Connection between forest fire emission and COVID-19 incidents in West Coast regions of the United States

TL;DR

This study investigates the link between forest fire emissions and increased COVID-19 cases in the US West Coast, showing significant correlations through spatial and non-spatial regression analyses.

Contribution

It introduces a comprehensive analysis of how forest fire-related air pollution correlates with COVID-19 incidents using advanced spatial and statistical models.

Findings

Increased particulate matter and NO2 levels during fire season

Significant statistical association between fire emissions and COVID-19 cases

Development of 30 models demonstrating local and spatial correlations

Abstract

Forest fires impact on soil, water and biota resources has been widely researched. Although forest fires profoundly impact the atmosphere and air quality across the ecosystems, much less research has been developed to examine its impact on the current pandemic. In-situ air pollution data were utilized to examine the effects of the 2020 forest fire on atmosphere and coronavirus (COVID 19) casualties. The spatiotemporal concentrations of particulate matter (PM2.5 and PM10) and Nitrogen Dioxide (NO2) were collected from August 1 to October 30 for 2020 (fire year) and 2019 (reference year). Both spatial (Multiscale Geographically Weighted Regression) and non spatial (negative binomial regression) regression analysis was performed to assess the adverse effects of fire emission on human health. The in situ data led measurements showed that the maximum increases in PM2.5, PM10, and NO2 concentrations were clustered in the West Coastal fire-prone states during the August 1 to October 30 period. The average concentration of particulate matter (PM2.5 and PM10) and NO2 were increased in all the fire states affected badly by forest fires. The average PM2.5 concentration over the period was recorded as 7.9, 6.3, 5.5, and 5.2 for California, Colorado, Oregon, and Washington in 2019, which was increased up to 24.9, 13.4, 25, and 17 in 2020. Both spatial and non-spatial regression models exhibited a statistically significant association between fire emission and COVID 19 incidents. A total of 30 models were developed for analyzing the spatial non-stationary and local association between the predictor and response factors. All these spatial models have demonstrated a statistically significant association between fire emissions and COVID counts. More thorough research is needed to better understand the complex association between forest fire and human health.