生态环境损害鉴定评估结果易受污染物时空分布异质性、损害范围模拟模型选取、价值量化参数取值等多重因素制约,存在不确定性。为系统构建生态环境损害鉴定评估不确定性分析技术体系,为损害赔偿磋商、司法诉讼等提供理论依据和技术支撑,本文梳理归纳了土壤和地下水环境损害鉴定评估不确定性的主要来源及主流分析手段。同时,以某典型土壤环境损害案件为实证研究对象,分别采用高斯序贯模拟和蒙特卡罗模拟方法,针对损害实物量化和价值量化两大核心环节开展不确定性量化解析。研究通过在高不确定性区域加密布设调查点位、合理优化损害修复单价取值区间,使土壤环境损害案例的损害面积和修复面积不确定性波动范围分别降至优化前的39.36%和65.38%;在90%概率水平下,损害数额较优化前下降69.99%,为后续损害赔偿磋商和司法裁决提供更为客观、精准的数据支撑。研究证实,针对关键不确定性区域开展靶向补充调查,合理筛选与校准修复单价等核心评估参数,能够有效压缩评估结果波动区间,显著提升生态环境损害鉴定评估结论的科学性与可靠性。
The identification and assessment of ecological and environmental damage are inherently uncertain due to various factors, including the spatiotemporal variability of pollutant distribution, the simulation models used to assess damage scope, and the parameters employed for value quantification. This study aims to establish a robust methodological framework for uncertainty analysis in these processes, providing a theoretical foundation and technical support for damage compensation negotiations and judicial litigation. The research outlines the primary sources of uncertainty and the prevailing analytical methods utilized in soil and groundwater damage assessment. Additionally, a case study of soil environmental damage is conducted employing Gaussian sequential simulation and Monte Carlo simulation to quantitatively assess uncertainties in physical and value quantification stages. Through additional sampling in high-uncertainty zones and optimizing the unit price range for soil remediation, the uncertainty ranges for damaged areas and areas to be remediated in the soil environmental damage case decreased to 39.36% and 65.38% of their original levels, respectively. Post-optimization, the damage amount decreased by 69.99% at a 90% probability level, enhancing the accuracy of data crucial for subsequent compensation negotiations and legal proceedings. This research confirms that targeted supplementary investigations in critical uncertain areas and the judicious refinement of key assessment parameters, such as the unit price for remediation, can effectively reduce the variability in assessment outcomes, significantly enhancing the scientific rigor and reliability of conclusions in ecological and environmental damage identification and assessment.
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