Geogenic control on soil chemistry in urban areas: A novel method for urban geochemical mapping using parent material classified data

被引:18
作者
Appleton, J. D. [1 ]
Adlam, K. A. M. [1 ]
机构
[1] British Geol Survey, Keyworth NG12 5GG, Notts, England
关键词
IRONSTONES;
D O I
10.1016/j.apgeochem.2011.10.001
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The purpose of the study reported here is to assess whether it may in some circumstances be useful and appropriate to use a parent material (PM) soil chemistry mapping method developed for national soil chemistry data to portray spatial variation in urban soil chemistry data in Great Britain. Analysis of variance (ANOVA) of the urban soil data suggests that spatial interpolation of soil ambient background concentrations (ABCs) using PM classified soil data may be justified for those elements with strong geogenic control. The PM soil chemistry mapping method for urban soil data is demonstrated using data from the Northampton urban area, in the English Midlands. Geometric mean (GM) and inverse distance weighting (IDW) interpolations based on the nearest four topsoil samples were evaluated. Independent validation indicated that for As, Cr, Fe and to a lesser extent K, which all exhibit relatively strong geogenic control in the Northampton urban area: (i) the PM soil chemistry mapping method is more accurate and effective than the conventional IDW grid mapping and (ii) PM soil chemistry mapping based on the average of the nearest four Ln(e) element concentrations is more accurate than mapping based on IDW values calculated from the nearest four Ln(e) element concentrations. The variation in effectiveness of the methods can be explained by the fact that PM exerts a significant control on As, Cr, Fe and K in the Northampton area whereas anthropogenic inputs appear to be the dominant control on the spatial variation of Pb, especially at high concentrations. The PM mapping method would be expected to work efficiently in other urban areas and for those elements where a significant proportion of the variation can be explained by PM. (C) 2011 Natural Environment Research Council. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:161 / 170
页数:10
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