An integrated GIS-pXRF approach assesses ecological and human health risks from heavy metals in county level soils

Abstract

Counties in China are the primary components of small and mid-sized city (SMC), and at the core of China's future urbanization and industrialization development. Land is an essential nature resource providing the basis for urban-rural development, which is directly influenced by anthropogenic processes and in turn has impacts on human health. Clarifying the distribution characteristics and causes of heavy metals (HMs) pollution in soils is key to ensuring human health, as well as promoting land sustainability at county-level. In order to efficiently identify high risk regions of HMs pollution, this study proposed a geographic information system (GIS)-portable X-ray fluorescence (pXRF)-based approach to measure local soil background of HMs and to screen high risk regions in Shangzhou, China. ICP-MS and pXRF results showed a good agreement of Cr, Ni, Cu, Zn, Pb and As with R² ranging from 0.757 to 0.966. Soil background of Ni, Cu, Zn, As and Pb had increased by 33.34-129.74% compared to 1990 levels. HMs concentrations in soils of urban-rural fringe were generally larger than those of urban and rural area. Particularly, soil background of Zn and Pb in urban-rural fringe exceeded 28.90% and 19.93% of urban area, 46.33% and 41.91% of rural area, respectively. In high soil background regions, 25% of sampling points were considered as moderate risk or above, with ecological risk index (RI) greater than 150. As, Cr and Ni were identified as major contributors to human health risk, and children were more vulnerable than adults with considerably total non-carcinogenic risk (THI = 1.46) and carcinogenic health risk (TCR = 1.52 × 10^{- 4}). Anthropogenic process including industrial manufacturing, agricultural practice, urban expansion and land conversion brought about the HMs accumulation in soils. This study indicated industrial zone in urban-rural fringe should be priority-controlled, and provided scientific basis for urban-rural environmental management and human health risk protection.

Keywords: Heavy metal; Human health risk; Small and mid-sized City; Soil background; Urban-rural fringe.

Fig. 1

Experimental area location (a) DEM of Shangzhou; (b) land use and land cover of Shangzhou; (c) remote sensing (RS) image of study area. Maps were prepared by the authors using ArcGIS software-version 10.3 (https://www.esri.com/) and basemaps were obtained from Geospatial Data Cloud (http://www.gscloud.cn/).

Fig. 2

Space identification and interpretation workflow. Maps were prepared by the authors using ArcGIS software-version 10.3 (https://www.esri.com/) and basemaps were obtained from Geospatial Data Cloud (http://www.gscloud.cn/).

Fig. 3

Space identification results of study area (a) general spatial range; (b) detection area based on RS image; (c) distribution of 80 detection points locations with identifiers. Maps were prepared by the authors using ArcGIS software-version 10.3 (https://www.esri.com/) and basemaps were obtained from Geospatial Data Cloud (http://www.gscloud.cn/).

Fig. 4

The comparative analysis of Cr, Ni, Cu, Zn, As and Pb concentrations at 20 soil samples obtained by pXRF and ICP-MS.

Fig. 5

Comparative analysis of HMs concentrations across urban area (n = 6), urban-rural fringe (n = 35), and rural area (n = 39).

Fig. 6

Spatial distribution of HMs concentrations in the study area based on inverse distance weighted (IDW) interpolation.

Fig. 7

Distribution of 20 soil sampling sites in high risk HMs contamination regions. Maps were prepared by the authors using ArcGIS software-version 10.3 (https://www.esri.com/) and basemap was obtained from Geospatial Data Cloud (http://www.gscloud.cn/).

Fig. 8

Statistics of index of geo-accumulation (Igeo) with box plot of 20 soil samples.

Fig. 9

Accumulated potential ecological risks index (RI) of HMs at 20 sampling points.

Fig. 10

Pairwise Pearson correlation analysis heatmap of HMs concentrations in 20 soil samples (*p ≤ 0.01).

Fig. 11

Land use maps of study area and typical risky points in urban-rural fringe (L15-18) based on RS image. Maps Data: Google, ©2025 Airbus, Maxar Technologies.