Citation:

Shankar, U., J. Prestemon, D. McKenzie, H. Pye, AND G. Pouliot. Projecting the Impacts of Climate and Socioeconomic Drivers of Wildfires on Southeastern Air Quality. AGU Fall Meeting, San Francisco, CA, December 11 - 15, 2023.

Impact/Purpose:

This sub-product describes a modeling application that projects wildfire activity, the associated emissions from wildfire smoke and the resulting air quality under the combined impacts of climate and socioeconomics in the region from the present to mid-century. Wildfire activity has dramatically increased in the US and elsewhere in the world in the past decade or more due, in part, to climate change. The adverse impacts of smoke from wildfire is felt in the health and wellbeing of humans, their economy and the environment. These impacts have widely varying characteristics in the various ecoregions of the US. In the rapidly growing US Southeast, therefore, it is important to take into account the changes in both the climate and socioeconomic drivers of wildfire to address the adverse impacts of air pollutants emitted in wildfire smoke and mitigate risks to public health and welfare in the region not only at present, but in the long-term. It also offers a method to perform similar analyses in other regions. 

Description:

Wildfires have increased dramatically over the past decade in extent and severity, with unprecedented adverse impacts on the wellbeing of humans and the environment. The US Southeast, with its rapidly changing economy and demographics, is a region where both climate and socioeconomic factors drive wildfires, and their air quality (AQ) impacts. Assessing these impacts and associated long-term health risks in this region needs representation of both these drivers in the regional wildfire emissions estimates. This led to the development and application of a wildfire emissions projection method over the US Southeast based on published regression models of annual areas burned (AAB) using county-level socioeconomic and climate projections from 2011 to 2060. AAB projected with two climate downscaling approaches, are used to estimate wildfire emissions for a retrospective period (2010) and four annual time slices between 2040 and 2060. Competing climate and socioeconomic factors result in 7% - 32% lower projected AAB than 18-year historical mean AABs, yielding 13% - 62% lower fine particulate matter (PM2.5) emissions in the selected years for the two projection methods. Evaluation of the two methods against network observations for 2010 using the Community Multiscale Air Quality Model (CMAQ) shows good model performance for ozone and primary PM2.5 constituents, but larger and comparable biases in both methods for secondary species, e.g., secondary organic aerosol (SOA) due to non-wildfire emissions or secondary chemical production. Improvements to address some of these secondary PM2.5 biases are being undertaken with an updated SOA mechanism, and preliminary analyses of these updates are presented. The projection methods show peak periods and locations of wildfire AQ impacts shifting from autumn in the western part of the modeling domain in 2010, to summer months in the eastern seaboard by mid-century, following the spatiotemporal patterns of projected AAB.  Disclaimer. The views expressed in this paper are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency

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