| Popis: |
The heavy metals in soil have serious impacts on safety, ecological environment and human health due to their toxicity and accumulation. It is necessary to efficiently identify the risk area of heavy metals in farmland soil, which is of important significance for environment protection, pollution warning and farmland risk control. We collected 204 samples and analyzed the contents of seven kinds of heavy metals (Cu, Zn, Pb, Cd, Cr, As, Hg) in Zengcheng District of Guangzhou, China. In order to overcame the problems of the data, including the limitation of abnormal values and skewness distribution and the smooth effect with the traditional kriging methods, we used sequential indicator simulation method (SISIM) to define the spatial distribution of heavy metals, and combined Hakanson index method to identify potential ecological risk area of heavy metals in farmland. The results showed that: (1) Based on the similar accuracy of spatial prediction of soil heavy metals, the SISIM had a better expression of detail rebuild than ordinary kriging in small scale area. Compared to indicator kriging, the SISIM had less error rate (4.9%-17.1%) in uncertainty evaluation of heavy-metal risk identification. The SISIM had less smooth effect and was more applicable to simulate the spatial uncertainty assessment of soil heavy metals and risk identification. (2) There was no pollution in Zengcheng's farmland. Moderate potential ecological risk was found in the southern part of study area due to enterprise production, human activities, and river sediments. This study combined the sequential indicator simulation with Hakanson risk index method, and effectively overcame the outlier information loss and smooth effect of traditional kriging method. It provided a new way to identify the soil heavy metal risk area of farmland in uneven sampling.农田土壤重金属的日益累积已对农作物安全、生态环境和人类健康造成严重威胁,高效、精确地识别农田土壤重金属风险区对农田的环境保护、污染预警和风险管控等有重要意义.以广州市增城区为研究对象,共采集204个农田土壤样点,测定了铜(Cu)、锌(Zn)、铅(Pb)、镉(Cd)、铬(Cr)、砷(As)和汞(Hg)7种重金属含量.针对实际采样数据中存在异常值与偏态分布,以及传统克里格法存在的平滑效应等问题,将序贯指示模拟引入农田土壤重金属的风险识别中,与常用识别方法进行比较,并根据Hakanson风险指数评价进行风险区划.结果表明: (1)对比普通克里格法,在精度相似情况下,序贯指示模拟法较为精细地模拟了重金属的空间分布,平滑效应低,预测的细节表现好;对比指示克里格法,其在划分风险区域时的不确定评估中准确度较高,其误判率仅为4.9%～17.1%,表明其能更好地适用于模拟农田土壤重金属的空间分布和风险识别; (2)增城区的农田土壤重金属均未超标,但在南部的极少数区域存在潜在中等风险,主要成因是包括企业生产、人类活动和河流沉积物等.本研究以序贯指示模拟为基础,有效克服了传统克里格法存在的异常值信息丢失和平滑效应问题,结合Hakanson风险指数法,为非均匀采样的土壤重金属空间风险的识别提供一种新的尝试. |
