RBCA、CLEA及CalTOX模型在苯并[a]芘污染场地健康风险评估中的应用比较

为探讨不同模型对污染场地健康风险评估结果的影响,以苯并a]芘为例,采用RBCA、CLEA和CalTOX模型对某工业污染场地表层土壤进行健康风险评估,分析了评估结果的差异和原因,同时对模型的主要暴露参数进行了敏感性分析,并推导出基于风险概率分布的土壤修复限值。结果表明,RBCA、CLEA和CalTOX模型计算的苯并a]芘致癌总风险分别为2.40×10-4、6.32×10-4和7.04×10-6,且经口摄入和皮肤接触2个途径对人体健康造成的危害最大。降解作用是影响CalTOX模型风险评估结果不同于RBCA和CLEA模型的重要因素,3个模型间参数取值及方法学的差异也会导致风险评估结果不同。各模型暴露参数的敏感性排序也有差异。采用基于风险概率分布的方法推导土壤修复限值,RBCA、CLEA和CalTOX模型所得结果分别为0.18、0.08、0.13(不考虑降解作用CalTOX模型)和10.74(考虑降解作用CalTOX模型)mg·kg-1,为各模型直接推导值的1.5～2.6倍。基于风险概率分布的方法可有效降低风险评估过程中参数不确定性的影响,为工业污染场地土壤修复值的制定提供参考。

Comparison of RBCA, CLEA and CalTOX for Health Risk Assessment of a Benzo [a] pyrene Contaminated Site

To investigate the differences in health risk assessment of contaminated sites using different models, RBCA, CLEA and CalTOX models were applied to conduct health risk assessment of an industrial site with surface soil contaminated by benzoa]pyrene (Ba]P). The differences in the assessment results and the causes of the differences among RBCA, CLEA and CalTOX models were discussed. The main exposure parameters in each model were ranked by sensitivity analysis. The soil cleanup levels were also developed based on risk probability distribution. Results showed that the total carcinogenic risk of Ba]P obtained by RBCA, CLEA and CalTOX was 2.40×10^-4, 6.32×10^-4 and 7.04×10^-6, respectively. Oral ingestion and dermal contact were the dominant exposure pathways, contributing most to the total risk. Degradation assumption in CalTOX model was an important reason for obtaining different results from those of RBCA and CLEA models. The parameter selection and methodological difference also contributed to the differences in the assessment results obtained by the three models. Besides, the sensitivity of exposure parameters ranked differently in the three models. Based on risk probability distribution, the soil cleanup levels obtained by RBCA, CLEA and CalTOX were 0.18, 0.08, 0.13 (CalTOX without degradation assumption) and 10.74 (CalTOX with degradation assumption) mg·kg^-1, which were 1.5-2.6 times of the values derived directly by the three models. The method based on risk probability distribution can reduce the influence of parameter uncertainty on the risk assessment, providing reference for developing soil cleanup levels of industrial contaminated sites.