A132-03
Improvement in Air Quality in Los Angeles due to Decreases in Traffic during the COVID-19 Outbreak based on High Resolution, Real-Time Data and Modeling

Friday, 11 December 2020: 16:06
Virtual
Jiani Yang1, Yuan Wang1, Yifan Wen2, Shaojun Zhang2, Joseph P Pinto3, Ye Wu2 and Yuk L Yung1, (1)California Institute of Technology, Pasadena, CA, United States, (2)School of Environment, Tsinghua University, Beijing, China, (3)University of North Carolina, Dept. of Environmental Sciences and Engineering, Chapel Hill, NC, United States
Abstract:
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 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 the California Department of Transportation to evaluate the drivers of the pollution sources. We estimated traffic activities for non-monitored roads based on monitored road and functional classification zone. We calculate emissions from light-duty vehicles and trucks using the EMFAC model. We estimated the lockdown reduced concentrations of ambient air pollutants by using the WRF-Chem model. We also mapped monthly spatial variations and constructed hourly heatmaps of those pollutants in 2020 to understand the impacts of the lockdown on different locations and times of day in the LA Basin.

Results: Compared to the same dates in 2019, traffic flow on highways in the Los Angeles Basin dropped by 20.86 % when the stay at home order was initiated and it continued to decrease along with dramatic declines in NO2, CO and PM2.5. 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(*). The results are statistically significant at the p ≤ 0.05 (*), p ≤ 0.01 (**), P≤ 0.001(***),p ≤ 0.0001 (****) levels.

Conclusion: The declines in truck flow are mainly responsible for the drop of NO2 and CO, with traffic having a slightly smaller effect on PM2.5. 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 for the 2028 Summer Olympics in LA.

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