代表性浓度途径
气候变化
空气污染
温室气体
地理
环境科学
人口
环境卫生
社会经济地位
环境保护
气候模式
自然资源经济学
医学
生物
生态学
经济
作者
Vijendra Ingole,Asya Dimitrova,Jon Sampedro,Charfudin Sacoor,Sozinho Ácacio,Sanjay Juvekar,Sudipto Roy,Paula Moraga,Xavier Basagaña,Joan Ballester,Josep M. Antó,Cathryn Tonne
标识
DOI:10.1016/j.scitotenv.2022.153832
摘要
The health impacts of global climate change mitigation will affect local populations differently. However, most co-benefits analyses have been done at a global level, with relatively few studies providing local level results. We aimed to quantify the local health impacts due to fine particles (PM2.5) under the governance arrangements embedded in the Shared Socioeconomic Pathways (SSPs1-5) under two greenhouse gas concentration scenarios (Representative Concentration Pathways (RCPs) 2.6 and 8.5) in local populations of Mozambique, India, and Spain. We simulated the SSP-RCP scenarios using the Global Change Analysis Model, which was linked to the TM5-FASST model to estimate PM2.5 levels. PM2.5 levels were calibrated with local measurements. We used comparative risk assessment methods to estimate attributable premature deaths due to PM2.5 linking local population and mortality data with PM2.5-mortality relationships from the literature, and incorporating population projections under the SSPs. PM2.5 attributable burdens in 2050 differed across SSP-RCP scenarios, and sensitivity of results across scenarios varied across populations. Future attributable mortality burden of PM2.5 was highly sensitive to assumptions about how populations will change according to SSP. SSPs reflecting high challenges for adaptation (SSPs 3 and 4) consistently resulted in the highest PM2.5 attributable burdens mid-century. Our analysis of local PM2.5 attributable premature deaths under SSP-RCP scenarios in three local populations highlights the importance of both socioeconomic development and climate policy in reducing the health burden from air pollution. Sensitivity of future PM2.5 mortality burden to SSPs was particularly evident in low- and middle- income country settings due either to high air pollution levels or dynamic populations.
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