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Spatial variations of concentrations of copper and its speciation in the soil-rice system in Wenling of southeastern China
Authors:Keli Zhao  Weijun Fu  Xingmei Liu  Dongliang Huang  Chaosheng Zhang  Zhengqian Ye  Jianming Xu
Institution:1. School of Environmental and Resource Sciences, Zhejiang A&F University, Lin’an, 311300, China
2. Institute of Soil and Water Resources and Environmental Science, Zhejiang University, Hangzhou, 310058, China
3. School of Law, Shanghai University of Finance and Economics, Shanghai, 200433, China
4. GIS Centre, Ryan Institute and School of Geography and Archaeology, National University of Ireland, Galway, Ireland
Abstract:Copper (Cu) is one of the essential elements for plant growth, while excessive Cu in soils has potential environmental risks. There is little information on spatial variation of Cu in practical paddy fields. This is now important for appropriate agricultural management. The spatial patterns of Cu, its fractions in soils, and its concentrations in rice were investigated in a typical rice production region—Wenling of southeastern China. A total of 96 pairs of rice grain and soil samples (0–15 cm) were collected. The total concentration of Cu and its fractions were very variable, with large skewness, kurtosis, and coefficient of variation (CV) values. Compared to the guideline value (50 mg kg?1), Cu pollution in paddy fields was observed in the study area. All the measured Cu concentrations in rice were lower than 10 mg kg?1, suggesting that they remained at a safe level. Spatial analyses including Moran’s I index and geostatistics results indicated that high-high spatial patterns for both Cu in soils and rice were found in the northwest part, which was mainly related to industrial and E-waste dismantling activities. The low-low spatial patterns of Cu in the soil-rice system were located in the south part of study area. The cross-correlogram results indicated that Cu concentration in rice was significantly spatially correlated with total Cu in soils, its fractions, and soil organic matter (SOM), but significantly negatively correlated with pH and electrical conductivity (EC). Most of the selected variables had a clear spatial correlation range with Cu in rice. The ranges of significant spatial correlation (p?<?0.05) could be obtained and further used for dividing agricultural management zones.
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