Climate Change Impacts on Power Plant Emissions, Air Quality and Health in the U.S.
NIEHS Grant: R21ES020232
Air pollution effects from climate change rank high among future health concerns, according to national and international assessments. Even today, air pollution persists as a major public health hazard in the US, where approximately 70 million Americans live in areas exceeding air quality standards for fine particulate matter (PM2.5), and an estimated 120 million reside in counties exceeding 8-hour ozone (O3) standards. Climatic effects on air quality are well documented, especially for O3, a secondary pollutant that increases with warmer temperatures. Yet there exists less certainty regarding climate change's atmospheric effects on PM2.5, the more hazardous pollutant. Given that the key source of PM2.5 is fossil fuel combustion, an increase in air pollution emissions from higher electricity usage associated with hotter summers has been posited. However, to date, this potentially important contribution has not been quantified. We, therefore, propose to augment air pollution studies of climate change by determining and mapping future power plant emissions in response to projected climate scenarios for the US. We will study the Eastern US, already facing a range of air pollution health risks, and the most highly populated region of the country. Our overarching goal is to utilize a coupled model approach to determine populations most exposed to air pollution-related health risks from climate change. We propose to achieve this goal through three Specific Aims:
- To model the atmospheric effects of climate change (alone) on air quality over the Eastern US for current and future climates (e.g. 2050s), assuming a business-as-usual emissions scenario of the IPCC;
- To model climate change impacts on the demand for electricity during summer seasons and determine spatially explicit emissions from electric power plants; and
- To geographically locate and quantify risks for populations in the Eastern US most vulnerable to climate change-driven air pollution.
These populations will be determined based on the air pollution exposure scenarios generated by the outputs from projected climate effects on air quality (Aim 1), augmented by projected air pollution emissions from electric power demands in a warmer world (Aim 2). By including a research component addressing climate/electricity/PM2.5 linkages, we will quantify for the first time, the relationship between climate change, air quality, societal adaptation (via air conditioning demand) and public health. For the population vulnerability analysis (Aim 3), we utilize the Environmental Benefits Mapping and Analysis Program (BenMAP), which uses concentration-response and economic valuation functions to model air pollution-related health outcomes. Our approach can be applied across any spatial scale and be customized for climate/air quality modeling in any region or country where power plant location and characteristics are known. This study can thus provide a modeling framework applicable to health risk assessment of climate change across multiple populations of the industrialized world.
Funded by NIEHS