农业环境科学学报2025，Vol.44Issue(4)：942-951,10.DOI:10.11654/jaes.2024-0294
长株潭地区稻田土壤淹水后有效态镉变异的主控因子研究
Study on main controlling factors of available cadmium variation in paddy soil after flooding in Changsha-Zhuzhou-Xiangtan area
摘要
Abstract
In Changsha-Zhuzhou-Xiangtan area of China,it is important to evaluate the mechanism of soil properties affecting soil available cadmium(Cd).In this paper,gradient diffusion film(DGT)technology was used to explore the differences of Cd content in different soils after short-term flooding,and data mining methods such as stepwise regression and mixed linear regression(Cubist)were used to analyze the independent and combined effects of environmental factors controlling Cd release.The results showed that the variation of total Cd content in soil could explain 75％of the variation of Cd release,and other soil factors such as Fe and Mn oxides,organic matter,soil antagonistic cations(such as Cu)and pH had different effects on Cd release under different conditions.Cadmium in manganese binding state is more easily released into soil solution,which promotes the increase of Cd activity.High content of iron inhibits the activity of Cd,and iron-bound Cd is also released into the soil solution to form a part of available Cd.Due to the galvanic effect between Cu and Cd,the increase of Cu content promotes the release of Cd,but the effect is weak.The inhibition effect of organic matter on Cd release is reflected in the soil with high Cd content,the pH variability in the sampling area is weak,and the control effect on Cd release is easily masked by other related factors such as Mn.关键词
镉/梯度扩散薄膜(DGT)技术/逐步回归模型/混合线性回归模型/释放Key words
cadmium/gradient diffusion thin film(DGT)technology/stepwise regression model/Cubist model/release分类
环境科学引用本文复制引用
吕丹蕾,王震,张闯闯,刘文婧,张铁亮,纪雄辉,赵玉杰..长株潭地区稻田土壤淹水后有效态镉变异的主控因子研究[J].农业环境科学学报,2025,44(4):942-951,10.基金项目
国家重点研发计划子课题:区域产地镉砷污染数据智能甄别与时空同化(2022YFD1700105)National Key Research and Development Program of China:Intelligent Identification and Spatio-temporal Assimilation of Cadmium and Arsenic Pollution Data of Regional Origin(2022YFD1700105) （2022YFD1700105）
