基于土壤气快速筛查的地下水苯系物(BTEX)污染反演试验研究

Simulation test study on inversion of BTEX pollution in groundwater based on soil gas rapid screening

以苯系物(BTEX)为代表的挥发性有机物(VOCs)是工业遗留场地中普遍存在的污染物之一,其迁移范围广,环境风险高。为现场快速识别地下水中的BTEX污染程度与范围,提高地下水监测井布点科学性和准确性,降低调查时间与经济成本,本研究基于BTEX相分配和稳态扩散模型,构建了理想状态的地下水-土壤气BTEX污染扩散三维模型,提出了通过土壤气现场快速筛查反演地下水BTEX污染的方法,并利用6.0 m×1.1 m×2.5 m的大型砂箱开展模拟试验。试验结果表明通过土壤气分层采样与现场快速检测,能够较为精准地反演地下水中BTEX的污染状况,地下水中苯、甲苯、乙苯、二甲苯的反演浓度分别为32.18~21 715.09μg/L、16.10~13 173.69μg/L、30.28~4 212.24μg/L、19.25~4 583.23μg/L,相较于实测浓度9.65~21 716.81μg/L、14.95~13 171.93μg/L、3.17~4 233.04μg/L、21.39~4 498.93μg/L,拟合度高达0.988 7~0.999 2。研究成果能够为污染场地调查监测与防控预警等提供参考,但对于实际复杂场地应用还需不断深入探索,进一步完善模型参数,提高反演精度。

VOCs represented by BTEX,are one of the common contaminants in industrial sites,which have a wide migration range and high environmental risk.In order to quickly identify the BTEX pollution in groundwater,improve the scientificity and accuracy of groundwater monitoring well placement,and reduce the investigation time and economic cost,this study built an ideal 3-dimensional model of BTEX pollution diffusion between groundwater and soil gas based on the BTEX phase distribution and steady-state diffusion model.A method of inversion of groundwater BTEX pollution through soil gas screening in the field was proposed,and a simulation test was carried out with a large sand box of 6.0 m×1.1 m×2.5 m.The results showed that the BTEX pollution in groundwater could be retrieved through stratified soil gas sampling and rapid detection.The inversion concentration of benzene,toluene,ethylbenzene and xylene in groundwater was 32.18~21715.09μg/L,16.10~13173.69μg/L,30.28~4212.24μg/L and 19.25~4583.23μg/L,respectively.Compared with the measured concentration 9.65~21716.81μg/L,14.95~13171.93μg/L,3.17~4233.04μg/L,21.39~4498.93μg/L,the R 2 was 0.9887~0.9992.The research can provide a reference for the contaminated site investigation and control warning,but for the actual application of complex sites,further exploration is needed to further improve the model parameters and improve the inversion accuracy.