Multivariate statistical and GIS-based approach to identify heavy metal sources in soils.

By A. Facchinelli, E. Sacchi, L. Mallen. Environmental Pollution, 2001

1,411 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Environmental Engineering, Pollution

View Paper: https://www.semanticscholar.org/paper/32fa3390addfabb5fa2e499a98d87326397b5e1d

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In Artificial Intelligence

1. Y. Zong
2. X. Qing
3. Yuanan Hu
4. Shenggao Lu
5. Hefa Cheng

In Environmental Engineering

1. Y. Zong
2. X. Qing
3. Shenggao Lu

In Pollution

1. Prabhat Kumar Rai
2. Y. Zong
3. Ki‐Hyun Kim
4. X. Qing
5. Yuanan Hu
6. Shenggao Lu
7. Hefa Cheng
8. C. Kumar

Citations in the corpus

• Urban environmental geochemistry of trace metals. (2006, background): “Thus far, there have been few studies (e.g., Facchinelli et al., 2001; Thums and Farago, 2001; Li et al., 2004; Lee et al., 2005) that have made use of GIS to graphically and digitally present the distribution of trace metals in urban environments.”
• Metal contamination in urban, suburban, and country park soils of Hong Kong: a study based on GIS and multivariate statistics. (2006, methodology): “, 2004) and other areas (Tao, 1995; Mielke et al., 2000; Facchinelli et al., 2001; Norra et al., 2001; Romic and Romic, 2003) to study the distribution of metals in soils and their sources using GIS methods.”
• Lead (Pb) isotopic fingerprinting and its applications in lead pollution studies in China: a review. (2010, background): “Traditional approaches rely heavily on statistical analysis of large databases of samples to identify the sources and pathways of heavy metal contamination (e.g., Facchinelli et al., 2001; Qishlaqi and Moore, 2007).”
• Heavy metals in food crops: Health risks, fate, mechanisms, and management. (2019, background): “Indoors, the source identification of heavy metals can be performed using advanced statistical and geospatial tools (Facchinelli et al., 2001; Acosta et al., 2011; Xu et al., 2015; Fan et al., 2017).”
• Assessment of heavy metal pollution and human health risk in urban soils of steel industrial city (Anshan), Liaoning, Northeast China. (2015, methodology): “Pearson's correlation coefficient analysis and principal component analysis (PCA) were used to determine the relationship among heavy metals in urban soils and their possible sources (Facchinelli et al., 2001).”