The contribution of emission sources to the future air pollution disease burden in China
Air pollution exposure is a leading public health problem in China. Despite recent air quality improvements, fine particulate matter (PM _2.5 ) exposure remains large, the associated disease burden is substantial, and population ageing is projected to increase the susceptibility to disease. Here, we...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2022-01-01
|
| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ac6f6f |
| _version_ | 1797746948196794368 |
|---|---|
| author | Luke Conibear Carly L Reddington Ben J Silver Stephen R Arnold Steven T Turnock Zbigniew Klimont Dominick V Spracklen |
| author_facet | Luke Conibear Carly L Reddington Ben J Silver Stephen R Arnold Steven T Turnock Zbigniew Klimont Dominick V Spracklen |
| author_sort | Luke Conibear |
| collection | DOAJ |
| description | Air pollution exposure is a leading public health problem in China. Despite recent air quality improvements, fine particulate matter (PM _2.5 ) exposure remains large, the associated disease burden is substantial, and population ageing is projected to increase the susceptibility to disease. Here, we used emulators of a regional chemical transport model to quantify the impacts of future emission scenarios on air pollution exposure in China. We estimated how key emission sectors contribute to these future health impacts from air pollution exposure. We found that PM _2.5 exposure declines in all scenarios across China over 2020–2050, with reductions of 15% under current air quality legislation, 36% when exploiting the full potential of air pollutant emission reduction technologies, and 39% when that technical mitigation potential is combined with emission controls for climate mitigation. However, population ageing means that the PM _2.5 disease burden under current legislation (CLE) increases by 17% in 2050 relative to 2020. In comparison to CLE in 2050, the application of the best air pollution technologies provides substantial health benefits, reducing the PM _2.5 disease burden by 16%, avoiding 536 600 (95% uncertainty interval, 95UI: 497 800–573 300) premature deaths per year. These public health benefits are mainly due to reductions in industrial (43%) and residential (30%) emissions. Climate mitigation efforts combined with the best air pollution technologies leads to an additional 2% reduction in the PM _2.5 disease burden, avoiding 57 000 (95UI: 52 800–61 100) premature deaths per year. Up to 90% of the 2020–2050 reductions in PM _2.5 exposure are already achieved by 2030, assuming efficient implementation and enforcement of currently committed air quality policies in key sectors. Achieving reductions in PM _2.5 exposure and the associated disease burden after 2030 will require further tightening of emission limits for regulated sectors, addressing other sources including agriculture and waste management, and international coordinated action to mitigate air pollution across Asia. |
| first_indexed | 2024-03-12T15:45:08Z |
| format | Article |
| id | doaj.art-7b6e2be202904308a16d88ae630f0dd9 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:45:08Z |
| publishDate | 2022-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-7b6e2be202904308a16d88ae630f0dd92023-08-09T15:30:46ZengIOP PublishingEnvironmental Research Letters1748-93262022-01-0117606402710.1088/1748-9326/ac6f6fThe contribution of emission sources to the future air pollution disease burden in ChinaLuke Conibear0https://orcid.org/0000-0003-2801-8862Carly L Reddington1https://orcid.org/0000-0002-5990-4966Ben J Silver2https://orcid.org/0000-0003-0395-0637Stephen R Arnold3https://orcid.org/0000-0002-4881-5685Steven T Turnock4https://orcid.org/0000-0002-0036-4627Zbigniew Klimont5https://orcid.org/0000-0003-2630-198XDominick V Spracklen6https://orcid.org/0000-0002-7551-4597Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds , Leeds, United KingdomInstitute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds , Leeds, United KingdomInstitute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds , Leeds, United KingdomInstitute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds , Leeds, United KingdomMet Office Hadley Centre , Exeter, United Kingdom; University of Leeds Met Office Strategic (LUMOS) Research Group, School of Earth and Environment, University of Leeds , Leeds, United KingdomUniversity of Leeds Met Office Strategic (LUMOS) Research Group, School of Earth and Environment, University of Leeds , Leeds, United KingdomInstitute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds , Leeds, United KingdomAir pollution exposure is a leading public health problem in China. Despite recent air quality improvements, fine particulate matter (PM _2.5 ) exposure remains large, the associated disease burden is substantial, and population ageing is projected to increase the susceptibility to disease. Here, we used emulators of a regional chemical transport model to quantify the impacts of future emission scenarios on air pollution exposure in China. We estimated how key emission sectors contribute to these future health impacts from air pollution exposure. We found that PM _2.5 exposure declines in all scenarios across China over 2020–2050, with reductions of 15% under current air quality legislation, 36% when exploiting the full potential of air pollutant emission reduction technologies, and 39% when that technical mitigation potential is combined with emission controls for climate mitigation. However, population ageing means that the PM _2.5 disease burden under current legislation (CLE) increases by 17% in 2050 relative to 2020. In comparison to CLE in 2050, the application of the best air pollution technologies provides substantial health benefits, reducing the PM _2.5 disease burden by 16%, avoiding 536 600 (95% uncertainty interval, 95UI: 497 800–573 300) premature deaths per year. These public health benefits are mainly due to reductions in industrial (43%) and residential (30%) emissions. Climate mitigation efforts combined with the best air pollution technologies leads to an additional 2% reduction in the PM _2.5 disease burden, avoiding 57 000 (95UI: 52 800–61 100) premature deaths per year. Up to 90% of the 2020–2050 reductions in PM _2.5 exposure are already achieved by 2030, assuming efficient implementation and enforcement of currently committed air quality policies in key sectors. Achieving reductions in PM _2.5 exposure and the associated disease burden after 2030 will require further tightening of emission limits for regulated sectors, addressing other sources including agriculture and waste management, and international coordinated action to mitigate air pollution across Asia.https://doi.org/10.1088/1748-9326/ac6f6fair qualityemulatormachine learningChinaparticulate matterhealth impact assessment |
| spellingShingle | Luke Conibear Carly L Reddington Ben J Silver Stephen R Arnold Steven T Turnock Zbigniew Klimont Dominick V Spracklen The contribution of emission sources to the future air pollution disease burden in China Environmental Research Letters air quality emulator machine learning China particulate matter health impact assessment |
| title | The contribution of emission sources to the future air pollution disease burden in China |
| title_full | The contribution of emission sources to the future air pollution disease burden in China |
| title_fullStr | The contribution of emission sources to the future air pollution disease burden in China |
| title_full_unstemmed | The contribution of emission sources to the future air pollution disease burden in China |
| title_short | The contribution of emission sources to the future air pollution disease burden in China |
| title_sort | contribution of emission sources to the future air pollution disease burden in china |
| topic | air quality emulator machine learning China particulate matter health impact assessment |
| url | https://doi.org/10.1088/1748-9326/ac6f6f |
| work_keys_str_mv | AT lukeconibear thecontributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT carlylreddington thecontributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT benjsilver thecontributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT stephenrarnold thecontributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT steventturnock thecontributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT zbigniewklimont thecontributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT dominickvspracklen thecontributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT lukeconibear contributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT carlylreddington contributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT benjsilver contributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT stephenrarnold contributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT steventturnock contributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT zbigniewklimont contributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina AT dominickvspracklen contributionofemissionsourcestothefutureairpollutiondiseaseburdeninchina |