Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China.
State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China.
Environ Sci Technol. 2024 May 21;58(20):8685-8695. doi: 10.1021/acs.est.4c02264. Epub 2024 May 6.
Forecasting alterations in ambient air pollution and the consequent health implications is crucial for safeguarding public health, advancing environmental sustainability, informing economic decision making, and promoting appropriate policy and regulatory action. However, predicting such changes poses a substantial challenge, requiring accurate data, sophisticated modeling methodologies, and a meticulous evaluation of multiple drivers. In this study, we calculate premature deaths due to ambient fine particulate matter (PM) exposure in India from the 2020s (2016-2020) to the 2100s (2095-2100) under four different socioeconomic and climate scenarios (SSPs) based on four CMIP6 models. PM concentrations decreased in all SSP scenarios except for SSP3-7.0, with the lowest concentration observed in SSP1-2.6. The results indicate an upward trend in the five-year average number of deaths across all scenarios, ranging from 1.01 million in the 2020s to 4.12-5.44 million in the 2100s. Further analysis revealed that the benefits of reducing PM concentrations under all scenarios are largely mitigated by population aging and growth. These findings underscore the importance of proactive measures and an integrated approach in India to improve atmospheric quality and reduce vulnerability to aging under changing climate conditions.
预测环境空气污染的变化及其对健康的影响对于保护公众健康、推进环境可持续性、为经济决策提供信息以及推动适当的政策和监管行动至关重要。然而，预测这种变化带来了巨大的挑战，需要准确的数据、复杂的建模方法以及对多种驱动因素的细致评估。在这项研究中，我们根据四个 CMIP6 模型，在四个社会经济和气候情景（SSP）下，计算了印度 21 世纪（2095-2100 年）因环境细颗粒物（PM）暴露导致的过早死亡人数。除了 SSP3-7.0 之外，所有 SSP 情景下的 PM 浓度都有所下降，在 SSP1-2.6 下浓度最低。结果表明，所有情景下的五年平均死亡人数呈上升趋势，从 2020 年代的 101 万人增加到 2100 年代的 412 万至 544 万人。进一步分析表明，所有情景下降低 PM 浓度的好处在很大程度上被人口老龄化和增长所抵消。这些发现强调了印度采取积极措施和综合方法的重要性，以改善大气质量并减少在不断变化的气候条件下的脆弱性。
