A Novel Method for Traffic Estimation and Air Quality Assessment in California

Jucheol Moon, Jin Gi Hong and Tae-Won Park
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Jucheol Moon: Department of Computer Engineering and Computer Science, California State University, Long Beach, CA 90840, USA
Jin Gi Hong: Department of Civil Engineering and Construction Engineering Management, California State University, Long Beach, CA 90840, USA
Tae-Won Park: Department of Earth Science Education, Chonnam National University, Gwangju 61186, Korea

Sustainability, 2022, vol. 14, issue 15, 1-12

Abstract: Motor vehicle traffic is recognized as one of the critical factors that causes air pollution; however, the relationship between traffic volume and air pollutant concentrations is unclear, especially at a local level. Traditional traffic volume monitoring systems collect traffic data through counting the number of vehicles, using either sensors or surveillance cameras, but they have clear limitations such as they can only monitor certain areas and specific occasions. To overcome such limitations, we introduce a method of monitoring traffic volume in the local area by collecting estimated travel times for virtual trips in Google Maps. We began collecting the data in January 2020; ironically, the COVID-19 pandemic provided a natural experimental environment of showing unusual trends in traffic volume and unexpected changes in air pollutants. We demonstrate monthly traffic volumes in urban areas and analyze the correlation of traffic volume with typical traffic-related air pollutants using the proposed traffic volume monitoring method.

Keywords: traffic volume; air pollutant; big data; COVID-19 (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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