ORIGINAL RESEARCH
Calculating Environmental Background Value: A Comparative Study of Statistical Versus Spatial Analyses
Sun Linhua 1  
 
 
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School of Resources and Civil Engineering, Suzhou University, Anhui, China National Engineering Research Center of Coal Mine Water Hazard Control, Anhui, China
Online publish date: 2018-07-31
Publish date: 2018-11-20
Submission date: 2017-11-28
Final revision date: 2018-01-24
Acceptance date: 2018-01-27
 
Pol. J. Environ. Stud. 2019;28(1):197–203
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ABSTRACT:
Local environmental background is important for environmental management. In this study, lead concentrations of shallow groundwater samples from the urban area of Suzhou in Anhui Province, China were measured and analyzed by statistical and spatial analyses for calculating the environmental background value. The results show that the lead concentrations in the groundwater range from 4.16-11.5 μg/L, and all of the samples were classified to be Class III or better according to the groundwater quality standard of China. The samples have medium coefficient of variation and low p-values of normal distribution test, suggesting that it may have been influenced by anthropogenic activities, which was further demonstrated by the consistency of the distribution of the samples with high lead concentrations and the areas with high density of transportation, as well as the high-low cluster of the spatial autocorrelation analysis. The environmental background values have been calculated to be 3.74-8.62 and 3.48-10.3 μg/L with box plot and spatial autocorrelation analyses, respectively. The study demonstrated that for calculating the environmental background value, the statistical and spatial methods should be chosen according to the current state – especially pre-consideration about the distribution of the elements or pollutants.
CORRESPONDING AUTHOR:
Sun Linhua   
School of Resources and Civil Engineering, Suzhou University, Anhui 234000, China; National Engineering Research Center of Coal Mine Water Hazard Controlling, Anhui 234000, China, 49# Bianhe Road, Suzhou City, Anhui Province, China, 234000 Suzhou, China
eISSN:2083-5906
ISSN:1230-1485