Biomass burning contributed most to the human cancer risk exposed to the soil-bound PAHs from Chengdu Economic Region, western China.

The purpose of this study was to assess the human cancer risk due to the exposure to the soil-bound polycyclic aromatic hydrocarbons (PAHs) from Chengdu Economic Region (CER), western China with the main concern on cancer risk source apportionment. The total concentrations of sixteen PAHs ranged from 12.5 to 75431 ng g-1, with a mean value of 3106 ng g-1, which suggested that the most areas of CER were contaminated. Source apportionment of PAHs was conducted by the positive matrix factorization (PMF) model and the biomass burning contributed most (63.6%) to the total PAHs, followed by petroleum combustion (16.0%), coke source (11.3%), and petrogenic source (9.2%). Results from incremental lifetime cancer risk (ILCR) calculation showed that soil ingestion exerted the highest cancer risk (accounted for 98.1 - 99.3% of the total cancer risk) on human health among three different exposure pathways, followed by dermal contact (0.66 - 1.83%) and inhalation (0.03 - 0.04%). Among different age groups, adult suffered the highest cancer risk via any exposure pathways. Based on PMF and ILCR methods, the cancer risk source apportionment was conducted and the biomass burning showed moderate cancer risk. The petrogenic, coke, and petroleum sources showed low cancer risks to human. To analyze the sensitivity of the parameters used in ILCR calculation, Monte Carlo simulation was employed. The results indicated that the contribution of each source and exposure duration (ED) were the influential parameters on human health associated with soil-bound PAHs. Therefore, much attentions should be paid to biomass burning to avoid cumulative cancer risk.

Source apportionment of polycyclic aromatic carbons (PAHs) in sediment core from Honghu Lake, central China: comparison study of three receptor models.

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.