The application of urban anthropogenic background to pollution evaluation and source identification of soil contaminants in Macau, China

Highlights: • ABVs were derived according to the accumulation distribution of contaminants. • ABVs combined with entropy weight method were applied in pollution assessment. • ABVs were utilized to specify uncertainty for pollution source identification. • The approaches in conformity with ABVs were proved applicable in the case of Macau. The anthropogenic background characterized by the accumulation characteristics of contaminants is recognized as an important evidence in pollution assessment and source identification in urban soil due to its less arbitrariness compared with the existing quality standards and the guidelines. A credible approach for pollution index calculation referring to anthropogenic background values (ABVs) combined with entropy weight method was developed. By the approach, the soil pollution degrees in Macau, China (one of the most densely populated region worldwide) were assessed based on the database of the heavy metals, Cd, Cu, Hg, Pb, and Zn, and high molecular weight polycyclic aromatic hydrocarbons (HMW PAHs) from 31 sites spatially distributed all over Macau. It was revealed that approximately half of the sites had no specific point source pollution. Mercury, benzo(a)anthracene (BaA), fluoranthene (FLT), and benzo(b)fluorantene (BbF), which had the highest weights were considered as the main contaminants. Macau Peninsula was identified as the critical polluted area. Then, the positive matrix factorization (PMF) coupled with ABVs as one of the data uncertainty inputs was used to identify the anthropogenic pollution sources of the contaminants. Three main anthropogenic sources with their contributions, including vehicle emissions (51.3%), use of hazard material (24.8%), and municipal or domestic waste (23.9%), could be well identified and quantified in the study area. The error estimation of the results showed that the variation of the contaminants in the derived factors were stable. The approaches which were in conformity with ABVs of soil contaminants are proved applicable in soil pollution assessment and source identification.