Risk Assessment of Polycyclic Aromatic Hydrocarbons in the Shenfu Irrigation Area in China and their Application for Determining the Optimum Land Use Model

Abstract

In order to use contaminated soil safely, risk and use planning of contaminated soils by 16 priority polycyclic aromatic hydrocarbons (PAHs) of the United States Environmental Protection Agency (USEPA) in Shenfu Irrigation Area (SIA) were investigated. The toxic equivalency factor (TEF) approach and the risk quotient (RQ) approach were used to assess the carcinogenic risk and ecological risk of PAHs in the current agricultural use, respectively, and the ecological risk of PAHs in SIA under residential, commercial, and industrial land uses which could be used in the future were also evaluated. The results were as follows: 95.9% of soils in SIA were heavily contaminated by PAHs; Benzo[a]pyrene (BaP), Benzo[a]anthrancene (BaA), Benzo[b]fluoranthene (BbF), Benzo[k]fluoranthen (BkF), Benzo[g,h,i]perylene, Chrysene, Dibenz[a,h]anthracene (Dba), and Indeno[1,2,3-c,d]pyrene (Ipy) were the dominated carcinogenic PAHs, and there were no carcinogenic concerns for 81.6% of SIA; Anthracene, BaP, Fluoranthene, Naphthalene, Phenanthrene, BaA, BbF, BkF, Dba, Ipyr and Pyrene were considered the major ecological risk drivers, and there were medium to high ecological risks in 56.3% of SIA under agricultural use. However, the ecological risk can be reduced markedly by changing the land use mode; under residential/parkland land use 65.1% of SIA faced low risk and the rest faced negligible risk, while all areas faced negligible risk under industrial/commercial usage. Based on the risk assessment results, an optimum land use model (both human health-based and eco-based in the SIA) was achieved and will be helpful for the local government to plan how to use the land under low risk in the SIA.

Keywords:

• Polycyclic aromatic hydrocarbons
• risk assessment
• risk quotient
• land use
• soil

Acknowledgements

We would like to thank Wei Hou for his assistance with fixed position and the use of GIS. The research was supported by “the Fundamental Research Funds for the Central Universities,” “National Scientific Foundation of China (41101295),” and “National Scientific Foundation of Liaoning Province (201102226).”