Citation

Vargo JA. Front. Public Health 2020; 8: e126.

Copyright

(Copyright © 2020, Frontiers Editorial Office)

DOI

10.3389/fpubh.2020.00126

PMID

unavailable

Abstract

As the threats of climate change become more immediate and persistent, there is a growing need for datasets to document the burden of climate-related events and exposures on human health over time. These data should be freely available, timely and long-running, spatially resolved, and consistent. This data report presents a new dataset for understanding the potential burden of smoke related to wildland fires (wildfires) on communities across the United States since 2010. The dataset combines data from the National Oceanic and Atmospheric Administration's (NOAA) Office of Satellite and Product Operations Hazard Mapping System's Smoke Product (HMS Smoke) with United States Census Block Group Centers of Population to estimate potential exposures to light, medium, and heavy categories of wildfire smoke. The result is a daily assignment of each of the 220,334 2010 U.S Block Groups for each of the HMS Smoke categories and includes 2010 Census population counts. This database can be used to identify populations potentially exposed to wildfire smoke on a given day or to calculate the potential person-days of wildfire smoke exposure for a specified period or spatial unit of interest. Using state, county or tract identifiers included in the database, aggregation to these familiar units of the US Census topology can be accomplished without the use of a geographic information system (GIS). This data report describes the datasets combined to produce this potential wildfire exposure database and outlines some basic use cases and ideas for future work.

It is fundamental to understand the methods, strengths, and limitations of the underlying information used to create this dataset. Most important is the HMS Smoke Product from NOAA's Office of Satellite and Product Operations (OSPO). HMS uses visible imagery from satellites to generate smoke plumes associated with fires. Although there are many air quality datasets available, HMS is particularly valuable as it is specific to fires, which are automatically detected using several satellites and algorithms...

Language: en

Keywords

exposure; air pollutants; climate change; remote sensing; smoke; wildfire