Better Measures of Outdoor and Indoor Exposure to Wildfire Smoke

Sponsored by Stanford Data Science Initiative and the Stanford Woods Institute for the Environment


Monday, May 10, 2021
12:30 pm – 1:30 pm
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Better Measures of Outdoor and Indoor Exposure to Wildfire Smoke

Marshall Burke, Deputy Director, Center on Food Security and the Environment 
Sam Heft-Neal, Research Scholar, Center on Food Security and the Environment

We use data from ground sensors and satellites to measure the contribution of wildfire smoke to ambient air pollution over the last two decades in the US, showing that wildfires now account for up to half of key air pollutants in recent years. Using distributed indoor sensors and leakage data on hundreds of thousands of residential homes, we then quantify how outdoor pollution infiltrates indoor environments.  We document wide variation in infiltration across houses, some of which is explained by socioeconomic and racial/ethnic differences. 

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Join Stanford Data Science and the Woods Institute in this series of discussions at the intersection of wildland fire research and data science.  In recent years, wildfire has gone from an infrequent and distant news item to a centerstage issue spanning many consecutive weeks for urban and suburban communities.

Frequent wildfires are changing everyday lives for California in numerous ways -- from public safety power shutoffs to hazardous air quality -- that seemed inconceivable as recently as 2015. Moreover, elevated wildfire risk in the western United States (and similar climates globally) is here to stay into the foreseeable future.

There is a plethora of problems that need solutions in the wildland fire arena; many of them are well suited to a data-driven approach. In this seminar series, we will hear from several Stanford researchers about how their areas of interest require a data-driven approach to find solutions to pressing wildfire problems. Each speaker will present a short 20-minute overview of a particular problem of interest, followed by a 30-minute Q&A session in hopes of creating a dialogue about data-driven wildland fire research.

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