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Sci Total Environ. 2015 May 15;515-516:198-206. doi: 10.1016/j.scitotenv.2015.02.030. Epub 2015 Feb 26.

Spatial analysis of environment and population at risk of natural gas fracking in the state of Pennsylvania, USA.

Author information

1
Department of Geosciences, Mississippi State University, MS 30762, USA. Electronic address: qmeng@geosci.msstate.edu.

Abstract

Hydraulic fracturing, also known as fracking, has been increasing exponentially across the United States, which holds the largest known shale gas reserves in the world. Studies have found that the high-volume horizontal hydraulic fracturing process (HVHFP) threatens water resources, harms air quality, changes landscapes, and damages ecosystems. However, there is minimal research focusing on the spatial study of environmental and human risks of HVHFP, which is necessary for state and federal governments to administer, regulate, and assess fracking. Integrating GIS and spatial kernel functions, we study the presently operating fracking wells across the state of Pennsylvania (PA), which is the main part of the current hottest Marcellus Shale in US. We geographically process the location data of hydraulic fracturing wells, 2010 census block data, urbanized region data, railway data, local road data, open water data, river data, and wetland data for the state of PA. From this we develop a distance based risk assessment in order to understand the environmental and urban risks. We generate the surface data of fracking well intensity and population intensity by integrating spatial dependence, semivariogram modeling, and a quadratic kernel function. The surface data of population risk generated by the division of fracking well intensity and population intensity provide a novel insight into the local and regional regulation of hydraulic fracturing activities in terms of environmental and health related risks due to the proximity of fracking wells.

KEYWORDS:

Environmental and human risks; Hydraulic fracturing activities; Marcellus Shale; Spatial dependence; Spatial kernel

PMID:
25727517
DOI:
10.1016/j.scitotenv.2015.02.030
[Indexed for MEDLINE]

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