Air quality and health co-benefits of climate change mitigation and adaptation actions by 2030 : an interdisciplinary modeling study in Ahmedabad, India
© 2023 Natural Resources Defense Council..
Climate change-driven temperature increases worsen air quality in places where coal combustion powers electricity for air conditioning. Climate solutions that substitute clean and renewable energy in place of polluting coal and promote adaptation to warming through reflective cool roofs can reduce cooling energy demand in buildings, lower power sector carbon emissions, and improve air quality and health. We investigate the air quality and health co-benefits of climate solutions in Ahmedabad, India-a city where air pollution levels exceed national health-based standards-through an interdisciplinary modeling approach. Using a 2018 baseline, we quantify changes in fine particulate matter (PM2.5) air pollution and all-cause mortality in 2030 from increasing renewable energy use (mitigation) and expanding Ahmedabad's cool roofs heat resilience program (adaptation). We apply local demographic and health data and compare a 2030 mitigation and adaptation (M&A) scenario to a 2030 business-as-usual (BAU) scenario (without climate change response actions), each relative to 2018 pollution levels. We estimate that the 2030 BAU scenario results in an increase of PM2.5 air pollution of 4.13 µg m-3 from 2018 compared to a 0.11 µg m-3 decline from 2018 under the 2030 M&A scenario. Reduced PM2.5 air pollution under 2030 M&A results in 1216-1414 fewer premature all-cause deaths annually compared to 2030 BAU. Achievement of National Clean Air Programme, National Ambient Air Quality Standards, or World Health Organization annual PM2.5 Air Quality Guideline targets in 2030 results in up to 6510, 9047, or 17 369 fewer annual deaths, respectively, relative to 2030 BAU. This comprehensive modeling method is adaptable to estimate local air quality and health co-benefits in other settings by integrating climate, energy, cooling, land cover, air pollution, and health data. Our findings demonstrate that city-level climate change response policies can achieve substantial air quality and health co-benefits. Such work can inform public discourse on the near-term health benefits of mitigation and adaptation.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:1 |
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| Enthalten in: |
Environmental research, health : ERH - 1(2023), 2 vom: 01. Juni, Seite 021003 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Limaye, Vijay S [VerfasserIn] |
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| Links: |
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| Themen: |
Adaptation |
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| Anmerkungen: |
Date Revised 07.03.2023 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1088/2752-5309/aca7d8 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM353792977 |
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| 100 | 1 | |a Limaye, Vijay S |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Air quality and health co-benefits of climate change mitigation and adaptation actions by 2030 |b an interdisciplinary modeling study in Ahmedabad, India |
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| 520 | |a © 2023 Natural Resources Defense Council. | ||
| 520 | |a Climate change-driven temperature increases worsen air quality in places where coal combustion powers electricity for air conditioning. Climate solutions that substitute clean and renewable energy in place of polluting coal and promote adaptation to warming through reflective cool roofs can reduce cooling energy demand in buildings, lower power sector carbon emissions, and improve air quality and health. We investigate the air quality and health co-benefits of climate solutions in Ahmedabad, India-a city where air pollution levels exceed national health-based standards-through an interdisciplinary modeling approach. Using a 2018 baseline, we quantify changes in fine particulate matter (PM2.5) air pollution and all-cause mortality in 2030 from increasing renewable energy use (mitigation) and expanding Ahmedabad's cool roofs heat resilience program (adaptation). We apply local demographic and health data and compare a 2030 mitigation and adaptation (M&A) scenario to a 2030 business-as-usual (BAU) scenario (without climate change response actions), each relative to 2018 pollution levels. We estimate that the 2030 BAU scenario results in an increase of PM2.5 air pollution of 4.13 µg m-3 from 2018 compared to a 0.11 µg m-3 decline from 2018 under the 2030 M&A scenario. Reduced PM2.5 air pollution under 2030 M&A results in 1216-1414 fewer premature all-cause deaths annually compared to 2030 BAU. Achievement of National Clean Air Programme, National Ambient Air Quality Standards, or World Health Organization annual PM2.5 Air Quality Guideline targets in 2030 results in up to 6510, 9047, or 17 369 fewer annual deaths, respectively, relative to 2030 BAU. This comprehensive modeling method is adaptable to estimate local air quality and health co-benefits in other settings by integrating climate, energy, cooling, land cover, air pollution, and health data. Our findings demonstrate that city-level climate change response policies can achieve substantial air quality and health co-benefits. Such work can inform public discourse on the near-term health benefits of mitigation and adaptation | ||
| 650 | 4 | |a Journal Article | |
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| 650 | 4 | |a adaptation | |
| 650 | 4 | |a air pollution | |
| 650 | 4 | |a climate change | |
| 650 | 4 | |a co-benefits | |
| 650 | 4 | |a health | |
| 650 | 4 | |a mitigation | |
| 700 | 1 | |a Magal, Akhilesh |e verfasserin |4 aut | |
| 700 | 1 | |a Joshi, Jaykumar |e verfasserin |4 aut | |
| 700 | 1 | |a Maji, Sujit |e verfasserin |4 aut | |
| 700 | 1 | |a Dutta, Priya |e verfasserin |4 aut | |
| 700 | 1 | |a Rajput, Prashant |e verfasserin |4 aut | |
| 700 | 1 | |a Pingle, Shyam |e verfasserin |4 aut | |
| 700 | 1 | |a Madan, Prima |e verfasserin |4 aut | |
| 700 | 1 | |a Mukerjee, Polash |e verfasserin |4 aut | |
| 700 | 1 | |a Bano, Shahana |e verfasserin |4 aut | |
| 700 | 1 | |a Beig, Gufran |e verfasserin |4 aut | |
| 700 | 1 | |a Mavalankar, Dileep |e verfasserin |4 aut | |
| 700 | 1 | |a Jaiswal, Anjali |e verfasserin |4 aut | |
| 700 | 1 | |a Knowlton, Kim |e verfasserin |4 aut | |
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