Agyeman Prince Chapman, John Kingsley, Kebonye Ndiye Michael, Borůvka Luboš, Vašát Radim
Department of Soil Science and Soil Protection, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, 16500, Prague, Czech Republic.
Department of Geosciences, Chair of Soil Science and Geomorphology, University of Tübingen, Rümelinstr, 19-23, Tübingen, Germany.
Environ Geochem Health. 2023 May;45(5):2359-2385. doi: 10.1007/s10653-022-01348-z. Epub 2022 Aug 16.
The study intended to assess the level of pollution of potential toxic elements (PTEs) at different soil depths and to evaluate the source contribution in agricultural soil. One hundred and two soil samples were collected for both topsoil (51), and the subsoil (51) and the content of PTEs (Cr, Cu, Cd, Mn, Ni, Pb, As and Zn) were determined using inductively coupled plasma-optical emission spectroscopy (ICP-OES). The concentrations of Zn and Cd in both soil horizons indicated that the current study levels were higher than the upper continental crust (UCC), world average value (WAV), and European average values (EAV). Nonetheless, the concentration values of PTEs such as Mn and Cu for EAV, As, Cu, Mn, and Pb for UCC, and Pb for WAV were lower than the average values of the corresponding PTEs in this study. The single pollution index, enrichment factor, and ecological risk revealed that the pollution level ranged from low to high. The pollution load index, Nemerow pollution index, and risk index all revealed that pollution levels ranged from low to high. The spatial distribution confirmed that pollution levels varied between the horizons; that is, the subsoil was considered slightly more enriched than the topsoil. Principal component analysis identified the PTE source as geogenic (i.e. for Mn, Cu, Ni, Cr) and anthropogenic (i.e. for Pb, Zn, Cd, and As). PTEs were attributed to various sources using enrichment factor-positive matrix factorization (EF-PMF) and positive matrix factorization (PMF), including geogenic (e.g. rock weathering), fertilizer application, steel industry, industrial sewage irrigation, agrochemicals, and metal works. Both receptor models allotted consistent sources for the PTEs. Multiple linear regression analysis was applied to the receptor models (EF-PMF and PMF), and their efficiency was tested and assessed using root-mean-square error (RMSE), mean absolute error (MAE), and R accuracy indicators. The validation and accuracy assessment of the receptor models revealed that the EF-PMF receptor model output significantly reduces errors compared with the parent model PMF. Based on the marginal error levels in RMSE and MAE, 7 of the 8 PTEs (As, Cd, Cr, Cu, Ni, Mn, Pb, and Zn) analysed performed better under the EF-PMF receptor model. The EF-PMF receptor model optimizes the efficiency level in source apportionment, reducing errors in determining the proportion contribution of PTEs in each factor. The purpose of building a model is to maximize efficiency while minimizing inaccuracy. The marginal error limitation encountered in the parent model PMF was circumvented by EF-PMF. As a result, EF-PMF is feasible and useful for apparently polluted environments, whether farmland, urban land, or peri-urban land.
该研究旨在评估不同土壤深度下潜在有毒元素（PTEs）的污染水平，并评估农业土壤中的污染源贡献。采集了102个土壤样本，包括表层土（51个）和下层土（51个），并使用电感耦合等离子体发射光谱法（ICP - OES）测定了PTEs（铬、铜、镉、锰、镍、铅、砷和锌）的含量。两个土壤层中锌和镉的浓度表明，当前研究水平高于上地壳（UCC）、世界平均值（WAV）和欧洲平均值（EAV）。尽管如此，EAV中锰和铜、UCC中砷、铜、锰和铅以及WAV中铅等PTEs的浓度值低于本研究中相应PTEs的平均值。单污染指数、富集因子和生态风险表明污染水平从低到高不等。污染负荷指数、内梅罗污染指数和风险指数均表明污染水平从低到高。空间分布证实不同土层的污染水平存在差异；也就是说，下层土被认为比表层土富集程度略高。主成分分析确定PTEs的来源为地质成因（如锰、铜、镍、铬）和人为来源（如铅、锌、镉和砷）。使用富集因子 - 正定矩阵因子分解法（EF - PMF）和正定矩阵因子分解法（PMF）将PTEs归因于各种来源，包括地质成因（如岩石风化）、肥料施用、钢铁工业、工业污水灌溉、农用化学品和金属加工。两种受体模型为PTEs分配了一致的来源。将多元线性回归分析应用于受体模型（EF - PMF和PMF），并使用均方根误差（RMSE）、平均绝对误差（MAE）和R准确性指标对其效率进行测试和评估。受体模型的验证和准确性评估表明，与母体模型PMF相比，EF - PMF受体模型输出显著减少了误差。基于RMSE和MAE中的边际误差水平，分析的8种PTEs（砷、镉、铬、铜、镍、锰、铅和锌）中有7种在EF - PMF受体模型下表现更好。EF - PMF受体模型优化了源分配中的效率水平，减少了确定各因素中PTEs比例贡献时的误差。建立模型的目的是在使误差最小化的同时使效率最大化。EF - PMF规避了母体模型PMF中遇到的边际误差限制。因此，EF - PMF对于明显污染的环境（无论是农田、城市土地还是城郊土地）都是可行且有用的。
