Soil heavy metal
收藏资源简介：
“原始数据”是指通过测量研究区域内六种重金属元素（Cr、Cu、Pb、Ni、Zn和Hg）的浓度而获得的数据。第一列X表示采样点的经度，第二列Y表示采样点的纬度，第三列Z表示采样点的高程，后列为六种重金属元素的浓度数据。利用这些数据，在EXCEL中完成了土壤重金属的描述性统计，包括最大值、最小值、平均值、标准差等。“空间变异性分析数据”用于分析土壤重金属的空间变异性。数据的第一列X表示经度（十进制表示），第二列Y表示纬度（十进制表示）。由于变异性分析要求数据服从正态分布或近似正态分布，因此除 Hg 外，其他元素都满足此要求。数据的最后一列显示了对数转换后汞浓度的正态分布。“单一污染指数”是单一污染物的指数数据。“综合污染指数”是各种污染物的综合指数数据。“源头识别数据（PCA-APCS）”是指使用PCA/APCS模型进行源头识别分析的数据。“源头识别数据（PMF）”是指使用PMF模型进行源头识别分析的数据。“不确定性”是PMF模型所需的不确定性数据。
"Raw Data" refers to the dataset acquired by measuring the concentrations of six heavy metal elements (Cr, Cu, Pb, Ni, Zn, and Hg) in the study area. The first column X represents the longitude of sampling points, the second column Y represents the latitude, the third column Z represents the elevation of sampling points, and the remaining columns correspond to the concentration data of the six heavy metal elements. Descriptive statistics for soil heavy metals, including maximum, minimum, mean, and standard deviation, were carried out in Excel using this dataset. "Spatial Variability Analysis Data" is dedicated to analyzing the spatial variability of soil heavy metals. The first column X of this dataset indicates longitude (expressed in decimal degrees), while the second column Y indicates latitude (expressed in decimal degrees). Since spatial variability analysis requires data to follow a normal or approximately normal distribution, all elements except Hg meet this criterion. The last column of the dataset displays the normal distribution of mercury concentration following logarithmic transformation. "Single Pollution Index" refers to the index data of individual pollutants. "Comprehensive Pollution Index" refers to the comprehensive index data integrating multiple pollutants. "Source Identification Data (PCA-APCS)" denotes the data used for source identification analysis via the PCA/APCS model. "Source Identification Data (PMF)" denotes the data used for source identification analysis via the PMF model. "Uncertainty Data" refers to the uncertainty data required for the PMF model.
