Climate Penalty on Air Pollution Mitigated by Anthropogenic Emission Reductions in the United States

LIFEI YIN, Qiao Zhu, Bin Bai, Bingqing Zhang, Qian Di, Weeberb Requia, Loretta Mickley, Joel Schwartz, Liuhua Shi, Pengfei Liu, Georgia Institute of Technology

     Abstract Number: 185
     Working Group: Health-Related Aerosols

Abstract
Climate change is one of the greatest global challenges in the 21^st century, exerting adverse impacts on human health. Previous studies have proposed numerous pathways for the health impact of climate change and have evaluated the health burden associated with rising temperature. One potential pathway is through interactions with air pollution, as a rising temperature can worsen air quality even in the absence of changes in anthropogenic activities, known as the “climate penalty” on air quality. However, how a warmer temperature deteriorates air quality remains highly uncertain in the United States, particularly under rapid reduction in anthropogenic emissions in recent decades. Here we examined the sensitivity of surface-level fine particulate matter (PM_2.5) and ozone (O₃) to summer temperature anomalies in the contiguous US and their decadal changes using high-resolution datasets generated by machine learning models. The machine learning datasets successfully reproduced the temperature sensitivities of PM_2.5 and O₃ observed at ground stations and provided a more representative regional sensitivity by completing the picture for areas without stations. Our findings demonstrate that, in the eastern US, efficient emission control strategies have largely reduced the climate penalty effects on PM_2.5 and O₃, lowering the population exposure and associated health risks. In contrast, summer and annual PM_2.5 in the western US have become more sensitive to summer temperature, highlighting the urgent need for the management and mitigation of worsening wildfires. The generated high-resolution data of temperature sensitivity of PM_2.5 and O₃ are helpful in evaluating the performance of chemistry transport models in capturing the response of air pollution to climate change. The evolution of temperature sensitivity of air pollutants with emission changes indicates that factors controlling air quality are not independent. The interactions should be considered when using models to predict future air quality.