Yin Lifei, Bai Bin, Zhang Bingqing, Zhu Qiao, Di Qian, Requia Weeberb J, Schwartz Joel D, Shi Liuhua, Liu Pengfei
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA.
Res Sq. 2023 Aug 16:rs.3.rs-3245771. doi: 10.21203/rs.3.rs-3245771/v1.
Climate change poses direct and indirect threats to public health, including exacerbating air pollution. However, how a warmer temperature deteriorates air quality, known as the "climate penalty" effect, remains highly uncertain in the United States, particularly under rapid reduction in anthropogenic emissions. Here we examined the sensitivity of surface-level fine particulate matter (PM) and ozone (O) to summer temperature anomalies in the contiguous US and their decadal changes using high-resolution datasets generated by machine learning models. Our findings demonstrate that, in the eastern US, efficient emission control strategies have significantly reduced the climate penalty effects on PM and O, lowering the associated population exposure. In contrast, summer and annual PM in the western US became more sensitive to temperature, highlighting the urgent need for the management and mitigation of worsening wildfires. Our results have important implications for air quality management and risk assessments of future climate change.
气候变化对公众健康构成直接和间接威胁,包括加剧空气污染。然而,在美国,气温升高如何恶化空气质量,即所谓的“气候惩罚”效应,仍高度不确定,尤其是在人为排放迅速减少的情况下。在此,我们使用机器学习模型生成的高分辨率数据集,研究了美国本土地表细颗粒物(PM)和臭氧(O)对夏季温度异常及其年代际变化的敏感性。我们的研究结果表明,在美国东部,有效的排放控制策略显著降低了气候惩罚对PM和O的影响,减少了相关的人口暴露。相比之下,美国西部夏季和年度PM对温度变得更加敏感,凸显了管理和减轻日益严重的野火的迫切需要。我们的结果对空气质量管理和未来气候变化风险评估具有重要意义。