Journal of
Public Health and Epidemiology

  • Abbreviation: J. Public Health Epidemiol.
  • Language: English
  • ISSN: 2141-2316
  • DOI: 10.5897/JPHE
  • Start Year: 2009
  • Published Articles: 655

Full Length Research Paper

Employing an Eigenfunction Eigendecomposition algorithm to cartographically and statistically delineate traffic-related carbon monoxide pollution in Hillsborough County, Florida

Jing Liu
  • Jing Liu
  • Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, Tampa, Fl, USA.
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Namit Choudhari
  • Namit Choudhari
  • School of Geosciences, University of South Florida, Tampa, Fl, USA.
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Brooke Yost
  • Brooke Yost
  • Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, Tampa, Fl, USA.
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Benjamin G. Jacob
  • Benjamin G. Jacob
  • Department of Global Health, College of Public Health, University of South Florida, Tampa, Fl, USA.
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  •  Received: 22 August 2023
  •  Accepted: 31 October 2023
  •  Published: 30 November 2023

Abstract

The traffic-related carbon monoxide (CO) pollution in Hillsborough County, Florida, has yet to be analyzed with high-resolution satellite data or algorithmic geo-spatiotemporal autocorrelation methods. This study aims to detect the association between traffic volume and CO pollution in Hillsborough County in 2022. It is hypothesized that daytime outdoor CO pollution positively correlates with traffic volume. High-resolution daily Giovanni remote sensing data of 1-degree spatial resolution from NASA Goddard Earth Sciences Data and Information Services Center was used to detect CO concentration on the roadways with annual average daily traffic (AADT) volumes larger than or equal to 80,000 in Hillsborough County. The results of AADT and CO concentrations indicated a clustering tendency. The Moran’s Indices (I) of AADT was 0.956, and CO was 0.973. The results revealed a non-homoscedastic distribution of both AADT and CO concentrations. The performance of continuous data of CO and AADT was assessed by Pearson’s correlation (r) to identify the strength and direction of CO concentration and AADT values. The results revealed a significant correlation between AADT and CO concentrations in this study with r=-0.119. The results also revealed an inversely proportional relationship; as AADT increased, daytime CO concentrations decreased. The clustered AADT and CO concentrations may account for biases in the correlation. 

Key words: Asthma, annual average daily traffic, carbon monoxide pollution, remote sensing, Hillsborough County, Florida.

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This article is published under the terms of the Creative Commons Attribution License 4.0

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