Citation

Enayati Ahangar F, Cobian-Iñiguez J, Cisneros R. Fire (Basel) 2022; 5(3): e64.

Copyright

(Copyright © 2022, MDPI: Multidisciplinary Digital Publications Institute)

DOI

10.3390/fire5030064

PMID

unavailable

Abstract

The San Joaquin Valley in California has some of the worst air quality conditions in the nation, affected by a variety of pollution sources including wildfires. Although wildfires are part of the regional ecology, recent increases in wildfire activity may pose increased risk to people and the environment. The 2020 wildfire season in California included the largest wildfires reported to date and resulted in poor air quality across the state. In this study, we looked at the air quality effects of these wildfires in the San Joaquin Valley area. We determined that four wildfires (LNU Lightning Complex, SCU Lightning Complex, Creek, and Castle) were primarily affecting the air quality in the area. The daily PM2.5 emissions from each one of these wildfires were estimated and the largest daily emissions, 1935 ton/day, were caused by the Creek fire. To analyze the air quality in the study area, we developed a method utilizing a combination of regulatory and low-cost sensor data to estimate the daily PM2.5 concentration levels at 5 km spatial resolution. The concentrations maps showed that the highest average concentration levels were reached on 17 September with an average of 130 μg/m3 when about one-fifth of the study area was affected by hazardous PM2.5 levels. A sensitivity study of our interpolation method showed that the addition of low-cost sensors to regulatory data improved the performance of area-wide concentration estimates and reduced the mean absolute error and the root mean square error by more than 20%.

Language: en

Keywords

air quality; AQI; back-trajectory modeling; low-cost sensor; San Joaquin Valley; wildfire