5 concentration was higher in PAs than in NPAs. Our findings provide insight into PM2.5-related premature death and environmental inequality, and may inform more equitable clean air policies to achieve China's sustainable development goals.
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Affiliation(s)
- Yan Li
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Baojie Li
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Hong Liao
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Bing-Bing Zhou
- School of International Affairs and Public Administration, Ocean University of China, Qingdao 266100, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States
| | - Yuxia Wang
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Yuzhu Zang
- School of Public Administration, China University of Geosciences, Wuhan 430074, China
| | - Yang Yang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Rui Liu
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Xiaorui Wang
- Jiangsu Provincial Land Development and Consolidation Center, Nanjing 210017, China
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Yang Y, Guo W, Sun J, Chen Q, Meng X, Wang L, Tao H, Yang L. Characteristics of volatile organic compounds and secondary organic aerosol pollution in different functional areas of petrochemical industrial cities in Northwest China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159903. [PMID: 36334656 DOI: 10.1016/j.scitotenv.2022.159903] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 10/25/2022] [Accepted: 10/29/2022] [Indexed: 06/16/2023]
Abstract
The aim of this study was to better understand the characteristics of volatile organic compounds (VOCs) and secondary organic aerosol (SOA) pollution in different functional areas of petrochemical industrial cities. In Lanzhou, a typical petrochemical industrial city in Northwest China, with the use of an Integrated Atmospheric Mobile Monitoring Vehicle (IAMMV), various real-time online monitoring instruments, including a VOC monitoring instrument (TH-300B) and single-particle aerosol mass spectrometer (SPAMS), were used in combination. These instruments were employed to determine PM2.5, VOCs and other factors at monitoring sites in Xigu (XG) and Chengguan (CG) districts in September 2020 and 2021, respectively. The results revealed that during the monitoring period, the average VOC concentrations at the XG and CG monitoring sites were 102.3 and 35.8 ppb, respectively. Benzene (45.58 %) and toluene (24.47 %) significantly contributed to the SOA formation potential at the XG site. M/P-xylene (27.88 %) and toluene (23.64 %) more notably contributed to the SOA formation potential at the CG site. The PM2.5 mass concentration at the XG site (24.1 μg·m-3) was similar to that at the CG site (21.2 μg·m-3), but the proportion of particulate matter components greatly differed. The proportion of organic carbon (OC) at the XG site (19.00 %) was higher than that at the CG site (9.97 %). The number of particles containing C2H3O+ (m/z = 43) accounted for 36.96 % and 15.41 % of the total particles at the XG and CG sites, respectively. The mixing ratios of OC and hybrid carbon (OCEC) with C2H3O+ (m/z = 43) were 0.81 and 0.53, respectively, at the XG site and reached only 0.48 and 0.25, respectively, at the CG site. The secondary ageing degree of particles in XG district was high. These results could provide a reference for ambient air quality improvement and the formulation of governance measures in different functional areas of petrochemical industrial cities.
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Affiliation(s)
- Yanping Yang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Northwest Institute of Eco-environmental Resources, Chinese Academy of Sciences, Lanzhou 730000, China; University of Chinese Academy of Sciences, Beijing 100049, China; Gansu Environmental Monitoring Centre, Lanzhou 730000, China
| | - Wenkai Guo
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; College of Science, Northwest A&F University, Yangling 712100, China.
| | - Jian Sun
- Gansu Environmental Monitoring Centre, Lanzhou 730000, China
| | - Qiang Chen
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Xianhong Meng
- Northwest Institute of Eco-environmental Resources, Chinese Academy of Sciences, Lanzhou 730000, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lina Wang
- Gansu Environmental Monitoring Centre, Lanzhou 730000, China
| | - Huijie Tao
- Gansu Environmental Monitoring Centre, Lanzhou 730000, China
| | - Lili Yang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Gansu Environmental Monitoring Centre, Lanzhou 730000, China
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Yang L, Wang N, Liu S, Xiao Q, Geng G, Zhang X, Li H, Zheng Y, Guo F, Li Q, Li J, Ren A, Xue T, Ji J. The PM 2.5 concentration reduction improves survival rate of lung cancer in Beijing. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159857. [PMID: 36328253 DOI: 10.1016/j.scitotenv.2022.159857] [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: 05/25/2022] [Revised: 10/11/2022] [Accepted: 10/27/2022] [Indexed: 06/16/2023]
Abstract
INTRODUCTION Long-term exposure to ambient fine particulate matter (PM2.5) has been linked to increases in the incidence of lung cancer. However, more evidence is needed to conclude its effects on lung cancer survival. OBJECTIVES The study aimed to explore the relationship between long-term PM2.5 exposure and lung cancer survival and evaluated the benefits of clean air actions in Beijing. METHODS A whole-population cohort study was conducted on lung cancer patients diagnosed between 2001 and 2017. An atmospheric chemical transport model was used to estimate exposure under a counterfactual scenario without the policy and then quantified the effect of the policy. Cox regression models were used with the seasonality-adjusted PM2.5 as the main effect. RESULTS A 10 μg/m3 increase in PM2.5 was estimated to be with a 6.5 % (95 % CI: 4.8 %, 8.2 %) increase in the mortality rates. The association was heterogeneous and modified by individual-level characteristics. The clean air actions were estimated to have prevented 3548 (95 % CI: 3280, 3825) premature deaths and to have prolonged survival time by 4.29 months (95 % CI: 0.01, 25.11). CONCLUSION Our findings suggest that PM2.5 exposure lowers the survival rate for lung cancer. The clean air actions implemented in Beijing can protect lung cancer patients by increasing their survival time. SYNOPSIS Long-term exposure to PM2.5 can lower lung patients' survival rates whereas the clean air actions in Beijing have prolonged these patients' survival time by reducing PM2.5 level.
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Affiliation(s)
- Lei Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Ning Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Shuo Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Qingyang Xiao
- Department of Earth System Science, Tsinghua University, Beijing, China, 100085
| | - Guannan Geng
- School of Environment, Tsinghua University, Beijing, China, 100085
| | - Xi Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Huichao Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Yixuan Zheng
- Center for Regional Air Quality Simulation and Control, Chinese Academy for Environmental Planning, Beijing 100012, China
| | - Fuyu Guo
- Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Qingyu Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Jiajianghui Li
- Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Aiguo Ren
- Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Tao Xue
- Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
| | - Jiafu Ji
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital & Institute, Beijing 100142, China.
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Estimation of stillbirths attributable to ambient fine particles in 137 countries. Nat Commun 2022; 13:6950. [PMID: 36446772 PMCID: PMC9709081 DOI: 10.1038/s41467-022-34250-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 10/18/2022] [Indexed: 11/30/2022] Open
Abstract
Gestational exposure to ambient fine particles (PM2.5) increases the risk of stillbirth, but the related disease burden is unknown, particularly in low- and middle-income countries (LMICs). We combine state-of-the-art estimates on stillbirths, and multiple exposure-response functions obtained from previous meta-analyses or derived by a self-matched case-control study in 54 LMICs. 13,870 stillbirths and 32,449 livebirths are extracted from 113 geocoded surveys from the Demographic and Health Surveys. Each stillbirth is compared to livebirth(s) of the same mother using a conditional logit regression. We find that 10-µg/m3 increase of PM2.5 is associated with an 11.0% (95% confidence interval [CI] 6.4, 15.7) increase in the risk of stillbirth, and the association is significantly enhanced by maternal age. Based on age-specific nonlinear PM2.5-stillbirth curves, we evaluate the PM2.5-related stillbirths in 137 countries. In 2015, of 2.09 (95% CI: 1.98, 2.20) million stillbirths, 0.83 (0.54, 1.08) million or 39.7% (26.1, 50.8) are attributable to PM2.5 exposure exceeding the reference level of 10 μg/m3. In LMICs, preventing pregnant women from being exposed to PM2.5 can improve maternal health.
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Zhang Q, Meng X, Shi S, Kan L, Chen R, Kan H. Overview of particulate air pollution and human health in China: Evidence, challenges, and opportunities. Innovation (N Y) 2022; 3:100312. [PMID: 36160941 PMCID: PMC9490194 DOI: 10.1016/j.xinn.2022.100312] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 08/31/2022] [Indexed: 11/25/2022] Open
Abstract
Ambient particulate matter (PM) pollution in China continues to be a major public health challenge. With the release of the new WHO air quality guidelines in 2021, there is an urgent need for China to contemplate a revision of air quality standards (AQS). In the recent decade, there has been an increase in epidemiological studies on PM in China. A comprehensive evaluation of such epidemiological evidence among the Chinese population is central for revision of the AQS in China and in other developing countries with similar air pollution problems. We thus conducted a systematic review on the epidemiological literature of PM published in the recent decade. In summary, we identified the following: (1) short-term and long-term PM exposure increase mortality and morbidity risk without a discernible threshold, suggesting the necessity for continuous improvement in air quality; (2) the magnitude of long-term associations with mortality observed in China are comparable with those in developed countries, whereas the magnitude of short-term associations are appreciably smaller; (3) governmental clean air policies and personalized mitigation measures are potentially effective in protecting public and individual health, but need to be validated using mortality or morbidity outcomes; (4) particles of smaller size range and those originating from fossil fuel combustion appear to show larger relative health risks; and (5) molecular epidemiological studies provide evidence for the biological plausibility and mechanisms underlying the hazardous effects of PM. This updated review may serve as an epidemiological basis for China’s AQS revision and proposes several perspectives in designing future health studies. Acute effects of PM are smaller in China compared with developed countries Health effects caused by PM depend on particle composition, source, and size There are no thresholds for the health effects of PM Mechanistic studies support the biological plausibility of PM’s health effects
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Affiliation(s)
- Qingli Zhang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China
| | - Lena Kan
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, MD 21205, USA
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai 200032, China.,Children's Hospital of Fudan University, National Center for Children's Health, Shanghai 201102, China
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