Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination

Hoehun Ha, Peter A. Rogerson, James R. Olson, Daikwon Han, Ling Bian and Wanyun Shao
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Hoehun Ha: Department of Sociology, Anthropology and Geography, Auburn University at Montgomery, 7041 Senators Drive, Montgomery, AL 36117, USA
Peter A. Rogerson: Department of Geography, University at Buffalo, Wilkeson Hall, Buffalo, NY 14261, USA
James R. Olson: Departments of Pharmacology and Toxicology and Epidemiology and Environmental Health, Farber Hall, University at Buffalo, Buffalo, NY 14214, USA
Daikwon Han: Department of Epidemiology and Biostatistics, School of Public Health, Texas A&M University, College Station, TX 77843, USA
Ling Bian: Department of Geography, University at Buffalo, Wilkeson Hall, Buffalo, NY 14261, USA
Wanyun Shao: Department of Sociology, Anthropology and Geography, Auburn University at Montgomery, 7041 Senators Drive, Montgomery, AL 36117, USA

IJERPH, 2016, vol. 13, issue 9, 1-15

Abstract: Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations.

Keywords: soil lead (Pb) contamination; physical and socioeconomic/demographic characteristics; spatial modelling; Anniston; Alabama (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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