Y Source identification and contribution of land uses to the observed values of heavy metals in soil samples of the border between the Northern Ireland and Republic of Ireland by receptor models and redundancy analysis

被引:44
作者
Sakizadeh, Mohamad [1 ]
Zhang, Chaosheng [2 ]
机构
[1] Shahid Rajaee Teacher Training Univ, Dept Environm Sci, Tehran, Iran
[2] Natl Univ Ireland, Galway, Ireland
关键词
PCA-APCS; PMF; Redundancy analysis; Unmix; Source identification; POLYCYCLIC AROMATIC-HYDROCARBONS; METALLIFEROUS MINE TAILINGS; POTENTIALLY TOXIC ELEMENTS; MATRIX FACTORIZATION MODEL; ECOLOGICAL RISK-ASSESSMENT; SOURCE APPORTIONMENT; SPATIAL-DISTRIBUTION; AGRICULTURAL SOIL; WATER-QUALITY; GEOSTATISTICAL ANALYSES;
D O I
10.1016/j.geoderma.2021.115313
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
The main objectives of the current research were source identification and quantification of the relationship between land use pattern and heavy metals (HMs) (Cr, Ni, Cd, Hg, Pb, Co, Zn, Cu, As) in soil samples collected in the border of Republic of Ireland and Northern Ireland. For the first goal, positive matrix factorization (PMF), principal component analysis with absolute principal component scores (PCA/APCS) and Unmix were utilized whereas, for the second objective, redundancy analysis (RDA) was employed. The results of source apportionment indicated that the geological formations (e.g. parent rocks), mineral explorations along with application of fertilizers in agriculture were the most influential contributing factors for the elevated levels of HMs. In this context, PCA/APCS and Unmix identified 3 sources compared to 4 sources detected by PMF with R-2 values larger than 0.7, except for As and Hg, indicating the reasonable accuracy of these receptor models for source identification. Among the 9 HMs considered, the performance of both PMF and PCA/APCS for As and Hg were poor with R-2 values equal to 0.23 and 0.51 for PMF versus 0.71 and 0.48 yielded by PCA-APCS. According to the findings of RDA; Cr, Co, As, Ni and Cu appeared to be the primary elements having strong correlations with pH and land use types. Additionally, the results of RDA demonstrated that Zn and Cu are the most probable elements that may be influenced by the amount of phosphorus in soil whereas Hg, Pb, Cr, Co and Ni are less likely to be affected.
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页数:13
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