Spatio-Temporal Analysis of the Roadside Transportation-Related Air Quality (StarTraq 2022): Data-Driven Exposure Analysis by Transportation Modes

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Spatio-Temporal Analysis of the Roadside Transportation-Related Air Quality (StarTraq 2022): Data-Driven Exposure Analysis by Transportation Modes

Abstract: 

Particulate matter (PM) pollution poses significant health risks, influenced by various meteorological factors and seasonal variations. This study investigates the impact of temperature and other meteorological variables on PM10 and PM2.5 levels in Fresno County, known for high air pollution. Multiple linear regression (MLR) and generalized additive models (GAMs) assess the significance of these relationships. Analyzing data from Fresno County, we examine PM10 and PM2.5 levels across "hot" (June to August) and "cool" (September to May) seasons. Findings indicate PM10, both MLR and GAM models identify statistically significant variables, excluding temperature and wind direction in each season. However, during the hot season, both temperature and wind direction become statistically significant predictors of PM10. These variables remain insignificant during the cool season. For PM2.5, the MLR model suggests that temperature, humidity, and wind direction are not significant throughout the entire season, while the GAM model finds only wind direction to be insignificant. The temperature is highly significant for hot and cool seasons under the MLR model, whereas humidity becomes insignificant under the GAM model. Model performance is evaluated using measures of fit, indicating that MLR outperforms GAM for PM10 during the entire and hot seasons, while GAM performs better during the cool season. For PM2.5, GAM outperforms MLR during the cool seasons, with no clear distinction in performance during the hot season. The regional air quality PM2.5 at Fresno and meteorological conditions were closely related to the concentration of on-road particulate matter. From the intercity monitoring of PM2.5 and BC, on-road concentrations were statistically significantly higher than those measured in-vehicle (p<.001). Therefore, in-vehicle particle concentrations were safe compared to the on-road concentrations. In most cases, PM2.5 on the highways was higher than PM2.5 on the local roadways. On-road transportation-related particles measured in the San Joaquin Valley were significantly higher than those measured in the Bay Area. The results from a daily dose of transportation-related PM2.5 estimation based on a 2-hour commute and an 8-hour trip demonstrated that children under 11 years of age are more vulnerable than adults. In-vehicle daily doses were significantly lower than the on-road daily doses. This study highlights the importance of considering seasonal variations and meteorological factors when modeling PM pollution. It underscores PM's sensitivity to temperature and wind direction in Fresno County's hot season, offering insights for effective pollution management from transportation and policy implementation to mitigate the adverse health effects.

Authors: 

JAYMIN KWON, PHD

Dr. Jaymin Kwon is an Associate Professor of Environmental and Occupational Health in the Department of Public Health at California State University in Fresno, CA. He obtained a BS and M.S. in Food Engineering and Biotechnology at Yonsei University, Korea and an MS and PhD in Environmental Sciences from Rutgers University, New Jersey. He joined Fresno State in 2011 after a postdoctoral fellowship at the School of Public Health at the University of Texas and Houston. His research focuses on the epidemiological human exposure assessment of traffic emissions and adverse health effects, developing sensors for air pollution monitoring, and the impact of traffic emissions in under-represented microenvironments and communities.

YUSHIN AHN, PHD

Dr. Yushin Ahn is an Assistant Professor in the Department of Civil and Geomatics Engineering at California State University in Fresno, CA. He received a B. Eng. Degree in civil engineering and an M.Sc. degree in surveying and digital photogrammetry from Inha University, Korea in 1998 and 2000, and an MSc and PhD in geodetic science from the Ohio State University, Columbus in 2005 and 2008 respectively. His research interests include digital photogrammetry, feature tracking, and sensor calibration and integration. Dr. Ahn received the Robert E. Altenhofen Memorial Scholarship from the American Society of Photogrammetry and Remote Sensing. He has been a certified Photogrammetrist since 2014.

STEVE CHUNG, PHD

Dr. Steve Chung is an Associate Professor in the Department of Mathematics at California State University, Fresno. He received a BS in Applied Mathematics at CalPoly Pomona and his PhD in Statistics from Florida State University. His research focuses on time series analysis and applied statistics. 

Published: 
July 2024
Keywords: 
Particulate matter (PM)
Transportation-related air pollutant exposure
Public health impact
Meteorological factors
Air quality analysis

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CSUTC
MCEEST
MCTM
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