The Improvement of the Air Quality due to Traffic Halting in Los Angeles during the COVID-19 OutbreakJiani Yang a,*, Yuan Wang a,b, Joseph Pinto c
a Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, 91125 USA
b Jet Propulsion Laboratory,4800 Oak Grove Dr, Pasadena, CA 91109 USA
c Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599 USA
Correspondence to: Jiani Yang (yjn@caltech.edu)
Background: On March 19, 2020, the government of California ordered all 40 million Californians to stay at home in the coming weeks as the result of the escalation of the coronavirus disease 2019 (COVID-19) pandemic. As lockdowns were implemented, the significant changes caused by these restrictions brought the dramatic improvement in air quality in metropolitan cities such as Los Angeles (LA Basin).
Methods: We use real-time data from The South Coast Air Quality Management District (South Coast AQMD), and California Department of Transportation (PeMS) to evaluate the anthropogenic drivers of the pollution sources. We fit the regression analysis to compare the correlation of 7 variables including traffic flow, truck flow, traffic speed, NO2, CO, PM2.5, and O3. We also mapped the monthly spatial variation and hourly heatmap of those 7 variables in 2020 to understand the impacts of the lockdown on different locations in the LA Basin.
Results: In the Los Angeles Basin, the traffic flow on highways started to drop an intensely by 20.86 % when initiating the stay at home order and it continued decreasing by 32.92% the first week, 30.94% the second week, 37.9% the third week, and 33.57% at the fourth week following the lockdown compared to corresponding dates during the year of 2019. The average truck flow for each sensor is generally higher in 2020 than 2019 before lockdown. The general weekly drops have also been observed for the truck flow on the highways by 1.63% the first week, then it raises back to 18.31% the second week, and declined again by 10.98% the third week, and declined by 2.55% at the fourth week following the county-wide lockdown. Accordingly, the change of traffic trigged the intensive decline of NO2 by 44.23% the first week, 12.96% the second week, 50.64% the third week, 32.65% the fourth week following the lockdown; We found a dramatic drop in PM2.5, NO2, CO during the first week after initiating the stay at home order. The correlation (Pierson r) between truck flow change and changes of NO2, CO, and PM2.5 is 0.91(****),0.88(****),0.74(**); The correlation between traffic flow change and changes of NO2 is 0.87(****), CO is 0.81(***), and PM2.5 is 0.62(**). The correlation between traffic speed change and changes of NO2 is -0.84(****), CO is -0.78 (***), and PM2.5 is -0.59(*). We found that a decline of 1% in NO2, CO and PM2.5 is associated with the decline of 15.79%, 17.15% and 9.43% in the truck flow; A decline of 1% in NO2, CO and PM2.5 is associated with the decline of 11.26%, 9.43% and 20.96% in traffic flow; A decline of 1% in NO2, CO and PM2.5 is associated with the increase of 3.45%, 3.13% and 5.21% in traffic speed. The results are all statistically significant.
Conclusion: The drop in truck flow is mainly responsible for the drop of NO2 and CO. The lockdowns provided a large-scale experiment into air quality research. The result of this research would provide an important reference for the policy markers regarding truck management in light of air quality control to prepare the 2028 Summer Olympics in LA.