ABSTRACT

In this study, a new approach to predicting the ability of a hydrometallurgical process to simultaneously remove metal(loid)s, pentachlorophenol (PCP), and polychlorodibenzodioxins and furans (PCDD/F) from contaminated soil is developed. The remediation process consisted of attrition and alkaline leaching steps applied for the coarse (> 0.250 mm) and fine (< 0.250 mm) fractions, respectively. First, a contaminant granulometric distribution-CGD model was established from granulo-chemical analyses performed on 5 selected sampling points collected from the contaminated site to estimate the levels of metallic and organic (PCP, PCDD/F) contamination in the coarse (> 0.250 mm) and fine (< 0.250 mm) fractions of the entire sample (24) and reduce the analytical costs. The accuracy of the CGD model for each contaminant in both fractions was then evaluated by cross-validation. The CGD model, sequential Gaussian simulation (SGS), and linear regression analyses were combined to predict the ability of the attrition and leaching processes applied to the coarse (> 0.250 mm) and fine (< 0.250 mm) soil fractions to simultaneously remove As, PCP, and PCDD/F from contaminated soil, respectively. The results showed that the attrition process could effectively remove the contaminants below the regulation standards to allow the industrial use of the rehabilitated site, as the coarse fraction represents an average proportion of 84 ± 2% of the total soil. However, the leaching process was ineffective in decontaminating the fine fraction (< 0.250 mm), which represented an average proportion of 14 ± 1% of the total soil. Based on these results, the most suitable strategy for this site can be established and a methodological reference for similar studies in risk assessment can be provided.

抽象的

在这项研究中，开发了一种新的方法来预测湿法冶金工艺从受污染的土壤中同时去除金属（胶体），五氯苯酚（PCP）以及多氯二苯并二恶英和呋喃（PCDD / F）的能力。修复过程包括分别对粗粒级分（> 0.250 mm）和细级分（<0.250 mm）进行磨耗和碱浸。首先，通过对从受污染地点收集的5个选定采样点进行的颗粒化学分析，建立了污染物粒度分布CGD模型，以估算粗颗粒（> 0.250毫米）中的金属和有机物（PCP，PCDD / F）污染水平）和整个样品（24）的细小部分（<0.250毫米），并降低了分析成本。然后通过交叉验证评估两种馏分中每种污染物的CGD模型的准确性。CGD模型，顺序高斯模拟（SGS）和线性回归分析相结合，可以预测应用于粗粒（> 0.250 mm）和细粒（<0.250 mm）的磨料的损耗和浸出过程同时去除As的能力， PCP和PCDD / F分别来自受污染的土壤。结果表明，减磨过程可以有效地去除低于法规标准的污染物，从而允许工业化使用修复后的场地，因为粗颗粒平均占土壤总面积的84±2％。但是，浸出过程无法有效净化细小颗粒（<0.250 mm），平均占土壤总量的14±1％。基于这些结果，可以为该站点建立最合适的策略，并可以为风险评估中的类似研究提供方法学参考。