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Zhao M, Xie Y, Xu M, Weng Z, Hanaoka T, Zhang Y, Tong D. Optimizing air quality and health Co-benefits of mitigation technologies in China: An integrated assessment. ENVIRONMENTAL SCIENCE AND ECOTECHNOLOGY 2024; 22:100454. [PMID: 39139782 PMCID: PMC11321320 DOI: 10.1016/j.ese.2024.100454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 07/05/2024] [Accepted: 07/07/2024] [Indexed: 08/15/2024]
Abstract
Carbon mitigation technologies lead to air quality improvement and health co-benefits, while the practical effects of the technologies are dependent on the energy composition, technological advancements, and economic development. In China, mitigation technologies such as end-of-pipe treatment, renewable energy adoption, carbon capture and storage (CCS), and sector electrification demonstrate significant promise in meeting carbon reduction targets. However, the optimization of these technologies for maximum co-benefits remains unclear. Here, we employ an integrated assessment model (AIM/enduse, CAM-chem, IMED|HEL) to analyze air quality shifts and their corresponding health and economic impacts at the provincial level in China within the two-degree target. Our findings reveal that a combination of end-of-pipe technology, renewable energy utilization, and electrification yields the most promising results in air quality improvement, with a reduction of fine particulate matter (PM2.5) by -34.6 μg m-3 and ozone by -18.3 ppb in 2050 compared to the reference scenario. In contrast, CCS technology demonstrates comparatively modest improvements in air quality (-9.4 μg m-3 for PM2.5 and -2.4 ppb for ozone) and cumulative premature deaths reduction (-3.4 million from 2010 to 2050) compared to the end-of-pipe scenario. Notably, densely populated regions such as Henan, Hebei, Shandong, and Sichuan experience the most health and economic benefits. This study aims to project effective future mitigation technologies and climate policies on air quality improvement and carbon mitigation. Furthermore, it seeks to delineate detailed provincial-level air pollution control strategies, offering valuable guidance for policymakers and stakeholders in pursuing sustainable and health-conscious environmental management.
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Affiliation(s)
- Mengdan Zhao
- School of Economics and Management, Beihang University, Beijing, 100191, China
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, 100191, China
| | - Meng Xu
- School of Management, Wuhan Institute of Technology, Wuhan, 430205, China
| | - Zhixiong Weng
- Institute of Circular Economy, Beijing University of Technology, Beijing, 100124, China
| | - Tatsuya Hanaoka
- Center for Social and Environmental Systems Research, National Institute for Environmental Studies, Tsukuba, 305 8506, Japan
| | - Yuqiang Zhang
- Environment Research Institute, Shandong University, Qingdao, Shandong, 266237, China
| | - Dan Tong
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
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Kim S, Woo S, Cui Y, Yon DK, Choi M. Unmet community care needs among older adults in China: an observational study on influencing factors. BMC Geriatr 2024; 24:719. [PMID: 39210252 PMCID: PMC11363479 DOI: 10.1186/s12877-024-05318-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 08/19/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND With the rapidly aging population in China, there is an urgent need to understand and address the community care needs of older adults. This study sought to examine these unmet community care needs of older adults in China and the factors influencing them, with the goal of providing essential groundwork for the development of community care health policies. METHODS This study used data from the 2018 China Longitudinal Healthy Longevity Survey of 8,870 adults aged 65 years and older. Logistic regression analysis was performed to identify factors related to unmet community care needs. RESULTS The results showed that lower number of children, increased years of schooling, poorer self-perceived economic and health status, residing in an institution rather than living with household members, not having public old-age pensions, and not having activity due to daily living impairments were associated with a higher likelihood of unmet community care needs among older adults. CONCLUSIONS These findings indicate the necessity for crafting policies that consider the factors affecting unmet community care needs of older adults, including their health vulnerabilities and individual needs. Implementing national initiatives aimed at enhancing the quality of services delivered to older adults is crucial, along with establishing programmes to proactively address their vulnerabilities and individual needs. This study can contribute to the formulation of policy measures aimed at enhancing community care services of older adults in China.
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Affiliation(s)
- Suyeon Kim
- Department of Public Health Science, Graduate School and Transdisciplinary Major in Learning Health Systems, Graduate School, Korea University, Seoul, South Korea
| | - Selin Woo
- Center for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, South Korea
| | - Ying Cui
- Department of Public Health Science, Graduate School and Transdisciplinary Major in Learning Health Systems, Graduate School, Korea University, Seoul, South Korea
| | - Dong Keon Yon
- Center for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, Seoul, South Korea
| | - Mankyu Choi
- School of Health Policy & Management, College of Public Health Science and Transdisciplinary Major in Learning Health Systems, Graduate School, Korea University, Seoul, South Korea.
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3
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He G, Lin Y, Hu J, Chen Y, Guo Y, Yu M, Zeng F, Duan H, Meng R, Zhou C, Xiao Y, Huang B, Gong W, Liu J, Liu T, Zhou M, Ma W. The trends of non-accidental mortality burden attributed to compound hot-dry events in China and its provinces in a global warming world. ENVIRONMENT INTERNATIONAL 2024; 191:108977. [PMID: 39216332 DOI: 10.1016/j.envint.2024.108977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Revised: 07/22/2024] [Accepted: 08/21/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Global warming has provoked more co-occurrence of hot extreme and dry extreme, namely compound hot-dry events (CHDEs). However, their health impacts have seldom been investigated. This study aimed to characterize CHDEs and assess its mortality burden in China from 1990 to 2100. METHODS CHDEs were defined as a day when daily maximum temperature > its 90th percentile and Standardized Precipitation Index < its 50th percentile. A two-stage approach, including a distributed lag nonlinear model (DLNM) and a multivariate meta-analysis, was used to estimate exposure-response associations of CHDEs with mortality in 358 counties/districts during 2006-2017 in China, which was then applied to assess the national mortality burden attributable to CHDEs from 1990 to 2100. FINDINGS We observed a significant increasing trend of CHDEs in China until mid-21st century, and then flatted, while the duration and intensity of CHDEs continuously increased across the 21st century. CHDEs were much riskier (ER=17.82 %, 95 %CI: 14.17 %-21.60 %) than independent hot events (ER=5.86 %,95 %CI: -0.04 %,12.45 %) or dry events (ER=0.07 %,95 %CI: -1.22 %, 1.38 %), and there was significantly additive interaction between hot events and dry events (AP=0.10,95 %CI: 0.04, 0.16). Females (ER=24.28 %, 95 %CI: 19.21 %-29.56 %), the elderly (ER=23.28 %, 95 %CI: 18.23 %-28.55 %), and people living in humid area (ER=18.98 %, 95 %CI: 15.08 %-23.02 %) had higher mortality risks than their counterparts. Mortality burden attributed to CHDEs significantly increased during historical observation and became stable since mid-21st century in China. INTERPRETATION CHDEs would significantly increase mortality with higher risk for females, the elderly and people living in humid areas. Mortality burden has significantly increased during historical observation and will keep relatively steady since mid-21st century.
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Affiliation(s)
- Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Yi Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Yang Chen
- State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yanfang Guo
- Bao'an Chronic Diseases Prevent and Cure Hospital, Shenzhen 518100, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310009, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Hailai Duan
- Climate Center of Guangdong Province, Guangzhou 510640, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Yize Xiao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Weiwei Gong
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310009, China
| | - Jiangmei Liu
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing 100050, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China.
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Shen N, Tan J, Wang W, Xue W, Wang Y, Huang L, Yan G, Song Y, Li L. Long-term changes of methane emissions from rice cultivation during 2000 - 2060 in China: Trends, driving factors, predictions and policy implications. ENVIRONMENT INTERNATIONAL 2024; 191:108958. [PMID: 39153386 DOI: 10.1016/j.envint.2024.108958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Revised: 07/15/2024] [Accepted: 08/13/2024] [Indexed: 08/19/2024]
Abstract
Regional budget assessments of methane (CH4) are critical for future climate and environmental management. CH4 emissions from rice cultivation (CH4-rice) constitute one of the most significant sources. However, previous studies mainly focus on historical emission estimates and lack consideration of future changes in CH4-rice under climate change or anthropogenic policy intervention, which hampers our understanding of long-term trends and the implementation of targeted emission reduction efforts. This study investigates the spatiotemporal variations of CH4-rice over the past two decades, using an integrated method to identify the major drivers and predict future emissions under climate change scenarios and policy perspectives. Results indicate that the CH4-rice emissions in China ranged between 6.21 and 6.57 Tg yr-1 over the past two decades, with a spatial distribution characterized by decreases in the south and increases in the north, associated with economic development, dietary shifts, technological advancements, and climate change. Factors such as the rate of straw added (RSA), fertilization, soil texture, temperature, and precipitation significantly influence CH4 emissions per unit rice production (CH4-urp), with RSA identified as the most significant tillage management factor, explaining 32 % of the variance. Lowering RSA to 8 % is beneficial for reducing CH4-urp. Scenario analysis indicates that under policies focusing on production or demand, CH4-rice is expected to increase by 0.3 % to 5.6 %, while adjusting RSA can reduce CH4-rice by 9.4 % to 10.0 %. Structural adjustments and regional cooperation serve as beneficial starting points for controlling and reducing CH4-rice in China, while optimizing industrial layouts contributes to regional development and CH4-rice control. Implementing policies related to maintaining field and crop yields can achieve a balance between rice supply and demand ahead of schedule. Dynamic adjustment of rice cultivation based on supply-demand balance can effectively reduce CH4-rice from excess rice production. By 2060, the reduction effect could reach 8.95 %-12.01 %. Introducing policy-driven tillage management measures as reference indicators facilitates the reduction of CH4-rice.
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Affiliation(s)
- Nanchi Shen
- School of Environmental and Chemical Engineering, Shanghai University, 200444 Shanghai, China
| | - Jiani Tan
- School of Environmental and Chemical Engineering, Shanghai University, 200444 Shanghai, China
| | - Wenjin Wang
- School of Environmental and Chemical Engineering, Shanghai University, 200444 Shanghai, China
| | - Wenbo Xue
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, 100012 Beijing, China
| | - Yangjun Wang
- School of Environmental and Chemical Engineering, Shanghai University, 200444 Shanghai, China
| | - Ling Huang
- School of Environmental and Chemical Engineering, Shanghai University, 200444 Shanghai, China
| | - Gang Yan
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, 100012 Beijing, China
| | - Yu Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, 100871 Beijing, China
| | - Li Li
- School of Environmental and Chemical Engineering, Shanghai University, 200444 Shanghai, China.
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5
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Sun Y, Jiang Y, Xing J, Ou Y, Wang S, Loughlin DH, Yu S, Ren L, Li S, Dong Z, Zheng H, Zhao B, Ding D, Zhang F, Zhang H, Song Q, Liu K, Klimont Z, Woo JH, Lu X, Li S, Hao J. Air Quality, Health, and Equity Benefits of Carbon Neutrality and Clean Air Pathways in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024. [PMID: 39133145 DOI: 10.1021/acs.est.3c10076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
In the pursuit of carbon neutrality, China's 2060 targets have been largely anchored in reducing greenhouse gas emissions, with less emphasis on the consequential benefits for air quality and public health. This study pivots to this critical nexus, exploring how China's carbon neutrality aligns with the World Health Organization's air quality guidelines (WHO AQG) regarding fine particulate matter (PM2.5) exposure. Coupling a technology-rich integrated assessment model, an emission-concentration response surface model, and exposure and health assessment, we find that decarbonization reduces sulfur dioxide (SO2), nitrogen oxides (NOx), and PM2.5 emissions by more than 90%; reduces nonmethane volatile organic compounds (NMVOCs) by more than 50%; and simultaneously reduces the disparities across regions. Critically, our analysis reveals that further targeted reductions in air pollutants, notably NH3 and non-energy-related NMVOCs, could bring most Chinese cities into attainment of WHO AQG for PM2.5 5 to 10 years earlier than the pathway focused solely on carbon neutrality. Thus, the integration of air pollution control measures into carbon neutrality strategies will present a significant opportunity for China to attain health and environmental equality.
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Affiliation(s)
- Yisheng Sun
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Yueqi Jiang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Jia Xing
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Yang Ou
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, P. R. China
- Institute of Carbon Neutrality, Peking University, Beijing 100871, P. R. China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Daniel H Loughlin
- U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States
| | - Sha Yu
- Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, Maryland 20740, United States
- Center for Global Sustainability, University of Maryland, College Park , Maryland 20742, United States
| | - Lu Ren
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Shengyue Li
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Zhaoxin Dong
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Haotian Zheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Bin Zhao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Dian Ding
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Fenfen Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Haowen Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Qian Song
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Kaiyun Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Zbigniew Klimont
- International Institute for Applied Systems Analysis (IIASA), Laxenburg 2361, Austria
| | - Jung-Hun Woo
- Department of Civil and Environmental Engineering, Konkuk University, Seoul 05029, Republic of Korea
| | - Xi Lu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
| | - Siwei Li
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, P. R. China
| | - Jiming Hao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, P. R. China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, P. R. China
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Liu R, Fang YR, Peng S, Benani N, Wu X, Chen Y, Wang T, Chai Q, Yang P. Study on factors influencing carbon dioxide emissions and carbon peak heterogenous pathways in Chinese provinces. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 365:121667. [PMID: 38959776 DOI: 10.1016/j.jenvman.2024.121667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 06/15/2024] [Accepted: 06/30/2024] [Indexed: 07/05/2024]
Abstract
Implementing a Carbon Peak Action Plan at the regional level requires comprehensive consideration of the developmental heterogeneity among different provinces, which is an effective pathway for China to realize the goal of carbon peak by 2030. However, there is currently no clear provincial roadmap for carbon peak, and existing studies on carbon peak pathways inadequately address provincial heterogeneity. Therefore, this paper employs the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model to decompose assess 8 factors influencing carbon emissions of 30 provinces. According to scenario analysis, the paper explores the differentiated pathways for provincial carbon peaks based on policy expectation indicators (including population, economy, and urbanization rate) and comprises policy control indicators (including the energy structure, energy efficiency, industrial structure, transportation structure, and innovation input). The results indicate that population, per capita GDP, urbanization rate, and innovation input are the primary factors for influencing (negatively) the growth of carbon emissions. In contrast, the optimization and upgrading of the industrial structure, energy intensity, energy structure, and transportation structure have mitigating effects on carbon emissions, especially for the first two factors. The forecasting results reveal that robust regulations of the energy and industry can effectively accelerate carbon peak at a reduced magnitude. If developed at BAU, China cannot achieve carbon peak by 2030, continuing an upward trend. However, by maximizing the adjustment strength of energy and industrial transformation within the scope of provincial capabilities, China could achieve carbon peak as early as 2025, with a peak of 12.069 billion tons. In this scenario, 24 provinces could achieve carbon peak before 2030. Overall, this study suggests the feasibility of differentiated pathway to achieve carbon peaks in China, exploring the carbon peak potential and paths of 30 provinces, and identifying provinces where carbon peak is more challenging. It also provides a reference for the design of carbon peak roadmaps at both provincial and national levels and offers targeted recommendations for the implementation of differentiated policy strategies for the government.
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Affiliation(s)
- Runpu Liu
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Yan Ru Fang
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Shuan Peng
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; School of Environmental Science & Engineering, Tianjin University, Tianjin, 300350, China
| | - Nihed Benani
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China; School of Environmental Science & Engineering, Tianjin University, Tianjin, 300350, China
| | - Xuefang Wu
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Yushuo Chen
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Tao Wang
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Qimin Chai
- National Center for Climate Change Strategy and International Cooperation, Beijing, 100035, China
| | - Pingjian Yang
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
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7
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Hou L, Yang J, Ji C, Liu M, Fang W, Ma Z, Bi J. Water Scarcity Assessment of Hydropower Plants in China under Climate Change, Sectoral Competition, and Energy Expansion. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:10536-10547. [PMID: 38833510 DOI: 10.1021/acs.est.4c00671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
Hydropower plays a pivotal role in low-carbon electricity generation, yet many projects are situated in regions facing heightened water scarcity risks. This research devised a plant-level Hydropower Water Scarcity Index (HWSI), derived from the ratio of water demand for electricity generation to basin-scale available runoff water. We assessed the water scarcity of 1736 hydropower plants in China for the baseline year 2018 and projected into the future from 2025 to 2060. The results indicate a notable increase in hydropower generation facing moderate to severe water scarcity (HWSI >0.05), rising from 10% in 2018 to 24-34% of the national total (430-630 TWh), with a projected peak in the 2030s-2040s under the most pessimistic scenarios. Hotspots of risk are situated in the southwest and northern regions, primarily driven by decreased river basin runoff and intensified sectoral water use, rather than by hydropower demand expansion. Comparative analysis of four adaptation strategies revealed that sectoral water savings and enhancing power generation efficiency are the most effective, potentially mitigating a high of 16% of hydropower risks in China. This study provides insights for formulating region-specific adaptation strategies and assessing energy-water security in the face of evolving environmental and societal challenges.
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Affiliation(s)
- Linze Hou
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Jianxun Yang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Chenyi Ji
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Miaomiao Liu
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Wen Fang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Zongwei Ma
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Jun Bi
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
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8
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Falchetta G, De Cian E, Sue Wing I, Carr D. Global projections of heat exposure of older adults. Nat Commun 2024; 15:3678. [PMID: 38744815 PMCID: PMC11094092 DOI: 10.1038/s41467-024-47197-5] [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: 04/25/2023] [Accepted: 03/24/2024] [Indexed: 05/16/2024] Open
Abstract
The global population is aging at the same time as heat exposures are increasing due to climate change. Age structure, and its biological and socio-economic drivers, determine populations' vulnerability to high temperatures. Here we combine age-stratified demographic projections with downscaled temperature projections to mid-century and find that chronic exposure to heat doubles across all warming scenarios. Moreover, >23% of the global population aged 69+ will inhabit climates whose 95th percentile of daily maximum temperature exceeds the critical threshold of 37.5 °C, compared with 14% today, exposing an additional 177-246 million older adults to dangerous acute heat. Effects are most severe in Asia and Africa, which also have the lowest adaptive capacity. Our results facilitate regional heat risk assessments and inform public health decision-making.
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Affiliation(s)
- Giacomo Falchetta
- CMCC Foundation - Euro-Mediterranean Center on Climate Change, Venice, Italy.
- RFF-CMCC European Institute on Economics and the Environment, Venice, Italy.
- International Institute for Applied Systems Analysis, Laxenburg, Austria.
| | - Enrica De Cian
- CMCC Foundation - Euro-Mediterranean Center on Climate Change, Venice, Italy
- RFF-CMCC European Institute on Economics and the Environment, Venice, Italy
- Department of Economics, Ca' Foscari University, Venice, Italy
| | - Ian Sue Wing
- Department of Earth & Environment, Boston University, Boston, MA, 02215, USA
| | - Deborah Carr
- Department of Sociology, Boston University, Boston, MA, 02215, USA
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Shi T, Peng Y, Ma X, Han G, Zhang H, Pei Z, Li S, Mao H, Zhang X, Gong W. China's "coal-to-gas" policy had large impact on PM 1.0 distribution during 2016-2019. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 359:121071. [PMID: 38718608 DOI: 10.1016/j.jenvman.2024.121071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 03/24/2024] [Accepted: 04/30/2024] [Indexed: 05/22/2024]
Abstract
Particulate matter with an aerodynamic diameter of less than 1 μm (PM1.0) can be extremely hazardous to human health, so it is imperative to accurately estimate the spatial and temporal distribution of PM1.0 and analyze the impact of related policies on it. In this study, a stacking generalization model was trained based on aerosol optical depth (AOD) data from satellite observations, combined with related data affecting aerosol concentration such as meteorological data and geographic data. Using this model, the PM1.0 concentration distribution in China during 2016-2019 was estimated, and verified by comparison with ground-based stations. The coefficient of determination (R2) of the model is 0.94, and the root-mean-square error (RMSE) is 8.49 μg/m3, mean absolute error (MAE) is 4.10 μg/m3, proving that the model has a very high performance. Based on the model, this study analyzed the PM1.0 concentration changes during the heating period (November and December) in the regions where the "coal-to-gas" policy was implemented in China, and found that the proposed "coal-to-gas" policy did reduce the PM1.0 concentration in the implemented regions. However, the lack of natural gas due to the unreasonable deployment of the policy in the early stage caused the increase of PM1.0 concentration. This study can provide a reference for the next step of urban air pollution policy development.
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Affiliation(s)
- Tianqi Shi
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91198 Gif-sur-Yvette, France; Electronic Information School, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Yanran Peng
- Electronic Information School, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Xin Ma
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China.
| | - Ge Han
- School of Remote Sensing and Information Engineering, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Haowei Zhang
- Electronic Information School, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Zhipeng Pei
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Siwei Li
- School of Remote Sensing and Information Engineering, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
| | - Huiqin Mao
- Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment, Beijing, China
| | - Xingying Zhang
- Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites (LRCVES/CMA), National Satellite Meteorological Center, China Meteorological Administration (NSMC/CMA), Beijing, 100081, China
| | - Wei Gong
- Electronic Information School, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Luoyu Road No.129, Wuhan, 430079, China
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10
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Yin P, He C, Chen R, Huang J, Luo Y, Gao X, Xu Y, Ji JS, Cai W, Wei Y, Li H, Zhou M, Kan H. Projection of Mortality Burden Attributable to Nonoptimum Temperature with High Spatial Resolution in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:6226-6235. [PMID: 38557021 DOI: 10.1021/acs.est.3c09162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The updated climate models provide projections at a fine scale, allowing us to estimate health risks due to future warming after accounting for spatial heterogeneity. Here, we utilized an ensemble of high-resolution (25 km) climate simulations and nationwide mortality data from 306 Chinese cities to estimate death anomalies attributable to future warming. Historical estimation (1986-2014) reveals that about 15.5% [95% empirical confidence interval (eCI):13.1%, 17.6%] of deaths are attributable to nonoptimal temperature, of which heat and cold corresponded to attributable fractions of 4.1% (eCI:2.4%, 5.5%) and 11.4% (eCI:10.7%, 12.1%), respectively. Under three climate scenarios (SSP126, SSP245, and SSP585), the national average temperature was projected to increase by 1.45, 2.57, and 4.98 °C by the 2090s, respectively. The corresponding mortality fractions attributable to heat would be 6.5% (eCI:5.2%, 7.7%), 7.9% (eCI:6.3%, 9.4%), and 11.4% (eCI:9.2%, 13.3%). More than half of the attributable deaths due to future warming would occur in north China and cardiovascular mortality would increase more drastically than respiratory mortality. Our study shows that the increased heat-attributable mortality burden would outweigh the decreased cold-attributable burden even under a moderate climate change scenario across China. The results are helpful for national or local policymakers to better address the challenges of future warming.
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Affiliation(s)
- Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Cheng He
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200082, China
- Institute of Epidemiology, Helmholtz Zentrum München─German Research Center for Environmental Health (GmbH), Neuherberg 85764, Germany
| | - Renjie Chen
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200082, China
| | - Jianbin Huang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Yong Luo
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Xuejie Gao
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100017, China
| | - Ying Xu
- National Climate Center, China Meteorological Administration, Beijing 100044, China
| | - John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China
| | - Wenjia Cai
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Yongjie Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Huichu Li
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Haidong Kan
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai 200082, China
- National Center for Children's Health, Children's Hospital of Fudan University, Shanghai 200032, China
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11
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Ji P, Chen J, Chen R, Liu J, Yu C, Chen F. Nitrogen and phosphorus trends in lake sediments of China may diverge. Nat Commun 2024; 15:2644. [PMID: 38531852 DOI: 10.1038/s41467-024-46968-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 03/15/2024] [Indexed: 03/28/2024] Open
Abstract
The brief history of monitoring nutrient levels in Chinese lake waters limits our understanding of the causes and the long-term trends of their eutrophication and constrains effective lake management. We therefore synthesize nutrient data from lakes in China to reveal the historical changes and project their future trends to 2100 using models. Here we show that the average concentrations of nitrogen and phosphorus in lake sediments have increased by 267% and 202%, respectively since 1850. In the model projections, 2030-2100, the nitrogen concentrations in the studied lakes in China may decrease, for example, by 87% in the southern districts and by 19% in the northern districts. However, the phosphorus concentrations will continue to increase by an average of 25% in the Eastern Plain, Yunnan-Guizhou Plateau, and Xinjiang. Based on this differentiation, we suggest that nitrogen and phosphorus management in Chinese lakes should be carried out at the district level to help develop rational and sustainable environmental management strategies.
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Affiliation(s)
- Panpan Ji
- MOE Key Laboratory of Western China's Environmental System, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Jianhui Chen
- MOE Key Laboratory of Western China's Environmental System, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
| | - Ruijin Chen
- MOE Key Laboratory of Western China's Environmental System, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Jianbao Liu
- ALPHA, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Chaoqing Yu
- College of Ecology and Environment, Hainan University, Haikou, 570228, China
| | - Fahu Chen
- MOE Key Laboratory of Western China's Environmental System, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
- ALPHA, State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
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12
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Xu H, Hou X, Pan S, Bray M, Wang C. Socioeconomic impacts from coastal flooding in the 21st century China's coastal zone: A coupling analysis between coastal flood risk and socioeconomic development. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170187. [PMID: 38278224 DOI: 10.1016/j.scitotenv.2024.170187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/09/2024] [Accepted: 01/13/2024] [Indexed: 01/28/2024]
Abstract
Coastal flooding due to sea level rise significantly affects socioeconomic development. The dynamic nature of coastal flood risk (CFR) and socioeconomic development level (SDL) leads to uncertainties in understanding their future interplay. This ambiguity challenges coastal nations in devising effective flood adaptation and coastal management strategies. This study quantitatively examines the expected GDP affected (EGA) and population affected (EPA) by coastal flooding in China's coastal zone (CCZ) from 2030 to 2100 under various climate scenarios (RCP2.6-SSP1, RCP4.5-SSP2, and RCP8.5-SSP5). The future SDL in CCZ is assessed using a method combining the analytic hierarchy process with entropy weight. The future CFR-SDL dynamic relationship is analyzed using the coupling coordination degree (CCD) model. The results reveal that in CCZ under the RCP2.6-SSP1, RCP4.5-SSP2, and RCP8.5-SSP5 scenarios: by 2100, the EGA and EPA will reach $814.90 billion & 6.17 million people, $828.16 billion & 7.63 million people, and $1568.83 billion & 8.05 million people, respectively, where the coastal cities in Jiangsu and Guangdong provinces will face more obvious risks of socioeconomic losses; The total area in the CCZ at "Very high" and "High" level of socioeconomic development by 2100 is projected to reach 11.33 × 103 km2, 12.86 × 103 km2, and 15.82 × 103 km2, respectively, with the Pearl River Delta, Yangtze River Delta, and Tianjin-Hebei remaining pivotal for CCZ's socioeconomic growth. Cities such as Lianyungang, Jiaxing, Shenzhen, Dongguan, and Foshan show notable CCD characteristics, and addressing the trade-off between SDL and CFR is crucial in achieving sustainable development. This study highlights the potential socioeconomic impacts of coastal flooding and emphasizes the importance of considering the interrelationship between CFR and SDL when developing coastal flood adaptation policies.
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Affiliation(s)
- He Xu
- Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, Shandong, PR China; University of Chinese Academy of Sciences, Beijing, PR China; Hydro-environmental Research Centre, School of Engineering, Cardiff University, Cardiff, United Kingdom
| | - Xiyong Hou
- Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, Shandong, PR China.
| | - Shunqi Pan
- Hydro-environmental Research Centre, School of Engineering, Cardiff University, Cardiff, United Kingdom
| | - Michaela Bray
- Hydro-environmental Research Centre, School of Engineering, Cardiff University, Cardiff, United Kingdom
| | - Chengxin Wang
- College of Geography and Environment, Shandong Normal University, Jinan, PR China
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13
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Zhang S, Xiong K, Min X, Zhang S. Demographic shrinkage promotes ecosystem services supply capacity in the karst desertification control. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170427. [PMID: 38281637 DOI: 10.1016/j.scitotenv.2024.170427] [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: 11/04/2023] [Revised: 01/22/2024] [Accepted: 01/23/2024] [Indexed: 01/30/2024]
Abstract
Although ecological services have been improved in karst desertification control areas, it is still unclear how population shrinkage affects ecosystem service supply capability through ecological assets. In this study, Theil-Sen median, regression analysis, and variance partitioning were applied to explore the linkages of population change (observed data and shared socioeconomic pathways 1-representative concentration pathways 2.6), ecological asset composition (land use), quality (Normalized difference vegetation index [NDVI] and tree height), and ecosystem services in different periods (population growth and decline periods). The results showed that the population change during the growth period (2000-2038) was dominated by migration patterns. In degraded ecoregions (karst desertification) dominated by population out-migration, the net expansion of forest was 15.88 % during 2000-2020, NDVI and tree height increased by 0.57 % and 54.96 %, and ecosystem service supply capability increased by 2.68 %. In contrast, in non-degraded ecoregions (non-karst and karst non-desertification) with population in-migration, change rates of forest (-5.40 % and - 23.68 %), NDVI (0.49 % and 0.53 %), tree height (-8.35 % and - 31.25 %), and ecosystem service supply capability (2.04 % and 2.18 %) were apparently lower than degraded ecoregions. During the population decline period (2039-2100), although the migration pattern between two regions during the growth period was replaced by a population drop within a single region, the positive correlation between population shrinkage with ecological assets and service supply capability was still followed. Overall, the study found that both ways of population shrinkage that involve out-migration and decline can alleviate the land pressure of degraded ecoregions, which enhances ecosystem service supply capability by regulating ecological assets.
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Affiliation(s)
- Shihao Zhang
- School of Karst Science, Guizhou Normal University/State Engineering Technology Institute for Karst Desertification Control, Guiyang 550001, People's Republic of China
| | - Kangning Xiong
- School of Karst Science, Guizhou Normal University/State Engineering Technology Institute for Karst Desertification Control, Guiyang 550001, People's Republic of China.
| | - Xiaoying Min
- School of Karst Science, Guizhou Normal University/State Engineering Technology Institute for Karst Desertification Control, Guiyang 550001, People's Republic of China
| | - Song Zhang
- School of Karst Science, Guizhou Normal University/State Engineering Technology Institute for Karst Desertification Control, Guiyang 550001, People's Republic of China
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14
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Sun X, Mi Z, Du H, Coffman D. Impacts of poverty eradication on carbon neutrality in China. Sci Bull (Beijing) 2024; 69:648-660. [PMID: 38218632 DOI: 10.1016/j.scib.2023.12.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 11/29/2023] [Accepted: 12/07/2023] [Indexed: 01/15/2024]
Abstract
China is facing challenges to tackle the threat of climate change while reducing social inequality. Poverty eradication requires improvement in the living conditions of low-income households, which leads in turn to higher carbon footprints and may undermine the efforts of climate change mitigation. Previous studies have assessed the climate impacts of poverty eradication, but few have quantified how the additional carbon emissions of poverty eradication are shared at the subnational level in China and the impact on China's climate targets. We investigated the recent trend of carbon footprint inequality in China's provinces and estimated the climate burden of different poverty reduction schemes, measured by increased carbon emissions. The results indicate that poverty eradication will not impede the achievement of national climate targets, with an average annual household carbon footprint increase of 0.1%-1.2%. However, the carbon emissions growth in less developed provinces can be 4.0%, five times that in wealthy regions. Less developed regions suffer a greater climate burden because of poverty eradication, which may offset carbon reduction efforts. Therefore, interregional collaboration is needed to coordinate inequality reduction with investments in low-carbon trajectories in all provinces.
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Affiliation(s)
- Xinlu Sun
- The Bartlett School of Sustainable Construction, University College London, London WC1E 7HB, UK
| | - Zhifu Mi
- The Bartlett School of Sustainable Construction, University College London, London WC1E 7HB, UK.
| | - Huibin Du
- College of Management and Economics, Tianjin University, Tianjin 300072, China; National Industry-Education Platform of Energy Storage, Tianjin University, Tianjin 300072, China.
| | - D'Maris Coffman
- The Bartlett School of Sustainable Construction, University College London, London WC1E 7HB, UK
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15
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Zhou Z, Ma X, Zhang S, Guo C, Liu X, Zhang L, Xie Y. Equity-based carbon neutral plan induces cross-regional coal leakage and industrial relocation. iScience 2024; 27:109079. [PMID: 38361631 PMCID: PMC10867442 DOI: 10.1016/j.isci.2024.109079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 01/03/2024] [Accepted: 01/26/2024] [Indexed: 02/17/2024] Open
Abstract
China as a major coal-consuming economy faces the challenge of balancing economic development and carbon neutrality goal. This paper incorporates both efficiency-based and equity-based carbon neutrality policies into a numerical model to quantitatively assess how coal reduction under various carbon-neutral policies affects energy mix, economic growth, and industrial structures by 2060. Results show the nationwide coal intensity will ultimately plunge by over 95% from 2017 to 2060, mainly attributed to the coal-phasing-out in most industries. National Gross Domestic Product losses reaches 4,951 billion USD in efficiency-based scenarios by 2060, and the economic losses are even more severe in less developed provinces, especially provinces in Northern China. Although the equity-based policy can reduce the economic burden for the Northern China, the equity-based policy is accompanied by a significant regional shift in coal across the country: eastern coal-intense industries will be relocated northward, leading to increases in embodied coal consumption.
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Affiliation(s)
- Ziqiao Zhou
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xiaotian Ma
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Silu Zhang
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Chaoyi Guo
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xiaorui Liu
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
- China Electric Power Research Institute, Beijing 100192, China
| | - Lin Zhang
- School of Energy and Environment, City University of Hong Kong, Kowloon Tong, Hong Kong SAR
- Center for Ocean Research in Hong Kong and Macau, Hong Kong, Hong Kong SAR
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing 100191, China
- Laboratory for Low-carbon Intelligent Governance, Beihang University, Beijing 100191, China
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16
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Li S, Cao Y, Liu J, Wang S. Simulating land use change for sustainable land management in China's coal resource-based cities under different scenarios. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 916:170126. [PMID: 38237789 DOI: 10.1016/j.scitotenv.2024.170126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 01/25/2024]
Abstract
Land use competition among economic development, food security and ecological protection posed challenges for the sustainable development in resource-based cities, especially those represented by coal resource-based cities in China. Predicting future land use change under the coupled framework of shared socioeconomic pathways and representative concentration pathways (SSP-RCPs) was a crucial step in devising sustainable development strategies. In this study, the patch-generated land use simulation (PLUS) model coupled with SSP-RCP scenarios (SSP126, SSP245, SSP585) was used to predict land use changes from year 2020 to 2060, identify key management regions for balancing the goals of ecological protection and food security, and propose corresponding measures. The results showed that, (1) the selected driving factors and model parameters effectively simulated land use changes with an Overall accuracy of 0.95, a Kappa coefficient of 0.92, a Figure of Merit of 0.16, an Exchange error ≤5.69 %, a Shift error ≤1.04 %, and a Quantity error ≤0.67 %. (2) All the scenarios, it was observed that the grassland continued to decrease by 0.86 % to 7.34 %, and the forest and built-up land continued to increase, of which forest increased by 2.34 % to 4.03 %, and built-up land increased by 21.02 % to 61.08 %. Cropland only increased in SSP585 scenario, by 4.76 %, but declining by 2.93 % in SSP126 and SSP245 scenario. (3) In future scenarios, the expansion of built-up land has escalated the risk of cropland and grassland loss. Based on the distribution of key land use conversions, four categories of prioritized land management regions and corresponding measures have been proposed. This provided a potential pathway to mitigate risks associated with the protection of cropland and ecological land. Therefore, this study was instrumental in understanding the mechanisms of land use changes in coal resource-based cities, and provided a reference for land use planning.
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Affiliation(s)
- Shengpeng Li
- School of Land Science and Technology, China University of Geosciences Beijing, Beijing 100083, China
| | - Yingui Cao
- School of Land Science and Technology, China University of Geosciences Beijing, Beijing 100083, China; Key Lab of Land Consolidation, Ministry of Natural Resources of the People's Republic of China, Beijing 100035, China.
| | - Jianling Liu
- College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China
| | - Shufei Wang
- School of Land Science and Technology, China University of Geosciences Beijing, Beijing 100083, China
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17
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Ban J, Cheng J, Zhang C, Lu K, Zhou Z, Liu Z, Chen Y, Wang C, Cai W, Gong P, Luo Y, Tong D, Hu J, Guo X, Hao J, Li T. China's carbon-neutral policies will reduce short-term PM 2.5-associated excess incidence of cardiovascular diseases. ONE EARTH (CAMBRIDGE, MASS.) 2024; 7:497-505. [PMID: 38532982 PMCID: PMC10962059 DOI: 10.1016/j.oneear.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/31/2023] [Accepted: 01/08/2024] [Indexed: 03/28/2024]
Abstract
China's carbon-neutral target could have benefits for ambient fine particulate matter (PM2.5)-associated mortality. Although previous studies have researched such benefits, the potential impact on cardiovascular disease incidence burden is yet to be investigated thoroughly. Here, we first estimate the association between short-term PM2.5 exposure and the incidence of stroke and coronary heart disease (CHD) via a case-crossover study before projecting future changes in short-term PM2.5-associated excess incidence across China from 2025 to 2060 under three different emission scenarios. We find that, compared to the 2015-2020 baseline, average PM2.5 concentrations nationwide in 2060 under SSP119 (an approximation of a carbon-neutral scenario) are projected to decrease by 81.07%. The short-term PM2.5-related excess incidence of stroke and CHD is projected to be reduced to 3,352 cases (95% confidence interval: 939, 5,738)-compared with 34,485 cases under a medium-emissions scenario (SSP245)-and is expected to be accompanied by a 95% reduction in the related economic burden. China's carbon-neutral policies are likely to bring health benefits for cardiovascular disease by reducing short-term PM2.5-related incidence burden.
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Affiliation(s)
- Jie Ban
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, 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
| | - Jing Cheng
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Can Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Kailai Lu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Zhen Zhou
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Zhao Liu
- School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing 100024, China
| | - Yidan Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
| | - Wenjia Cai
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Peng Gong
- Department of Earth Sciences and Geography, University of Hong Kong, Hong Kong Special Administrative Region 999077, China
| | - Yong Luo
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Dan Tong
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Jianlin Hu
- 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
| | - Xinbiao Guo
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, No. 38 Xueyuan Road, Beijing 100191, China
| | - Junwei Hao
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, No. 45 Changchun Street, Xicheng District, Beijing 100053, China
- Key Laboratory for Neurodegenerative Diseases of Ministry of Education, No. 45 Changchun Street, Xicheng District, Beijing 100053, China
- Beijing Municipal Geriatric Medical Research Center, No. 45 Changchun Street, Xicheng District, Beijing 100053, China
| | - Tiantian Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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18
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Zhang Z, Sun L, Deng C, Dong L, Xu R, Nie C, Yang Q. A new perspective on anthropogenic nitrogen loss mitigation strategies: Integrated control via sustainable regional integration. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 916:170188. [PMID: 38244631 DOI: 10.1016/j.scitotenv.2024.170188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 01/09/2024] [Accepted: 01/13/2024] [Indexed: 01/22/2024]
Abstract
Unregulated regional integrated development disrupts the reactive nitrogen (Nr) cycle, adding complexity to anthropogenic Nr environmental losses. The objective of this study was to establish a framework for mitigating anthropogenic Nr loss through a new regional integration perspective by analyzing anthropogenic Nr loss and integrated control strategies in the Yangtze River Delta (YRD) region from 2011 to 2020. The results revealed that the total Nr loss in the YRD ranged from 1780.7 to 1972.0 Gg N yr-1. Re-linking cropland and livestock is crucial for reducing Nr loss, as they act as the main sources of Nr loss. Spatial analysis at the regional scale revealed that regional integration has led to a dispersion of Nr loss, while uneven development among cities has resulted in a westward shift of 8.6 km in the Nr loss centroid, suggesting the need for the implementation of collaborative governance and integrated environmental regulation in the YRD. At the city scale, 27 cities were clustered into six types based on the similarity of Nr loss structural characteristics, allowing for the development of targeted reduction policies based on the specific Nr structural characteristics of each city. The results of driver and mitigation potential analysis indicated the feasibility of achieving the shared goal of sustainable regional integration and the application of optimal mitigation strategies in different cities and the YRD. Overall, the new-perspective framework established in this study provides valuable references for sustainable Nr management in the context of regional integration.
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Affiliation(s)
- Zeqian Zhang
- State key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Lihui Sun
- State key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Chenning Deng
- State key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Li Dong
- State key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Rui Xu
- State key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Chong Nie
- State key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Queping Yang
- State key Laboratory of Environment Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
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19
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Feng H, Schyns JF, Krol MS, Yang M, Su H, Liu Y, Lv Y, Zhang X, Yang K, Che Y. Water pollution scenarios and response options for China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 914:169807. [PMID: 38211873 DOI: 10.1016/j.scitotenv.2023.169807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/11/2023] [Accepted: 12/29/2023] [Indexed: 01/13/2024]
Abstract
China has formulated several policies to alleviate the water pollution load, but few studies have quantitatively analyzed their impacts on future water pollution loads in China. Based on grey water footprint (GWF) assessment and scenario simulation, we analyze the water pollution (including COD, NH3-N, TN and TP) in China from 2021 to 2035 under different scenarios for three areas: consumption-side, production-side and terminal treatment. We find that under the current policy scenario, the GWF of COD, NH3-N, TN, and TP in China could be reduced by 15.0 % to 39.9 %; the most effective measures for GWF reduction are diet structure change (in the consumption-side area), and the wastewater treatment rate and livestock manure utilization improvement (in the terminal treatment area). However, the GWF will still increase in 8 provinces, indicating that the current implemented policy is not universally effective in reducing GWF across all provinces. Under the technical improvement scenario, the GWF of the four pollutants will decrease by 54.9 %-71.1 % via improvements in the current measures related to current policies and new measures in the production-side area and the terminal treatment area; thus, GWF reduction is possible in all 31 provinces. However, some policies face significant challenges in achieving full implementation, and certain policies are only applicable to a subset of provinces. Our detailed analysis of future water pollution scenarios and response options to reduce pollution loads can help to inform the protection of freshwater resources in China and quantitatively assess the effectiveness of policies in other fields.
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Affiliation(s)
- Haoyuan Feng
- Multidisciplinary Water Management, Faculty of Engineering Technology, University of Twente, 7522 NB Enschede, the Netherlands; Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, 200241 Shanghai, China; College of Geography and Environmental Sciences, Northwest Normal University, 730070 Lanzhou, China.
| | - Joep F Schyns
- Multidisciplinary Water Management, Faculty of Engineering Technology, University of Twente, 7522 NB Enschede, the Netherlands
| | - Maarten S Krol
- Multidisciplinary Water Management, Faculty of Engineering Technology, University of Twente, 7522 NB Enschede, the Netherlands
| | - Mengjie Yang
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, 200241 Shanghai, China
| | - Han Su
- Multidisciplinary Water Management, Faculty of Engineering Technology, University of Twente, 7522 NB Enschede, the Netherlands
| | - Yaoyi Liu
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, 200241 Shanghai, China
| | - Yongpeng Lv
- Shanghai Municipal Engineering Design Institute (Group) CO., LTD, 200092 Shanghai, China
| | - Xuebin Zhang
- College of Geography and Environmental Sciences, Northwest Normal University, 730070 Lanzhou, China
| | - Kai Yang
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, 200241 Shanghai, China; Shanghai Institute of Pollution Control and Ecological Security, 200092 Shanghai, China
| | - Yue Che
- Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, School of Ecological and Environmental Sciences, East China Normal University, 200241 Shanghai, China.
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20
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Dong D, Tao H, Zhang Z. Projected population exposure to heatwaves in Xinjiang Uygur autonomous region, China. Sci Rep 2024; 14:4570. [PMID: 38403647 PMCID: PMC10894881 DOI: 10.1038/s41598-024-54885-1] [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: 11/20/2023] [Accepted: 02/17/2024] [Indexed: 02/27/2024] Open
Abstract
The intensification of heatwaves dues to climate change is a significant concern, with substantial impacts on ecosystems and human health, particularly in developing countries. This study utilizes NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) and projected population data accounting for China's population policies to project changes in various grades of heatwaves (light, moderate, and severe) and the population exposure to heatwaves (PEH) in Xinjiang under three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results show that the number of days and intensity of heatwaves in Xinjiang are projected to increase. Heatwaves occurring in Xinjiang will predominantly be severe heatwaves (SHW) in the long-term under the SSP5-8.5 scenario, and the number of SHW days projected to increase by 62 ± 18.4 days compared to the reference period. Changes in heatwaves are anticipated to influence PEH, estimating population exposure to light, moderate, and severe heatwaves (LPEH, MPEH, and SPEH) at 534.6 ± 64 million, 496.2 ± 43.5 million, and 1602.4 ± 562.5 million person-days, respectively, in the long-term under the SSP5-8.5 scenario. The spatial distribution of PEH is projected to be consistent with that of the reference period, with high values persisting in Urumqi, Kashgar and Hotan. Changes in PEH are primarily driven by climate effects, followed by interactive effects, while population effects contribute the least. Therefore, mitigating climate change is crucial to reduce the PEH in Xinjiang.
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Affiliation(s)
- Diwen Dong
- College of Ecology and Environment, Xinjiang University, Urumqi, 830017, China
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China
- Institute of Statistics and Data Science, Xinjiang University of Finance & Economics, Urumqi, 830012, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hui Tao
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China.
| | - Zengxin Zhang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China
- Joint Innovation Center for Modern Forestry Studies, College of Forestry, Nanjing Forestry University, Nanjing, 210037, China
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21
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Deng P, Zhou Q, Luo J, Hu X, Yu F. Urbanization influences dissolved organic matter characteristics but microbes affect greenhouse gas concentrations in lakes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169191. [PMID: 38092202 DOI: 10.1016/j.scitotenv.2023.169191] [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: 08/31/2023] [Revised: 12/03/2023] [Accepted: 12/06/2023] [Indexed: 01/18/2024]
Abstract
Recognition and prediction of dissolved organic matter (DOM) properties and greenhouse gas (GHG) emissions is critical to understanding climate change and the fate of carbon in aquatic ecosystems, but related data is challenging to interpret due to covariance in multiple natural and anthropogenic variables with high spatial and temporal heterogeneity. Here, machine learning modeling combined with environmental analysis reveals that urbanization (e.g., population density and artificial surfaces) rather than geography determines DOM composition and properties in lakes. The structure of the bacterial community is the dominant factor determining GHG emissions from lakes. Urbanization increases DOM bioavailability and decreases the DOM degradation index (Ideg), increasing the potential for DOM conversion into inorganic carbon in lakes. The traditional fossil fuel-based path (SSP5) scenario increases carbon emission potential. Land conversion from water bodies into artificial surfaces causes organic carbon burial. It is predicted that increased urbanization will accelerate the carbon cycle in lake ecosystems in the future, which deserves attention in climate models and in the management of global warming.
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Affiliation(s)
- Peng Deng
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Qixing Zhou
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Jiwei Luo
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xiangang Hu
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
| | - Fubo Yu
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
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22
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Liu H, Zhang X, Deng L, Zhao Y, Tao S, Jia H, Xu J, Xia J. A simulation and risk assessment framework for water-energy-environment nexus: A case study in the city cluster along the middle reach of the Yangtze River, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169212. [PMID: 38097084 DOI: 10.1016/j.scitotenv.2023.169212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 11/16/2023] [Accepted: 12/06/2023] [Indexed: 12/17/2023]
Abstract
In the Anthropocene, there is a strong interlinkage among water, energy, and the environment. The water-energy-environment nexus (WEEN) has been vigorously advocated as an emerging development paradigm and a global research agenda. Based on the nexus concept, a framework for the WEEN complex system simulation and risk assessment is developed. The three metropolitan areas of the city cluster along the middle reaches of the Yangtze River (CCMRYR) are taken as the objects. Regional policies are combined with generic shared socio-economic pathways (SSPs) to form a localized SSPs suitable for the research region. The dynamic simulation of the WEEN complex system and the risk analysis are carried out with the combination of system dynamics models and copula functions. Results show that: There are obvious differences in water utilization, energy consumption, air pollutant emissions, and water pollutant emissions among the three metropolitan areas. The issue of high carbon intensity in the Wuhan Metropolitan Coordinating Region needs to be emphasized and solved from the perspective of optimizing the industrial structure. Adhering to current development patterns, there will be successive peaks in water utilization, energy consumption, and carbon emissions in Wuhan, Dongting Lake, and Poyang Lake Metropolitan Coordinating Region by 2030, leading to high synergy risks at the systemic level, with maximum values of 0.84, 0.85, 0.62, respectively. A development path based on conservation priorities indicates that future policymaking needs to prioritize a resource-saving and pollution-control development pattern directed by technological upgrading against the backdrop of scarce natural resource endowments. The localized SSPs are a beneficial extension that enriches the narrative of regional-scale SSPs. The evolutionary trajectories and risk assessments of WEEN complex systems under different localized SSPs provide a sweeping insight into the consequences of policy decisions, thus enabling policymakers to appraise policy rationality and implement appropriate corrective measures.
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Affiliation(s)
- Haoyuan Liu
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; Hubei Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China
| | - Xiang Zhang
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; Hubei Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China.
| | - Liangkun Deng
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; Hubei Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China
| | - Ye Zhao
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; Hubei Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China
| | - Shiyong Tao
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; Hubei Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China
| | - Haifeng Jia
- School of environment, Tsinghua University, Beijing 100084, China
| | - Jing Xu
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; Hubei Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China
| | - Jun Xia
- State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; Hubei Key Laboratory of Water System Science for Sponge City Construction, Wuhan University, Wuhan 430072, China
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23
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Zhao M, Zhu M, Chen Y, Zhang C, Cai W. The uneven impacts of climate change on China's labor productivity and economy. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 351:119707. [PMID: 38043317 DOI: 10.1016/j.jenvman.2023.119707] [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: 10/25/2023] [Revised: 11/14/2023] [Accepted: 11/22/2023] [Indexed: 12/05/2023]
Abstract
Climate change is considered to increase economic costs by worsening heat-related labor productivity loss. While extensive global and national research has been conducted on this topic, few studies have analyzed subnational and individual economic impacts, potentially weakening local governments' motivation to tackle climate change. Figuring out the most affected regions and labors could help climate policymakers to identify priority regions and sectors to allocate adaptation resources efficiently, and enhance stakeholder engagement. This study adopted a provincial Computable General Equilibrium model by distinguishing different labors and regions in modelling work to address the aforementioned gap. The study estimated economic costs at different level under three climate change scenarios (lower (SSP126), middle (SSP245), and higher (SSP585) warming scenario). Low-income regions located in southwest part of China (such as Guangxi and Guizhou), would experience the largest economic loss, 3.4-7.1 times higher than high-income in China by 2100 under SSP245 scenario. Additionally, wages for labors highly sensitive to heat in these regions are expected to rise, for example, by an 8.3% rise in Guangxi, driven by the rising demand for these labors. Conversely, others would experience a significant wage decrease, especially those with less sensitivity (e.g., managers). Therefore, we recommended that national financial supports be allocated more to these most affected regions and that government encourage managers provide assistance to workers vulnerable to heat.
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Affiliation(s)
- Mengzhen Zhao
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
| | - Mengke Zhu
- Department of Earth System Science, Institute for Global Change Studies, Ministry of Education Ecological Field Station for East Asian Migratory Birds, Tsinghua University, Beijing, 100084, China
| | - Yuyou Chen
- School of Economics, Center for Economic Behavior and Decision-making (CEBD), Zhejiang University of Finance and Economics, Hangzhou, 310018, China
| | - Chi Zhang
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China.
| | - Wenjia Cai
- Department of Earth System Science, Institute for Global Change Studies, Ministry of Education Ecological Field Station for East Asian Migratory Birds, Tsinghua University, Beijing, 100084, China.
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24
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Wang Y, Zhang C, Gao J, Chen Z, Liu Z, Huang J, Chen Y, Li Z, Chang N, Tao Y, Tang H, Gao X, Xu Y, Wang C, Li D, Liu X, Pan J, Cai W, Gong P, Luo Y, Liang W, Liu Q, Stenseth NC, Yang R, Xu L. Spatiotemporal trends of hemorrhagic fever with renal syndrome (HFRS) in China under climate variation. Proc Natl Acad Sci U S A 2024; 121:e2312556121. [PMID: 38227655 PMCID: PMC10823223 DOI: 10.1073/pnas.2312556121] [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: 07/23/2023] [Accepted: 12/05/2023] [Indexed: 01/18/2024] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic disease caused by the rodent-transmitted orthohantaviruses (HVs), with China possessing the most cases globally. The virus hosts in China are Apodemus agrarius and Rattus norvegicus, and the disease spread is strongly influenced by global climate dynamics. To assess and predict the spatiotemporal trends of HFRS from 2005 to 2098, we collected historical HFRS data in mainland China (2005-2020), historical and projected climate and population data (2005-2098), and spatial variables including biotic, environmental, topographical, and socioeconomic. Spatiotemporal predictions and mapping were conducted under 27 scenarios incorporating multiple integrated representative concentration pathway models and population scenarios. We identify the type of magistral HVs host species as the best spatial division, including four region categories. Seven extreme climate indices associated with temperature and precipitation have been pinpointed as key factors affecting the trends of HFRS. Our predictions indicate that annual HFRS cases will increase significantly in 62 of 356 cities in mainland China. Rattus regions are predicted to be the most active, surpassing Apodemus and Mixed regions. Eighty cities are identified as at severe risk level for HFRS, each with over 50 reported cases annually, including 22 new cities primarily located in East China and Rattus regions after 2020, while 6 others develop new risk. Our results suggest that the risk of HFRS will remain high through the end of this century, with Rattus norvegicus being the most active host, and that extreme climate indices are significant risk factors. Our findings can inform evidence-based policymaking regarding future risk of HFRS.
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Affiliation(s)
- Yuchen Wang
- Vanke School of Public Health, Tsinghua University, Beijing100084, China
- Institute for Healthy China, Tsinghua University, Beijing100084, China
| | - Chutian Zhang
- Vanke School of Public Health, Tsinghua University, Beijing100084, China
- Institute for Healthy China, Tsinghua University, Beijing100084, China
- College of Natural Resources and Environment, Northwest A&F University, Yangling712100, China
| | - Jing Gao
- Vanke School of Public Health, Tsinghua University, Beijing100084, China
- Institute for Healthy China, Tsinghua University, Beijing100084, China
- Respiratory Medicine Unit, Department of Medicine & Centre for Molecular Medicine, Karolinska Institute, Stockholm171 77, Sweden
- Heart and Lung Centre, Department of Pulmonary Medicine, University of Helsinki and Helsinki University Hospital, Helsinki00290, Finland
| | - Ziqi Chen
- Vanke School of Public Health, Tsinghua University, Beijing100084, China
- Institute for Healthy China, Tsinghua University, Beijing100084, China
| | - Zhao Liu
- School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing100102, China
| | - Jianbin Huang
- Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing101408, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing100190, China
| | - Yidan Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Zhichao Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing100101, China
| | - Nan Chang
- School of Public Health, Nanjing Medical University, Nanjing210000, China
| | - Yuxin Tao
- Center for Statistical Science, Department of Industrial Engineering, Tsinghua University, Beijing100084, China
| | - Hui Tang
- Department of Geosciences, Natural History Museum, University of Oslo, Blindern, Oslo0316, Norway
- Natural History Museum, University of Oslo, Blindern, Oslo0316, Norway
- Department of Geosciences and Geography, University of Helsinki, Helsinki00014, Finland
| | - Xuejie Gao
- Climate Change Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing100029, China
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing100049, China
| | - Ying Xu
- National Climate Centre, China Meteorological Administration, Beijing100081, China
| | - Can Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Dong Li
- Center for Statistical Science, Department of Industrial Engineering, Tsinghua University, Beijing100084, China
| | - Xiaobo Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing102206, China
| | - Jingxiang Pan
- Joan & Sanford I. Weill Medical College, Cornell University, Ithaca, New York10065
| | - Wenjia Cai
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing100084, China
| | - Peng Gong
- Department of Earth Sciences and Geography, University of Hong Kong, Hong Kong Special Administrative Region999077, China
| | - Yong Luo
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing100084, China
| | - Wannian Liang
- Vanke School of Public Health, Tsinghua University, Beijing100084, China
- Institute for Healthy China, Tsinghua University, Beijing100084, China
| | - Qiyong Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing102206, China
| | - Nils Chr. Stenseth
- Vanke School of Public Health, Tsinghua University, Beijing100084, China
- Centre for Pandemics and One-Health Research, Faculty of Medicine, University of Oslo, OsloN-0316, Norway
- Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, Faculty of Mathematics and Natural Sciences, University of Oslo, OsloN-0315, Norway
| | - Ruifu Yang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing100071, China
| | - Lei Xu
- Vanke School of Public Health, Tsinghua University, Beijing100084, China
- Institute for Healthy China, Tsinghua University, Beijing100084, China
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25
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Cheng X, Zhang J, Zhang L. How to influence food waste behaviour of urban residents? The combined effect of network embeddedness and incentive measures. WASTE MANAGEMENT & RESEARCH : THE JOURNAL OF THE INTERNATIONAL SOLID WASTES AND PUBLIC CLEANSING ASSOCIATION, ISWA 2024:734242X231221082. [PMID: 38193464 DOI: 10.1177/0734242x231221082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2024]
Abstract
Residents' food waste is a key part of environmental sustainability and food security. This study investigates influencing factors in reducing food waste by constructing a conceptual model examining the relationship between network embeddedness (NE) and food waste behaviour (FWB), using questionnaire data from 853 urban residents in eastern China, as well as the moderating role of incentive measures (IMs). We find that NE consists of three dimensions: structural embeddedness, relational embeddedness and functional embeddedness. There is an inverted-U-shaped relationship between structural embeddedness and food waste reduction behaviour, whereas relational embeddedness and functional embeddedness positively correlate with food waste reduction behaviour. Furthermore, IMs significantly strengthen the inverted-U-shaped relationship between NE and food waste reduction behaviour. This article reveals the significance of NE and IMs in influencing FWB, expands the application fields of NE and provides valuable guidance for policymakers to better utilize policy interventions.
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Affiliation(s)
- Xiu Cheng
- College of Economics and Management, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Jie Zhang
- College of Economics and Management, Nanjing Forestry University, Nanjing, Jiangsu, China
| | - Linling Zhang
- School of Public Finance and Taxation, Nanjing University of Finance & Economics, Nanjing, Jiangsu, China
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26
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Cao X, Wang H, Zhang B, Liu J, Yang J, Song Y. Land use spatial optimization for city clusters under changing climate and socioeconomic conditions: A perspective on the land-water-energy-carbon nexus. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 349:119528. [PMID: 37988892 DOI: 10.1016/j.jenvman.2023.119528] [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: 08/07/2023] [Revised: 10/12/2023] [Accepted: 11/01/2023] [Indexed: 11/23/2023]
Abstract
Unbalanced land use development has resulted in water scarcity, high energy consumption, and a significant increase in carbon emissions. Complex and changing environments make it more difficult to manage land use sustainably. This study constructed a variety of future change scenarios coupling climate and socioeconomic development and developed a multidimensional land use spatial optimization (LUSO) model linked with water-energy-carbon. The model is solved using a nondominated sorting genetic algorithm-III (NSGA-Ⅲ) coupled with the information feedback model (IFM). The advantages of this framework include: (1) LUSO based on the clarification of the interactions between different land use types and water-energy-carbon; (2) trade-offs between dimensions are considered to achieve coordinated multidimensional development of the economy, resources, environment, and spatial conversion; and (3) a spatial optimization pattern of land use in response to climate change and socioeconomic development changes can be obtained. The model framework is applied to the Mid-Yangtze River City Cluster for empirical analysis. The results show that socioeconomic development can lead to rapid changes in land use patterns, especially in cultivated and construction land. By 2030, the optimized land use pattern under the intermediate route model is the most suitable land use scenario for the region to achieve sustainable development. Under this scenario, the area of construction land increased by 22.09%, the area of cultivated land decreased by 2.2%, the economic output increased by 76,678.31 (1012 yuan), and the carbon emissions increased by only 5677.79 (107 kg), with an overall sustainability level of 0.85. This study can provide decision-makers with sustainable land resource management options that can respond to changing environments and achieve multidimensional synergistic development.
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Affiliation(s)
- Xiaoxu Cao
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei, 430079, China
| | - Haijun Wang
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei, 430079, China; Key Laboratory of Territorial Spatial Planning and Development-Protection of the Ministry of Natural Resources of PR China and CAUPD Beijing Planning & Design Consultants LTD, Beijing, 100871, China.
| | - Bin Zhang
- School of Public Administration, China University of Geosciences, Wuhan, Hubei, 430074, China; Key Laboratory of the Ministry of Natural Resources for Research on Rule of Law, Wuhan, Hubei, 430074, China
| | - Juelin Liu
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei, 430079, China
| | - Jun Yang
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei, 430079, China
| | - Youcheng Song
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei, 430079, China
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Chen J, Qiu Y, Wu W, Yang R, Li L, Yang Y, Yang X, Xu L. Trends and Projection of the Incidence of Active Pulmonary Tuberculosis in Southwestern China: Age-Period-Cohort Analysis. JMIR Public Health Surveill 2023; 9:e48015. [PMID: 38157236 PMCID: PMC10787335 DOI: 10.2196/48015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 06/19/2023] [Accepted: 10/31/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND The control of pulmonary tuberculosis (PTB) is critical for achieving the vision of World Health Organization's End TB goal. OBJECTIVE This study analyzes the temporal trends in PTB incidence associated with age, period, and birth cohorts from 2006 to 2020 in Yunnan, China; projects the PTB burden till 2030; and explores the drivers of PTB incidence. METHODS The aggregated PTB incidence rates between 2005 and 2020 were obtained from the National Notifiable Disease Reporting System. We used the age-period-cohort model to evaluate the age, period, and cohort effects on PTB incidence. We applied the Bayesian age-period-cohort model to project future PTB incidence from 2021 to 2030. We applied the decomposition algorithm to attribute the incidence trends to population aging, population growth, and age-specific changes from 2006 to 2030. RESULTS From 2006 to 2020, the PTB incidence in Yunnan was relatively stable, although the absolute number showed an increase. The net drift was -1.56% (95% CI -2.41% to -0.70%). An M-shaped bimodal local drift and a longitudinal age curve were observed. The overall local drift was below zero for most age groups except for the age groups of 15-19 years (2.37%, 95% CI -0.28% to 5.09%) and 50-54 years (0.41%, 95% CI -1.78% to 2.64%). The highest risk of PTB incidence was observed in the age group of 65-69 years, and another peak was observed in the age group of 20-24 years. Downward trends were observed for both period and cohort effects, but the cohort effect trends were uneven. A higher risk was observed for the birth cohorts of 1961-1970 (rate ratio [RR]1961-1965=1.10, 95% CI 0.88-1.38; RR1966-1970=1.11, 95% CI 0.92-1.37) and 2001-2010 (RR2001-2005=0.92, 95% CI 0.63-1.34; RR2006-2010=0.84, 95% CI 0.45-1.58) than for the adjacent cohorts. The Bayesian age-period-cohort model projected that PTB incidence will continually increase from 2021 to 2030 and that PTB incidence in 2030 will be 2.28 times higher than that in 2006. The age-specific change was the leading cause for the growing PTB disease burden. CONCLUSIONS Although there are several levels and measures for PTB control, the disease burden is likely to increase in the future. To bridge the gap of TB-free vision, our study suggests that public health policies be put in place soon, including large-scale active case-finding, priority prevention policies for high-risk older adult and young adult populations, and reduction of possible grandparent-grandchildren transmission patterns.
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Affiliation(s)
- Jinou Chen
- Division of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Yubing Qiu
- Division of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Wei Wu
- Division of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Rui Yang
- Division of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Ling Li
- Division of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Yunbin Yang
- Division of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Xing Yang
- Division of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Lin Xu
- Division of Tuberculosis Control and Prevention, Yunnan Center for Disease Control and Prevention, Kunming, China
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Yu B, Zhao Z, Wei YM, Liu LC, Zhao Q, Xu S, Kang JN, Liao H. Approaching national climate targets in China considering the challenge of regional inequality. Nat Commun 2023; 14:8342. [PMID: 38102105 PMCID: PMC10724292 DOI: 10.1038/s41467-023-44122-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 11/30/2023] [Indexed: 12/17/2023] Open
Abstract
Achievement of national climate targets and the corresponding costs would entirely depend on regional actions within the country. However, because of substantial inequalities and heterogeneities among regions, especially in developing economies, aggressive or uniform actions may exacerbate inequity and induce huge economic losses, which in turn challenges the national climate pledges. Hence, this study extends prior research by proposing economically optimal strategies that can achieve national climate targets and ensure the greatest local and national benefits as well as regional equality. Focusing on the biggest developing country China, we find this strategy can avoid up to 1.54% of cumulative GDP losses for approaching carbon neutrality, and more than 90% of regions would obtain economic gains compared either with existing independently launched targets or with the uniform strategy that all regions achieve peak carbon emissions before 2030. We also provide optimal carbon mitigation pathways to regional peak carbon, carbon intensity and energy consumption.
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Affiliation(s)
- Biying Yu
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China.
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China.
- Beijing Key Lab of Energy Economics and Environmental Management, Beijing, 100081, China.
| | - Zihao Zhao
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
| | - Yi-Ming Wei
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China.
- Beijing Key Lab of Energy Economics and Environmental Management, Beijing, 100081, China.
| | - Lan-Cui Liu
- School of Business Administration, Beijing Normal University, Beijing, 100875, China.
| | - Qingyu Zhao
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
| | - Shuo Xu
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
| | - Jia-Ning Kang
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
| | - Hua Liao
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
- Beijing Key Lab of Energy Economics and Environmental Management, Beijing, 100081, China
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29
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Cheng L, Gu K, Zhao L, Wang H, Ji JS, Liu Z, Huang J, Chen Y, Gao X, Xu Y, Wang C, Luo Y, Cai W, Gong P, Liang W, Huang C. Projecting future labor losses due to heat stress in China under climate change scenarios. Sci Bull (Beijing) 2023; 68:2827-2837. [PMID: 37858411 PMCID: PMC10694465 DOI: 10.1016/j.scib.2023.09.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 10/21/2023]
Abstract
Climate change is expected to increase occupational heat stress, which will lead to diminished work performance and labor losses worldwide. However, sub-regional analyses remain insufficient, especially for countries with a heterogeneous spatial distribution of working populations, industries and climates. Here, we projected heat-induced labor losses in China, by considering local climate simulations, working population characteristics and developing an exposure-response function suitable for Chinese workers. We showed that the annual heat-induced work hours lost (WHL), compared to the baseline of 21.3 billion hours, will increase by 121.1% (111.2%-131.1%), 10.8% (8.3%-15.3%), and -17.8% (-15.3%--20.3%) by the end of the century under RCP(Representative Concentration Pathways)8.5, RCP4.5, and RCP2.6, respectively. We observed an approximately linear upward trend of WHL under RCP8.5, despite the decrease in future working population. Notably, WHL will be most prominent in the southern, eastern and central regions, with Guangdong and Henan accounting for a quarter of national total losses; this is largely due to their higher temperature exposure, larger population size, and higher shares of vulnerable population in total employment. In addition, limiting global warming to 1.5 °C would yield substantial gains. Compared to RCP2.6, RCP4.5, and RCP8.5, all provinces can avoid an average of 11.8%, 33.7%, and 53.9% of annual WHL if the 1.5 °C target is achieved, which is equivalent to avoiding 0.1%, 0.6%, and 1.4% of annual GDP losses in China, respectively. This study revealed climate change will exacerbate future labor losses, and adverse impacts can be minimized by adopting stringent mitigation policies coupled with effective adaptation measures. Policymakers in each province should tailor occupation health protection measures to their circumstances.
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Affiliation(s)
- Liangliang Cheng
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; Vanke School of Public Health, Tsinghua University, Beijing 100084, China
| | - Kuiying Gu
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China; Institute of Healthy China, Tsinghua University, Beijing 100084, China
| | - Liang Zhao
- State Key Laboratory of Numerical Modelling for Atmosphere Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Huibin Wang
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China
| | - Zhao Liu
- School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing 100102, China
| | - Jianbin Huang
- Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
| | - Yidan Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Xuejie Gao
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100084, China; Climate Change Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Ying Xu
- National Climate Centre, China Meteorological Administration, Beijing 100081, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yong Luo
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Wenjia Cai
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Peng Gong
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China; Department of Earth Sciences and Department of Geography, University of Hong Kong, Hong Kong 999077, China
| | - Wannian Liang
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China; Institute of Healthy China, Tsinghua University, Beijing 100084, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China; Institute of Healthy China, Tsinghua University, Beijing 100084, China.
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30
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Zhang S, Zhao M, Liu Z, Yang F, Lu B, Zhao Z, Gu K, Zhang S, Lei M, Zhang C, Wang C, Cai W. City-level population projection for China under different pathways from 2010 to 2100. Sci Data 2023; 10:809. [PMID: 37978198 PMCID: PMC10656476 DOI: 10.1038/s41597-023-02735-6] [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: 06/06/2023] [Accepted: 11/08/2023] [Indexed: 11/19/2023] Open
Abstract
Cities play a fundamental role in policy decision-making processes, necessitating the availability of city-level population projections to better understand future population dynamics and facilitate research across various domains, including urban planning, shrinking cities, GHG emission projections, GDP projections, disaster risk mitigation, and public health risk assessment. However, the current absence of city-level population projections for China is a significant gap in knowledge. Moreover, aggregating grid-level projections to the city level introduces substantial errors of approximately 30%, leading to discrepancies with actual population trends. The unique circumstances of China, characterized by comprehensive poverty reduction, compulsory education policies, and carbon neutrality goals, render scenarios like SSP4(Shared Socioeconomic Pathways) and SSP5 less applicable. To address the aforementioned limitations, this study made three key enhancements, which significantly refines and augments our previous investigation. Firstly, we refined the model, incorporating granular demographic data at the city level. Secondly, we redesigned the migration module to consider both regional and city-level population attractiveness. Lastly, we explored diverse fertility and migration scenarios.
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Affiliation(s)
- Shangchen Zhang
- Ministry of Education Ecological Field Station for East Asian Migratory Birds, Institute for Global Change Studies, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Mengzhen Zhao
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
| | - Zhao Liu
- School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing, 100102, China
| | - Fan Yang
- Center for Population and Development Studies, Renmin University of China, Beijing, 100872, China
| | - Bo Lu
- National Climate Center, China Meteorological Administration, NO. 46, Zhongguancun Nandajie, Haidian District, Beijing, China
| | - Zhenping Zhao
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, No. 27 Nanwei Road, Xicheng District, Beijing, 100050, China
| | - Kuiying Gu
- Vanke School of Public Health, Tsinghua University, Beijing, 100084, China
| | - Shihui Zhang
- Ministry of Education Ecological Field Station for East Asian Migratory Birds, Institute for Global Change Studies, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Mingyu Lei
- Ministry of Education Ecological Field Station for East Asian Migratory Birds, Institute for Global Change Studies, Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Chi Zhang
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, 100084, China
| | - Wenjia Cai
- Ministry of Education Ecological Field Station for East Asian Migratory Birds, Institute for Global Change Studies, Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
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31
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Ren S, Huang Z, Bao Y, Yin G, Yang J, Shan X. Matching end-of-life household vehicle generation and recycling capacity in Chinese cities: A spatio-temporal analysis for 2022-2050. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 899:165498. [PMID: 37442483 DOI: 10.1016/j.scitotenv.2023.165498] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/10/2023] [Accepted: 07/10/2023] [Indexed: 07/15/2023]
Abstract
End-of-life vehicles (ELVs) present both opportunities and challenges for the environment and the economy, where effective recycling management plays a decisive role. Recently, the primary focus of recycling management has shifted from simply meeting demand to refining and optimizing processes at the city-scale. However, the mismatch in recycling capacity has become a significant obstacle to maximizing environmental and economic benefits. To reveal this issue and propose improvements in the context of China, this study simulates end-of-life internal combustion engine vehicles (ICEVs) and new energy vehicles (NEVs) at the city-scale from 2021 to 2050, and analyzes their spatio-temporal pattern and recycling capacity matching. The results indicate that the number of ELVs in China will continue to increase, peaking between 3.5 and 3.7 million. This growth will be mainly driven by third- to fifth-tier cities, as well as central and southwestern cities. Regarding recycling capacity matching, most cities possess excess dismantling capacity, while first-tier cities face coordination problems in battery collection. Spatial coordination across cities or provinces is a viable approach for dismantling enterprises and should be prioritized over indiscriminate deregistration or establishing new facilities. The absence of initiative within the recycling system results in uncoordinated battery collection. Implementing a recycling-sharing mechanism and establishing a reuse market can effectively tackle this problem by leveraging market incentives. These analyses provide practical suggestions to maximize the environmental and economic benefits of resource recycling, thereby contributing to the UN's 2030 Sustainable Development Goals (SDGs).
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Affiliation(s)
- Shuliang Ren
- Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China; Beijing Key Lab of Spatial Information Integration & Its Applications, Peking University, Beijing 100871, China
| | - Zhou Huang
- Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China; Beijing Key Lab of Spatial Information Integration & Its Applications, Peking University, Beijing 100871, China; International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China.
| | - Yi Bao
- Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China; Beijing Key Lab of Spatial Information Integration & Its Applications, Peking University, Beijing 100871, China
| | - Ganmin Yin
- Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China; Beijing Key Lab of Spatial Information Integration & Its Applications, Peking University, Beijing 100871, China
| | - Jingfan Yang
- Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China; Beijing Key Lab of Spatial Information Integration & Its Applications, Peking University, Beijing 100871, China
| | - Xv Shan
- State Key Laboratory of Media Convergence Production Technology and Systems, Beijing, China
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32
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Yue W, Zhou Q, Li M, van Vliet J. Relocating built-up land for biodiversity conservation in an uncertain future. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 345:118706. [PMID: 37536125 DOI: 10.1016/j.jenvman.2023.118706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 07/06/2023] [Accepted: 07/26/2023] [Indexed: 08/05/2023]
Abstract
Land use changes associated with habitat loss, fragmentation, and degradation exert profoundly detrimental impacts on biodiversity conservation. Urban development is one of the prevailing anthropogenic disturbances to wildlife habitat, because these developments are often considered permanent and irreversible. As a result, the potential benefits of built-up land relocation for biodiversity conservation have remained largely unexplored in environmental management practices. Here, we analyze recent built-up land relocation in Shanghai and explore how such restoration programs can affect future land change trajectories with regards to biodiversity conservation. Results show that 187.78 km2 built-up land in Shanghai was restored to natural habitat between 2017 and 2020. Further simulation analysis highlights that relocating built-up land can substantially promote conserve biodiversity. In particular, there would be less habitat loss, better natural habitat quality and more species habitat-suitable range under the scenarios with built-up land relocation. Species extinction assessment suggest that amphibians, mammals, and reptiles will all have an increasingly high extinction risk without built-up land relocation. However, there will even be a marginal decrease in extinction risk over time for mammals and reptiles if the relocation of built-up land is permitted, but still a moderate increase in extinction risk for amphibians. This study highlights the importance of incorporating rigorous conservation planning prior to development activities, thereby underpinning a sustainable approach to environmental management.
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Affiliation(s)
- Wenze Yue
- Department of Land Management, Zhejiang University, Hangzhou, China
| | - Qiushi Zhou
- Department of Land Management, Zhejiang University, Hangzhou, China
| | - Mengmeng Li
- Department of Land Management, Zhejiang University, Hangzhou, China; Institute for Environmental Studies, VU University Amsterdam, Amsterdam, the Netherlands; Swiss Federal Research Institute WSL, Zürcherstrasse 111, CH-8903, Birmensdorf, Switzerland.
| | - Jasper van Vliet
- Institute for Environmental Studies, VU University Amsterdam, Amsterdam, the Netherlands
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33
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Ma T, Zhang S, Xiao Y, Liu X, Wang M, Wu K, Shen G, Huang C, Fang YR, Xie Y. Costs and health benefits of the rural energy transition to carbon neutrality in China. Nat Commun 2023; 14:6101. [PMID: 37773252 PMCID: PMC10541415 DOI: 10.1038/s41467-023-41707-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 09/14/2023] [Indexed: 10/01/2023] Open
Abstract
The rural energy transition is critical in China's efforts to achieve carbon neutrality and improve air quality. However, the costs and health benefits associated with the transition to carbon neutrality remain unclear. Here we explore the cost-effective transition pathways and air quality-related health impacts using an integrated energy-air quality-health modeling framework. We find that decarbonizing rural cooking and heating would triple contemporary energy consumption from 2014 to 2060, considerably reducing energy poverty nationwide. By 2060, electric cooking ranges and air-to-air heat pumps should be widely integrated, costing an additional 13 billion USD nationally in transformation costs, with ~40% concentrated in Shandong, Heilongjiang, Shanxi and Hebei provinces. Rural residential decarbonization would remarkably improve air quality in northern China, yielding substantial health co-benefits. Notably, monetized health benefits in most provinces are projected to offset transformation costs, except for certain relatively lower-development southwestern provinces, implying more financial support for rural residents in these areas will be needed.
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Affiliation(s)
- Teng Ma
- College of Environmental Sciences and Engineering, Peking University, 100871, Beijing, China
| | - Silu Zhang
- College of Environmental Sciences and Engineering, Peking University, 100871, Beijing, China
| | - Yilong Xiao
- College of Environmental Sciences and Engineering, Peking University, 100871, Beijing, China
| | - Xiaorui Liu
- College of Environmental Sciences and Engineering, Peking University, 100871, Beijing, China
| | - Minghao Wang
- School of Economics and Management, Beihang University, 100191, Beijing, China
| | - Kai Wu
- College of Environmental Sciences and Engineering, Peking University, 100871, Beijing, China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
- Institute of Carbon Neutrality, Peking University, 100871, Beijing, China
| | - Chen Huang
- College of Environmental Sciences and Engineering, Peking University, 100871, Beijing, China
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
| | - Yan Ru Fang
- College of Environmental Sciences and Engineering, Peking University, 100871, Beijing, China.
| | - Yang Xie
- School of Economics and Management, Beihang University, 100191, Beijing, China.
- Laboratory for Low-carbon Intelligent Governance, Beihang University, 100191, Beijing, China.
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Xu F, Huang Q, Yue H, Feng X, Xu H, He C, Yin P, Bryan BA. The challenge of population aging for mitigating deaths from PM 2.5 air pollution in China. Nat Commun 2023; 14:5222. [PMID: 37633954 PMCID: PMC10460422 DOI: 10.1038/s41467-023-40908-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 08/14/2023] [Indexed: 08/28/2023] Open
Abstract
Estimating the health burden of air pollution against the background of population aging is of great significance for achieving the Sustainable Development Goal 3.9 which aims to substantially reduce the deaths and illnesses from air pollution. Here, we estimated spatiotemporal changes in deaths attributable to PM2.5 air pollution in China from 2000 to 2035 and examined the drivers. The results show that from 2019 to 2035, deaths were projected to decease 15.4% (6.6%-20.7%, 95% CI) and 8.4% (0.6%-13.5%) under the SSP1-2.6 and SSP5-8.5 scenario, respectively, but increase 10.4% (5.1%-20.5%) and 18.1% (13.0%-28.3%) under SSP2-4.5 and SSP3-7.0 scenarios. Population aging will be the leading contributor to increased deaths attributable to PM2.5 air pollution, which will counter the positive gains achieved by improvements in air pollution and healthcare. Region-specific measures are required to mitigate the health burden of air pollution and this requires long-term efforts and mutual cooperation among regions in China.
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Affiliation(s)
- Fangjin Xu
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China
- School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Qingxu Huang
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China.
- School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
- Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
| | - Huanbi Yue
- School of International Affairs and Public Administration, Ocean University of China, Qingdao, 266100, China
| | - Xingyun Feng
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China
- School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Haoran Xu
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China
- Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Chunyang He
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China
- Key Laboratory of Environmental Change and Natural Disasters, Ministry of Education, Beijing Normal University, Beijing, 100875, China
- Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing, 100875, China
- Academy of Plateau Science and Sustainability, People's Government of Qinghai Province and Beijing Normal University, Xining, China
| | - Peng Yin
- National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Brett A Bryan
- School of Life and Environmental Sciences, Deakin University, Melbourne, VIC3125, Australia
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Zhang H, Sun M, Yao X, Xie Z, Zhang M. Increasing probability of record-population exposure to high temperature and related health-risks in China. ENVIRONMENTAL RESEARCH 2023; 231:116176. [PMID: 37209980 DOI: 10.1016/j.envres.2023.116176] [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: 09/14/2022] [Revised: 05/08/2023] [Accepted: 05/15/2023] [Indexed: 05/22/2023]
Abstract
Combining the comprehensive effects of temperature and humidity, this study applies a heat stress index to project future population exposure to high temperature and related health-risks over China under different climate change scenarios. Results show that the number of high temperature days, population exposure and their related health-risks will increase significantly in the future compared to the reference period (1985-2014), which is mainly caused by the change of >T99p (the wet bulb globe temperature >99th percentile derived from the reference period). The population effect is absolutely dominant in influencing the decrease in exposure to T90-95p (the wet bulb globe temperature is in the range of (90th, 95th]) and T95-99p (the wet bulb globe temperature is in the range of (95th, 99th]), and the climate effect is the most prominent contributor to the upsurge in exposure to > T99p in most areas. An additional 0.1 billion person-days increase in population exposure to T90-95p, T95-99p and >T99p in a given year is associated with the number of deaths by 1002 (95% CI: 570-1434), 2926 (95% CI: 1783-4069) and 2635 (95% CI: 1345-3925), respectively. Compared with the reference period, total exposure to high temperature under the SSP2-4.5 (SSP5-8.5) scenario will increase to 1.92 (2.01) times in the near-term (2021-2050) and 2.16 (2.35) times in the long-term (2071-2100), which will increase the number of people at heat risk by 1.2266 (95% CI: 0.6341-1.8192) [1.3575 (95% CI: 0.6926-2.0223)] and 1.5885 (95% CI: 0.7869-2.3902) [1.8901 (95% CI:0.9230-2.8572)] million, respectively. Significant geographic variations exist in the changes of exposure and related health-risks. The change is greatest in the southwest and south, whereas it is relatively small in the northeast and north. The findings provide several theoretical references for climate change adaptation.
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Affiliation(s)
- Haiyan Zhang
- College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, China; Key Laboratory of Resource Environment and Sustainable Development of Oasis, Gansu Province, China
| | - Meiping Sun
- College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, China; Key Laboratory of Resource Environment and Sustainable Development of Oasis, Gansu Province, China; Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China.
| | - Xiaojun Yao
- College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, China; Key Laboratory of Resource Environment and Sustainable Development of Oasis, Gansu Province, China
| | - Zhenyu Xie
- College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, China; Key Laboratory of Resource Environment and Sustainable Development of Oasis, Gansu Province, China
| | - Mingjun Zhang
- College of Geography and Environment Sciences, Northwest Normal University, Lanzhou, China; Key Laboratory of Resource Environment and Sustainable Development of Oasis, Gansu Province, China
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He C, Yin P, Liu Z, Huang J, Chen Y, Gao X, Xu Y, Wang C, Cai W, Gong P, Luo Y, Ji JS, Kan H, Chen R, Zhou M. Projections of excess deaths related to cold spells under climate and population change scenarios: A nationwide time series modeling study. ENVIRONMENT INTERNATIONAL 2023; 178:108034. [PMID: 37348158 DOI: 10.1016/j.envint.2023.108034] [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: 03/10/2023] [Revised: 05/23/2023] [Accepted: 06/09/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND Future climate change is likely to alter cold spell-related disease burden. Few projection studies have considered the potential impact of the aging population with changing population size on cold spell-related disease burdens. METHODS We derived the association between cold spells and daily mortality for 272 main cities in mainland China. We combined these associations with modeled daily temperatures from three different climate models under two climate change scenarios and three population scenarios to project excess deaths related to cold spells. Furthermore, we used the factor separation method to calculate the independent contribution of future population size, age structure, and climate change on projected deaths attributable to cold spells. FINDINGS Compared to the baseline period, future excess deaths related to cold spells are expected to increase over most of the decades under RCP 2.6 (81.5% in 2050 s and 37% in 2090 s) and RCP 4.5 (55.5% in 2050 s and -19% in 2090 s). The factor analysis indicated that the rise of the aged population (≥65) substantially would amplify the excess deaths related to cold spells (increase by 101.1% in the 2050 s and 146.2% in the 2090 s). For the near future (2021-2040), population aging could fully offset the influence of decreased cold-spell days. In the middle of this century (2051-2070), the total excess deaths will exhibit significant variation across three scenarios. By the end of 21 century (2081-2100), the population shrinking would reduce the total excess deaths. INTERPRETATION Excess deaths related to cold spells may still increase in a warming climate and future demographic shifts would produce considerable influences in this increase for different periods.
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Affiliation(s)
- Cheng He
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China; Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhao Liu
- School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing, China
| | - Jianbin Huang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Yidan Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
| | - Xuejie Gao
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China; Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Ying Xu
- National Climate Center, China Meteorological Administration, Beijing, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
| | - Wenjia Cai
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Peng Gong
- Institute for Climate and Carbon Neutrality, Department of Earth Sciences and Geography, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yong Luo
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - John S Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Haidong Kan
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China; Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China
| | - Renjie Chen
- School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China.
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
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Fang YR, Sun X, Zhang S, Liu G, Liu X, Zhang P, Kang Y, Dai H. Regionally differentiated promotion of electric vehicles in China considering environmental and human health impacts. ENVIRONMENTAL RESEARCH LETTERS : ERL [WEB SITE] 2023; 18:074022. [PMID: 37362199 PMCID: PMC10285718 DOI: 10.1088/1748-9326/acdbde] [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: 02/19/2023] [Revised: 05/12/2023] [Accepted: 06/06/2023] [Indexed: 06/28/2023]
Abstract
Private passenger vehicles, with its high emissions of CO2 and air pollutants, poses a severe threat to global climate and human health, particularly for a large developing country like China. Although both energy efficiency improvement of internal combustion engine vehicles (ICEVs) and the wide adoption of electric vehicles (EVs) could contribute to reducing emissions, how they should be jointly implemented in provinces with a heterogeneous context to maximize their net benefits remains insufficiently explored. Here, based on an integrated modeling framework associated with one factual (REF) and four counterfactual scenarios to explore the priority and best-ranked ordering of both EVs' penetration and high energy-efficient ICEVs in 31 Chinese provinces to achieve the most environmental and human health benefits from 2011 to 2018. The results demonstrate that electrification of the passenger fleet, which is charged by a slightly cleaner power source relative to 2011, yields significant co-benefits of CO2 reduction and air quality improvement. Compared with REF, the fleet electrification scenario would lead to 3167 cases of avoided mortality and attain US$4.269 billion of health benefits in 2018, accounting for 0.03% of China's gross domestic product. Nonetheless, highly efficient ICEVs are found to harbor decarbonization potential and health benefits in northern China. Based on these results, Sichuan, Hebei and seven other provinces in east China should promote EVs imminently; conversely, eight provinces with a high share of thermal power must continually advance their implementation of ICEVs in the near future. Such prioritization of EVs and ICEV development at the provincial level provides timely insights for devising tailored policies regarding passenger car transition and for maximizing climate and health benefits based on regional heterogeneity.
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Affiliation(s)
- Yan Ru Fang
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, People’s Republic of China
| | - Xin Sun
- China Automotive Technology and Research Center Co., Ltd, No. 68, East Xianfeng Road, Dongli District, Tianjin 300300, People’s Republic of China
- Automotive Data of China (Tianjin) Co., Ltd, No. 3 Wanhui Road, Zhongbei Town, Xiqing District, Tianjin 300393, People’s Republic of China
- Automotive Data of China Co., Ltd, Boxing 6th Road, Beijing Economic Development Zone, Beijing 100176, People’s Republic of China
| | - Silu Zhang
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, People’s Republic of China
| | - Gang Liu
- College of Urban and Environmental Sciences, Peking University, Beijing 100871, People’s Republic of China
| | - Xiaorui Liu
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, People’s Republic of China
| | - Peng Zhang
- China Automotive Technology and Research Center Co., Ltd, No. 68, East Xianfeng Road, Dongli District, Tianjin 300300, People’s Republic of China
- Automotive Data of China (Tianjin) Co., Ltd, No. 3 Wanhui Road, Zhongbei Town, Xiqing District, Tianjin 300393, People’s Republic of China
- Automotive Data of China Co., Ltd, Boxing 6th Road, Beijing Economic Development Zone, Beijing 100176, People’s Republic of China
| | - Yifei Kang
- Beijing Yiwei New Energy Vehicles Big Data Application &Technology Research Center, 2 North Xisanhuan Road, Haidian District, Beijing 100081, People’s Republic of China
| | - Hancheng Dai
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, People’s Republic of China
- Institute for Global Health and Development, Peking University, Beijing 100871, People’s Republic of China
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Luo Z, Chen X, Li N, Li J, Zhang W, Wang T. Spatiotemporal foresting of soil erosion for SSP-RCP scenarios considering local vegetation restoration project: A case study in the three gorges reservoir (TGR) area, China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 337:117717. [PMID: 36958284 DOI: 10.1016/j.jenvman.2023.117717] [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: 12/01/2022] [Revised: 02/12/2023] [Accepted: 03/08/2023] [Indexed: 06/18/2023]
Abstract
Soil erosion is a common form of land degradation. The Coupled Model Intercomparison Project Phase 6 (CMIP6) provides a scenario framework for global socio-economic development and climate change by combining Shared Socioeconomic Pathways (SSP) and Representative Concentration Pathways (RCP). The soil erosion estimation under global climate change and land-use change scenarios provided by CMIP6 is valuable for representing future changes and hotspots. This study estimated the future changes in soil erosion in the Three Gorges Reservoir (TGR) area, China, which has suffered severe soil loss over an extended period, and vegetation restoration projects have been conducted since 1999. The scenarios provided by SSP1-2.6, SSP2-4.5, and SSP5-8.5 were coupled with the scenarios of regional vegetation restoration projects to reflect future land use changes (LUC) and climate change. The results showed that future soil erosion from 2020 to 2100 in the TGR area will experience a non-significant decreasing trend (with trend slopes of -0.013, -0.020, and-0.006 in SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively, with p > 0.05). However, with the R factors calculated by different methods, this decreasing trend becomes either insignificant or a significant increasing trend. SSP1-2.6 will experience the lowest soil erosion in 2100 owing to the large amount of forest increase in this scenario. Furthermore, as estimates, the grain-for-green policy (GGP) will reduce 89353.47, 92737.73 and 42916.52 ton soil erosion per year in SSP1-2.6, SSP2-4.5 and SSP3-8.5 by 2100, respectively. In the future, the GGP will become increasingly important for controlling soil loss in the TGR area owing to the increasing precipitation in all scenarios, which increases the risk of soil loss.
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Affiliation(s)
- Zhibang Luo
- College of Resources and Environment, Huazhong Agricultural University, Wuhan, China.
| | - Xiao Chen
- College of Resources and Environment, Huazhong Agricultural University, Wuhan, China.
| | - Nian Li
- College of Resources and Environment, Huazhong Agricultural University, Wuhan, China.
| | - Jingyi Li
- The University of Arizona, Tucson, USA.
| | - Wenting Zhang
- College of Resources and Environment, Huazhong Agricultural University, Wuhan, China; Research Center for Territorial Spatial Governance and Governance and Green Development, Huazhong Agricultural University, Wuhan, China.
| | - Tianwei Wang
- College of Resources and Environment, Huazhong Agricultural University, Wuhan, China.
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Gu X, Sun M, Long X, Deng H, Wang Y. Environmental impact of adult incontinence products in China in the context of population aging. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 875:162596. [PMID: 36898540 DOI: 10.1016/j.scitotenv.2023.162596] [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: 01/04/2023] [Revised: 02/16/2023] [Accepted: 02/27/2023] [Indexed: 06/18/2023]
Abstract
With the rise of the aging population, the demand for adult incontinence products keeps increasing in developing countries. The increasing market demand for adult incontinence products will inevitably drive up upstream production, leading to more resources and energy consumption, carbon emissions, and heavier environmental pollution. It is imperative to explore the environmental impact of those products and seek opportunities to reduce the environmental impact, which is insufficient. This study aims to fill the gap in research on comparative analysis of energy consumption, carbon emissions, and the environmental impact of adult incontinence products from a life cycle perspective under different energy saving and emission reduction scenarios in the context of aging in China. Based on empirical data from a top papermaking manufacturer in China, this study applies Life Cycle Assessment (LCA) method to analyze the impact of adult incontinence products from cradle to grave. Then different scenarios in the future are set to explore the potential of and the possible pathways for energy-saving and emission-reduction of adult incontinence products from the perspective of the whole life cycle. The results indicate that the energy and materials inputs are the environmental hotspots of adult incontinence products. Under the future trend of the aging population, the predictable optimization of energy structure, optimization of material composition, and final disposal methods are far from being able to cope with the enormous environmental burden brought by the increase in the consumption of adult incontinence products, especially in 2060 which shows 3.33 to 18.40 times the annual environmental burden under the optimal energy saving and emission reduction scenario, compared to the base year 2020. Research on new environmentally friendly materials and recycling technology should be the focus of the technological development of adult incontinence products.
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Affiliation(s)
- Xinkai Gu
- Fudan Tyndall Center, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Mingxing Sun
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Xinyi Long
- Fudan Tyndall Center, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Huijing Deng
- Fudan Tyndall Center, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Yutao Wang
- Fudan Tyndall Center, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China; Institute of Eco-Chongming (IEC), No.3663 Northern Zhongshan Road, Shanghai 200062, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather, Shanghai, China; Shanghai Institute for Energy and Carbon Neutrality Strategy, Fudan University, Shanghai, China.
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40
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Ye Q, Krol MS, Shan Y, Schyns JF, Berger M, Hubacek K. Allocating capital-associated CO 2 emissions along the full lifespan of capital investments helps diffuse emission responsibility. Nat Commun 2023; 14:2727. [PMID: 37169782 PMCID: PMC10173932 DOI: 10.1038/s41467-023-38358-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 04/25/2023] [Indexed: 05/13/2023] Open
Abstract
Capital assets such as machinery and infrastructure contribute substantially to CO2 emissions over their lifetime. Unique features of capital assets such as their long durability complicate the assignment of capital-associated CO2 emissions to final beneficiaries. Whereas conventional approaches allocate emissions required to produce capital assets to the year of formation, we propose an alternative perspective through allocating required emissions from the production of assets over their entire lifespans. We show that allocating CO2 emissions embodied in capital assets over time relieves emission responsibility for the year of formation, with 25‒46% reductions from conventional emission accounts. This temporal allocation, although virtual, is important for assessing the equity of CO2 emissions across generations due to the inertia of capital assets. To re-allocate emission responsibilities to the future, we design three capital investment scenarios with different investment purposes until 2030. Overall, the existing capital in 2017 will still carry approximately 10% responsibilities of China's CO2 emissions in 2030, and could reach more than 40% for capital-intensive service sectors.
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Affiliation(s)
- Quanliang Ye
- Multidisciplinary Water Management, Faculty of Engineering Technology, University of Twente, 7522 NB, Enschede, the Netherlands
- Integrated Research on Energy, Environment and Society (IREES), Energy and Sustainability Research Institute Groningen (ESRIG), University of Groningen, 9747 AG, Groningen, the Netherlands
- Department of Planning, Aalborg University, 9000, Aalborg, Denmark
| | - Maarten S Krol
- Multidisciplinary Water Management, Faculty of Engineering Technology, University of Twente, 7522 NB, Enschede, the Netherlands
| | - Yuli Shan
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK.
| | - Joep F Schyns
- Multidisciplinary Water Management, Faculty of Engineering Technology, University of Twente, 7522 NB, Enschede, the Netherlands
| | - Markus Berger
- Multidisciplinary Water Management, Faculty of Engineering Technology, University of Twente, 7522 NB, Enschede, the Netherlands
| | - Klaus Hubacek
- Integrated Research on Energy, Environment and Society (IREES), Energy and Sustainability Research Institute Groningen (ESRIG), University of Groningen, 9747 AG, Groningen, the Netherlands.
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41
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Yin R, Wang Z, Xu F. Multi-scenario simulation of China's dynamic relationship between water-land resources allocation and cultivated land use based on shared socioeconomic pathways. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 341:118062. [PMID: 37141718 DOI: 10.1016/j.jenvman.2023.118062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/17/2023] [Accepted: 04/28/2023] [Indexed: 05/06/2023]
Abstract
Rapid urban expansion, population growth, and limited cultivated land in China necessitate rethinking the path to sustainable management of cultivated land. Understanding the long-term dynamic relationship between water-land resource endowment and cultivated land use contributes to effective management and use of cultivated land. However, few studies have systematically documented this relationship, especially for future trends. Accordingly, we modified water-land resource matching (WLRM) using a more refined grid-scale and assessed cultivated land use efficiency (CLUE), then deployed spatial panel regression models to quantify historical changes. We subsequently simulated future trends under three Shared Socioeconomic Pathways scenarios. The results showed that the relationship assumed an N-shaped curve in nation, while the curve followed a down-up-down pattern in economically less developed regions, largely because of structural transformations of production factors. Under three development scenarios, the stage-specific characteristics of production factors were pronounced, and the dynamic relationship varied across regions.
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Affiliation(s)
- Ruimin Yin
- School of Public Administration, China University of Geosciences, Wuhan, 430074, China.
| | - Zhanqi Wang
- School of Public Administration, China University of Geosciences, Wuhan, 430074, China.
| | - Feng Xu
- School of Public Administration, China University of Geosciences, Wuhan, 430074, China.
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Li C, Liu Z, Li W, Lin Y, Hou L, Niu S, Xing Y, Huang J, Chen Y, Zhang S, Gao X, Xu Y, Wang C, Zhao Q, Liu Q, Ma W, Cai W, Gong P, Luo Y. Projecting future risk of dengue related to hydrometeorological conditions in mainland China under climate change scenarios: a modelling study. Lancet Planet Health 2023; 7:e397-e406. [PMID: 37164516 DOI: 10.1016/s2542-5196(23)00051-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 02/01/2023] [Accepted: 02/28/2023] [Indexed: 05/12/2023]
Abstract
BACKGROUND We have limited knowledge on the impact of hydrometeorological conditions on dengue incidence in China and its associated disease burden in a future with a changed climate. This study projects the excess risk of dengue caused by climate change-induced hydrometeorological conditions across mainland China. METHODS In this modelling study, the historical association between the Palmer drought severity index (PDSI) and dengue was estimated with a spatiotemporal Bayesian hierarchical model from 70 cities. The association combined with the dengue-transmission biological model was used to project the annual excess risk of dengue related to PDSI by 2100 across mainland China, under three representative concentration pathways ([RCP] 2·6, RCP 4·5, and RCP 8·5). FINDINGS 93 101 dengue cases were reported between 2013 and 2019 in mainland China. Dry and wet conditions within 3 months lag were associated with increased risk of dengue. Locations with potential dengue risk in China will expand in the future. The hydrometeorological changes are projected to substantially affect the risk of dengue in regions with mid-to-low latitudes, especially the coastal areas under high emission scenarios. By 2100, the annual average increased excess risk is expected to range from 12·56% (95% empirical CI 9·54-22·24) in northwest China to 173·62% (153·15-254·82) in south China under the highest emission scenario. INTERPRETATION Hydrometeorological conditions are predicted to increase the risk of dengue in the future in the south, east, and central areas of mainland China in disproportionate patterns. Our findings have implications for the preparation of public health interventions to minimise the health hazards of non-optimal hydrometeorological conditions in a context of climate change. FUNDING National Natural Science Foundation of China.
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Affiliation(s)
- Chuanxi Li
- Department of Epidemiology, Shandong University, Jinan, China; School of Public Health, Cheeloo College of Medicine, and Shandong University Climate Change and Health Centre, Shandong University, Jinan, China
| | - Zhao Liu
- School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing, China
| | - Wen Li
- Department of Epidemiology, Shandong University, Jinan, China; School of Public Health, Cheeloo College of Medicine, and Shandong University Climate Change and Health Centre, Shandong University, Jinan, China
| | - Yuxi Lin
- Department of Epidemiology, Shandong University, Jinan, China; School of Public Health, Cheeloo College of Medicine, and Shandong University Climate Change and Health Centre, Shandong University, Jinan, China
| | - Liangyu Hou
- Department of Epidemiology, Shandong University, Jinan, China; School of Public Health, Cheeloo College of Medicine, and Shandong University Climate Change and Health Centre, Shandong University, Jinan, China
| | - Shuyue Niu
- Department of Epidemiology, Shandong University, Jinan, China; School of Public Health, Cheeloo College of Medicine, and Shandong University Climate Change and Health Centre, Shandong University, Jinan, China
| | - Yue Xing
- Department of Epidemiology, Shandong University, Jinan, China; School of Public Health, Cheeloo College of Medicine, and Shandong University Climate Change and Health Centre, Shandong University, Jinan, China
| | - Jianbin Huang
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China; Beijing Yanshan Earth Critical Zone National Research Station, Chinese Academy of Sciences, Beijing, China
| | - Yidan Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
| | - Shangchen Zhang
- Department of Earth System Science, Institute for Global Change Studies, Ministry of Education Key Laboratory for Earth System Modelling, Tsinghua University, Beijing, China
| | - Xuejie Gao
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China; Climate Change Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Ying Xu
- National Climate Centre, China Meteorological Administration, Beijing, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
| | - Qi Zhao
- Department of Epidemiology, Shandong University, Jinan, China; School of Public Health, Cheeloo College of Medicine, and Shandong University Climate Change and Health Centre, Shandong University, Jinan, China; Department of Epidemiology, IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany.
| | - Qiyong Liu
- Department of Epidemiology, Shandong University, Jinan, China; Department of Vector Control, Shandong University, Jinan, China; School of Public Health, Cheeloo College of Medicine, and Shandong University Climate Change and Health Centre, Shandong University, Jinan, China; State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Centre for Disease Control and Prevention, Beijing, China.
| | - Wei Ma
- Department of Epidemiology, Shandong University, Jinan, China; School of Public Health, Cheeloo College of Medicine, and Shandong University Climate Change and Health Centre, Shandong University, Jinan, China.
| | - Wenjia Cai
- Ministry of Education Ecological Field Station for East Asian Migratory Birds, Tsinghua University, Beijing, China
| | - Peng Gong
- Institute for Climate and Carbon Neutrality, Department of Earth Sciences and Geography, University of Hong Kong, Hong Kong, China
| | - Yong Luo
- Department of Earth System Science, Institute for Global Change Studies, Ministry of Education Key Laboratory for Earth System Modelling, Tsinghua University, Beijing, China
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Li R, Yu Y, Cai W, Liu Q, Liu Y, Zhou H. Interprovincial differences in the historical peak situation of building carbon emissions in China: Causes and enlightenments. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 332:117347. [PMID: 36708600 DOI: 10.1016/j.jenvman.2023.117347] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 01/18/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
Scientific assessment of the historical carbon peak situation of provincial buildings in China is the premise and basis for understanding the country's development trends and formulating carbon peak goals. The population size, urbanization stages, economic development levels, natural resources endowment, and energy structure characteristics vary significantly for the different provinces in China, resulting in significant differences in the peaking situation of building carbon emissions (BCE). The differences require more attention given the current environmental status. Based on the judgment function of carbon peaking conditions and the statistical Mann-Kendall (MK) trend test method, this study evaluates the historical peak situation of building carbon emissions at the provincial level in China. The peaking sequence of BCE, building carbon emissions per capita (BCEP), and carbon emissions per unit floor area (BCEA) were analyzed, and the driving factors that cause different carbon peak situations were discussed. Further, with reference to the experience of the United States, a peak strategy for building carbon emissions in China was proposed. The research results showed that BCE in Beijing and Yunnan have peaked, and the three provinces of Shanghai, Sichuan, and Hubei have plateaued. The most important factors that cause different peaking situations for BCE are the floor area per capita and carbon emissions per unit of energy consumption. In addition, the peak order of building carbon emissions was BCEA, BCEP, and BCE. A strategy that should be adopted in the promotion of buildings' carbon peak in China is to formulate phased peak goals for BCE, BCEP, and BCEA at a national level and differentiated echelon peak goals at a provincial level considering interprovincial differences. This study provides a scientific basis and decision-making reference for formulating a path to buildings' carbon peak at a provincial level in China.
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Affiliation(s)
- Rui Li
- School of Management Science and Real Estate, Chongqing University, Chongqing 400045, China.
| | - Yanhui Yu
- School of Management Science and Real Estate, Chongqing University, Chongqing 400045, China
| | - Weiguang Cai
- School of Management Science and Real Estate, Chongqing University, Chongqing 400045, China.
| | - Qiqi Liu
- School of Management Science and Real Estate, Chongqing University, Chongqing 400045, China
| | - Yuan Liu
- School of Management Science and Real Estate, Chongqing University, Chongqing 400045, China
| | - Haonan Zhou
- School of Economics and Management, Hebei University of Technology, Tianjin 300401, China
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Jiang J, Wang Z, Lai C, Wu X, Chen X. Climate and landuse change enhance spatio-temporal variability of Dongjiang river flow and ammonia nitrogen. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 867:161483. [PMID: 36634765 DOI: 10.1016/j.scitotenv.2023.161483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 06/17/2023]
Abstract
The adverse impacts of climate and landuse change are threatening the availability of water quantity and its quality, yet there are limited understandings in the response of water availability to changing environment at different spatio-temporal scales. Aimed at quantifying the individual and superimposed effects of climate and landuse change on streamflow and ammonia nitrogen (NH3-N) load in the Dongjiang River Basin (DRB), we dynamically simulated the historical (1981-2010) and future (2030-2070) variation of runoff depth and NH3-N load coupling multiple regional climate model and landuse data. The increase in runoff depth (avg. +233.9 mm) due to climate change was about 33 times greater than that caused by landuse change (avg. -7.2 mm). Especially in the downstream of DRB (Hong Kong, Shenzhen and Dongguan cities, etc.), the maximum rise of runoff depth under climate change was near twice compared with baseline period, indicating the dominant control of climate change on runoff. Also there existed higher coefficient of variation (Cv) value of runoff in the dry season of downstream DRB, contributing potential great fluctuation in runoff. Besides, the variation of NH3-N load was jointly influenced by climate and landuse change, revealing an offset or amplification effect. Moreover, the variability of NH3-N load (Cv value as the metric) increased from 2030, reached a maximum in 2050, following decreased to 2070. The spatial distribution of NH3-N load, in general, presented a downward trend and concentrated near the water body, while the monthly average NH3-N load showed distinct peaks in spring and late summer temporally. Overall, the results highlight the significance of investigating the water availability under changing environment and more adaptive strategies should be proposed for better basin water management.
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Affiliation(s)
- Jie Jiang
- School of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510641, China; Pazhou Lab, Guangzhou 510335, China
| | - Zhaoli Wang
- School of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510641, China; Pazhou Lab, Guangzhou 510335, China.
| | - Chengguang Lai
- School of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510641, China; Pazhou Lab, Guangzhou 510335, China
| | - Xushu Wu
- School of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou 510641, China
| | - Xiaohong Chen
- Center for Water Resource and Environment, Sun Yat-sen University, Guangzhou 510275, China
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Dong J, Cai B, Zhang S, Wang J, Yue H, Wang C, Mao X, Cong J, Guo F. Closing the Gap between Carbon Neutrality Targets and Action: Technology Solutions for China's Key Energy-Intensive Sectors. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:4396-4405. [PMID: 36942443 DOI: 10.1021/acs.est.2c08171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Facing significant carbon emissions annually, China requires a clear decarbonization strategy to meet its climate targets. This study presents a MESSAGEix-CAEP model to explore Chinese decarbonization pathways and their cost-benefit under two mitigation scenarios by establishing connections between five energy-intensive sectors based on energy and material flows. The results indicated the following: 1) Interaction and feedback between sectors should not be disregarded. The electrification process of the other four sectors was projected to increase electricity production by 206%, resulting in a higher power demand than current forecasts. 2) The marginal abatement cost to achieve carbon neutrality across all five sectors was 2189 CNY/tCO2, notably higher than current Chinese carbon emission trading prices. 3) The cost-benefit analysis indicates that a more ambitious abatement strategy would decrease the marginal abatement cost and result in a higher net carbon abatement benefit. The cumulative net benefit of carbon reduction was 7.8 trillion CNY under ambitious mitigation scenario, 1.3 trillion CNY higher than that under current Chinese mitigation scenario. These findings suggest that policy-makers should focus on the interaction effects of decarbonization pathways between sectors and strengthen their decarbonization efforts to motivate early carbon reduction.
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Affiliation(s)
- Jinchi Dong
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Bofeng Cai
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Shaohui Zhang
- School of Economics and Management, Beihang University, Beijing 100191, China
- International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria
| | - Jinnan Wang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, Jiangsu 210023, China
- Center for Carbon Neutrality, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Hui Yue
- Center for Energy, Environment & Economy Research, School of Management, Zhengzhou University, Zhengzhou 450001, China
- Copernicus Institute of Sustainable Development, Utrecht University, Princetonlaan 8a, 3584 CB Utrecht, Netherlands
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing 100084, China
| | - Xianqiang Mao
- School of Environment, Beijing Normal University, Beijing 100875, China
| | - Jianhui Cong
- School of Economics and Management, Shanxi University, Taiyuan 030000, China
| | - Fei Guo
- International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria
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Qi J, Chen L, Yin P, Zhou M, Peng S, Liu G, Wang L, Noman M, Xie Y, Dong Z, Guo Y. Projecting the excess mortality related to diurnal temperature range: A nationwide analysis in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 864:160971. [PMID: 36535487 DOI: 10.1016/j.scitotenv.2022.160971] [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: 10/05/2022] [Revised: 11/24/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
The projection of excess mortality due to diurnal temperature range (DTR) in future has not been evaluated yet in China. Based on daily cause-specific mortality data from 266 cities in China, this study aimed to examine the association between DTR and mortality, which help project the future mortality burden attributable to DTR by considering the modification effects of altitude and population migration. We first found that every 10 °C increase in the DTR would result in a 3.3 % (95 % confidence interval: 2.6 %-4.1 %) excess risk of non-accidental mortality. The unit risk of DTR-associated cause-specific mortality at moderate or high altitudes was significantly lower than at lower altitudes, especially for cardiovascular disease. Subsequently, DTR-associated excess mortality in 2017 in China was 233,154 deaths (with a population-weighted attributable fraction of 2.9 %). Furthermore, we projected DTR-attributable additional mortality in the future, with the associated mortalities to be 221,860 deaths in 2050-2059 (2050s) and 132,305 deaths in 2090-2099 (2090s), under the SSP1-2.6 scenario. Meanwhile, the regional inequalities were exacerbated by 18 % in 2050s and 13 % in 2090s when considering the modification effects of city altitude. Future population migration would increase excess mortality in most areas in central and southern China, and reduce the disease burden in most areas in eastern, western, and northern China. Our findings underpinned that regional strategies should be adopted to mitigate excess mortality attributable to global climate change.
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Affiliation(s)
- Jinlei Qi
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lili Chen
- Beijing Academy of Blockchain and Edge Computing, Beijing, China
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shushi Peng
- College of Urban and Environmental Sciences, Peking University, China
| | - Gang Liu
- College of Urban and Environmental Sciences, Peking University, China
| | - Lijun Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Muhammad Noman
- School of Space and Environment, Beihang University, Beijing, China
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, China; Laboratory for Low-carbon Intelligent Governance, Beihang University, Beijing, China.
| | - Zhaomin Dong
- School of Space and Environment, Beihang University, Beijing, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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47
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Guo L, Wang L. Peak water: future long-term changes driven by socio-economic development in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:1306-1317. [PMID: 35913694 PMCID: PMC9341153 DOI: 10.1007/s11356-022-21472-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 06/10/2022] [Indexed: 06/15/2023]
Abstract
Population and economic growth cause an increase in water demand leading to ever-increasing water shortage and water crisis. The paper presents China's future long-term changes in water demand driven by socio-economic development based on the construction of a water demand model. At the national and state or provincial level, the water demand model was calibrated and validated with historical data involving developed countries and developing countries, respectively, which exemplifies the feasibility and applicability of the model. Through analyzing the historical data and predicting the future water demand, the following conclusions are obtained. First, total water use in 2013 is not peak water. Second, total water demand is projected to continue increasing to an extent, which would not surge for the next few decades. Third, peak water of around 630 billion m3 may appear in 2026 or 2027. Fourth, the peak water will not be beyond 700 billion m3 issued by the National Comprehensive Water Resources Plan from China, even at the possible peak of population. In general, the water demand model can inform early intervention to prepare for times of scarcity and help track the effectiveness of water policy and management activities.
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Affiliation(s)
- Lishuo Guo
- School of Management Science and Engineering, Hebei University of Economics and Business, Shijiazhuang, 050061, China
- School of Management, Northwestern Polytechnical University, 710129, Xi'an, Shaanxi Province, China
| | - Lifang Wang
- School of Management, Northwestern Polytechnical University, 710129, Xi'an, Shaanxi Province, China.
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Wu J, Luo J, Zhang H, Qin S, Yu M. Projections of land use change and habitat quality assessment by coupling climate change and development patterns. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 847:157491. [PMID: 35870584 DOI: 10.1016/j.scitotenv.2022.157491] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/27/2022] [Accepted: 07/14/2022] [Indexed: 06/15/2023]
Abstract
Exploring future land use changes and assessing the habitat quality remains a challenging topic for watershed ecological sustainability. However, most studies ignore the effects of coupled climate change and development patterns. In this study, a framework for assessing habitat quality under the influence of future land use change is constructed based on exploring the driving forces of land use change factors and integrating the system dynamics (SD) model, future land use simulation (FLUS) model and InVest model. The framework enables the projection of land use change and the assessment of habitat quality in the context of future climate change and different development strategies. Applying the framework to the Weihe River Basin, the main driving forces of land-use change in the Weihe River Basin were identified based on geographical detectors, and habitat quality assessment was realized for the Weihe River Basin under the coupled scenarios of three typical shared socioeconomic pathways and future development patterns (SSP126-EP, SSP245-ND, SSP585-EG). The results show that 1) population, precipitation, and temperature are the major driving factors for land use change. 2) The coupling model of SD and FLUS can effectively simulate the future trend of land use change, the relative error is within 2 %, and the overall accuracy is 93.58 %. 3) Significant differences in habitat quality as a result of modifications in land use patterns in different contexts. Affected by ecological protection, the habitat quality in SSP126-EP was significantly better than that in SSP245-ND and SSP585-EG. This research can provide references for future watershed ecological management decisions.
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Affiliation(s)
- Jingyan Wu
- State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi'an, Shaanxi 710048, China
| | - Jungang Luo
- State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi'an, Shaanxi 710048, China.
| | - Han Zhang
- State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi'an, Shaanxi 710048, China
| | - Shuang Qin
- State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi'an, Shaanxi 710048, China
| | - Mengjie Yu
- State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi'an, Shaanxi 710048, China
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Li J, Chen Y, Cai K, Fu J, Ting T, Chen Y, Folberth C, Liu Y. A high-resolution nutrient emission inventory for hotspot identification in the Yangtze River Basin. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 321:115847. [PMID: 35981504 DOI: 10.1016/j.jenvman.2022.115847] [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: 05/11/2022] [Revised: 07/05/2022] [Accepted: 07/21/2022] [Indexed: 06/15/2023]
Abstract
A high-resolution nutrient emission inventory can provide reliable and accurate identification of priority control areas, which is crucial for efficient decisions on water quality restoration. However, the inventories widely used in large-scale modeling are usually based on provincial inputs, which induce the challenges of lacking localized parameters and missing localized characteristic when provincial scale inputs are converted to finer scales with the down-scale methods. Based on elaborate investigations and statistical data at the county scale with multi-scale data conversion, the China Emission Inventory of Nutrients (CEIN) was developed with a spatial resolution of a 0.1° grid and sub-basin scales. The Yangtze River Basin was used as a case study to illustrate the potential applications of CEIN. The emissions of total nitrogen (TN) and total phosphorus (TP) of Yangtze River Basin is 0.43 Mt and 0.04 Mt for point sources, 11.09 Mt and 4.64 Mt for diffuse sources in 2017. The hotspot analysis for 2606 sub-basins indicated that cropland is the key source of nutrient emissions, accounting for 58.88% and 79.15% of TN and TP, respectively. Industrial sewage and freshwater aquaculture accounted for 27.39% (TN) and 21.98% (TP) of the point sources, which is substantial due to their direct discharge into surface waters. The current results also reveal that, in contrast to CEIN, the previously used common emission factors based on GDP per capita produced considerable overestimations of 2.37 and 2.65 times the actual TN and TP emissions, respectively. Additional advantages of the CEIN have been demonstrated in identifying priority control areas more accurately with reduced bias and quantifying the effects of policies at much smaller scales. For example, the CEIN helps to distinguish hotspots, which was neglected when identifying sources at the level-III sub-basin scale, and indicates that the management of fractional areas (TN: 16.97%; TP: 13.44%) provides the highest nutrient emissions control (TN: 44.34%; TP: 48.65%) for the entire basin. The evaluation of China's toilet revolution policy demonstrates that achieving equitable access to safe sanitation has resulted in a reduction of 7240 t of TN and 833 t of TP, which is extremely critical for rural water quality and health.
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Affiliation(s)
- Jincheng Li
- College of Environmental Sciences and Engineering, State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, Peking University, Beijing, 100871, China
| | - Yan Chen
- United Center for Eco-Environment in Yangtze River Economic Belt, Chinese Academy for Environmental Planning, Beijing, 100012, China
| | - Kaikui Cai
- College of Environmental Sciences and Engineering, State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, Peking University, Beijing, 100871, China
| | - Jiaxing Fu
- College of Environmental Sciences and Engineering, State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, Peking University, Beijing, 100871, China
| | - Tang Ting
- International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1 - A-2361, Laxenburg, Austria.
| | - Yihui Chen
- Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Kunming, 650034, China
| | - Christian Folberth
- International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1 - A-2361, Laxenburg, Austria
| | - Yong Liu
- College of Environmental Sciences and Engineering, State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, Peking University, Beijing, 100871, China.
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Chen H, Zhao L, Cheng L, Zhang Y, Wang H, Gu K, Bao J, Yang J, Liu Z, Huang J, Chen Y, Gao X, Xu Y, Wang C, Cai W, Gong P, Luo Y, Liang W, Huang C. Projections of heatwave-attributable mortality under climate change and future population scenarios in China. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2022; 28:100582. [PMID: 36105236 PMCID: PMC9465423 DOI: 10.1016/j.lanwpc.2022.100582] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Background In China, most previous projections of heat-related mortality have been based on modeling studies using global climate models (GCMs), which can help to elucidate the risks of extreme heat events in a changing climate. However, spatiotemporal changes in the health effects of climate change considering specific regional characteristics remain poorly understood. We aimed to use credible climate and population projections to estimate future heatwave-attributable deaths under different emission scenarios and to explore the drivers underlying these patterns of changes. Methods We derived climate data from a regional climate model driven by three CMIP5 GCM models and calculated future heatwaves in China under Representative Concentration Pathway (RCP) 2.6, RCP4.5, and RCP8.5. The future gridded population data were based on Shared Socioeconomic Pathway 2 assumption with different fertility rates. By applying climate zone-specific exposure-response functions to mortality during heatwave events, we projected the scale of heatwave-attributable deaths under each RCP scenario. We further analyzed the factors driving changes in heatwave-related deaths and main sources of uncertainty using a decomposition method. We compared differences in death burden under the 1.5°C target, which is closely related to achieving carbon neutrality by mid-century. Findings The number of heatwave-related deaths will increase continuously to the mid-century even under RCP2.6 and RCP4.5 scenarios, and will continue increasing throughout the century under RCP8.5. There will be 20,303 deaths caused by heatwaves in 2090 under RCP2.6, 35,025 under RCP4.5, and 72,260 under RCP8.5, with half of all heatwave-related deaths in any scenario concentrated in east and central China. Climate effects are the main driver for the increase in attributable deaths in the near future till 2060, explaining 78% of the total change. Subsequent population decline cannot offset the losses caused by higher incidence of heatwaves and an aging population under RCP8.5. Although health loss under the 1.5°C warming scenario is 1.6-fold higher than the baseline period 1986-2005, limiting the temperature rise to 1.5°C can reduce the annual mortality burden in China by 3,534 deaths in 2090 compared with RCP2.6 scenarios. Interpretation With accelerating climate change and population aging, the effects of future heatwaves on human health in China are likely to increase continuously even under a low emission scenario. Significant health benefits are expected if the optimistic 1.5°C goal is achieved, suggesting that carbon neutrality by mid-century is a critical target for China's sustainable development. Policymakers need to tighten climate mitigation policies tailored to local conditions while enhancing climate resilience technically and infrastructurally, especially for vulnerable elderly people. Funding National Key R&D Program of China (2018YFA0606200), Wellcome Trust (209734/Z/17/Z), Natural Science Foundation of China (41790471), and Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004).
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Affiliation(s)
- Huiqi Chen
- Vanke School of Public Health, Tsinghua University, Beijing, China
- School of Public Health, Sun Yat-sen University, Guangzhou, China
- Shanghai Typhoon Institute, China Meteorological Administration & Shanghai Key Laboratory of Meteorology and Health, Shanghai Meteorological Service, Shanghai, China
| | - Liang Zhao
- The State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Liangliang Cheng
- Vanke School of Public Health, Tsinghua University, Beijing, China
- School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yali Zhang
- School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Huibin Wang
- School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Kuiying Gu
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Junzhe Bao
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jun Yang
- School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Zhao Liu
- School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing, China
| | - Jianbin Huang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Yidan Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
| | - Xuejie Gao
- College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
- Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Ying Xu
- National Climate Center, China Meteorological Administration, Beijing, China
| | - Can Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
| | - Wenjia Cai
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
- State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
| | - Peng Gong
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
- Department of Earth Sciences and Geography, University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yong Luo
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Wannian Liang
- Vanke School of Public Health, Tsinghua University, Beijing, China
- Institute of Healthy China, Tsinghua University, Beijing, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
- Institute of Healthy China, Tsinghua University, Beijing, China
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