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首页> 外文期刊>International Journal of Environmental Research and Public Health >Contamination and Spatial Variation of Heavy Metals in the Soil-Rice System in Nanxun County, Southeastern China
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Contamination and Spatial Variation of Heavy Metals in the Soil-Rice System in Nanxun County, Southeastern China

机译:中国东南Nan县土壤-水稻系统中重金属的污染及其空间变异

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There is an increasing concern about heavy metal contamination in farmland in China and worldwide. In order to reveal the spatial features of heavy metals in the soil-rice system, soil and rice samples were collected from Nanxun, Southeastern China. Compared with the guideline values, elevated concentrations of heavy metals in soils were observed, while heavy metals in rice still remained at a safe level. Heavy metals in soils and rice had moderate to strong spatial dependence (nugget/sill ratios: 13.2% to 49.9%). The spatial distribution of copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) in soils illustrated that their high concentrations were located in the southeast part. The high concentrations of cadmium (Cd) in soils were observed in the northeast part. The accumulation of all the studied metals is related to the long-term application of agrochemicals and industrial activities. Heavy metals in rice showed different spatial distribution patterns. Cross-correlograms were produced to quantitatively determine the spatial correlation between soil properties and heavy metals composition in rice. The pH and soil organic matter had significant spatial correlations with the concentration of heavy metals in rice. Most of the selected variables had clear spatial correlation ranges for heavy metals in rice, which could be further applied to divide agricultural management zones.
机译:在中国和世界范围内,农田中的重金属污染日益引起人们的关注。为了揭示土壤-水稻系统中重金属的空间特征,从中国东南部的南x采集了土壤和水稻样品。与指导值相比,土壤中的重金属浓度升高,而水稻中的重金属仍保持在安全水平。土壤和水稻中的重金属具有中度到强度的空间依赖性(金块/基石比率:13.2%至49.9%)。土壤中铜(Cu),镍(Ni),铅(Pb)和锌(Zn)的空间分布表明它们的高浓度位于东南部。在东北部,土壤中的镉含量很高。所有研究金属的积累与农药的长期应用和工业活动有关。水稻中的重金属表现出不同的空间分布模式。制作了互相关图,以定量确定水稻的土壤特性和重金属组成之间的空间相关性。 pH和土壤有机质与水稻中重金属的含量具有显着的空间相关性。所选的大多数变量对水稻中的重金属具有明确的空间相关性范围,可进一步用于划分农业管理区。

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