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Liu J, Ye Z, Christensen JH, Dong S, Geels C, Brandt J, Nenes A, Yuan Y, Im U. Impact of anthropogenic emission control in reducing future PM 2.5 concentrations and the related oxidative potential across different regions of China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170638. [PMID: 38316299 DOI: 10.1016/j.scitotenv.2024.170638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/29/2024] [Accepted: 01/31/2024] [Indexed: 02/07/2024]
Abstract
Affected by both future anthropogenic emissions and climate change, future prediction of PM2.5 and its Oxidative Potential (OP) distribution is a significant challenge, especially in developing countries like China. To overcome this challenge, we estimated historical and future PM2.5 concentrations and associated OP using the Danish Eulerian Hemispheric Model (DEHM) system with meteorological input from WRF weather forecast model. Considering different future socio-economic pathways and emission scenario assumptions, we quantified how the contribution from various anthropogenic emission sectors will change under these scenarios. Results show that compared to the CESM_SSP2-4.5_CLE scenario (based on moderate radiative forcing and Current Legislation Emission), the CESM_SSP1-2.6_MFR scenario (based on sustainability development and Maximum Feasible Reductions) is projected to yield greater environmental and health benefits in the future. Under the CESM_SSP1-2.6_MFR scenario, annual average PM2.5 concentrations (OP) are expected to decrease to 30 (0.8 nmolmin-1m-3) in almost all regions by 2030, which will be 65 % (67 %) lower than that in 2010. From a long-term perspective, it is anticipated that OP in the Fen-Wei Plain region will experience the maximum reduction (82.6 %) from 2010 to 2049. Largely benefiting from the effective control of PM2.5 in the region, it has decreased by 82.1 %. Crucially, once emission reduction measures reach a certain level (in 2040), further reductions become less significant. This study also emphasized the significant role of secondary aerosol formation and biomass-burning sources in influencing OP during both historical and future periods. In different scenarios, the reduction range of OP from 2010 to 2049 is estimated to be between 71 % and 85 % by controlling precursor emissions involved in secondary aerosol formation and emissions from biomass burning. Results indicate that strengthening the control of anthropogenic emissions in various regions are key to achieving air quality targets and safeguarding human health in the future.
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Affiliation(s)
- Jiemei Liu
- Key Laboratory of Aerospace Thermophysics, Ministry of Industry and Information Technology, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China; Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Zhuyun Ye
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Jesper H Christensen
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Shikui Dong
- Key Laboratory of Aerospace Thermophysics, Ministry of Industry and Information Technology, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China
| | - Camilla Geels
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Jørgen Brandt
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark
| | - Athanasios Nenes
- Laboratory of Atmospheric Processes and Their Impacts, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Center for the Study of Air Quality and Climate Change, Foundation for Research and Technology Hellas (FORTH), Thessaloniki, Greece
| | - Yuan Yuan
- Key Laboratory of Aerospace Thermophysics, Ministry of Industry and Information Technology, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China.
| | - Ulas Im
- Aarhus University, Department of Environmental Science/Interdisciplinary Centre for Climate Change, Frederiksborgvej 399, Roskilde, Denmark.
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Huo L. Haze pollution and urban sprawl: An empirical analysis based on panel simultaneous equation model. PLoS One 2024; 19:e0296814. [PMID: 38421968 PMCID: PMC10903875 DOI: 10.1371/journal.pone.0296814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 12/19/2023] [Indexed: 03/02/2024] Open
Abstract
Based on the panel data of 227 prefecture-level and above cities in China from 2002 to 2018, a panel linkage equation model is constructed to explore the bidirectional influence relationship between haze pollution and urban sprawl, and the results of the study find that, firstly, there is a bidirectional promotion of causality between haze pollution and urban sprawl. That is, PM2.5 not only has a significant positive effect on urban sprawl, but also urban sprawl has a significant positive correlation with haze pollution, which is further strengthened by adding the air flow coefficient instrumental variable. Second, the heterogeneity analysis yields that haze pollution has different effects on urban sprawl in different regions. Under the sub-regional samples, haze pollution and urban sprawl have a bi-directional significant negative impact relationship in the eastern region, none of the haze pollution and urban sprawl have a bi-directional significant impact relationship in the western region, but both the central region and the northeastern region have a significant positive impact relationship. Under different city sizes, haze pollution and urban sprawl in large, medium and small cities have a bi-directional significant positive impact relationship, and from the numerical size, the degree of influence of haze pollution on urban sprawl in large cities is greater than that in small and medium cities; while the degree of influence of urban sprawl on haze pollution in medium cities is greater than that in large and small cities. Accordingly, it is proposed that urban governance should be adapted to local conditions, focus on innovative technologies to reduce energy consumption, and utilize big data to manage cities.
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Affiliation(s)
- Luping Huo
- College of Economics and Finance, Xi’an International Studies University, Xi’an, China
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McNeil W, Tong F, Harley RA, Auffhammer M, Scown CD. Corridor-Level Impacts of Battery-Electric Heavy-Duty Trucks and the Effects of Policy in the United States. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:33-42. [PMID: 38109378 PMCID: PMC10785805 DOI: 10.1021/acs.est.3c05139] [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: 06/30/2023] [Revised: 09/15/2023] [Accepted: 11/15/2023] [Indexed: 12/20/2023]
Abstract
Electrifying freight trucks will be key to alleviating air pollution burdens on disadvantaged communities and mitigating climate change. The United States plans to pursue this aim by adding vehicle charging infrastructure along specific freight corridors. This study explores the coevolution of the electricity grid and freight trucking landscape using an integrated assessment framework to identify when each interstate and drayage corridor becomes advantageous to electrify from a climate and human health standpoint. Nearly all corridors achieve greenhouse gas emission reductions if electrified now. Most can reduce health impacts from air pollution if electrified by 2040 although some corridors in the Midwest, South, and Mid-Atlantic regions remain unfavorable to electrify from a human health standpoint, absent policy support. Recent policy, namely, the Inflation Reduction Act, accelerates this timeline to 2030 for most corridors and results in net human health benefits on all corridors by 2050, suggesting that near-term investments in truck electrification, particularly drayage corridors, can meaningfully reduce climate and health burdens.
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Affiliation(s)
- Wilson
H. McNeil
- Energy
Technologies Area, Lawrence Berkeley National
Laboratory, Berkeley, California 94720, United States
- Department
of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United States
- Department
of Civil and Natural Resources Engineering, University of Canterbury, Christchurch 8041, New Zealand
| | - Fan Tong
- School
of Economics and Management, Beihang University, Beijing 100191, People’s Republic of China
- Lab
for Low-carbon Intelligent Governance, Beihang
University, Beijing 100191, People’s Republic
of China
- Peking
University Ordos Research Institute of Energy, Ordos City 017000, Inner Mongolia, People’s Republic of
China
| | - Robert A. Harley
- Department
of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California 94720, United States
| | - Maximilian Auffhammer
- Energy
Technologies Area, Lawrence Berkeley National
Laboratory, Berkeley, California 94720, United States
- Department
of Agricultural and Resource Economics, University of California, Berkeley, Berkeley, California 94720, United States
- National
Bureau of Economic Research, Cambridge, Massachusetts 02138, United States
| | - Corinne D. Scown
- Energy
Technologies Area, Lawrence Berkeley National
Laboratory, Berkeley, California 94720, United States
- Life-Cycle,
Economics and Agronomy Division, Joint BioEnergy
Institute, Emeryville, California 94608, United States
- Biosciences
Area, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
- Energy
and Biosciences Institute, University of
California, Berkeley, Berkeley, California 94720, United States
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Chen W, Lu X, Yuan D, Chen Y, Li Z, Huang Y, Fung T, Sun H, Fung JCH. Global PM 2.5 Prediction and Associated Mortality to 2100 under Different Climate Change Scenarios. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023. [PMID: 37377020 DOI: 10.1021/acs.est.3c03804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
Ambient fine particulate matter (PM2.5) has severe adverse health impacts, making it crucial to reduce PM2.5 exposure for public health. Meteorological and emissions factors, which considerably affect the PM2.5 concentrations in the atmosphere, vary substantially under different climate change scenarios. In this work, global PM2.5 concentrations from 2021 to 2100 were generated by combining the deep learning technique, reanalysis data, emission data, and bias-corrected CMIP6 future climate scenario data. Based on the estimated PM2.5 concentrations, the future premature mortality burden was assessed using the Global Exposure Mortality Model. Our results reveal that SSP3-7.0 scenario is associated with the highest PM2.5 exposure, with a global concentration of 34.5 μg/m3 in 2100, while SSP1-2.6 scenario has the lowest exposure, with an estimated of 15.7 μg/m3 in 2100. PM2.5-related deaths for individuals under 75 years will decrease by 16.3 and 10.5% under SSP1-2.6 and SSP5-8.5, respectively, from 2030s to 2090s. However, premature mortality for elderly individuals (>75 years) will increase, causing the contrary trends of improved air quality and increased total PM2.5-related deaths in the four SSPs. Our results emphasize the need for stronger air pollution mitigation measures to offset the future burden posed by population age.
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Affiliation(s)
- Wanying Chen
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
- Atmospheric Research Center, Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China
| | - Xingcheng Lu
- Department of Geography and Resource Management, Chinese University of Hong Kong, Hong Kong SAR 999077, China
| | - Dehao Yuan
- Department of Computer Science, University of Maryland, College Park, Maryland 20742, United States
| | - Yiang Chen
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
- Atmospheric Research Center, Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China
| | - Zhenning Li
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
| | - Yeqi Huang
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
| | - Tung Fung
- Department of Geography and Resource Management, Chinese University of Hong Kong, Hong Kong SAR 999077, China
| | - Haochen Sun
- Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
- Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
| | - Jimmy C H Fung
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
- Atmospheric Research Center, Guangzhou HKUST Fok Ying Tung Research Institute, Guangzhou 511458, China
- Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
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Leão MLP, Zhang L, da Silva Júnior FMR. Effect of particulate matter (PM 2.5 and PM 10) on health indicators: climate change scenarios in a Brazilian metropolis. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 45:2229-2240. [PMID: 35870077 PMCID: PMC9308372 DOI: 10.1007/s10653-022-01331-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 06/27/2022] [Indexed: 05/23/2023]
Abstract
Recife is recognized as the 16th most vulnerable city to climate change in the world. In addition, the city has levels of air pollutants above the new limits proposed by the World Health Organization (WHO) in 2021. In this sense, the present study had two main objectives: (1) To evaluate the health (and economic) benefits related to the reduction in mean annual concentrations of PM10 and PM2.5 considering the new limits recommended by the WHO: 15 µg/m3 (PM10) and 5 µg/m3 (PM2.5) and (2) To simulate the behavior of these pollutants in scenarios with increased temperature (2 and 4 °C) using machine learning. The averages of PM2.5 and PM10 were above the limits recommended by the WHO. The scenario simulating the reduction in these pollutants below the new WHO limits would avoid more than 130 deaths and 84 hospital admissions for respiratory or cardiovascular problems. This represents a gain of 15.2 months in life expectancy and a cost of almost 160 million dollars. Regarding the simulated temperature increase, the most conservative (+ 2 °C) and most drastic (+ 4 °C) scenarios predict an increase of approximately 6.5 and 15%, respectively, in the concentrations of PM2.5 and PM10, with a progressive increase in deaths attributed to air pollution. The study shows that the increase in temperature will have impacts on air particulate matter and health outcomes. Climate change mitigation and pollution control policies must be implemented for meeting new WHO air quality standards which may have health benefits.
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Affiliation(s)
- Marcos Lorran Paranhos Leão
- Faculdade de Ciências Médicas (FCM) e Hospital, Universitário Oswaldo Cruz (HUOC) da Universidade de Pernambuco (UPE), Campus Santo Amaro, Recife. Rua Arnóbio Marques, 310 - Santo Amaro, Recife, PE, CEP: 50100-130, Brazil
| | - Linjie Zhang
- Universidade Federal do Rio Grande, Rua Visconde de Paranaguá 102 Centro, Rio Grande, RS, CEP: 96203-900, Brazil
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