Climate Change and Future Air Pollution Mortality: Exploration of Scenarios and Benefits of Actions Using Global Atmospheric Modeling
Jason West, Ph.D.
NIEHS Grant: R21ES022600
Climate change is likely to profoundly influence air quality, with impacts on human health. Conversely, actions to address climate change are expected to benefit air quality and health, both by reducing co-emitted air pollutants and by slowing the effects of climate change on air quality. Our overall goals are to quantify the effects of climate change on global human health through changes in air quality, in the past and in future scenarios, and to quantify the air quality and health benefits of actions to slow climate change. This is done by combining global atmospheric modeling with methods of assessing human health impacts, in simulations reflecting climate change, future emission projections, and policies to reduce emissions.
In Aim 1, we will assess premature human mortality caused by exposure to outdoor ozone and fine particulate matter (PM2.5) for current simulations from an ensemble of global climate-chemistry models. For the present, we will attribute mortalities to anthropogenic air pollution and the component attributable to climate change, which has not been quantified previously. We will likewise model future air pollution mortality to 2100 in four scenarios, and attribute changes in mortality to changes in pollutant emissions and changes in climate. By analyzing global distributions, we will identify the populations most vulnerable to air pollution mortality and changes in air quality due to climate change, at present and in the future.
Aim 2 emphasizes the air quality and health co-benefits of widespread actions to address climate change. We will quantify co-benefits of global greenhouse gas mitigation using our own global atmospheric model simulations of scenarios to 2100. This study differs from previous co-benefits studies by being global, by considering future scenarios, and by distinguishing two mechanisms of co-benefits — reducing co-emitted air pollutants and slowing the effects of climate change on air quality.
Similarly, in Aim 3, we will quantify the air quality and human health benefits of seven specific actions to reduce emissions of short-lived climate forcers — black carbon and co-emitted species. We will build on recent research that shows the substantial climate and air quality benefits of these seven actions together, by modeling the air quality benefits and avoided mortalities of each action individually, as well as the benefits of selected actions in specific world regions.
In support of these aims, Aim 4 will improve methods of modeling of PM2.5 exposure for global health assessment, as coarse resolution global models cannot resolve gradients in pollutant concentrations near urban areas. We will improve these methods by modeling sub-grid cell variability using newly available satellite data, using fine-resolution regional air quality models to apportion that variability to different chemical components, and using new fine-resolution emissions inventories to attribute variability to source categories. Overall, this research will improve understanding of the range of future health impacts of air pollution and climate change, and of climate-air interactions, to inform decisions on mitigation of climate change and adaptation to climate change through air quality management.