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      Substantial differences in source contributions to carbon emissions and health damage necessitate balanced synergistic control plans in China

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          Abstract

          China’s strategy to concurrently address climate change and air pollution mitigation is hindered by a lack of comprehensive information on source contributions to health damage and carbon emissions. Here we show notable discrepancies between source contributions to CO 2 emissions and fine particulate matter (PM 2.5)-related mortality by using adjoint emission sensitivity modeling to attribute premature mortality in 2017 to 53 sector and fuel/process combinations with high spatial resolution. Our findings reveal that monetized PM 2.5 health damage exceeds climate impacts in over half of the analyzed subsectors. In addition to coal-fired energy generators and industrial boilers, the combined health and climate costs from energy-intensive processes, diesel-powered vehicles, domestic coal combustion, and agricultural activities exceed 100 billion US dollars, with health-related costs predominating. This research highlights the critical need to integrate the social costs of health damage with climate impacts to develop more balanced mitigation strategies toward these dual goals, particularly during fuel transition and industrial structure upgrading.

          Abstract

          Comprehensive modeling analysis reveals significant differences in the source contribution of PM 2.5-related mortality and CO 2 emissions in China, highlighting the need for a balanced approach to synergistic control.

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          Most cited references52

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          Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015

          Summary Background Exposure to ambient air pollution increases morbidity and mortality, and is a leading contributor to global disease burden. We explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels. Methods We estimated global population-weighted mean concentrations of particle mass with aerodynamic diameter less than 2·5 μm (PM2·5) and ozone at an approximate 11 km × 11 km resolution with satellite-based estimates, chemical transport models, and ground-level measurements. Using integrated exposure–response functions for each cause of death, we estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using non-linear exposure–response functions spanning the global range of exposure. Findings Ambient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000–422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015. Interpretation Ambient air pollution contributed substantially to the global burden of disease in 2015, which increased over the past 25 years, due to population ageing, changes in non-communicable disease rates, and increasing air pollution in low-income and middle-income countries. Modest reductions in burden will occur in the most polluted countries unless PM2·5 values are decreased substantially, but there is potential for substantial health benefits from exposure reduction. Funding Bill & Melinda Gates Foundation and Health Effects Institute.
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            The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview

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              The contribution of outdoor air pollution sources to premature mortality on a global scale.

              Assessment of the global burden of disease is based on epidemiological cohort studies that connect premature mortality to a wide range of causes, including the long-term health impacts of ozone and fine particulate matter with a diameter smaller than 2.5 micrometres (PM2.5). It has proved difficult to quantify premature mortality related to air pollution, notably in regions where air quality is not monitored, and also because the toxicity of particles from various sources may vary. Here we use a global atmospheric chemistry model to investigate the link between premature mortality and seven emission source categories in urban and rural environments. In accord with the global burden of disease for 2010 (ref. 5), we calculate that outdoor air pollution, mostly by PM2.5, leads to 3.3 (95 per cent confidence interval 1.61-4.81) million premature deaths per year worldwide, predominantly in Asia. We primarily assume that all particles are equally toxic, but also include a sensitivity study that accounts for differential toxicity. We find that emissions from residential energy use such as heating and cooking, prevalent in India and China, have the largest impact on premature mortality globally, being even more dominant if carbonaceous particles are assumed to be most toxic. Whereas in much of the USA and in a few other countries emissions from traffic and power generation are important, in eastern USA, Europe, Russia and East Asia agricultural emissions make the largest relative contribution to PM2.5, with the estimate of overall health impact depending on assumptions regarding particle toxicity. Model projections based on a business-as-usual emission scenario indicate that the contribution of outdoor air pollution to premature mortality could double by 2050.
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                Author and article information

                Contributors
                ylchen2023@pku.edu.cn
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                13 July 2024
                13 July 2024
                2024
                : 15
                : 5880
                Affiliations
                [1 ]School of Urban Planning and Design, Peking University Shenzhen Graduate School, ( https://ror.org/02v51f717) Shenzhen, 518055 China
                [2 ]Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, ( https://ror.org/049tv2d57) Shenzhen, 518055 China
                [3 ]Guangdong Provincial Observation and Research Station for Coastal Atmosphere and Climate of the Greater Bay Area, School of Environmental Science and Engineering, Southern University of Science and Technology, ( https://ror.org/049tv2d57) Shenzhen, 518055 China
                [4 ]College of Urban and Environmental Sciences, Peking University, ( https://ror.org/02v51f717) Beijing, 100871 China
                [5 ]Max Planck Institute for Chemistry, ( https://ror.org/02f5b7n18) Mainz, 55128 Germany
                [6 ]School of Civil and Environmental Engineering, Georgia Institute of Technology, ( https://ror.org/01zkghx44) Atlanta, GA 30332 USA
                [7 ]Department of Civil and Environmental Engineering, Carleton University, ( https://ror.org/02qtvee93) Ottawa, ON K1S5B6 Canada
                Author information
                http://orcid.org/0000-0001-5532-4115
                http://orcid.org/0000-0003-1335-8477
                http://orcid.org/0000-0002-7731-5399
                http://orcid.org/0000-0002-6593-570X
                http://orcid.org/0000-0003-4912-9879
                http://orcid.org/0000-0003-2027-8870
                http://orcid.org/0000-0003-3122-9548
                http://orcid.org/0000-0002-7374-7063
                Article
                50327
                10.1038/s41467-024-50327-8
                11245606
                38997317
                c267147a-3bdb-401a-8cdd-940dfdb01cef
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 July 2023
                : 4 July 2024
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 42207116
                Award ID: 42192510
                Award Recipient :
                Funded by: fellowship of China Postdoctoral Science Foundation (2021M701573)
                Funded by: FundRef https://doi.org/10.13039/501100002855, Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology);
                Award ID: 2023YFE0112900
                Award Recipient :
                Funded by: the Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks (ZDSYS20220606100604008), Shenzhen Science and Technology Program (JCYJ20220818100611024), Department of Science and Technology of Guangdong Province (2021B1212050024 and 2020B1111360001), Department of Education of Guangdong Province (2021KCXTD004), High level of special funds (G03050K001 and G030290001)
                Funded by: FundRef https://doi.org/10.13039/100007225, Ministry of Science and Technology (Ministry of Science and Technology of the Socialist Republic of Vietnam);
                Award ID: 2023YFE0112900
                Award Recipient :
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