Multivariate linear regression model for source apportionment and health risk assessment of heavy metals from different environmental media.

The study evaluated source apportionment of heavy metals in vegetable samples from the potential sources of fertilizer, water and soil samples collected along the Changjiang River delta in China. The results showed that 25.72% of vegetable samples (Brassica chinensis L.) containing Pb, and Cd, Cu, Hg and Zn at relatively serious levels were from soil. Combined with principle component analysis (PCA) and cluster analysis (CA), the results of the spatial distribution of heavy metals in different environmental media indicated that fertilizer, water and soil were the main sources of heavy metals in vegetables. The results of multivariate linear regression (MLR) using partition indexes (P) showed that fertilizer contributed to 38.5%, 40.56%, 46.01%, 53.34% and 65.25% of As, Cd, Cu, Pb and Zn contents in vegetables, respectively. In contrast, 44.58% of As, 32.57% of Hg and 32.83% of Pb in vegetables came from soil and 42.78% of Cd and 66.97% of Hg contents in vegetables came from the irrigation water. The results of PCA and CA verified that MLR using P was suitable for determining source apportionment in a vegetable. A health risk assessment was performed; As, Cd and Pb contributed to more than 75% of the total hazard quotient (THQ) values and total carcinogenic risk values (Risktotal) for adults and children through oral ingestion. More than 70% of the estimated THQ and Risktotal is contributed by water and fertilizer. Therefore, it is necessary to increase efforts in screening limits/levels of heavy metals in fertilizer and irrigation water and prioritize appropriate pollution management strategies.

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