Abstract

Heavy metals in the soil of mining areas have become a primary source of pollution, which could cause deleterious health effects in people exposed through soil-plant systems via multi-pathways. A long-term field experiment under natural conditions was carried out to explore the distribution characteristic and migration law of heavy metals in a soil-wheat system of a mining area in Xuzhou. According to the second level standard of environmental quality standards for soils of China (GB 15618-1995), 30.8 g of CrCl3·6H2O, 8.3 g of Pb(CH3COO)2·3H2O, and 16.5 g of ZnSO4·7H2O were added into the soil of three experimental sites, respectively. The other experimental site with no additional compounds was used as the control site. The Cr, Pb, and Zn concentrations in the soil-wheat system were counted and their corresponding migration models were constructed. From 2014 to 2017, the mean concentrations of Cr (49.09 mg·kg−1), Pb (20.08 mg·kg−1), and Zn (39.11 mg·kg−1) in the soil of the addition sites were higher than that of the control site. The mean concentrations of Cr, Pb, and Zn in wheat of the addition sites were greater than that of the control site with the values of 3.29, 0.06, and 29 mg·kg−1. In comparison, the Cr, Pb, and Zn concentrations in the soil of all experimental sites were lower than the second level standard of environmental quality standards for soils of China (GB 15618-1995), whereas the Cr concentration exceeded its corresponding soil background value of Xuzhou in 2017. The Pb concentration in soil of the addition site was greater than its corresponding background value from 2014 to 2016. The Pb and Zn concentrations in wheat of all experimental sites were lower than the national hygienic standard for grains of China (GB2715-2005) and the national guidelines for cereals of China (NY 861-2004), but the Cr concentration significantly exceeded the national guidelines for cereals of China (NY 861-2004). By constructing the Identical-Discrepant-Contrary (IDC) gray connection models, the result showed that there was a non-linear relationship of Cr, Pb, and Zn concentrations in the soil-wheat system, and the absolute values of most correlation coefficients were lower than 0.5 and the values of greyness were more than 0.5. The curvilinear regression models could not reflect the relationship of Cr, Pb, and Zn concentrations in the soil-wheat system with the regression coefficient values far less than 1. Due to the values of regression coefficient being close to 1, this study suggested that the allocation estimation models could be used for simulating the Cr, Pb, and Zn migration in the soil-wheat system of a mining area in Xuzhou.

Highlights

  • The exploitation and utilization of mineral resources have changed the material cycle and energy flow of mining area ecosystem, resulting in serious ecological damage and environmental pollution.Int

  • The curvilinear regression models could not reflect the relationship of Cr, Pb, and Zn concentrations in the soil-wheat system with the regression coefficient r2 values far less than 1

  • Due to the values of regression coefficient r2 being close to 1, this study suggested that the allocation estimation models could be used for simulating the Cr, Pb, and Zn migration in the soil-wheat system of a mining area in Xuzhou

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Summary

Introduction

The exploitation and utilization of mineral resources have changed the material cycle and energy flow of mining area ecosystem, resulting in serious ecological damage and environmental pollution. Common heavy metals that have been identified in polluted soil include arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), lead (Pb), and zinc (Zn) Release of these metals without proper treatment poses a significant threat to public health because of their persistence, biomagnification, and accumulation in the food chain [5]. A regression coefficient has been used to identify whether these models can reflect the linear relationship between heavy metal concentration and influencing factors. The aims were to (1) investigate the migration characteristics of Cr, Pb, and Zn in the soil-wheat system, (2) assess the pollution status of Cr, Pb, and Zn in the soil-wheat system, (3) analyse the relationship of Cr, Pb, and Zn concentrations in soil and wheat, and (4) construct the optimal model for simulating the heavy metal migration

Experimental Sites and Scheme
Samples Collection and Chemical Analysis
Data Processing
Results and Discussion
Spatial
Curvilinear Regression Model
Allocation Estimation Model
Selection and Verification of Optimal Model
Conclusions
Full Text
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