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Yu S, Zhu Q, Yu M, Zhou C, Meng R, Bai G, Huang B, Xiao Y, Wu W, Guo Y, Zhang J, Tang W, Xu J, Liang S, Chen Z, He G, Ma W, Liu T. The association between long-term exposure to ambient formaldehyde and respiratory mortality risk: A national study in China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 283:116860. [PMID: 39126815 DOI: 10.1016/j.ecoenv.2024.116860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 08/05/2024] [Accepted: 08/07/2024] [Indexed: 08/12/2024]
Abstract
INTRODUCTION While ambient formaldehyde (HCHO) concentrations are increasing worldwide, there was limited research on its health effects. OBJECTIVES To assess the association of long-term exposure to ambient HCHO with the risk of respiratory (RESP) mortality and the associated mortality burden in China. METHODS Annual and seasonal RESP death and tropospheric HCHO vertical columns data were collected in 466 counties/districts across China during 2013-2016. A difference-in-differences approach combined with a generalized linear mixed-effects regression model was employed to assess the exposure-response association between long-term ambient HCHO exposure and RESP mortality risk. Additionally, we computed the attributable fraction (AF) to gauge the proportion of RESP mortality attributable to HCHO exposure. RESULTS This analysis encompassed 560,929 RESP deaths. The annual mean ambient HCHO concentration across selected counties/districts was 8.02×1015 ± 2.22×1015 molec.cm-2 during 2013-2016. Each 1.00×1015 molec.cm-2 increase in ambient HCHO was associated with a 1.61 % increase [excess risk (ER), 95 % confidence interval (CI): 1.20 %, 2.03 %] in the RESP mortality risk. The AF of RESP mortality attributable to HCHO was 12.16 % (95 %CI:9.33 %, 14.88 %), resulting in an annual average of 125,422 (95 %CI:96,404, 153,410) attributable deaths in China. Stratified analyses suggested stronger associations in individuals aged ≥65 years old (ER=1.87 %, 95 %CI:1.43 %, 2.32 %), in cold seasons (ER=1.00 %, 95 %CI:0.56 %, 1.44 %), in urban areas (ER=1.65 %, 95 %CI:1.15 %, 2.16 %), and in chronic obstructive pulmonary disease patients (ER=1.95 %, 95 %CI:1.42 %, 2.48 %). CONCLUSIONS This study suggested that long-term HCHO exposure may significantly increase the risk of RESP mortality, leading to a substantial mortality burden. Targeted measures should be implemented to control ambient HCHO pollution promptly.
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Affiliation(s)
- Siwen Yu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Key Laboratory of Viral Pathogenesis & Infection Prevention and Control, Jinan University, Ministry of Education, Guangzhou 510632, China
| | - Qijiong Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Key Laboratory of Viral Pathogenesis & Infection Prevention and Control, Jinan University, Ministry of Education, Guangzhou 510632, China
| | - Min Yu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang 310051, China
| | - Chunliang Zhou
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha 450001, China
| | - Ruilin Meng
- Guangdong Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Guoxia Bai
- Institute of Non-communicable Diseases Prevention and Control, Tibet Center for Disease Control and Prevention, Lhasa 850000, China
| | - Biao Huang
- Health Hazard Factors Control Department, Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Yize Xiao
- Yunnan Center for Disease Control and Prevention, Kunming 650022, China
| | - Wei Wu
- Guangdong Provincial Institute of Public Health, Guangdong Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Yanfang Guo
- Bao'an District Hospital for Chronic Diseases Prevention and Cure, Shenzhen 518101, China
| | - Juanjuan Zhang
- Bao'an Center for Chronic Disease Control, Shenzhen 518101, China
| | - Weiling Tang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Jiahong Xu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Shuru Liang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Zhiqing Chen
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China.
| | - Tao Liu
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Key Laboratory of Viral Pathogenesis & Infection Prevention and Control, Jinan University, Ministry of Education, Guangzhou 510632, China.
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Liu S, Li X, Wei J, Shu L, Jin J, Fu TM, Yang X, Zhu L. Short-Term Exposure to Fine Particulate Matter and Ozone: Source Impacts and Attributable Mortalities. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:11256-11267. [PMID: 38885093 PMCID: PMC11223482 DOI: 10.1021/acs.est.4c00339] [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: 01/10/2024] [Revised: 06/03/2024] [Accepted: 06/04/2024] [Indexed: 06/20/2024]
Abstract
Short-term exposure to particles with aerodynamic diameters less than 2.5 μm (PM2.5) and ozone (O3) are important risk factors for human health. Despite the awareness of reducing attributable health burden, region-specific and source-specific strategies remain less explored due to the gap between precursor emissions and health effects. In this study, we isolate the health burden of individual sector sources of PM2.5 and O3 precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), across the globe. Specifically, we estimate mortalities attributable to short-term exposure using machine-learning-based daily exposure estimates and quantify sectoral impacts using chemical transport model simulations. Globally, short-term exposure to PM2.5 and O3 result in 713.5 (95% Confidence Interval: 598.8-843.3) thousand and 496.3 (371.3-646.1) thousand mortalities in 2019, respectively, of which 12.5% are contributed by fuel-related NOx emissions from transportation, energy, and industry. Sectoral impacts from anthropogenic NOx and VOC emissions on health burden vary significantly among seasons and regions, requiring a target shift from transportation in winter to industry in summer for East Asia, for instance. Emission control and health management are additionally complicated by unregulated natural influences during climatic events. Fire-sourced NOx and VOC emissions, respectively, contribute to 8.5 (95% CI: 6.2-11.7) thousand and 4.8 (3.6-5.9) thousand PM2.5 and O3 mortalities, particularly for tropics with high vulnerability to climate change. Additionally, biogenic VOC emissions during heatwaves contribute to 1.8 (95% CI: 1.5-2.2) thousand O3-introduced mortalities, posing challenges in urban planning for high-income regions, where biogenic contributions to health burden during heatwaves are 13% of anthropogenic contributions annually. Our study provides important implications for temporally dynamic and sector-targeted emission control and health management strategies, which are of urgency under the projection of continuously increasing energy consumption and changing climate.
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Affiliation(s)
- Song Liu
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- Collaborative
Innovation Center of Atmospheric Environment and Equipment Technology,
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution
Control (AEMPC), Nanjing University of Information
Science and Technology, Nanjing 210044, China
| | - Xicheng Li
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Jing Wei
- Department
of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary
Center, University of Maryland, College Park, Maryland 20742-5031, United
States
| | - Lei Shu
- School
of Geographical Sciences, Fujian Normal
University, Fuzhou 350117, China
| | - Jianbing Jin
- Jiangsu
Key Laboratory of Atmospheric Environment Monitoring and Pollution
Control, Collaborative Innovation Center of Atmospheric Environment
and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Tzung-May Fu
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- Guangdong
Provincial Observation and Research Station for Coastal Atmosphere
and Climate of the Greater Bay Area, Shenzhen 518055, China
- Shenzhen
Key Laboratory of Precision Measurement and Early Warning Technology
for Urban Environmental Health Risks, School of Environmental Science
and Engineering, Southern University of
Science and Technology, Shenzhen 518055, China
| | - Xin Yang
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- Guangdong
Provincial Observation and Research Station for Coastal Atmosphere
and Climate of the Greater Bay Area, Shenzhen 518055, China
- Shenzhen
Key Laboratory of Precision Measurement and Early Warning Technology
for Urban Environmental Health Risks, School of Environmental Science
and Engineering, Southern University of
Science and Technology, Shenzhen 518055, China
| | - Lei Zhu
- School
of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- Guangdong
Provincial Observation and Research Station for Coastal Atmosphere
and Climate of the Greater Bay Area, Shenzhen 518055, China
- Shenzhen
Key Laboratory of Precision Measurement and Early Warning Technology
for Urban Environmental Health Risks, School of Environmental Science
and Engineering, Southern University of
Science and Technology, Shenzhen 518055, China
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Li K, Ye H, Dong Z, Amujilite, Zhao M, Xu Q, Xu J. The health and economic burden of ozone pollution on Alzheimer's disease and mild cognitive impairment in China. ENVIRONMENTAL RESEARCH 2024; 259:119506. [PMID: 38944103 DOI: 10.1016/j.envres.2024.119506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 06/23/2024] [Accepted: 06/26/2024] [Indexed: 07/01/2024]
Abstract
Ozone pollution is increasingly recognized as a serious environmental threat that exacerbates dementia risks, including Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI). Amid rapid industrialization, China faces significant air quality challenges. However, there has been a scarcity of detailed studies assessing the health and economic impacts of ozone pollution on these conditions. This study aims to address this gap by utilizing the BenMap-CE tool and incorporating parameters obtained from systematic reviews of epidemiological studies, official statistics, and weighted averages, to accurately quantify the effects of ozone exposure in China. This research evaluated the health and economic burdens at both national and provincial levels, focusing on the additional impacts attributed to increased ozone levels. The results reveal that in 2023, compared to 2015, ozone pollution contributed to approximately 110,000 new cases (5.6 per 10,000) of AD and 1.6 million new cases (81.7 per 10,000) of MCI, imposing significant economic costs of about US $1200 million for AD and US $18,000 million for MCI, based on 2015 dollar values. Additionally, our projections indicate that reducing the 2023 ozone concentrations to 70 μg/m3 could significantly curb these conditions, potentially preventing over 210,000 new AD cases (10.7 per 10,000) and 2.9 million (148.1 per 10,000) MCI cases. Such reductions are projected to yield substantial economic benefits, estimated at US $2200 million for AD and US $34,000 million for MCI (2015 dollar values). These findings underscore the profound implications of ozone pollution on public health and the economy in China, highlighting the urgent need for effective ozone management strategies to mitigate these impacts.
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Affiliation(s)
- Kai Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.
| | - Hong Ye
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.
| | - Ziyu Dong
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Amujilite
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.
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Zhang R, Zhu S, Zhang Z, Zhang H, Tian C, Wang S, Wang P, Zhang H. Long-term variations of air pollutants and public exposure in China during 2000-2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 930:172606. [PMID: 38642757 DOI: 10.1016/j.scitotenv.2024.172606] [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: 01/15/2024] [Revised: 04/12/2024] [Accepted: 04/17/2024] [Indexed: 04/22/2024]
Abstract
Since 2000, China has faced severe air pollution challenges,prompting the initiation of comprehensive emission control measures post-2013. The subsequent implementation of these measures has led to remarkable enhancements in air quality. This study aims to enhance our understanding of the long-term trends in fine particulate matter (PM2.5) and gaseous pollutants of ozone (O3) and nitrogen dioxide (NO2) across China from 2000 to 2020. Utilizing the Community Multiscale Air Quality (CMAQ) model, we conducted a nationwide analysis of air quality, systematically quantifying model predictions against observations for pollutants. The CMAQ model effectively captured the trends of air pollutants, meeting recommended performance benchmarks. The findings reveal variations in pollutant concentrations, with initial increases in PM2.5 followed by a decline after 2013. The proportion of the population living in high PM2.5 concentrations (>75 μg/m3) decreased to <5 % after 2015. However, during the period from 2017 to 2020, around 40 % of the population continued to live in regions that did not meet the criteria for Chinese air quality standards (35 μg/m3). From 2000 to 2019, fewer than 20 % of the population met the WHO standard (100 μg/m3) for MDA8 O3. In 2000, 77 % of the population met the NO2 standard (<20 μg/m3), a figure that declined to 60 % between 2005 and 2014, nearly reaching 70 % in 2020. This study offers a comprehensive analysis of the changes in pollutants and public exposure in 2000-2020. It serves as a foundational resource for future efforts in air pollution control and health research.
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Affiliation(s)
- Ruhan Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Shengqiang Zhu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Zhaolei Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Haoran Zhang
- School of Atmospheric Sciences, Nanjing University, Nanjing, China
| | - Chunfeng Tian
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai, China
| | - Shuai Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Peng Wang
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai, China; Shanghai Key Laboratory of Ocean-land-atmosphere Boundary Dynamics and Climate Change, China; IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China.
| | - Hongliang Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, China; IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China; Institute of Eco-Chongming, Shanghai, China.
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5
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Hu W, Yang J. Effect of ambient ozone pollution on disease burden globally: A systematic analysis for the global burden of disease study 2019. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171739. [PMID: 38508259 DOI: 10.1016/j.scitotenv.2024.171739] [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: 01/28/2024] [Revised: 03/11/2024] [Accepted: 03/14/2024] [Indexed: 03/22/2024]
Abstract
BACKGROUND Exposure to ambient ozone pollution causes health loss and even death, and both are the main risk factors for the disease burden worldwide. We comprehensively evaluated the ozone pollution-related disease burden. METHODS First, numbers and age-standardized rates of deaths and disability-adjusted life years (DALYs) were assessed globally and by sub-types in 2019. Furthermore, the temporal trend of the disease burden was explored by the linear regression model from 1990 to 2019. The cluster analysis was used to evaluate the changing pattern of related disease burden across Global Burden of Disease Study (GBD) regions. Finally, the age-period-cohort (APC) model and the Bayesian age-period-cohort (BAPC) model were used to predict the future disease burden in the next 25 years. RESULT Exposure to ozone pollution contributed to 365,222 deaths and 6,210,145 DALYs globally in 2019, which accounted for 0.65 % of deaths globally and 0.24 % of DALYs globally. The disease burden was consistently increasing with age. Males were high-risk populations and low-middle socio-demographic index (SDI) regions were high-risk areas. The disease burden of ozone pollution varied considerably across the GBD regions and the countries. In 2019, the number of deaths and DALYs cases increased by 76.11 % and 56.37 %, respectively compared to those in 1990. The predicted results showed that the number of deaths cases and DALYs cases for both genders would still increase from 2020 to 2044. CONCLUSION In conclusion, ambient ozone pollution has threatened public health globally. More proactive and effective strategic measures should be developed after considering global-specific circumstances.
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Affiliation(s)
- Wan Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui 230032, China
| | - Junnan Yang
- School of Public Health, BengBu Medical University, 2600 Donghai Avenue, Bengbu, Anhui 233030, China.
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Zhou Y, Zhang X, Zhang C, Chen B, Gu B. Mitigating air pollution benefits multiple sustainable development goals in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 349:123992. [PMID: 38631451 DOI: 10.1016/j.envpol.2024.123992] [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: 01/23/2024] [Revised: 03/27/2024] [Accepted: 04/14/2024] [Indexed: 04/19/2024]
Abstract
Achieving the United nations 2030 Sustainable Development Goals (SDGs) remains a significant challenge, necessitating urgent and prioritized strategies. Among the various challenges, air pollution continues to pose one of the most substantial threats to the SDGs due to its widespread adverse effects on human health and ecosystems. However, the connections between air pollution and the SDGs have often been overlooked. This study reveals that out of the 169 SDG targets, 71 are adversely impacted by air pollution, while only 6 show potential positive effects. In China, two major atmospheric nitrogen pollutants, ammonia and nitrogen oxides, resulted in an economic loss of 400 billion United States Dollar (USD) in 2020, which could be reduced by 33% and 34% by 2030, respectively. It would enhance the progress towards SDGs in China by 14%, directly contributing to the achievement of SDGs 1 to 6 and 11 to 15. This improvement is estimated to yield overall benefits totaling 119 billion USD, exceeded the total implementation cost of 82 billion USD with ammonia as the preferential mitigation target. This study underscores the importance of robust scientific evidence in integrated policies aimed at aligning improvements in environmental quality with the priorities of sustainable development.
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Affiliation(s)
- Yi Zhou
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Xiuming Zhang
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; Policy Simulation Laboratory, Zhejiang University, Hangzhou 310058, China
| | - Chuanzhen Zhang
- School of Agriculture, Food and Ecosystem Sciences, The University of Melbourne, Victoria 3010, Australia
| | - Binhui Chen
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Baojing Gu
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, Zhejiang University, Hangzhou 310058, China.
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7
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Wang L, Xu H, Yang Y, Guan H, He X, Wu R, Wu J, Yuan N, Guo T, Zhang Y, Zhang H, He Y, Peng Z, Wang Y, Shen H, Wang Q, Zhang Y, Yan D, Song X, Zhang Q, Wang Z, Ma X, Huang W. Association between short-term air pollution exposure and perturbation in thyrotropin levels in 1.38 million Chinese women: A national longitudinal analysis, 2014-2019. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133094. [PMID: 38029589 DOI: 10.1016/j.jhazmat.2023.133094] [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: 08/23/2023] [Revised: 11/08/2023] [Accepted: 11/23/2023] [Indexed: 12/01/2023]
Abstract
Prevalence of subclinical hypothyroidism substantially increased during the last decade in China, which has been commonly/clinically diagnosed as elevation in thyrotropin (thyroid-stimulating hormone [TSH]). Tobacco smoke containing toxic substances has been linked to thyroid dysfunction; however, data on perturbation of TSH following air pollution exposure in human has not been assessed at nationwide population level. We investigated the longitudinal impact of daily ambient air pollution estimated at residential level on serum TSH in 1.38 million women from China's 29 mainland provinces between 2014 and 2019. We observed that particulate matter with aerodynamic diameter ≤ 10 and ≤ 2.5 µm (PM10, PM2.5) and nitrogen dioxide (NO2) at cumulative lag 0-7 days of exposure were associated with percent elevations in TSH (0.88% [95% CI: 0.71, 1.05] per [interquartile range, IQR: 54.8 μg/m3] of PM10; 0.89% [95% CI, 0.71, 1.07] per IQR [40.3 μg/m3] of PM2.5; 2.01% [95% CI: 1.81, 2.22] per IQR [27.4 μg/m3] of NO2). Greater associations were observed in participants living in areas with ≥adequate iodine intake and those with low BMI levels and high inflammation status. Our results suggest that increased concentrations of recent ambient air pollutants at exposure ranges commonly encountered in Asia were associated with increases in TSH, supporting disturbing role of short-term air pollution exposure on the regulation of thyroid hormone homeostasis.
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Affiliation(s)
- Long Wang
- National Research Institute for Family Planning, Beijing, China; Institute of Epidemiology and Statistics, School of Public Health, Lanzhou University, Lanzhou, China
| | - Hongbing Xu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Ying Yang
- National Research Institute for Family Planning, Beijing, China; National Human Genetic Resources Centre, Beijing, China; Graduate School of Peking Union Medical College, Beijing, China
| | - Haixia Guan
- Department of Endocrinology and Metabolism, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xinghou He
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Rongshan Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Jianbin Wu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Ningman Yuan
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China
| | - Tonglei Guo
- National Research Institute for Family Planning, Beijing, China
| | - Ya Zhang
- National Research Institute for Family Planning, Beijing, China; National Human Genetic Resources Centre, Beijing, China
| | - Hongguang Zhang
- National Research Institute for Family Planning, Beijing, China; National Human Genetic Resources Centre, Beijing, China
| | - Yuan He
- National Research Institute for Family Planning, Beijing, China; National Human Genetic Resources Centre, Beijing, China
| | - Zuoqi Peng
- National Research Institute for Family Planning, Beijing, China; National Human Genetic Resources Centre, Beijing, China
| | - Yuanyuan Wang
- National Research Institute for Family Planning, Beijing, China; National Human Genetic Resources Centre, Beijing, China
| | - Haiping Shen
- Department of Maternal and Child Health, National Health Commission, Beijing, China
| | - Qiaomei Wang
- Department of Maternal and Child Health, National Health Commission, Beijing, China
| | - Yiping Zhang
- Department of Maternal and Child Health, National Health Commission, Beijing, China
| | - Donghai Yan
- Department of Maternal and Child Health, National Health Commission, Beijing, China
| | - Xiaoming Song
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China; National Human Genetic Resources Centre, Beijing, China
| | - Qinghong Zhang
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China
| | - Zifa Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
| | - Xu Ma
- National Research Institute for Family Planning, Beijing, China; National Human Genetic Resources Centre, Beijing, China; Graduate School of Peking Union Medical College, Beijing, China.
| | - Wei Huang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China.
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Jia H, Guo Y, Luo H, Meng X, Zhang L, Yu K, Zheng X, Sun Y, Hu W, Wu Z, Chen R, Sun X. Association of long-term ozone air pollution and age-related macular degeneration in older Chinese population. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169145. [PMID: 38061653 DOI: 10.1016/j.scitotenv.2023.169145] [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: 09/12/2023] [Revised: 11/25/2023] [Accepted: 12/04/2023] [Indexed: 01/18/2024]
Abstract
BACKGROUND Age-related macular degeneration (AMD) is the leading cause of legal blindness. It remains unclear whether and to what extent the ambient ozone pollution could increase the risk of AMD. METHODS A nationwide cross-sectional survey was conducted in 129 major cities in 27 of 31 provincial regions across China from 2018 to 2021. Data in relation to demographics, residential address, and medical histories were collected. The exposure-response relationship between ozone exposure and AMD was explored using the restricted cubic splines. A piecewise logistic regression model was used to examine the magnitudes of the association, after adjusting demographic, social-economic and co-pollutants. Residential ozone exposures were estimated using a satellite-based model. RESULTS A total of 624,167 middle-aged and older participants were included in the final analyses, the overall prevalence of AMD was 16.76 %. The risk of AMD was consistently increasing with higher warm-season ozone concentration, and the risk became much larger after the cut-off of 110 μg/m3 (approximately 50 ppb). Every 10 μg/m3 increment in warm-season ozone concentration, the adjusted odds ratio (OR) for AMD were 1.15 (1.13, 1.16) and 1.66 (1.63, 1.69) when the warm-season ozone concentration was below or above 110 μg/m3, respectively. CONCLUSION This large-scale nationwide study provides the first epidemiological evidence demonstrating significant associations between long-term residential ozone exposure and AMD prevalence. Based on our findings, in conjunction with WHO global air quality guidelines, we suggest that a warm-season ozone of 110 μg/m3 should be adopted for middle-aged and older populations to reduce the risk of AMD. Ongoing efforts to reduce ozone exposure in communities through improved air quality regulations and public education are essential for the improvement of public health.
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Affiliation(s)
- Huixun Jia
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China; Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, China; National Clinical Research Center for Eye Diseases, Shanghai, China
| | - Yi Guo
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Huihuan Luo
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Lina Zhang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Kexin Yu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Xueying Zheng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Yiqing Sun
- Eberly College of Science, The Pennsylvania State University, University Park, PA, United States
| | - Weiting Hu
- Shanghai Phoebus Medical Co. Ltd., Shanghai, China
| | - Zhenyu Wu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China.
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China.
| | - Xiaodong Sun
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, China; National Clinical Research Center for Eye Diseases, Shanghai, China.
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9
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Li B, Ni J, Liu J, Zhao Y, Liu L, Jin J, He C. Spatiotemporal patterns of surface ozone exposure inequality in China. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:265. [PMID: 38351419 DOI: 10.1007/s10661-024-12426-3] [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: 09/16/2023] [Accepted: 02/02/2024] [Indexed: 02/16/2024]
Abstract
Rising surface ozone (O3) levels in China are increasingly emphasizing the potential threats to public health, ecological balance, and economic sustainability. Using a 1 km × 1 km dataset of O3 concentrations, this research employs subpopulation demographic data combined with a population-weighted quality model. Its aim is to evaluate quantitatively the differences in O3 exposure among various subpopulations within China, both at a provincial and urban cluster level. Additionally, an exposure disparity indicator was devised to establish unambiguous exposure risks among significant urban agglomerations at varying O3 concentration levels. The findings reveal that as of 2018, the population-weighted average concentration of O3 for all subgroups has experienced a significant uptick, surpassing the average O3 concentration (118 μg/m3). Notably, the middle-aged demographic exhibited the highest O3 exposure level at 135.7 μg/m3, which is significantly elevated compared to other age brackets. Concurrently, there exists a prominent positive correlation between educational attainment and O3 exposure levels, with the medium-income bracket showing the greatest susceptibility to O3 exposure risks. From an industrial vantage point, the secondary sector demographic is the most adversely impacted by O3 exposure. In terms of urban-rural structure, urban groups in all regions had higher levels of exposure to O3 than rural areas, with North and East China having the most significant levels of exposure. These findings not only emphasize the intricate interplay between public health and environmental justice but further highlight the indispensability of segmented subgroup strategies in environmental health risk assessment. Moreover, this research furnishes invaluable scientific groundwork for crafting targeted public health interventions and sustainable air quality management policies.
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Affiliation(s)
- Bin Li
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China
- Hubei Key Laboratory of Petroleum Geochemistry and Environment, Yangtze University, Wuhan, 430100, China
| | - Jinmian Ni
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China
- Hubei Key Laboratory of Petroleum Geochemistry and Environment, Yangtze University, Wuhan, 430100, China
| | - Jianhua Liu
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China
- Hubei Key Laboratory of Petroleum Geochemistry and Environment, Yangtze University, Wuhan, 430100, China
| | - Yue Zhao
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China
- Hubei Key Laboratory of Petroleum Geochemistry and Environment, Yangtze University, Wuhan, 430100, China
| | - Lijun Liu
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China
- Hubei Key Laboratory of Petroleum Geochemistry and Environment, Yangtze University, Wuhan, 430100, China
| | - Jiming Jin
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China
- Hubei Key Laboratory of Petroleum Geochemistry and Environment, Yangtze University, Wuhan, 430100, China
| | - Chao He
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China.
- Hubei Key Laboratory of Petroleum Geochemistry and Environment, Yangtze University, Wuhan, 430100, China.
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10
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Su D, Chen L, Wang J, Zhang H, Gao S, Sun Y, Zhang H, Yao J. Long- and short-term health benefits attributable to PM 2.5 constituents reductions from 2013 to 2021: A spatiotemporal analysis in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 907:168184. [PMID: 37907103 DOI: 10.1016/j.scitotenv.2023.168184] [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: 09/06/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/02/2023]
Abstract
Long- and short-term exposure to constituents of fine particulate matter (PM2.5) substantially affects human health. However, assessments of the health and economic benefits of reducing PM2.5 constituents are scarce. This study estimates the number of premature deaths from all-cause, cardiovascular (CVD), and respiratory diseases avoided due to reductions in daily and annual average concentrations of PM2.5 constituents. The Environmental Benefits Mapping and Analysis Program was used for two scenarios: we used yearly concentrations of PM2.5 constituents from 2013 to 2020 as the baseline concentration surface (Scenario I), and 2021 as the baseline year (Scenario II). With reductions in daily and annual average concentrations of PM2.5 constituents, 309,099 (95 % confidence interval [CI]: 37,265-571,485) and 195,297 (95 % CI: 178,192-211,914) premature deaths were avoided in Scenario I, respectively; meanwhile, 347,296 (95 % CI: 79,258-604,758) and 201,567 (95 % CI: 185,038-217,530) premature deaths were avoided in Scenario II, respectively. Moreover, economic benefits associated with the prevention of premature deaths were estimated using the willingness to pay (WTP) and modified human capital (AHC) methods. The total estimated economic benefits amounted to 563.32 billion RMB (WTP) and 322.03 billion RMB (AHC) in Scenario I. In Scenario II, the associated economic benefits were 751.48 billion RMB (WTP) and 427.56 billion RMB (AHC), accounting for 0.657 and 0.374 % of China's gross domestic product in 2021, respectively. Additionally, we analyzed the sensitivity of CVD-related premature deaths to the concentrations of PM2.5 constituents, and found that CVD-related premature deaths were more sensitive to black carbon.
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Affiliation(s)
- Die Su
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Li Chen
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China.
| | - Jing Wang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Hui Zhang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Shuang Gao
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Yanling Sun
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Hu Zhang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Jiaqi Yao
- Academy of Eco-civilization Development for Jing-Jin-Ji Megalopolis, China
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11
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Tian X, Zeng J, Li X, Li S, Zhang T, Deng Y, Yin F, Ma Y. Assessing the short-term effects of PM 2.5 and O 3 on cardiovascular mortality using high-resolution exposure: a time-stratified case cross-over study in Southwestern China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:3775-3785. [PMID: 38087153 DOI: 10.1007/s11356-023-31276-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 11/24/2023] [Indexed: 01/19/2024]
Abstract
Air pollution is a major risk factor of cardiovascular disease (CVD). To date, limited studies have estimated the effects of ambient air pollution on CVD mortality using high-resolution exposure assessment, which might fail to capture the spatial variation in exposure and introduce bias in results. Besides, the three-year action plan (TYAP, 2018-2020) was released; thus, the constitution and health effect of air pollutants may have changed. In this study, we estimated the short-term effect exposed to particulate matters with parameter less than 2.5 µm (PM2.5) and ozone (O3) with 0.05° × 0.05° resolution on CVD mortality and measured the influence of TYAP in the associations. We used random forest models with spatial weight matrices to attain high-resolution pollutant concentrations and conditional Poisson regression to assess the relationship between air pollution and cardiovascular mortality. With an increase of 10 µg/m3 in PM2.5 and O3 during 2018-2021 in the Sichuan Basin (SCB), CVD mortality increased 1.0134 (95% CI 1.0102, 1.0166) and 1.0083 (95% CI 1.0060, 1.0107), respectively, using high-resolution air pollutant concentration, comparing to 1.0070 (95% CI 1.0052, 1.0087) and 1.0057 (95% CI 1.0037, 1.0078) using data from air quality monitoring stations (AQMs). After TYAP, the relative risk (RR) due to PM2.5 rose up to 1.0149 (95% CI 1.0054, 1.0243), and the RR due to O3 rose up to 1.0089 (95% CI 1.0030, 1.0148) in Sichuan Province. We found significantly positive association of cardiovascular mortality and air pollution in Sichuan Province. And using high-resolution exposure would be more accurate to estimate the effect of air pollution on CVD. After TYAP, the cardiovascular mortality risk estimation due to PM2.5 decreased in elderly in SCB, and the risk due to O3 increased in Sichuan Province.
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Affiliation(s)
- Xinyue Tian
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jing Zeng
- Department of Chronic Disease Surveillance, Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Xuelin Li
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Sheng Li
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Tao Zhang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ying Deng
- Department of Chronic Disease Surveillance, Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Fei Yin
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yue Ma
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
- Institute of Systems Epidemiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
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12
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Chen X, Gao J, Chen L, Khanna M, Gong B, Auffhammer M. The spatiotemporal pattern of surface ozone and its impact on agricultural productivity in China. PNAS NEXUS 2024; 3:pgad435. [PMID: 38152458 PMCID: PMC10752353 DOI: 10.1093/pnasnexus/pgad435] [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: 06/20/2023] [Accepted: 12/04/2023] [Indexed: 12/29/2023]
Abstract
The slowing of agricultural productivity growth globally over the past two decades has brought a new urgency to detect its drivers and potential solutions. We show that air pollution, particularly surface ozone (O3), is strongly associated with declining agricultural total factor productivity (TFP) in China. We employ machine learning algorithms to generate estimates of high-resolution surface O3 concentrations from 2002 to 2019. Results indicate that China's O3 pollution has intensified over this 18-year period. We coupled these O3 estimates with a statistical model to show that rising O3 pollution during nonwinter seasons has reduced agricultural TFP by 18% over the 2002-2015 period. Agricultural TFP is projected to increase by 60% if surface O3 concentrations were reduced to meet the WHO air quality standards. This productivity gain has the potential to counter expected productivity losses from 2°C warming.
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Affiliation(s)
- Xiaoguang Chen
- Research Institute of Economics and Management, Southwestern University of Finance and Economics, 610074 Chengdu, China
| | - Jing Gao
- Research Institute of Economics and Management, Southwestern University of Finance and Economics, 610074 Chengdu, China
| | - Luoye Chen
- Carbon Neutrality and Climate Change Thrust, Society Hub, Hong Kong University of Science and Technology (Guangzhou), 511453 Guangzhou, China
| | - Madhu Khanna
- Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Binlei Gong
- China Academy for Rural Development (CARD) and School of Public Affairs, Zhejiang University, 310025 Hangzhou, China
| | - Maximilian Auffhammer
- Department of Agricultural and Resource Economics, University of California, Berkeley, CA 94720, USA
- National Bureau of Economic Research, Cambridge, MA 02138, USA
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13
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Anbari K, Sicard P, Omidi Khaniabadi Y, Raja Naqvi H, Rashidi R. Assessing the effect of COVID-19 pandemic on air quality change and human health outcomes in a capital city, southwestern Iran. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:1716-1727. [PMID: 36099327 DOI: 10.1080/09603123.2022.2120967] [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: 05/24/2022] [Accepted: 08/30/2022] [Indexed: 06/15/2023]
Abstract
The aimsof this study were to assess the spatial variation of PM2.5, NO2, and O3 between 2019 (before) and 2020 (during COVID-19 pandemic); and calculation the health outcomes of exposure to these pollutants. The daily PM2.5, NO2, and O3 concentrations were applied to assess health effects by relative risk, and baseline incidence. The annual PM2.5 and NO2 mean concentrations exceeded the WHO guideline values, while O3 did not exceed. The restrictive measures associated to COVID-19 led to reduction at the annual means of PM2.5 and NO2 by -25.5% and -23.1%, respectively, while the annual mean of O3 increased by +7.9%. The number of M-CVD and M-RD (-25.6%, -26.1%) related to PM2.5 exposure, and HA-COPD and HA-RD >65 years old (-21% and -3.84%) related to NO2 exposure were reduced in 2020, and O3 exposure-related M-CVD (+30.1%) and HA-RD >65 years old (+23.4%) increased compared to the previous year 2019.
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Affiliation(s)
- Khatereh Anbari
- Social Determinants of Health Research Center, School of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran
| | | | - Yusef Omidi Khaniabadi
- Occupational and Environmental Health Research Center, Petroleum Industry Health Organization (PIHO), Ahvaz, Iran
| | - Hasan Raja Naqvi
- Department of Geography, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi, India
| | - Rajab Rashidi
- Department of Occupational Health, Nutritional Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
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14
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Huang Z, Wu J, Qiu Y, Lin J, Huang W, Ma X, Zhang H, Yang X. Association between gestational exposure and risk of orofacial clefts: a systematic review and meta-analysis. BMC Pregnancy Childbirth 2023; 23:829. [PMID: 38041018 PMCID: PMC10691060 DOI: 10.1186/s12884-023-06104-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 11/02/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND The occurrence of orofacial Clefts (OFCs) is a congenital disease caused by many factors. According to recent studies, air pollution has a strong correlation with the occurrence of OFCs. However, there are still some controversies about the current research results, and there is no relevant research to review the latest results in recent years. OBJECTIVE In this paper, the authors conducted a systematic review and meta-analysis to explore the correlation between ambient air pollution and the occurrence of neonatal OFCs deformity. METHODS We searched Pubmed, Web of science, and Embase databases from the establishment of the database to May 2023. We included observational studies on the relationship between prenatal exposure to fine particulate matter 2.5 (PM2.5), fine particulate matter 10 (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO) and the risk of cleft lip (CL), cleft palate (CP), cleft lip with or without palate (CL/P). the Newcastle-Ottawa quality assessment scale (NOS) was used to evaluate the quality of the literature. Funnel plot and Egger's regression were used to verify the publication bias. Random effect model or fixed effect model was used to estimate the combined relative risk (RR) and 95% confidence interval (95%CI). RESULTS A total of eleven studies were included in this study, including four cohort studies and seven case-control studies, including 22,453 cases of OFCs. Ten studies had low risk of bias and only one study had high risk of bias. Three studies reported that PM2.5 was positively correlated with CL and CP, with a combined RR and 95%CI of 1.287(1.174,1.411) and 1.267 (1.105,1.454). Two studies reported a positive correlation between O3 and CL, with a combined RR and 95%CI of 1.132(1.047,1.225). Two studies reported a positive correlation between PM10 and CL, with a combined RR and 95%CI of 1.108 (1.017,1.206). No association was found between SO2, CO, NO2 exposure during pregnancy and the risk of OFCs. CONCLUSION The results of this study showed that there was a significant statistical correlation between exposure to PM10, PM2.5, O3 and the risk of OFCs in the second month of pregnancy. Exposure assessment, research methods and mechanisms need to be further explored.
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Affiliation(s)
- ZhiMeng Huang
- Department Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Fujian Province, 361000, China
| | - JinZhun Wu
- Department Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Fujian Province, 361000, China
| | - Yue Qiu
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Fujian Province, 361000, China
| | - Jiayan Lin
- Department Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Fujian Province, 361000, China
| | - Wanting Huang
- Department Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Fujian Province, 361000, China
| | - Xiaohui Ma
- Department Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Fujian Province, 361000, China
| | - Huifen Zhang
- Department Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Fujian Province, 361000, China
| | - Xiaoqing Yang
- Department Pediatrics, Women and Children's Hospital, School of Medicine, Xiamen University, Fujian Province, 361000, China.
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15
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Liu B, Wang L, Zhang L, Liao Z, Wang Y, Sun Y, Xin J, Hu B. Analysis of severe ozone-related human health and weather influence over China in 2019 based on a high-resolution dataset. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:111536-111551. [PMID: 37819470 DOI: 10.1007/s11356-023-30178-4] [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: 07/19/2023] [Accepted: 09/26/2023] [Indexed: 10/13/2023]
Abstract
Ozone pollution in 2019 in China is particularly severe posing a tremendous threat to the health of Chinese inhabitants. In this study, we constructed a more reliable and accurate 1-km gridded dataset for 2019 with as many sites as possible using the inverse distance weight interpolation method to analyze spatiotemporal ozone pollution characteristics and health burden attributed to ozone exposure from the perspective of different diseases and weather influence. The accuracy of this new dataset is higher than other public datasets, with the coefficient of determination of 0.84 and root-mean-square error of 8.77 ppb through the validation of 300 external sites which were never used for establishing retrieval methods by the datasets mentioned-above. The averaged MDA8 (the daily maximum 8 h average) ozone concentrations over China was 43.5 ppb, and during April-July, 83.9% of total grids occurred peak-month ozone concentrations. Overall, the highest averaged exceedance days (60 days) and population-weighted ozone concentrations (55.0 ppb) both concentrated in central-eastern China including 9 provinces (only 11.4% of the national territory); meanwhile, all-cause premature deaths attributable to ozone exposure reached up to 142,000 (54.9% of national total deaths) with higher deaths for cardiovascular and respiratory, and the provincial per capita premature mortality was 0.27~0.44‰. The six most polluted weather types in the central-eastern China are in order as follows: westerly (SW and W), cyclonic, northerly, and southerly (NW, N, and S) types, which accounts for approximately 73.2% of health burden attributed to daily ozone exposure and poses the greatest public health risk with mean daily premature deaths ranging from 466 to 610. Our findings could provide an effective support for regional ozone pollution control and public health management in China.
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Affiliation(s)
- Boya Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lili Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China.
| | - Lei Zhang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhiheng Liao
- Institute of Urban Meteorology, China Meteorological Administration, Beijing, 100089, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yang Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Jinyuan Xin
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Bo Hu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
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16
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Deng Y, Wang J, Sun L, Wang Y, Chen J, Zhao Z, Wang T, Xiang Y, Wang Y, Chen J, He M. Effects of Ambient O 3 on Respiratory Mortality, Especially the Combined Effects of PM 2.5 and O 3. TOXICS 2023; 11:892. [PMID: 37999544 PMCID: PMC10675328 DOI: 10.3390/toxics11110892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND In China, the increasing concentration of ozone (O3) has emerged as a significant air pollution issue, leading to adverse effects on public health, particularly the respiratory system. Despite the progress made in managing air pollution in China, it is crucial to address the problem of environmental O3 pollution at present. METHODS The connection between O3 exposure and respiratory mortality in Shenyang, China, from 2014 to 2018 was analyzed by a time-series generalized additive regression model (GAM) with quasi-Poisson regression. Additionally, the potential combined effects of fine particulate matter (PM2.5) and O3 were investigated using the synergy index (SI). RESULTS Our findings indicate that each 10 μg/m3 increase in O3 at lag 2 days was associated with a maximum relative risk (RR) of 1.0150 (95% CI: 1.0098-1.0202) for respiratory mortality in the total population. For individuals aged ≥55 years, unmarried individuals, those engaged in indoor occupations, and those with low educational attainment, each 10 μg/m3 increase in O3 at lag 07 days was linked to RR values of 1.0301 (95% CI: 1.0187-1.0417), 1.0437 (95% CI: 1.0266-1.0610), 1.0317 (95% CI: 1.0186-1.0450), and 1.0346 (95% CI: 1.0222-1.0471), respectively. Importantly, we discovered a synergistic effect of PM2.5 and O3, resulting in an SI of 2.372 on the occurrence of respiratory mortality. CONCLUSIONS This study confirmed a positive association between O3 exposure and respiratory mortality. Furthermore, it highlighted the interaction between O3 and PM2.5 in exacerbating respiratory deaths.
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Affiliation(s)
- Ye Deng
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Junlong Wang
- Liaoning Provincial Center for Disease Control and Prevention, Shenyang 110005, China
| | - Li Sun
- Liaoning Provincial Center for Disease Control and Prevention, Shenyang 110005, China
| | - Yue Wang
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Jiaoyang Chen
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Zhixin Zhao
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Tianyun Wang
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Yuting Xiang
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Yuting Wang
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Jiamei Chen
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
| | - Miao He
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, Ministry of Education, China Medical University, Shenyang 110122, China
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University, Shenyang 110122, China
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17
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Guo X, Su W, Wang H, Li N, Song Q, Liang Q, Sun C, Liang M, Zhou Z, Song EJ, Sun Y. Short-term exposure to ambient ozone and cardiovascular mortality in China: a systematic review and meta-analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:958-975. [PMID: 35438585 DOI: 10.1080/09603123.2022.2066070] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 04/09/2022] [Indexed: 06/14/2023]
Abstract
Air pollution is a major public health concern in China. Notwithstanding this, there is limited evidence regarding the impact of short-term exposure to ambient ozone on cardiovascular mortality in the Chinese population. Therefore, we conducted this meta-analysis to address this important question. The random-effects model was applied to pool the results from individual studies. Finally, 32 effect estimates extracted from 19 studies were pooled in this meta-analysis. The pooled relative risk for cardiovascular mortality for each 10 µg/m3 increment in ozone concentration was 1.0068 (95% CI: 1.0049, 1.0086). Ths significant positive association between ozone exposure and cardiovascular mortality was also observed in different two-pollutant models. This meta-analysis revealed that exposure to ozone was associated with an increased risk of cardiovascular mortality in China, and more efforts on controlling the population from ozone are needed to improve cardiovascular health of Chinese population.
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Affiliation(s)
- Xianwei Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Wanying Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Hao Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Ning Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Qiuxia Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Qiwei Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Chenyu Sun
- Internal Medicine, AMITA Health Saint Joseph Hospital Chicago, Chicago, IL, USA
| | - Mingming Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
| | - Zhen Zhou
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Evelyn J Song
- Division of Hospital Medicine, Department of Medicine, University of California, San Francisco, CA, USA
| | - Yehuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, P.R. China
- Chaohu Hospital of Anhui Medical University, Hefei, Anhui Province, P.R. China
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18
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Ma Y, Zhao H, Su Y. Ozone Pollution and Acute Exacerbation of Asthma in Residents of China: An Ecological Study. J Asthma Allergy 2023; 16:951-960. [PMID: 37700876 PMCID: PMC10493139 DOI: 10.2147/jaa.s422476] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 08/17/2023] [Indexed: 09/14/2023] Open
Abstract
Purpose The evidence for a causal relationship between high-level ozone (O3) exposure and acute exacerbation of asthma among adults is limited, and the conclusions are less definitive. Patients and methods Here we collected the daily data on asthma cases, O3 exposure, and meteorological factors from 2010 to 2016 in Shijiazhuang, China. We investigated the risk of asthma exacerbation associated with high-level ozone exposure using a polynomial distributed lag model (PDLM). Using a generalized additive model (GAM), we estimated the interactive effects between O3 and other pollutants as well as meteorological factors on asthma exacerbation. Results A total of 7270 patients with asthma were enrolled from 22 governmental hospitals in 13 counties. Each 10 μg/m3 increase in O3 concentration on the exacerbation of asthma was associated with a 1.92% (95% CI = 0.80-3.03%) higher risk of asthma exacerbation on day lag 7. The cumulative risk of O3 on asthma exacerbation increased by 18.9% (95% CI = 12.8-25.4%) on the 14th day. High consecutive levels of O3 increase the risk of asthma exacerbation, and the interactive effect of O3 and sulfur dioxide (SO2) appears before the exacerbation onset. Conclusion These findings suggested that O3 should be an important risk factor for asthma exacerbation, and health benefits in reducing asthma exacerbation risk would be gained with continued efforts to improve the air quality in China.
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Affiliation(s)
- Yunlei Ma
- Department of Respiratory Medicine, Traditional Chinese Medicine Hospital of Hebei Province, Shijiazhuang, People’s Republic of China
| | - Hanjun Zhao
- Department of Respiratory Medicine, Fourth Hospital of Hebei Medical University, Shijiazhuang, People’s Republic of China
| | - Yinghao Su
- Department of Respiratory Medicine, Traditional Chinese Medicine Hospital of Hebei Province, Shijiazhuang, People’s Republic of China
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19
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Tan Q, Wang B, Ye Z, Mu G, Liu W, Nie X, Yu L, Zhou M, Chen W. Cross-sectional and longitudinal relationships between ozone exposure and glucose homeostasis: Exploring the role of systemic inflammation and oxidative stress in a general Chinese urban population. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 329:121711. [PMID: 37100372 DOI: 10.1016/j.envpol.2023.121711] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 04/05/2023] [Accepted: 04/22/2023] [Indexed: 05/21/2023]
Abstract
The adverse health effects of ozone pollution have been a globally concerned public health issue. Herein we aim to investigate the association between ozone exposure and glucose homeostasis, and to explore the potential role of systemic inflammation and oxidative stress in this association. A total of 6578 observations from the Wuhan-Zhuhai cohort (baseline and two follow-ups) were included in this study. Fasting plasma glucose (FPG) and insulin (FPI), plasma C-reactive protein (CRP, biomarker for systemic inflammation), urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG, biomarker for oxidative DNA damage), and urinary 8-isoprostane (biomarker for lipid peroxidation) were repeatedly measured. After adjusting for potential confounders, ozone exposure was positively associated with FPG, FPI, and homeostasis model assessment of insulin resistance (HOMA-IR), and negatively associated with HOMA of beta cell function (HOMA-β) in cross-sectional analyses. Each 10 ppb increase in cumulative 7-days moving average ozone was associated with a 13.19%, 8.31%, and 12.77% increase in FPG, FPI, and HOMA-IR, respectively, whereas a 6.63% decrease in HOMA-β (all P < 0.05). BMI modified the associations of 7-days ozone exposure with FPI and HOMA-IR, and the effects were stronger in subgroup whose BMI ≥24 kg/m2. Consistently high exposure to annual average ozone was associated with increased FPG and FPI in longitudinal analyses. Furthermore, ozone exposure was positively related to CRP, 8-OHdG, and 8-isoprostane in dose-response manner. Increased CRP, 8-OHdG, and 8-isoprostane could dose-dependently aggravate glucose homeostasis indices elevations related to ozone exposure. Increased CRP and 8-isoprostane mediated 2.11-14.96% of ozone-associated glucose homeostasis indices increment. Our findings suggested that ozone exposure could cause glucose homeostasis damage and obese people were more susceptible. Systemic inflammation and oxidative stress might be potential pathways in glucose homeostasis damage induced by ozone exposure.
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Affiliation(s)
- Qiyou Tan
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Bin Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Zi Ye
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Ge Mu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Wei Liu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Xiuquan Nie
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Linling Yu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
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20
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Dai H, Huang G, Wang J, Zeng H. VAR-tree model based spatio-temporal characterization and prediction of O 3 concentration in China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 257:114960. [PMID: 37116452 DOI: 10.1016/j.ecoenv.2023.114960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 04/16/2023] [Accepted: 04/24/2023] [Indexed: 05/08/2023]
Abstract
Ozone (O3) pollution in the atmosphere is getting worse in many cities. In order to improve the accuracy of O3 prediction and obtain the spatial distribution of O3 concentration over a continuous period of time, this paper proposes a VAR-XGBoost model based on Vector autoregression (VAR), Kriging method and XGBoost (Extreme Gradient Boosting). China is used as an example and its spatial distribution of O3 is simulated. In this paper, the O3 concentration data of the monitoring sites in China are obtained, and then a spatial prediction method of O3 mass concentration based on the VAR-XGBoost model is established, and finnally its influencing factors are analyzed. This paper concludes that O3 features the highest correlation with PM2.5 and the lowest correlation with SO2. Among the measurement factors, wind speed and temperature are the most important factors affecting O3 pollution, which are positively correlated to O3 pollution. In addition, precipitation is negatively correlated with 8-hour ozone concentration. In this paper, the performance of the VAR-XGBoost model is evaluated based on the ten-fold cross-validation method of sample, site and time, and a comparison with the results of XGBoost, CatBoost (categorical boosting), ExtraTrees, GBDT (gradient boosting decision tree), AdaBoost (adaptive boosting), RF (random forest), Decision tree, and LightGBM (light gradient boosting machine) models is conducted. The result shows that the prediction accuracy of the VAR-XGBoost model is better than other models. The seasonal and annual average R2 reaches 0.94 (spring), 0.93 (summer), 0.92 (autumn), 0.93 (winter), and 0.95 (average from 2016 to 2021). The data show that the applicability of the VAR-XGBoost model in simulating the spatial distribution of O3 concentrations in China performs well. The spatial distribution of O3 concentrations in the Chinese region shows an obvious feature of high in the east and low in the west, and the spatial distribution is strongly influenced by topographical factors. The mean concentration is clearly low in winter and high in summer within a season. The results of this study can provide a scientific basis for the prevention and control of regional O3 pollution in China, and can also provide new ideas for the acquisition of data on the spatial distribution of O3 concentrations within cities.
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Affiliation(s)
- Hongbin Dai
- School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Guangqiu Huang
- School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China
| | - Jingjing Wang
- College of Vocational and Technical Education, Guangxi Science&Technology of Normal University, Laibin 546199, China.
| | - Huibin Zeng
- School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China
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21
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Meng X, Jiang J, Chen T, Zhang Z, Lu B, Liu C, Xue L, Chen J, Herrmann H, Li X. Chemical drivers of ozone change in extreme temperatures in eastern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162424. [PMID: 36868278 DOI: 10.1016/j.scitotenv.2023.162424] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 02/14/2023] [Accepted: 02/19/2023] [Indexed: 06/18/2023]
Abstract
Surface ozone pollution has become the biggest issue in China's air pollution since particulate matters have been improved in the atmosphere. Compared with normal winter/summer, extremely cold/hot weather sustained several days and nights by unfavorable meteorology is more impactful in this regard. However, ozone changes in extreme temperatures and their driving processes remain rarely understood. Here, we combine comprehensive observational data analysis and 0-D box models to quantify the contributions of different chemical processes and precursors to ozone change in these unique environments. Analyses of radical cycling indicate that temperature accelerates OH-HO2-RO2, optimizing ozone production efficiency in higher temperatures. The HO2 + NO → OH + NO2 reaction was the most influenced by temperature change, followed by OH + VOCs → HO2/RO2. Although most reactions in ozone formation increased with temperature, the increase in ozone production rates was greater than the rate of ozone loss, leading to a fast net ozone accumulation in heat waves. Our results also show that the ozone sensitivity regime is VOC-limited in extreme temperatures, highlighting the significance of volatile organic compound (VOC) control (particularly the control of alkenes and aromatics). In the context of global warming and climate change, this study helps us deeply understand ozone formation in extreme environments and design abatement policies for ozone pollution in such conditions.
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Affiliation(s)
- Xue Meng
- Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Jiakui Jiang
- Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Tianshu Chen
- Environmental Research Institute, Shandong University, Shandong, China
| | - Zekun Zhang
- Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Bingqing Lu
- Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Chao Liu
- Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Likun Xue
- Environmental Research Institute, Shandong University, Shandong, China
| | - Jianmin Chen
- Department of Environmental Science & Engineering, Fudan University, Shanghai, China
| | - Hartmut Herrmann
- Leibniz-Institut für Troposphärenforschung (IfT), Permoserstr. 15, Leipzig, Germany
| | - Xiang Li
- Department of Environmental Science & Engineering, Fudan University, Shanghai, China.
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22
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Yang L, Hong S, Mu H, Zhou J, He C, Wu Q, Gong X. Ozone exposure and health risks of different age structures in major urban agglomerations in People's Republic of China from 2013 to 2018. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:42152-42164. [PMID: 36645592 DOI: 10.1007/s11356-022-24809-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
High concentration of surface ozone (O3) will cause health risks to people. In order to analyze the spatiotemporal characteristics of O3 and assess O3 exposure and health risks for different age groups in China, we applied multiple methods including standard deviation ellipse, spatial autocorrelation, and exposure-response functions. Results show that O3 concentrations increased in 64.5% of areas in China from 2013 to 2018. The central plain urban agglomeration (CPU), Beijing-Tianjin-Hebei (BTH), and Yangtze River Delta (YRD) witnessed the greatest incremental rates of O3 by 16.7%, 14.3%, and 13.1%. Spatially, the trend of O3 shows a significant positive autocorrelation, and high trend values primarily in central and east China. The proportion of the total population exposed to high O3 (above 160 μg/m3) increased annually. Compared to 2013, the proportion of the young, adult, and old populations exposed to high O3 increased to different extents in 2018 by 26.8%, 29.6%, and 27.2%, respectively. The extent of population exposure risk areas in China expanded in size, particularly in north and east China. The total premature respiratory mortalities attributable to long-term O3 exposure in six urban agglomerations were about 177,000 in 2018 which has increased by 16.4% compared to that in 2013. Among different age groups, old people are more vulnerable to O3 pollution, so we need to strengthen their relevant health protection of them.
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Affiliation(s)
- Lu Yang
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, Hubei, China
| | - Song Hong
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, Hubei, China.
| | - Hang Mu
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, Hubei, China
| | - Jingwei Zhou
- Wageningen Institute for Environment and Climate Research, Wageningen University & Research, 6700 HB, Wageningen, Gelderland, Netherlands
| | - Chao He
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China
| | - Qian Wu
- School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, Hubei, China
| | - Xi Gong
- School of Low Carbon Economics, Hubei University of Economics, Wuhan, 430205, China
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23
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Chen L, Liao H, Zhu J, Li K, Bai Y, Yue X, Yang Y, Hu J, Zhang M. Increases in ozone-related mortality in China over 2013-2030 attributed to historical ozone deterioration and future population aging. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159972. [PMID: 36356763 DOI: 10.1016/j.scitotenv.2022.159972] [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: 07/31/2022] [Revised: 10/18/2022] [Accepted: 11/01/2022] [Indexed: 06/16/2023]
Abstract
We systematically examine historical and future changes in premature respiratory mortalities attributable to ozone (O3) exposure (O3-mortality) in China and identify the leading cause of respective change for the first time. The historical assessment for 2013-2019 is based on gridded O3 concentrations generated by a multi-source-data-fusion algorithm; the future prediction for 2019-2030 uses gridded O3 concentrations projected by four Coupled Model Intercomparison Project Phase 6 (CMIP6) models under three Shared Socioeconomic Pathways (SSP) scenarios. During 2013-2019, national annual O3-mortality is 176.3 thousand (95%CI: 123.5-224.0 thousand) averaged over 2013-2019 with an increasing trend of 14.1 thousand yr-1 (95%CI: 10.2-17.4 thousand yr-1); sensitivity experiments show that the O3-mortality varies at a rate of +12.7 (95%CI: 9.2-15.6), +5.8 (95%CI: 4.0-7.4), +1.0 (95%CI: 0.7-1.2), -5.4 (95%CI: -6.9 to -3.7) thousand yr-1, owing to changes in O3 concentration, population age structure, population size, mortality rate for respiratory disease, respectively. The deterioration of O3 air quality, shown as significant increase in O3 concentration, is identified as the primary factor which contributes 90.1 % of 2013-2019 O3-mortality rise. Compared with O3-mortality estimated in this study, the widely-used O3-mortality assessment method based on urban-site-dominant O3 measurements generates close national O3-mortality but overestimates (underestimates) provincial O3-mortality in coastal (central) provinces. From 2019 to 2030, national O3-mortality is projected to increase by 50.4-103.7 thousand under different SSP scenarios. The change in age structure (i.e. population aging) alone will result in significant O3-mortality rises of 137.9-160.5 thousand. Compared with 2013-2019 rapid O3 increase (+2.5 μg m-3 yr-1 at national level), O3 concentrations are projected to increase at a lower rate (+0.4 μg m-3 yr-1 in SSP5-8.5) or even decrease (-0.7 μg m-3 yr-1 in SSP1-2.6) from 2019 to 2030. Therefore, population aging, in place of O3 air quality deterioration, will become the leading cause of future O3-mortality rises during the coming decade.
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Affiliation(s)
- Lei Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Hong Liao
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
| | - Jia Zhu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Ke Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Yang Bai
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Xu Yue
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Yang Yang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Meigen Zhang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
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24
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Williams ID, Blyth M. Autogeddon or autoheaven: Environmental and social effects of the automotive industry from launch to present. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159987. [PMID: 36372167 DOI: 10.1016/j.scitotenv.2022.159987] [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: 07/21/2022] [Revised: 10/28/2022] [Accepted: 10/28/2022] [Indexed: 06/16/2023]
Abstract
The automotive industry is one of the most significant and increasing sources of pollution worldwide. Previous studies examining its impacts focus on the post-1950 era as data available before this period is scarce. This study carefully reconstructs six datasets from the early 20th century to 2019 for the UK: annual number of motor cars, road lengths, road fatalities, NOx and CO emissions, and fuel consumption. Interpolation was prudently used to fill gaps in the data sets. Results highlight changing health, social and environmental effects throughout the growth of the automotive sector. Ratios of fatalities to cars indicate social ingraining of the car and rapid response to legislation. Significant emissions resulted from the early industry. Successful remediation of emissions occurred in the late 20th century. All variables studied were interrelated, but expansion of road networks particularly contributed to a range of both positive and (unintended) negative consequences. World War 2 appears to have been a landmark for the automotive industry, producing capacity for mass production, personal mobility and research and therefore a struggle between impacts and social policies. We have demonstrated that technological developments and regulatory interventions relating to the motor industry, alongside events that have catalysed societal change, have been crucial in terms of subsequently providing benefits to society whilst also acting to mitigate (but not prevent) the adverse and frequently devastating impacts of motor vehicles on human health and the environment. A periodic, regular, overarching, independent review (~ every 5 years) of the collective positive and negative impacts of the motor vehicle industry and appropriate interventions are essential to maintain and improve social benefits and public and environmental health, as well as supporting delivery of the United Nations' Sustainable Development Goals by 2030 and beyond.
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Affiliation(s)
- Ian D Williams
- Faculty of Engineering and Physical Sciences, University of Southampton, Highfield Campus, University Road, Southampton SO17 1BJ, United Kingdom.
| | - Michael Blyth
- Faculty of Environmental and Life Sciences, University of Southampton, Highfield Campus, University Road, Southampton SO17 1BJ, United Kingdom
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Yin S. Spatiotemporal variation of PM 2.5-related preterm birth in China and India during 1990-2019 and implications for emission controls. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 249:114415. [PMID: 36521268 DOI: 10.1016/j.ecoenv.2022.114415] [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: 09/06/2022] [Revised: 11/29/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
Preterm birth is the leading threat to neonatal health. The variation of PM2.5-associated preterm birth in China and India from 1990 through 2019 was estimated in this study. Meanwhile, four mitigation scenarios were proposed, and the corresponding PM2.5-related preterm birth was projected for 2030. Owing to differences in emission control policies and the effects of various factors (e.g., differences in population-control policies), the PM2.5 concentration and PM2.5-associated preterm birth in the two countries presented disparate spatiotemporal characteristics and variation trends during 1990-2019. The 30-year average of annual PM2.5-associated preterm birth in India was 1018 (95% confidence interval, 718-1289) thousand, which was much larger than in China (280 [196-358] thousand). To fight air pollution, China launched several control strategies in the past two decades, and the nationwide maternal exposure risk dramatically decreased after 2010. In contrast, India's air-pollution control measures and policies have not effectively mitigated the nationwide PM2.5 pollution. Under current mitigation measures and policies, the projected decrease in maternal exposure risk by 2030 is greater for China than India, and the scope for controlling air pollutant emissions and reducing maternal exposure risk is much large for India. The results of all four scenarios revealed that the annual PM2.5-associated preterm birth in the two countries is likely to decrease in the future. In particular, if China and India implement more robust emission control strategies than those currently, the number of associated preterm birth is projected to be more than 50% lower in 2030 compared with 2019 rates.
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Affiliation(s)
- Shuai Yin
- Earth System Division, National Institute for Environmental Studies, Tsukuba 3058506, Japan.
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He C, Wu Q, Li B, Liu J, Gong X, Zhang L. Surface ozone pollution in China: Trends, exposure risks, and drivers. Front Public Health 2023; 11:1131753. [PMID: 37026118 PMCID: PMC10071862 DOI: 10.3389/fpubh.2023.1131753] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 03/03/2023] [Indexed: 04/08/2023] Open
Abstract
Introduction Within the context of the yearly improvement of particulate matter (PM) pollution in Chinese cities, Surface ozone (O3) concentrations are increasing instead of decreasing and are becoming the second most important air pollutant after PM. Long-term exposure to high concentrations of O3 can have adverse effects on human health. In-depth investigation of the spatiotemporal patterns, exposure risks, and drivers of O3 is relevant for assessing the future health burden of O3 pollution and implementing air pollution control policies in China. Methods Based on high-resolution O3 concentration reanalysis data, we investigated the spatial and temporal patterns, population exposure risks, and dominant drivers of O3 pollution in China from 2013 to 2018 utilizing trend analysis methods, spatial clustering models, exposure-response functions, and multi-scale geographically weighted regression models (MGWR). Results The results show that the annual average O3 concentration in China increased significantly at a rate of 1.84 μg/m3/year from 2013 to 2018 (160 μg/m3) in China increased from 1.2% in 2013 to 28.9% in 2018, and over 20,000 people suffered premature death from respiratory diseases attributed to O3 exposure each year. Thus, the sustained increase in O3 concentrations in China is an important factor contributing to the increasing threat to human health. Furthermore, the results of spatial regression models indicate that population, the share of secondary industry in GDP, NOx emissions, temperature, average wind speed, and relative humidity are important determinants of O3 concentration variation and significant spatial differences are observed. Discussion The spatial differences of drivers result in the spatial heterogeneity of O3 concentration and exposure risks in China. Therefore, the O3 control policies adapted to various regions should be formulated in the future O3 regulation process in China.
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Affiliation(s)
- Chao He
- College of Resources and Environment, Yangtze University, Wuhan, China
| | - Qian Wu
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
| | - Bin Li
- College of Resources and Environment, Yangtze University, Wuhan, China
| | - Jianhua Liu
- College of Resources and Environment, Yangtze University, Wuhan, China
| | - Xi Gong
- School of Low Carbon Economics, Hubei University of Economics, Wuhan, China
- Collaborative Innovation Center for Emissions Trading System Co-constructed by the Province and Ministry, Wuhan, China
- *Correspondence: Xi Gong
| | - Lu Zhang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, China
- Lu Zhang
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Lyu Y, Wu Z, Wu H, Pang X, Qin K, Wang B, Ding S, Chen D, Chen J. Tracking long-term population exposure risks to PM 2.5 and ozone in urban agglomerations of China 2015-2021. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 854:158599. [PMID: 36089013 DOI: 10.1016/j.scitotenv.2022.158599] [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: 07/06/2022] [Revised: 08/24/2022] [Accepted: 09/04/2022] [Indexed: 06/15/2023]
Abstract
China has experienced severe air pollution in the past decade, especially PM2.5 and emerging ozone pollution recently. In this study, we comprehensively analyzed long-term population exposure risks to PM2.5 and ozone in urban agglomerations of China during 2015-2021 regarding two-stage clean-air actions based on the Ministry of Ecology and the Environment (MEE) air monitoring network. Overall, the ratio of the population living in the regions exceeding the Chinese National Ambient Air Quality Standard (35 μg/m3) decreases by 29.9 % for PM2.5 from 2015 to 2021, driven by high proportions in the Middle Plain (MP, 42.3 %) and Lan-Xi (35.0 %) regions. However, this ratio almost remains unchanged for ozone and even increases by 1.5 % in the MP region. As expected, the improved air quality leads to 234.7 × 103 avoided premature mortality (ΔMort), mainly ascribed to the reduction in PM2.5 concentration. COVID-19 pandemic may influence the annual variation of PM2.5-related ΔMort as it affects the shape of the population exposure curve to become much steeper. Although all eleven urban agglomerations share stroke (43.6 %) and ischaemic heart disease (IHD, 30.1 %) as the two largest contributors to total ΔMort, cause-specific ΔMort is highly regional heterogeneous, in which ozone-related ΔMort is significantly higher (21 %) in the Tibet region than other urban agglomeration. Despite ozone-related ΔMort being one order of magnitude lower than PM2.5-related ΔMort from 2015 to 2021, ozone-related ΔMort is predicted to increase in major urban agglomerations initially along with a continuous decline for PM2.5-related ΔMort from 2020 to 2060, highlighting the importance of ozone control. Coordinated controls of PM2.5 and O3 are warranted for reducing health burdens in China during achieving carbon neutrality.
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Affiliation(s)
- Yan Lyu
- College of Environment, Zhejiang University of Technology, Hangzhou 310032, China; School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China; Shaoxing Research Institute, Zhejiang University of Technology, Shaoxing 312077, China.
| | - Zhentao Wu
- College of Environment, Zhejiang University of Technology, Hangzhou 310032, China
| | - Haonan Wu
- College of Environment, Zhejiang University of Technology, Hangzhou 310032, China
| | - Xiaobing Pang
- College of Environment, Zhejiang University of Technology, Hangzhou 310032, China.
| | - Kai Qin
- School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
| | - Baozhen Wang
- Green intelligence Environmental School, Yangtze Normal University, Chongqing 408100, China
| | - Shimin Ding
- Green intelligence Environmental School, Yangtze Normal University, Chongqing 408100, China
| | - Dongzhi Chen
- School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316000, China
| | - Jianmeng Chen
- College of Environment, Zhejiang University of Technology, Hangzhou 310032, China; School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316000, China
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Huang L, Zhu Y, Liu H, Wang Y, Allen DT, Chel Gee Ooi M, Manomaiphiboon K, Talib Latif M, Chan A, Li L. Assessing the contribution of open crop straw burning to ground-level ozone and associated health impacts in China and the effectiveness of straw burning bans. ENVIRONMENT INTERNATIONAL 2023; 171:107710. [PMID: 36566719 DOI: 10.1016/j.envint.2022.107710] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/28/2022] [Accepted: 12/19/2022] [Indexed: 06/17/2023]
Abstract
In recent years, ozone pollution in China has been shown to increase in frequency and persistence despite the concentrations of fine particulate matter (PM2.5) decreasing steadily. Open crop straw burning (OCSB) activities are extensive in China and emit large amounts of trace gases during a short period that could lead to elevated ozone concentrations. This study addresses the impacts of OCSB emissions on ground-level ozone concentration and the associated health impact in China. Total VOCs and NOx emissions from OCSB in 2018 were 798.8 Gg and 80.6 Gg, respectively, with high emissions in Northeast China (31.7%) and North China (23.7%). Based on simulations conducted for 2018, OCSB emissions are estimated to contribute up to 0.95 µg/m3 increase in annual averaged maximum daily 8-hour (MDA8) ozone and up to 1.35 µg/m3 for the ozone season average. The significant impact of OCSB emissions on ozone is mainly characterized by localized and episodic (e.g., daily) changes in ozone concentration, up to 20 µg/m3 in North China and Yangtze River Delta region and even more in Northeast China during the burning season. With the implementation of straw burning bans, VOCs and NOx emissions from OCSB dropped substantially by 46.9%, particularly over YRD (76%) and North China (60%). Consequently, reduced OCSB emissions result in an overall decrease in annual averaged MDA8 ozone, and reductions in monthly MDA8 ozone could be over 10 µg/m3 in North China. The number of avoided premature death due to reduced OCSB emissions (considering both PM2.5 and ozone) is estimated to be 6120 (95% Confidence Interval: 5320-6800), with most health benefits gained over east and central China. Our results illustrate the effectiveness of straw burning bans in reducing ozone concentrations at annual and national scales and the substantial ozone impacts from OCSB events at localized and episodic scales.
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Affiliation(s)
- Ling Huang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Yonghui Zhu
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Hanqing Liu
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Yangjun Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - David T Allen
- Center for Energy and Environmental Resources, University of Texas at Austin, 10100 Burnet Road, Austin, TX 78758, United States
| | - Maggie Chel Gee Ooi
- Institute of Climate Change (IPI), Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
| | - Kasemsan Manomaiphiboon
- The Joint Graduate School of Energy and Environment, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand
| | - Mohd Talib Latif
- Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
| | - Andy Chan
- Department of Civil Engineering, University of Nottingham Malaysia, Semenyih 43500, Selangor, Malaysia
| | - Li Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China.
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Rashidi R, Khaniabadi YO, Sicard P, De Marco A, Anbari K. Ambient PM 2.5 and O 3 pollution and health impacts in Iranian megacity. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT : RESEARCH JOURNAL 2023; 37:175-184. [PMID: 35965492 PMCID: PMC9358119 DOI: 10.1007/s00477-022-02286-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 07/15/2022] [Indexed: 05/21/2023]
Abstract
The main objectives of this study were to (i) assess variation within fine particles (PM2.5) and tropospheric ozone (O3) time series in Khorramabad (Iran) between 2019 (before) and 2020 (during COVID-19 pandemic); (ii) assess relationship between PM2.5 and O3, the PM2.5/O3 ratio, and energy consumption; and (iii) estimate the health effects of exposure to ambient PM2.5 and O3. From hourly PM2.5 and O3 concentrations, we applied both linear-log and integrated exposure-response functions, city-specific relative risk, and baseline incidence values to estimate the health effects over time. A significant correlation was found between PM2.5 and O3 (r =-0.46 in 2019, r =-0.55 in 2020, p < 0.05). The number of premature deaths for all non-accidental causes (27.5 and 24.6), ischemic heart disease (7.3 and 6.3), chronic obstructive pulmonary disease (17 and 19.2), and lung cancer (9.2 and 6.25) attributed to ambient PM2.5 exposure and for respiratory diseases (4.7 and 5.4) for exposure to O3 above 10 µg m-3 for people older than 30-year-old were obtained in 2019 and 2020. The number of years of life lost declined by 11.6% in 2020 and exposure to PM2.5 reduced the life expectancy by 0.58 and 0.45 years, respectively in 2019 and 2020. Compared to 2019, the restrictive measures associated to COVID-19 pandemic led to reduction in PM2.5 (-25.5%) and an increase of O3 concentration (+ 8.0%) in Khorramabad.
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Affiliation(s)
- Rajab Rashidi
- Department of Occupational Health, Nutritional Health Research Center, School of Health and Nutrition,
Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Yusef Omidi Khaniabadi
- Occupational and Environmental Health Research Center, Petroleum Industry Health Organization (PIHO), Ahvaz, Iran
| | | | | | - Khatereh Anbari
- Social Determinants of Health Research Center, School of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran
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30
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Khojasteh D, Davani E, Shamsipour A, Haghani M, Glamore W. Climate change and COVID-19: Interdisciplinary perspectives from two global crises. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 844:157142. [PMID: 35798107 PMCID: PMC9252874 DOI: 10.1016/j.scitotenv.2022.157142] [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: 05/02/2022] [Revised: 06/29/2022] [Accepted: 06/29/2022] [Indexed: 05/12/2023]
Abstract
The repercussions of the COVID-19 pandemic and climate change - two major current global crises - are far-reaching, the parallels between the two are striking, and their influence on one another are significant. Based on the wealth of evidence that has emerged from the scientific literature during the first two years of the pandemic, this study argues that these two global crises require holistic multisectoral mitigation strategies. Despite being different in nature, neither crisis can be effectively mitigated without considering their interdependencies. Herein, significant interactions between these two crises are highlighted and discussed. Major implications related to the economy, energy, technology, environment, food systems and agriculture sector, health systems, policy, management, and communities are detailed via a review of existing joint literature. Based on these outcomes, practical recommendations for future research and management are provided. While the joint timing of these crises has created a global conundrum, the COVID-19 pandemic has demonstrated opportunities and lessons for devising sustainable recovery plans in relation to the climate crisis. The findings indicated that governments should work collaboratively to develop durable and adjustable strategies in line with long-term, global decarbonisation targets, promote renewable energy resources, integrate climate change into environmental policies, prioritise climate-smart agriculture and local food systems, and ensure public and ecosystem health. Further, differences in geographic distributions of climate change and COVID-19 related death cases revealed that these crises pose different threats to different parts of the world. These learnings provide insights to address the climate emergency - and potential future global problems with similar characteristics - if international countries act urgently and collectively.
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Affiliation(s)
- Danial Khojasteh
- Water Research Laboratory, School of Civil and Environmental Engineering, UNSW, Sydney, NSW, Australia.
| | - Ehsan Davani
- School of Mechanical Engineering, Shiraz University, Shiraz, Iran
| | - Abbas Shamsipour
- School of Mechanical Engineering, Shiraz University, Shiraz, Iran
| | - Milad Haghani
- Research Centre for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, The University of New South Wales, UNSW, Sydney, Australia.
| | - William Glamore
- Water Research Laboratory, School of Civil and Environmental Engineering, UNSW, Sydney, NSW, Australia.
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31
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Zhang X, Xiao X, Wang F, Brasseur G, Chen S, Wang J, Gao M. Observed sensitivities of PM 2.5 and O 3 extremes to meteorological conditions in China and implications for the future. ENVIRONMENT INTERNATIONAL 2022; 168:107428. [PMID: 35985105 DOI: 10.1016/j.envint.2022.107428] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/19/2022] [Accepted: 07/20/2022] [Indexed: 06/15/2023]
Abstract
Frequent extreme air pollution episodes in China accompanied with high concentrations of particulate matters (PM2.5) and ozone (O3) are partly supported by meteorological conditions. However, the relationships between meteorological variables and pollution extremes can be poorly estimated solely based on mean pollutant level. In this study, we use quantile regression to investigate meteorological sensitivities of PM2.5 and O3 extremes, benefiting from nationwide observations of air pollutants over 2013-2019 in China. Results show that surface winds and humidity are identified as key drivers for high PM2.5 events during both summer and winter, with greater sensitivities at higher percentiles. Higher humidity favors the hydroscopic growth of particles during winter, but it tends to decrease PM2.5 through wet scavenging during summer. Surface temperature play dominant role in summer O3 extremes, especially in VOC-limited regime, followed by surface winds and radiation. Sensitivities of O3 to meteorological conditions are relatively unchanging across percentiles. Under the fossil-fueled development pathway (SSP5-8.5) scenario, meteorological conditions are projected to favor winter PM2.5 extremes in North China Plain (NCP), Yangtze River Delta (YRD) and Sichuan Basin (SCB), mainly due to enhanced surface specific humidity. Summer O3 extremes are likely to occur more frequently in the NCP and YRD, associated with warmer temperature and stronger solar radiation. Besides, meteorological conditions over a relatively longer period play a more important role in the formation of pollution extremes. These results improve our understanding of the relationships between extreme PM2.5 and O3 pollution and meteorology, and can be used as a valuable reference of model predicted air pollution extremes.
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Affiliation(s)
- Xiaorui Zhang
- Department of Geography, Hong Kong Baptist University, Hong Kong, China
| | - Xiang Xiao
- Department of Geography, Hong Kong Baptist University, Hong Kong, China
| | - Fan Wang
- Department of Geography, Hong Kong Baptist University, Hong Kong, China
| | - Guy Brasseur
- Atmospheric Chemistry Observation & Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
| | - Siyu Chen
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, Lanzhou University, Lanzhou, China
| | - Jing Wang
- Tianjin Key Laboratory for Oceanic Meteorology, and Tianjin Institute of Meteorological Science, Tianjin, China
| | - Meng Gao
- Department of Geography, Hong Kong Baptist University, Hong Kong, China; Hong Kong Branch of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Hong Kong, China.
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32
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Bi Z, Ye Z, He C, Li Y. Analysis of the meteorological factors affecting the short-term increase in O 3 concentrations in nine global cities during COVID-19. ATMOSPHERIC POLLUTION RESEARCH 2022; 13:101523. [PMID: 35996529 PMCID: PMC9385202 DOI: 10.1016/j.apr.2022.101523] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 07/25/2022] [Accepted: 08/05/2022] [Indexed: 05/15/2023]
Abstract
Surface ozone (O3) is a major air pollutant around the world. This study investigated O3 concentrations in nine cities during the Coronavirus disease 2019 (COVID-19) lockdown phases. A statistical model, named Generalized Additive Model (GAM), was also developed to assess different meteorological factors, estimate daily O3 release during COVID-19 lockdown and determine the relationship between the two. We found that: (1) Daily O3 significantly increased in all selected cities during the COVID-19 lockdown, presenting relative increases from -5.7% (in São Paulo) to 58.9% (in Guangzhou), with respect to the average value for the same period in the previous five years. (2) In the GAM model, the adjusted coefficient of determination (R2) ranged from 0.48 (Sao Paulo) to 0.84 (Rome), and it captured 51-85% of daily O3 variations. (3) Analyzing the expected O3 concentrations during the lockdown, using GAM fed by meteorological data, showed that O3 anomalies were dominantly controlled by meteorology. (4) The relevance of different meteorological variables depended on the cities. The positive O3 anomalies in Beijing, Wuhan, Guangzhou, and Delhi were mostly associated with low relative humidity and elevated maximum temperature. Low wind speed, elevated maximum temperature, and low relative humidity were the leading meteorological factors for O3 anomalies in London, Paris, and Rome. The two other cities had different leading factor combinations.
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Affiliation(s)
- Zhongsong Bi
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
- School of Architecture and Civil Engineering, Huangshan University, Huangshan, 245041, China
| | - Zhixiang Ye
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, China
| | - Chao He
- College of Resources and Environment, Yangtze University, Wuhan, 430100, China
| | - Yunzhang Li
- College of Architecture and Environment, Sichuan University, Chengdu, 610065, China
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Guan Y, Xiao Y, Chu C, Zhang N, Yu L. Trends and characteristics of ozone and nitrogen dioxide related health impacts in Chinese cities. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 241:113808. [PMID: 35759982 DOI: 10.1016/j.ecoenv.2022.113808] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 06/02/2022] [Accepted: 06/21/2022] [Indexed: 06/15/2023]
Abstract
Ambient ozone pollution has been becoming severe and attributed to considerable health impacts in China. Nitrogen dioxide (NO2) is involved in atmospheric ozone production while also affecting public health directly. Joint control ozone and NO2 pollution would be of significance. This study quantitatively assessed the health impact attributed to ambient ozone and NO2 pollution in 338 Chinese cities from 2015 to 2020. The results reveal the generally opposite trends of ozone- and NO2-related health impacts in China. From 2015-2020, respiratory and chronic obstructive pulmonary disease (COPD) health impacts attributed to ozone in 338 cities increased by 65.30% and 63.98%. The NO2-attributed health impacts decreased by 24.80% and 24.62%. In 2020, the ozone- and NO2-related respiratory health impacts were 3.96 million DALYs (disability-adjusted life years) and 1.47 million DALYs. High health impacts are concentrated in big cities and city clusters. In 2020, the sum of ozone- and NO2-related respiratory health impacts in the top 20 cities was 0.98 million DALYs and 0.44 million DALYs, accounting for 24.70% and 30.24% of the 338 cities. The population attribution fraction analysis identified the increasing distributional consistency of ozone and NO2-related health impacts, emphasizing the necessity and possible efficiency of ozone-NO2 joint control. Emission source analysis based on gridded data provided a reference for understanding health impacts and developing targeted strategies.
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Affiliation(s)
- Yang Guan
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China; The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Yang Xiao
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China; The Center for Beautiful China, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Chengjun Chu
- Center of Environmental Status and Plan Assessment, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Nannan Zhang
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
| | - Lei Yu
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing 100012, China.
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Xue W, Zhang J, Hu X, Yang Z, Wei J. Hourly Seamless Surface O3 Estimates by Integrating the Chemical Transport and Machine Learning Models in the Beijing-Tianjin-Hebei Region. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19148511. [PMID: 35886364 PMCID: PMC9324222 DOI: 10.3390/ijerph19148511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 07/09/2022] [Accepted: 07/10/2022] [Indexed: 02/04/2023]
Abstract
Surface ozone (O3) is an important atmospheric trace gas, posing an enormous threat to ecological security and human health. Currently, the core objective of air pollution control in China is to realize the joint treatment of fine particulate matter (PM2.5) and O3. However, high-accuracy near-surface O3 maps remain lacking. Therefore, we established a new model to determine the full-coverage hourly O3 concentration with the WRF-Chem and random forest (RF) models combined with anthropogenic emission data and meteorological datasets. Based on this method, choosing the Beijing-Tianjin-Hebei (BTH) region in 2018 as an example, full-coverage hourly O3 maps were generated at a horizontal resolution of 9 km. The performance evaluation results indicated that the new model is reliable with a sample (station)-based 10-fold cross-validation (10-CV) R2 value of 0.94 (0.90) and root mean square error (RMSE) of 14.58 (19.18) µg m−3. In addition, the estimated O3 concentration is accurately determined at varying temporal scales with sample-based 10-CV R2 values of 0.96, 0.98 and 0.98 at the daily, monthly, and seasonal scales, respectively, which is highly superior to traditional derivation algorithms and other techniques in previous studies. An initial increase and subsequent decrease, which constitute the diurnal variation in the O3 concentration associated with temperature and solar radiation variations, were captured. The highest concentration reached approximately 112.73 ± 9.65 μg m−3 at 15:00 local time (1500 LT) in the BTH region. Summertime O3 posed a high pollution risk across the whole BTH region, especially in southern cities, and the pollution duration accounted for more than 50% of the summer season. Additionally, 43 and two days exhibited light and moderate O3 pollution, respectively, across the BTH region in 2018. Overall, the new method can be beneficial for near-surface O3 estimation with a high spatiotemporal resolution, which can be valuable for research in related fields.
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Affiliation(s)
- Wenhao Xue
- School of Economics, Qingdao University, Qingdao 266071, China; (W.X.); (Z.Y.)
| | - Jing Zhang
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China;
- Correspondence: (J.Z.); (J.W.)
| | - Xiaomin Hu
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China;
| | - Zhe Yang
- School of Economics, Qingdao University, Qingdao 266071, China; (W.X.); (Z.Y.)
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742, USA
- Correspondence: (J.Z.); (J.W.)
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Wang Y, Zhang Y, Zhang L, Li M, Zhu P, Ji W, Liang R, Qiin L, Wu W, Feng F, Jin Y. [Angiotensin-converting enzyme 2 particapates in ozone-induced lung inflammation and airway remodeling in mice]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2022; 42:860-867. [PMID: 35790436 DOI: 10.12122/j.issn.1673-4254.2022.06.09] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To investigate the roles of angiotensin-converting enzyme 2 (ACE2) in ozone-induced pulmonary inflammation and airway remodeling in mice. METHODS Sixteen wild-type (WT) C57BL/6J mice and 16 ACE2 knock-out (KO) mice were exposed to either filtered air or ozone (0.8 ppm) for 3 h per day for 5 consecutive days. Masson's staining and HE staining were used to observe lung pathologies. Bronchoalveolar lavage fluid (BALF) was collected and the total cell count was determined. The total proteins and cytokines in BALF were determined by BCA and ELISA method. The transcription levels of airway remodeling-related indicators in the lung tissues were detected using real-time quantitative PCR. The airway resistance of the mice was measured using a small animal ventilator with methacholine stimulation. RESULTS Following ozoneexposure ACE2 KO mice had significantly higher lung pathological scores than WT mice (P < 0.05). Masson staining results showed that compared with ozone-exposed WT mice, ozone-exposed ACE2 KO mice presented with significantly larger area of collagen deposition in the bronchi [(19.62±3.16)% vs (6.49±1.34)%, P < 0.05] and alveoli [(21.63±3.78)% vs (4.44±0.99)%, P < 0.05]. The total cell count and total protein contents in the BALF were both higher in ozone-exposed ACE2 KO mice than in WT mice, but these differences were not statistically significant (P > 0.05). The concentrations of IL-6, IL-1β, TNF-α, CXCL1/KC and MCP-1 in the BALF were all higher in ozone-exposed ACE2 KO mice than in ozone-exposed WT mice, but only the difference in IL-1β was statistically significant (P < 0.05). The transcription levels of MMP-9, MMP-13, TIMP 4, COL1A1, and TGF-β in the lung tissues were all significantly higher in ozone-exposed ACE2 KO mice (P < 0.01). No significant difference was found in airway resistance between ozone-exposed ACE KO mice and WT mice after challenge with 0, 10, 25, or 100 mg/mL of methacholine. CONCLUSION ACE2 participates in ozone-induced lung inflammation and airway remodeling in mice.
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Affiliation(s)
- Y Wang
- Department of epidemiology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Y Zhang
- Department of epidemiology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - L Zhang
- Department of epidemiology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - M Li
- Department of Toxicology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - P Zhu
- Department of epidemiology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - W Ji
- Department of epidemiology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - R Liang
- Department of epidemiology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - L Qiin
- Institute of Chronic and Non-communicable Disease Prevention and Control, Henan Provincial Center for Disease Control and Prevention, Zhengzhou 450001, China
| | - W Wu
- Department of Occupational and Environmental Health, School of Public Health, Xinxiang Medical University, Xinxiang 453000, China
| | - F Feng
- Department of Toxicology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Y Jin
- Department of epidemiology, School of Public Health, Zhengzhou University, Zhengzhou 450001, China
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Xiao Q, Geng G, Xue T, Liu S, Cai C, He K, Zhang Q. Tracking PM 2.5 and O 3 Pollution and the Related Health Burden in China 2013-2020. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:6922-6932. [PMID: 34941243 DOI: 10.1021/acs.est.1c04548] [Citation(s) in RCA: 82] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Based on the exposure data sets from the Tracking Air Pollution in China (TAP, http://tapdata.org.cn/), we characterized the spatiotemporal variations in PM2.5 and O3 exposures and quantified the long- and short-term exposure related premature deaths during 2013-2020 with respect to the two-stage clean air actions (2013-2017 and 2018-2020). We find a 48% decrease in national PM2.5 exposure during 2013-2020, although the decrease rate has slowed after 2017. At the same time, O3 pollution worsened, with the average April-September O3 exposure increased by 17%. The improved air quality led to 308 thousand and 16 thousand avoided long- and short-term exposure related deaths, respectively, in 2020 compared to the 2013 level, which was majorly attributed to the reduction in ambient PM2.5 concentration. It is also noticed that with smaller PM2.5 reduction, the avoided long-term exposure associated deaths in 2017-2020 (13%) was greater than that in 2013-2017 (9%), because the exposure-response curve is nonlinear. As a result of the efforts in reducing PM2.5-polluted days with the daily average PM2.5 higher than 75 μg/m3 and the considerable increase in O3-polluted days with the daily maximum 8 h average O3 higher than 160 μg/m3, deaths attributable to the short-term O3 exposure were greater than those due to PM2.5 exposure since 2018. Future air quality improvement strategies for the coordinated control of PM2.5 and O3 are urgently needed.
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Affiliation(s)
- Qingyang Xiao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Guannan Geng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, 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 100080, China
| | - Shigan Liu
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Cilan Cai
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
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Wu K, Wang Y, Qiao Y, Liu Y, Wang S, Yang X, Wang H, Lu Y, Zhang X, Lei Y. Drivers of 2013-2020 ozone trends in the Sichuan Basin, China: Impacts of meteorology and precursor emission changes. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 300:118914. [PMID: 35124125 DOI: 10.1016/j.envpol.2022.118914] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 01/06/2022] [Accepted: 01/25/2022] [Indexed: 06/14/2023]
Abstract
The Sichuan Basin (SCB) of China is known for excessive ozone (O3) pollution owing to high anthropogenic emissions combined with terrain-induced poor ventilation and weak wind fields against the surrounding mountains. While O3 pollution has emerged as a prominent concern in southwestern China yet variations in O3 levels during 2013-2020 are still unclear and the dominant factor in explaining the long-term O3 trend throughout the SCB remains elusive due to uncertainties in emission inventory and variability associated with meteorological conditions. Here, we use extensive basin-wide ambient measurements to examine the spatial pattern and trend of O3 and leverage OMI and TROPOMI satellites in conjunction with MEIC emission inventory to track emission changes. Sensitivity simulations are conducted by using WRF-CMAQ model to investigate the impacts of meteorological variability and emission changes on O3 changes over 2013-2020. O3 concentrations exhibit obvious interannual increases during 2013-2019 and a slight decrease in 2020. Both decreases in the MEIC emission inventory (-2.9% yr-1) and OMI NO2 column density (-3.1% yr-1) reflects the declining trend in NOx emissions over 2013-2020, while anthropogenic VOCs were not adequately regulated during 2013-2017, which explained the majority of deteriorated O3 pollution from 2013 to 2017. Furthermore, attribution analysis based on CMAQ simulations indicate that the unexpected aggravated O3 levels in 2019 is not only modulated by disproportional reductions in VOCs and NOx emissions, but also associated with unfavorable meteorological conditions featured by profound heatwaves and frequent stagnant conditions. In 2020, the abnormal meteorological conditions in May leads to substantial increase of O3 by 26.8 μg m-3 as compared to May 2019, while the considerable enhancement was fully offset by low O3 levels over the whole period which attributes to substantial emission reductions. This study reveals the long-term trend of O3 levels and precursor emissions and highlights the effects of meteorological variability and emission changes on O3 pollution over the SCB, with strong implications for designing effective O3 control measures.
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Affiliation(s)
- Kai Wu
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China; Department of Land, Air, and Water Resources, University of California, Davis, One Shields Avenue, Davis, CA, USA
| | - Yurun Wang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China; Department of Land, Air, and Water Resources, University of California, Davis, One Shields Avenue, Davis, CA, USA
| | - Yuhong Qiao
- Sichuan Academy of Environmental Sciences, Chengdu, China
| | - Yiming Liu
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
| | - Shigong Wang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China
| | - Xianyu Yang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China.
| | - Haolin Wang
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China
| | - Yaqiong Lu
- Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China
| | - Xiaoling Zhang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China
| | - Yu Lei
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China
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Zhao H, Wang L, Zhang Z, Qi Q, Zhang H. Quantifying ecological and health risks of ground-level O 3 across China during the implementation of the "Three-year Action Plan for Cleaner Air". THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 817:153011. [PMID: 35026272 DOI: 10.1016/j.scitotenv.2022.153011] [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: 10/25/2021] [Revised: 01/03/2022] [Accepted: 01/05/2022] [Indexed: 05/29/2023]
Abstract
After China implemented the Air Pollution Prevention and Control Action Plan (APPCAP), PM2.5 concentrations decreased but were still higher than national standards in major areas and ozone (O3) concentration increased unintentionally. To further decrease PM2.5 concentrations and reduce days with severe air pollution, the government promulgated the "Three-year (2018-2020) Action Plan for Cleaner Air" (the Three-year Action Plan) in 2018. During the three-year Action Plan, a few studies reported a continuous decline in PM2.5, but it is unclear whether O3 and its effects also increase with the decrease of PM2.5 like during APPCAP. In this study, for the first time, we systematically assessed changes in ground-level O3 concentrations and related ecological and health risks during the period of the Three-year Action Plan using nationwide O3 measurements. The national MDA8, Exceedance, and SOMO35 indicators were reduced by 3.8%, 28.5%, and 12.6%, respectively, ecological risk indicators of M12, M7, SUM06, AOT40, and W126 were reduced by 5.4%, 5.6%, 19.5%, 15.4%, and 18.6%, respectively, from 2018 to 2020. Spatially, the greatest reduction in all the indicators except MDA8 occurred in Pearl River Delta, followed by Fen Wei Plains, while Beijing-Tianjin-Hebei, Chengdu-Chongqing, and Yangtze River Delta presented relatively small reductions. Between 2018 and 2020, the production losses caused by O3 for wheat and rice decreased by 21.4% and 17.6%, respectively. Long-term exposure to O3 across China over 2020 was estimated to cause about 160,795 (95% CI: 81,515-312,983) for all-cause mortality, 107,128 (95% CI: 36,703-173,823) for cardiovascular mortality, and 34,444 (95% CI: 0-72,609) for respiratory mortality, indicating decreases of 9.93%, 9.86%, and 9.78%, respectively, compared to the year 2018. Taken together, our results provided the first direct evidence for China's efforts to control O3 pollution in recent years.
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Affiliation(s)
- Hui Zhao
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control (AEMPC), Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Lin Wang
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Zhen Zhang
- Shaanxi Meteorological Service Center of Agricultural Remote Sensing and Economic Crops, Xi'an 710014, China
| | - Qi Qi
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Hongliang Zhang
- Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China; Institute of Eco-Chongming (IEC), Shanghai 200062, China.
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Zhang Y, Li J, Li J, Pan X, Wang W, Zhu L, Wang Z, Chen X, Yang W, Wang Z. An intercomparison of ozone taken from the Copernicus atmosphere monitoring service and the second Modern-Era retrospective analysis for research and applications over China during 2018 and 2019. J Environ Sci (China) 2022; 114:514-525. [PMID: 35459513 DOI: 10.1016/j.jes.2022.01.045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 01/09/2022] [Accepted: 01/29/2022] [Indexed: 11/15/2022]
Abstract
Spatiotemporal variations of ozone (O3) taken from the Copernicus Atmosphere Monitoring Service (CAMS) and the second Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) were intercompared and evaluated with ground and ozone-sonde observations over China in 2018 and 2019. Intercomparison of the surface ozone from CAMS and MERRA-2 reanalysis showed significant negative bias (CAMS minus MERRA-2, same below) at Tibetan Plateau of up to 80 µg/m3, and the average R2 was about 0.6 across China. Evaluated with the ground observations from China National Environmental Monitoring Center (CNEMC), we found that CAMS and MERRA-2 reanalysis were capable of capturing the key patterns of monthly and diurnal variations of surface ozone over China except for the western region, and MERRA-2 overestimated the observations compared to CAMS. Vertically, the CAMS profiles overestimated the ozone-sonde from the World Ozone and Ultraviolet Radiation Data Center (WOUDC) above 200 hPa with the magnitude reaching up to 150 µg/m3, while little bias was found between the reanalysis and observations below 200 hPa. Intercomparison drawn from the vertical distribution between CAMS and MERRA-2 reanalysis showed that the negative bias appeared throughout the troposphere over China, while the positive bias emerged in the upper troposphere and lower stratosphere (UTLS) with high order of magnitude exceeding 100 µg/m3, indicating large uncertainties at higher altitudes. In summary, we concluded that CAMS reanalysis showed better agreement with the observations in contrast to MERRA-2, and the large discrepancy especially at higher altitudes between these two reanalysis datasets could not be ignored.
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Affiliation(s)
- Yujing Zhang
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jie Li
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
| | - Jianjun Li
- China National Environmental Monitoring Center, Beijing 100012, China
| | - Xiaole Pan
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Wang
- China National Environmental Monitoring Center, Beijing 100012, China
| | - Lili Zhu
- China National Environmental Monitoring Center, Beijing 100012, China
| | - Zixi Wang
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xueshun Chen
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Wenyi Yang
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Zifa Wang
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
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Wang Y, Huang C, Hu J, Wang M. Development of high-resolution spatio-temporal models for ambient air pollution in a metropolitan area of China from 2013 to 2019. CHEMOSPHERE 2022; 291:132918. [PMID: 34798111 DOI: 10.1016/j.chemosphere.2021.132918] [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: 05/03/2021] [Revised: 10/23/2021] [Accepted: 11/14/2021] [Indexed: 06/13/2023]
Abstract
Modeling high-resolution air pollution concentrations is essential to accurately assess exposure for population studies. The aim of this study is to establish an advanced exposure model to predict spatiotemporal changes in fine particulate matter (PM2.5), nitrogen dioxides (NO2), and ozone (O3) concentrations in Shanghai, China. The model is constructed on a geo-statistical modeling framework that incorporates a dimension reduction regression approach and a spatial smoothing function to deal with fine-scale exposure variations. We used a dataset with comprehensive observational and predictor variables that included monitoring data from both national and local agencies from 2013 to 2019, a high-resolution geographical dataset of predictor variables, and a full-coverage weekly satellite data of the aerosol optical depth at a 1 × 1 km2 resolution. Our model performed well in terms of the spatial and temporal prediction ability assessed by cross-validation (CV) for PM2.5 (spatial R2 = 0.89, temporal R2 = 0.91), NO2 (R2 = 0.49, 0.78), and O3 (R2 = 0.67, 0.81) at the national monitors over seven years according to the leave-one-out CV. For the predictions at the local agency monitoring stations, the overall CV R2 was between 0.77 and 0.89 across the air pollutants. We visualized the long-term and seasonal averaged predictions of the PM2.5, NO2, and O3 exposure on maps with a spatial resolution of 100 × 100 m2. Our study provides a useful tool to accurately estimate air pollution exposure with high spatial and temporal resolution at the urban scale. These model predictions will be useful to assess both short-term and long-term air pollution exposure for health studies.
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Affiliation(s)
- Yiyi Wang
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Conghong Huang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA
| | - Jianlin Hu
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA; RENEW Institute, University at Buffalo, Buffalo, NY, USA; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, USA.
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41
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Wang Y, Wild O, Ashworth K, Chen X, Wu Q, Qi Y, Wang Z. Reductions in crop yields across China from elevated ozone. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 292:118218. [PMID: 34571069 DOI: 10.1016/j.envpol.2021.118218] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 08/28/2021] [Accepted: 09/20/2021] [Indexed: 06/13/2023]
Abstract
Exposure of crops to high concentrations of ozone can cause substantial reductions in yield that pose a serious threat to global food security. Here we provide comprehensive estimates of yield losses for key crops across China between 2014 and 2017 attributed to ozone using a number of new approaches. We use an air quality model at 5 km resolution and crop-specific dose-response functions developed for both concentration- and flux-based metrics. We bias correct modelled ozone concentrations and metrics using observations from more than 1000 locations. We find that on a 4-year average basis, production losses of key crops are 34-91 million metric tonnes (Mt/yr), dependent on the approach used, with highest losses in Henan province. At a national level, loss of winter wheat production derived using a China-specific dose-response function increased by 82% from 2014 to 2017, with large interannual variations in the North China Plain and in eastern China. Winter wheat losses estimated using flux-based functions, which require robust simulation of stomatal conductance and underlying vegetation physiology, are significantly lower, at 30 Mt/yr. We show that the definition of the growing season may have a greater impact on estimated losses than small biases in ozone surface concentrations. Although uncertainties remain, our findings demonstrate that increasing ozone concentrations have substantial adverse impacts on crop yields and threaten food security in China. It is important to control ozone concentrations to mitigate these negative impacts.
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Affiliation(s)
- Yuanlin Wang
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; Lancaster Environment Centre, Lancaster University, LA1 4YQ, United Kingdom.
| | - Oliver Wild
- Lancaster Environment Centre, Lancaster University, LA1 4YQ, United Kingdom
| | - Kirsti Ashworth
- Lancaster Environment Centre, Lancaster University, LA1 4YQ, United Kingdom
| | - Xueshun Chen
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Qizhong Wu
- College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Yi Qi
- School of Architecture and Urban Planning, Nanjing University, Nanjing, 210093, China
| | - Zifa Wang
- The State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; Centre for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China; College of Earth Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
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Xing J, Zheng S, Li S, Huang L, Wang X, Kelly JT, Wang S, Liu C, Jang C, Zhu Y, Zhang J, Bian J, Liu TY, Hao J. Mimicking atmospheric photochemical modelling with a deep neural network. ATMOSPHERIC RESEARCH 2022; 265:1-11. [PMID: 34857979 PMCID: PMC8630640 DOI: 10.1016/j.atmosres.2021.105919] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
Fast and accurate prediction of ambient ozone (O3) formed from atmospheric photochemical processes is crucial for designing effective O3 pollution control strategies in the context of climate change. The chemical transport model (CTM) is the fundamental tool for O3 prediction and policy design, however, existing CTM-based approaches are computationally expensive, and resource burdens limit their usage and effectiveness in air quality management. Here we proposed a novel method (noted as DeepCTM) that using deep learning to mimic CTM simulations to improve the computational efficiency of photochemical modeling. The well-trained DeepCTM successfully reproduces CTM-simulated O3 concentration using input features of precursor emissions, meteorological factors, and initial conditions. The advantage of the DeepCTM is its high efficiency in identifying the dominant contributors to O3 formation and quantifying the O3 response to variations in emissions and meteorology. The emission-meteorology-concentration linkages implied by the DeepCTM are consistent with known mechanisms of atmospheric chemistry, indicating that the DeepCTM is also scientifically reasonable. The DeepCTM application in China suggests that O3 concentrations are strongly influenced by the initialized O3 concentration, as well as emission and meteorological factors during daytime when O3 is formed photochemically. The variation of meteorological factors such as short-wave radiation can also significantly modulate the O3 chemistry. The DeepCTM developed in this study exhibits great potential for efficiently representing the complex atmospheric system and can provide policymakers with urgently needed information for designing effective control strategies to mitigate O3 pollution.
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Affiliation(s)
- 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
| | | | - Siwei Li
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
| | - Lin Huang
- Microsoft Research Asia, Beijing 100080, China
| | - Xiaochun 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
| | - James T. Kelly
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - 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
| | - Chang Liu
- Microsoft Research Asia, Beijing 100080, China
| | - Carey Jang
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Yun Zhu
- College of Environment and Energy, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
| | - Jia Zhang
- Microsoft Research Asia, Beijing 100080, China
| | - Jiang Bian
- Microsoft Research Asia, Beijing 100080, China
| | - Tie-Yan Liu
- Microsoft Research Asia, Beijing 100080, 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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Guan Y, Xiao Y, Wang Y, Zhang N, Chu C. Assessing the health impacts attributable to PM 2.5 and ozone pollution in 338 Chinese cities from 2015 to 2020. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 287:117623. [PMID: 34171728 DOI: 10.1016/j.envpol.2021.117623] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 05/13/2023]
Abstract
China has effectively reduced the fine particulate (PM2.5) pollution from 2015 to 2020. Ozone pollution and related health impacts have become severe contemporaneously. The coordinated control of PM2.5 and ozone is becoming a new issue for China's air pollution control. This study quantitatively assessed the health impacts attributed to PM2.5 and ozone pollution in 338 Chinese cities from 2015 to 2020 and estimated the possible health benefits from achieving dual concentration targets during 2021-2025. Results show PM2.5 caused a total health impact of 2.45 × 107 disability-adjusted life years (DALYs) in 2020. All-cause and respiratory ozone-related health impact in 2020 was 1.04 × 107 DALYs and 1.56 × 106 DALYs. Between 2015 and 2020, the PM2.5-related health impacts decreased by 14.97%, while those ozone-related increased by 94.61% and 96.54% for all-cause and respiratory. Cities in the North China Plain have suffered higher health impacts attributable to PM2.5 and ozone pollution, indicating that the two-pollutant coordinated control is primarily needed. By achieving aggressive concentration target (decreasing 10%) between 2020 and 2025, China will reduce the PM2.5-related health impacts in 338 cities by 1.56 × 106 DALYs (improving 6.37%). By achieving general target (decreasing 10% or within the Interim target-1 of World Health Organization), the PM2.5-related health benefit will be 7.98 × 105 DALYs (improving 3.25%). The deteriorating ozone health risks will also be improved. Controlling air pollution in large cities and regional center cities can achieve remarkable health benefits. Due to the inter-region, inter-province, and inter-city difference of health impacts, targeted and differentiated pollution prevention and control need to be implemented.
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Affiliation(s)
- Yang Guan
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Yang Xiao
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Yameng Wang
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing, 100012, China
| | - Nannan Zhang
- Institute of Strategic Planning, Chinese Academy of Environmental Planning, Beijing, 100012, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
| | - Chengjun Chu
- Center of Environmental Status and Plan Assessment, Chinese Academy of Environmental Planning, Beijing, 100012, China
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Wang C, Wang Y, Shi Z, Sun J, Gong K, Li J, Qin M, Wei J, Li T, Kan H, Hu J. Effects of using different exposure data to estimate changes in premature mortality attributable to PM 2.5 and O 3 in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 285:117242. [PMID: 33957508 DOI: 10.1016/j.envpol.2021.117242] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 04/20/2021] [Accepted: 04/23/2021] [Indexed: 06/12/2023]
Abstract
The assessment of premature mortality associated with the dramatic changes in fine particulate matter (PM2.5) and ozone (O3) has important scientific significance and provides valuable information for future emission control strategies. Exposure data are particularly vital but may cause great uncertainty in health burden assessments. This study, for the first time, used six methods to generate the concentration data of PM2.5 and O3 in China between 2014 and 2018, and then quantified the changes in premature mortality due to PM2.5 and O3 using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results show that PM2.5-related premature mortality in China decreases by 263 (95% confidence interval (CI95): 142-159) to 308 (CI95: 213-241) thousands from 2014 to 2018 by using different concentration data, while O3-related premature mortality increases by 67 (CI95: 26-104) to 103 (CI95: 40-163) thousands. The estimated mean changes are up to 40% different for the PM2.5-related mortality, and up to 30% for the O3-related mortality if different exposure data are chosen. The most significant difference due to the exposure data is found in the areas with a population density of around 103 people/km2, mostly located in Central China, for both PM2.5 and O3. Our results demonstrate that the exposure data source significantly affects mortality estimations and should thus be carefully considered in health burden assessments.
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Affiliation(s)
- Chunlu Wang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Yiyi Wang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Zhihao Shi
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Jinjin Sun
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Kangjia Gong
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Jingyi Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Momei Qin
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, 20740, USA
| | - Tiantian Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, Fudan University, Shanghai, 200032, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
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Zhang Z, Yao M, Wu W, Zhao X, Zhang J. Spatiotemporal assessment of health burden and economic losses attributable to short-term exposure to ground-level ozone during 2015-2018 in China. BMC Public Health 2021; 21:1069. [PMID: 34090376 PMCID: PMC8178864 DOI: 10.1186/s12889-021-10751-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 04/05/2021] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Ground-level ozone (O3) pollution is currently the one of the severe environmental problems in China. Although existing studies have quantified the O3-related health impact and economic loss, few have focused on the acute health effects of short-term exposure to O3 and have been limited to a single temporal and spatial dimension. METHODS Based on the O3 concentration obtained from ground monitoring networks in 334 Chinese cities in 2015-2018, this study used a two-stage exposure parameter weighted Log-linear exposure-response function to estimate the cause-specific mortality for short-term exposure to O3. RESULTS The value of statistical life (VSL) method that were used to calculate the economic loss at the city-level. Our results show that in China, the national all-cause mortality attributed to O3 was 0.27(95% CI: 0.14-0.55) to 0.39 (95% CI: 0.20-0.67) million across 2015-2018. The estimated economic loss caused by O3 was 387.76 (95% CI: 195.99-904.50) to 594.08 (95% CI: 303.34-1140.65) billion CNY, accounting for 0.52 to 0.69% of total reported GDP. Overall, the O3 attributed health and economic burden has begun to decline in China since 2017. However, highly polluted areas still face severe burden, and undeveloped areas suffer from high GDP losses. CONCLUSIONS There are substantial health impacts and economic losses related to short-term O3 exposure in China. The government should pay attention to the emerging ozone pollution, and continue to strengthen the intervention in traditional priority areas while solving the pollution problem in non-priority areas.
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Affiliation(s)
- Zihan Zhang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.16 Section 3, Renmin South Road, Chengdu, 610044, China
| | - Minghong Yao
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.16 Section 3, Renmin South Road, Chengdu, 610044, China
| | - Wenjing Wu
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.16 Section 3, Renmin South Road, Chengdu, 610044, China
| | - Xing Zhao
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.16 Section 3, Renmin South Road, Chengdu, 610044, China.
| | - Juying Zhang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, No.16 Section 3, Renmin South Road, Chengdu, 610044, China.
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Yang X, Wu K, Lu Y, Wang S, Qiao Y, Zhang X, Wang Y, Wang H, Liu Z, Liu Y, Lei Y. Origin of regional springtime ozone episodes in the Sichuan Basin, China: Role of synoptic forcing and regional transport. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 278:116845. [PMID: 33689943 DOI: 10.1016/j.envpol.2021.116845] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 02/12/2021] [Accepted: 02/25/2021] [Indexed: 06/12/2023]
Abstract
The Sichuan Basin (SCB) located in southwestern China has long been considered the most polluted city cluster with exposure to unhealthy levels of ozone (O3) at times. However, the features of O3 regional transport and source contributions in SCB are poorly understood. In this study, ambient measurements, ERA5 reanalysis dataset, IASI O3 column, and the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) modeling system coupled with the Integrated Source Apportionment Method (ISAM) module were used to investigate the formation mechanism and sources of a severe O3 episode in spring 2020 over the SCB. In the first stage of the O3 episode, a high-pressure system persisted over the western SCB and caused northeasterly wind fields, leading to enhanced regional transport from the northern boundary with the O3 contribution from the boundary exceeding 50% across the SCB. As the synoptic pattern evolved, southeasterly winds dominated the SCB and the stagnant zone over the Chengdu Plain confined O3 originating from the southern SCB and Chongqing city, leading to the accumulation of precursors and elevated O3 levels. During the O3 episode, transportation and industrial sources were major contributors to O3 formation especially for the Chengdu Plain and Chongqing city. In addition, the O3-rich air mass in the nocturnal residual layer that formed over Chongqing city was transported to the Chengdu Plain through southeastern corridor at 400-1600m above ground-level under the prevailing southeasterly winds. With sunrise and the development of the atmospheric boundary layer, the O3-rich air mass in the residual layer (RL) was entrained to the ground-level via vertical mixing, which further enhanced O3 pollution across the Chengdu Plain. Our results revealed the mechanism of regional transport via northeastern and southeastern corridors during an O3 episode and demonstrated the need for joint emission regulation across the SCB to mitigate O3 pollution.
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Affiliation(s)
- Xianyu Yang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China
| | - Kai Wu
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China.
| | - Yaqiong Lu
- Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China.
| | - Shigong Wang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China
| | - Yuhong Qiao
- Sichuan Academy of Environmental Sciences, Chengdu, China
| | - Xiaoling Zhang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China
| | - Yurun Wang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China
| | - Haolin Wang
- School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, Guangdong, China
| | - Zhihong Liu
- School of Resources and Environment, Chengdu University of Information Technology, Chengdu, China
| | - Yilin Liu
- Chinese Academy of Meteorological Sciences, Beijing, China
| | - Yu Lei
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, China
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Albert S, Amarilla AA, Trollope B, Sng JDJ, Setoh YX, Deering N, Modhiran N, Weng SH, Melo MC, Hutley N, Nandy A, Furlong MJ, Young PR, Watterson D, Grinham AR, Khromykh AA. Assessing the potential of unmanned aerial vehicle spraying of aqueous ozone as an outdoor disinfectant for SARS-CoV-2. ENVIRONMENTAL RESEARCH 2021; 196:110944. [PMID: 33647300 PMCID: PMC7908847 DOI: 10.1016/j.envres.2021.110944] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 02/21/2021] [Accepted: 02/23/2021] [Indexed: 05/15/2023]
Abstract
The COVID-19 pandemic has revealed gaps in our understanding of safe, effective and efficient means of disinfecting high use public spaces. Whilst this creates an opportunity for development and application of innovative approaches such as unmanned aerial vehicle (UAV) based disinfection, unregulated outdoor disinfection using chlorine has led to environmental and public health risks. This study has quantified the efficiency, safety and efficacy of UAV-based spraying of aqueous ozone. Optimised UAV flight characteristics of 4.7 km/h at 1.7 m elevation spraying 2.4 L/min were able to provide >97% and >92% coverage of a 1 m and 2 m wide swath respectively. During spraying operations using 1 mg/L aqueous ozone, atmospheric concentrations of ozone remained within background levels (<0.04 ppm). Highly efficient inactivation of two different isolates of SARS-CoV-2 virus was achieved at aqueous ozone concentrations of 0.75 mg/L after an incubation period of only 5 min, with 0.375 mg/L achieving 82-91.5% inactivation in this time. Exposure of diamondback moth larvae and parasitic wasps to 1 mg/L aqueous ozone did not significantly affect their survivorship. These results indicate for the first time that aqueous ozone may provide the required balance between human and environmental safety and viral inactivation efficacy for targeted application in high risk outdoor settings.
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Affiliation(s)
- Simon Albert
- School of Civil Engineering, The University of Queensland, St. Lucia, QLD, 4072, Australia.
| | - Alberto A Amarilla
- Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Ben Trollope
- The Ripper Group Pty Ltd, Level 5/50 York Street, Sydney, NSW, 2000, Australia
| | - Julian D J Sng
- Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Yin Xiang Setoh
- Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Nathaniel Deering
- School of Civil Engineering, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Naphak Modhiran
- Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Sung-Hsia Weng
- School of Biological Sciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Maria C Melo
- School of Biological Sciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Nicholas Hutley
- School of Civil Engineering, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Avik Nandy
- Remote Sensing Research Centre, School of Earth and Environmental Sciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Michael J Furlong
- School of Biological Sciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Paul R Young
- Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Daniel Watterson
- Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Alistair R Grinham
- School of Civil Engineering, The University of Queensland, St. Lucia, QLD, 4072, Australia
| | - Alexander A Khromykh
- Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD, 4072, Australia.
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