Heavy metals in agricultural soils from a typical township in Guangdong Province, China: Occurrences and spatial distribution.

Multiple methods for the identification of heavy metal sources in cropland soils from a resource-based region.

Risk assessment, spatial patterns and source apportionment of soil heavy metals in a typical Chinese hickory plantation region of southeastern China

Spatial characteristics of heavy metal contamination and potential human health risk assessment of urban soils: A case study from an urban region of South India.

The contamination of heavy metals (HMs) in agricultural soil lands has attracted the environmental world due to their abundance, persistence, and toxicity. A study has been conducted to evaluate the degree of HM contamination in the agricultural soils of northern Telangana, using geo-accumulation index (Igeo), pollution index (PI), pollution load index (PLI), enrichment factor (EF), statistical analysis, and also spatial distribution. In this study, a total of 15 surface agricultural soil samples were collected and analyzed for the concentration of HMs including Cr, Cu, Co, Ba, V, As, Ni, Pb, and Zn. Their average values vary from 3.5 to 778, which show the increasing order of their abundance: As < Ni < Pb < Co < Cu < Zn < Cr < V < Ba. The concentrations of Ba, V, Zn, and Cu are significantly higher than their guideline values, while Co, Ni, Pb, Zn, and As are within prescribed limits proposed by Canadian soil quality guidelines. The highest Igeo (1.04) indicated the extreme degree of contamination due to Cu. The estimated PI and PLI specified the low to moderate soil pollution, whereas EF showed the moderate soil pollution due to Cr, Co, V, Zn, and As. According to principal component analysis with eigenvalue, more than one account for 53.020% of the total variance, indicating the major source of anthropogenic activity. Spatial distribution maps of HMs displayed four highly polluted zones found in the agricultural sites such as Oni, Yamcha, Bederelli, and Mudhol, in northern Telangana.

Assessment of heavy metal (HM) contamination in agricultural soil lands in northern Telangana, India: an approach of spatial distribution and multivariate statistical analysis.

Understanding the spatial distribution and sources of soil heavy metals (HMs) in a large city helps prevent and control soil pollution. This study aimed to investigate the spatial patterns of soil HMs and identify their main sources in a regional scale. A total of 110 topsoil samples were collected from Tai’an City, China. Cd, Cr, Cu, Hg, Ni, Pb, and Zn concentrations in each soil sample were determined. Geostatistics, geographic information system (GIS), and positive matrix factorization (PMF) were used to explore the spatial distribution of seven soil HMs and to reveal the main sources of soil HMs in Tai’an City, respectively. Soil Cd, Cr, Pb, and Zn generally showed slight pollution levels in the study area. However, soil Hg and Cu contents reached moderate to heavy pollution levels in some areas. Soil Hg content increased from north to south across the city, and the highest Hg concentration was detected in Ningyang County. Soil Cd, Cu, and Zn distributions exhibited a similar pattern, and their contents increased from west to east; the highest Cd, Cu, and Zn concentrations were found in Xintai County. The highest soil Ni concentration was obtained in the northeast of Feicheng and Xintai counties. PMF analysis revealed the following four potential sources of agricultural soil HMs in Tai’an City: industrial and mining activities, agricultural activities, residential living activities, and business activities. Soil Hg mainly originated from residential living activities, which accounted for 75.3% of the total source. The main sources of soil Ni were residential living activities, agricultural activities, and industrial and mining activities, which account for 38.2, 27.50, and 25.1% of the total source, respectively. Soil Cu was mainly produced by agricultural activities (36.6%), followed by residential living activities (29.8%) and industrial and mining activities (25.8%). PMF combined with GIS could be effectively applied to determine the main sources of HMs in agricultural soils in a regional scale.

Kelin Hu

Papers

Spatial distribution and source apportionment of the heavy metals in the agricultural soil in a regional scale