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基于 CMIP6 模式的 SSP 情景下亚洲地区 PM 空气质量长期暴露的区域特征。

Regional Features of Long-Term Exposure to PM Air Quality over Asia under SSP Scenarios Based on CMIP6 Models.

机构信息

Innovative Meteorological Research Department, National Institute of Meteorological Sciences, Seogwipo-si 63568, Jeju-do, Korea.

Met Office Hadley Centre, Exeter EX1 3PB, UK.

出版信息

Int J Environ Res Public Health. 2021 Jun 25;18(13):6817. doi: 10.3390/ijerph18136817.

DOI:10.3390/ijerph18136817
PMID:34201984
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8297095/
Abstract

This study investigates changes in fine particulate matter (PM) concentration and air-quality index (AQI) in Asia using nine different Coupled Model Inter-Comparison Project 6 (CMIP6) climate model ensembles from historical and future scenarios under shared socioeconomic pathways (SSPs). The results indicated that the estimated present-day PM concentrations were comparable to satellite-derived data. Overall, the PM concentrations of the analyzed regions exceeded the WHO air-quality guidelines, particularly in East Asia and South Asia. In future SSP scenarios that consider the implementation of significant air-quality controls (SSP1-2.6, SSP5-8.5) and medium air-quality controls (SSP2-4.5), the annual PM levels were predicted to substantially reduce (by 46% to around 66% of the present-day levels) in East Asia, resulting in a significant improvement in the AQI values in the mid-future. Conversely, weak air pollution controls considered in the SSP3-7.0 scenario resulted in poor AQI values in China and India. Moreover, a predicted increase in the percentage of aged populations (>65 years) in these regions, coupled with high AQI values, may increase the risk of premature deaths in the future. This study also examined the regional impact of PM mitigations on downward shortwave energy and surface air temperature. Our results revealed that, although significant air pollution controls can reduce long-term exposure to PM, it may also contribute to the warming of near- and mid-future climates.

摘要

本研究使用来自共享社会经济路径(SSP)下历史和未来情景的九个不同耦合模式比较计划第六阶段(CMIP6)气候模型集合,调查了亚洲细颗粒物(PM)浓度和空气质量指数(AQI)的变化。结果表明,估算的当前 PM 浓度与卫星衍生数据相当。总体而言,分析区域的 PM 浓度超过了世界卫生组织的空气质量指南,特别是在东亚和南亚。在考虑实施重大空气质量控制(SSP1-2.6、SSP5-8.5)和中等空气质量控制(SSP2-4.5)的未来 SSP 情景中,预计东亚的年 PM 水平将大幅降低(目前水平的 46%至 66%左右),从而在中期内显著改善 AQI 值。相比之下,SSP3-7.0 情景中考虑的空气污染控制较弱,导致中国和印度的 AQI 值较差。此外,这些地区老年人口(>65 岁)比例的预测增加,加上高 AQI 值,可能会增加未来过早死亡的风险。本研究还检查了 PM 缓解对短波能量和地表空气温度的区域影响。我们的结果表明,尽管重大空气污染控制可以减少长期暴露于 PM,但它也可能导致近中期气候变暖。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/203a6cbd9ca7/ijerph-18-06817-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/ae14f819abc9/ijerph-18-06817-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/0c4852b263a0/ijerph-18-06817-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/1a3943d39a73/ijerph-18-06817-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/2027df94cf30/ijerph-18-06817-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/7e9f425a2d08/ijerph-18-06817-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/193ca828fc04/ijerph-18-06817-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/ac67ae853da2/ijerph-18-06817-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/6035ee67352d/ijerph-18-06817-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/4ee9827ce92b/ijerph-18-06817-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/203a6cbd9ca7/ijerph-18-06817-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/ae14f819abc9/ijerph-18-06817-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/0c4852b263a0/ijerph-18-06817-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/1a3943d39a73/ijerph-18-06817-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/2027df94cf30/ijerph-18-06817-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/7e9f425a2d08/ijerph-18-06817-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/193ca828fc04/ijerph-18-06817-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/ac67ae853da2/ijerph-18-06817-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/6035ee67352d/ijerph-18-06817-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/4ee9827ce92b/ijerph-18-06817-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8297095/203a6cbd9ca7/ijerph-18-06817-g010.jpg

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