Conventional monitoring and mapping approaches are laborious, expensive, and time-consuming because they need a large number of data and consequently extensive sampling and experimental operations. Therefore, due to the growing concern about the potential of contamination of soils and agricultural products with heavy metals (HMs), a field experiment was conducted on 77 farm lands in an area of 2300 ha in the southeast of Shiraz (Iran) to investigate the source of metal contamination in the soils and vegetables and to model spatial distribution of HMs (iron, Fe; manganese, Mn; copper, Cu; zinc, Zn; cadmium, Cd; nickel, Ni, and lead, Pb) over the region using geographic information system (GIS) and geostatistical (Ordinary Kriging, OK) approaches and compare the results with deterministic approaches (Inverse Distance Weighting, IDW with different weighting power). Furthermore, some ecological and health risks indices including Pollution index (PI), Nemerow integrated pollution index (NIPI), pollution load index (PLI), degree of contamination (Cdeg), modified contamination degree (mCd), PIaverage and PIvector for soil quality, multi-element contamination (MEC), the probability of toxicity (MERMQ), the potential ecological index (RI), total hazard index (THI) and total carcinogenic risk index (TCR) based on ingestion, inhalation, and dermal exposure pathways for adults and children respectively for analyzing the noncarcinogenic and carcinogenic risks were calculated. Experimental semivariogram of the mentioned HMs were calculated and theoretical models (i.e., exponential, spherical, Gaussian, and linear models) were fitted in order to model their spatial structures and to investigate the most representative models. Moreover, principal component analysis (PCA) and cluster analysis (CA) were used to identify sources of HMs in the soils. Results showed that IDW method was more efficient than the OK approach to estimate the properties and HMs contents in the soils and plants. The estimated daily intake of metals (DIM) values of Pb and Ni exceeded their safe limits. In addition, Cd was the main element responsible for ecological risk. The PIave and PIvector indices showed that soil quality in the study area is not suitable. According to mCd values, the soils classified as ultra-high contaminated for Cu and Cd, extremely high for Zn and Pb, very high, high, and very low degree of contamination for Ni, Mn, and Fe, respectively. 36, 60, and 4 % of the sampling sites had high, medium, and low risk levels with 49, 21, and 9 % probability of toxicity, respectively. The maximum health risk index (HRI) value of 20.42 with extremely high risk for children was obtained for Ni and the HI for adults and children were 0.22 and 1.55, respectively. The THI values of Pb and Cd were the highest compared to the other HMs studied, revealing a possible non-cancer risk in children associated with exposure to these metals. The routes of exposure with the greatest influence on the THI and TCR indices were in the order of ingestion > inhalation > dermal. Therefore, ingestion, as the main route of exposure, is the route of greatest contribution to health risks. PCA analysis revealed that Fe, Mn, Cu, and Ni may originate from natural sources, while Fe was appeared to be controlled by fertilizer, and Cu primarily coming from pesticide, while Cd and Pb were mainly associated with the anthropogenic contamination, atmospheric depositions, and terrific in the urban soils. While, Zn mainly originated from fertilization. Findings are vital for developing remediation approaches for controlling the contaminants distribution as well as for monitoring and mapping the quality and health of soil resources.
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