IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v13y2016i9p915-d78214.html
   My bibliography  Save this article

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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Hoehun Ha & Peter A. Rogerson & James R. Olson & Daikwon Han & Ling Bian & Wanyun Shao, 2016. "Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination," IJERPH, MDPI, vol. 13(9), pages 1-15, September.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:9:p:915-:d:78214
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/13/9/915/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/13/9/915/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    2. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    3. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Deniz Yeter & Ellen C. Banks & Michael Aschner, 2020. "Disparity in Risk Factor Severity for Early Childhood Blood Lead among Predominantly African-American Black Children: The 1999 to 2010 US NHANES," IJERPH, MDPI, vol. 17(5), pages 1-26, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Álvarez, Inmaculada C. & Barbero, Javier & Zofío, José L., 2017. "A Panel Data Toolbox for MATLAB," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i06).
    2. Oliver W. Lerbs & Christian A. Oberst, 2014. "Explaining the Spatial Variation in Homeownership Rates: Results for German Regions," Regional Studies, Taylor & Francis Journals, vol. 48(5), pages 844-865, May.
    3. Christian Helmers & Manasa Patnam, 2014. "Does the rotten child spoil his companion? Spatial peer effects among children in rural India," Quantitative Economics, Econometric Society, vol. 5, pages 67-121, March.
    4. Preinerstorfer, David & Pötscher, Benedikt M., 2016. "On Size And Power Of Heteroskedasticity And Autocorrelation Robust Tests," Econometric Theory, Cambridge University Press, vol. 32(2), pages 261-358, April.
    5. repec:asg:wpaper:1019 is not listed on IDEAS
    6. Liu, Shew Fan & Yang, Zhenlin, 2015. "Modified QML estimation of spatial autoregressive models with unknown heteroskedasticity and nonnormality," Regional Science and Urban Economics, Elsevier, vol. 52(C), pages 50-70.
    7. Mack, Elizabeth A. & Rey, Sergio J., 2014. "An econometric approach for evaluating the linkages between broadband and knowledge intensive firms," Telecommunications Policy, Elsevier, vol. 38(1), pages 105-118.
    8. Elizabeth A. Mack & Luc Anselin & Tony H. Grubesic, 2011. "The importance of broadband provision to knowledge intensive firm location," Regional Science Policy & Practice, Wiley Blackwell, vol. 3(1), pages 17-35, March.
    9. Emanuela Marrocu & Raffaele Paci & Stefano Usai, 2013. "Productivity Growth In The Old And New Europe: The Role Of Agglomeration Externalities," Journal of Regional Science, Wiley Blackwell, vol. 53(3), pages 418-442, August.
    10. Ariane Amin & Johanna Choumert, 2015. "Development and biodiversity conservation in Sub-Saharan Africa: A spatial analysis," Economics Bulletin, AccessEcon, vol. 35(1), pages 729-744.
    11. Debarsy, Nicolas & Jin, Fei & Lee, Lung-fei, 2015. "Large sample properties of the matrix exponential spatial specification with an application to FDI," Journal of Econometrics, Elsevier, vol. 188(1), pages 1-21.
    12. Baltagi, Badi H. & Yang, Zhenlin, 2013. "Heteroskedasticity and non-normality robust LM tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 43(5), pages 725-739.
    13. repec:asg:wpaper:1045 is not listed on IDEAS
    14. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    15. Lin, Xu & Lee, Lung-fei, 2010. "GMM estimation of spatial autoregressive models with unknown heteroskedasticity," Journal of Econometrics, Elsevier, vol. 157(1), pages 34-52, July.
    16. Gianfranco Piras & Mauricio Sarrias, 2023. "Heterogeneous spatial models in R: spatial regimes models," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-32, December.
    17. Marques, André M., 2022. "Is income inequality good or bad for growth? Further empirical evidence using data for all Brazilian cities," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 360-376.
    18. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    19. repec:rri:wpaper:201301 is not listed on IDEAS
    20. repec:esx:essedp:772 is not listed on IDEAS
    21. Lorea Mendiola & Pilar González, 2021. "Urban Development and Sustainable Mobility: A Spatial Analysis in the Buenos Aires Metropolitan Area," Land, MDPI, vol. 10(2), pages 1-23, February.
    22. Rabovič, Renata & Čížek, Pavel, 2023. "Estimation of spatial sample selection models: A partial maximum likelihood approach," Journal of Econometrics, Elsevier, vol. 232(1), pages 214-243.
    23. Jin, Fei & Lee, Lung-fei, 2018. "Irregular N2SLS and LASSO estimation of the matrix exponential spatial specification model," Journal of Econometrics, Elsevier, vol. 206(2), pages 336-358.
    24. Kim, Min Seong & Sun, Yixiao, 2013. "Heteroskedasticity and spatiotemporal dependence robust inference for linear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 177(1), pages 85-108.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:13:y:2016:i:9:p:915-:d:78214. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.