Abstract
The spatial distribution of polycyclic aromatic hydrocarbons (PAHs) and their source contributions employing receptor models has been widely reported. However, the temporal distribution of PAH source contributions is less studied. Thus, in this paper, three receptor models including principle component analysis-multiple linear regression (PCA-MLR), positive matrix factorization (PMF), and Unmix were used to PAH source apportionment study in a sediment core from Honghu Lake, China. Sixteen USEPA priority PAHs in 37 sliced sediment layers (1-cm interval) were measured, with the concentrations of ∑16PAH (sum of 16 PAHs) ranging from 93.0 to 431 ng g−1. The source apportionment results derived from three receptor models were similar, with three common sources: mixed sources of biomass burning and coal combustion (31.0–41.4% on average), petroleum combustion (31.8–45.5%), and oil leakage (13.1–21.3%). The PMF model segregated an additional source: domestic coal combustion (contributed 20.9% to the ∑16PAHs). Four aspects including intra-comparison, inter-comparison, source numbers and compositions, and source contributions were considered in comparison study. The results indicated that the PMF model was most reasonable in PAH source apportionment research in this study.
http://ift.tt/2xnSENe
Δεν υπάρχουν σχόλια:
Δημοσίευση σχολίου