纳米铁原位注入技术对六价铬污染地下水的修复

纳米零价铁原位注入是六价铬污染地下水的有效修复技术之一。为验证其场地修复效果,在北京某电镀厂搬迁后的遗留六价铬污染场地,现场制备纳米铁并通过原位注入对场地内六价铬污染地下水进行原位修复现场中试研究。选取6 m×6 m实验场地,在地下水中六价铬污染浓度最高为2 mg·L~(-1)的中心点设置注射井并在四周设置4口监测井。实验结果表明,原位注入纳米铁药剂具有良好修复效果,修复后该实验场地范围内地下水中六价铬浓度均低于地下水质量Ⅳ类标准0.1 mg·L~(-1),注射井中六价铬还原率达到99%。通过对注射井及监测井地下水中pH、溶解氧、氧化还原电位等检测指标进行跟踪监测和相关性分析,发现氧化还原电位与污染物浓度变化相关性最强,可以作为污染物变化的表征因子。该中试研究结果对于六价铬污染地下水的原位修复具有重要的参考价值。     

铬渣污染场地污染状况研究与修复技术分析

选取某一化工厂铬渣堆放场地作为典型铬渣污染场地,对其钻孔并采集不同深度土壤和地下水样品进行分析。研究发现，该铬渣污染场地存在很严重的土壤和地下水污染。污染物地表扩散较小，剖面扩散很严重，污染深度达6 m，不同特性土壤对六价铬的截留作用不同。在此基础上，归纳总结了国外常用铬渣污染场地修复治理技术的优缺点，并提出具体污染场地修复技术的选取应该根据勘探情况选择合适的某些技术组合。     

典型场地地下水污染源强分级评价方法研究

地下水污染程度评价是地下水研究领域的研究热点。以场地浅层地下水为研究对象,基于目前国内工业场地有无防渗措施的分类原则,综合考虑污染源和场地包气带特征因子,构建了地下水污染源强分级评价指标体系。将修正的内梅罗污染指数法应用于污染源危害性分级,并将改进后的DRTAS模型应用于包气带阻控性分级,利用矩阵法构建两方面多因素耦合模型,最后形成了适合典型工业场地的地下水污染源强分级评价的方法。选择4个典型污染场地对评价方法进行实地验证,分析结果表明,对于已建的或拟建的有防渗措施的项目,污染源危害性是造成场地地下水污染的主因;对于已建的无防渗措施项目,污染源危害性和包气带阻控性共同决定地下水污染源强。场地评价结果与水质监测报告结论相符,说明本研究建立的分级评价方法对于地下水污染的预防和控制具有借鉴意义。     

搬迁化工企业遗留场地氯苯污染迁移模拟与不确定分析

基于某搬迁化工企业场地污染调查数据,应用跃迁概率地质统计工具(T-progs)建立了溶质迁移地质统计模型,对该场地氯苯污染进行了不确定评估和风险分析。结果表明,研究场地地下水氯苯污染主要集中在场地的北部和南部,模拟初期场地北部污染羽中心氯苯最高质量浓度为1 240mg/L,污染物在地下水中随时间迁移扩散,100年后该污染羽氯苯最高质量浓度降低到1 030mg/L,但污染羽整体迁移速度较慢。地质统计模型不确定评估结果显示,100年后污染羽在最小分布条件下的氯苯最高质量浓度约为540mg/L,最大分布条件下约为1 207mg/L;场地氯苯污染风险集中在场地东北部和西南部区域,与地下水流动方向一致,但受场地非均值影响,氯苯阀值捕获风险区分布呈不规则形状。     

基于两步优劣解距离法的地下水污染监测网优化

地下水污染监测网的优化能让监测网以合理监测成本获取精确的地下水水质信息.为兼顾监测网空间特征与统计特征,综合考虑区域地下水水质状况和水文地质状况,提出了两步优劣解距离法优化监测网.首先以地下水典型污染物加权综合污染指数和防污性能指数为指标,采用优劣解距离法对现有监测网各监测井评分,并筛选得到不同监测井数量条件下的备选优...     

基于蒙特卡罗法和层次分析法的污染场地地下水修复技术筛选方法研究

在工业转型发展过程中,出现了大量遗留污染场地,对地下水造成严重污染,并加重水资源短缺,而现阶段缺乏易操作的污染场地地下水修复技术筛选方法。为筛选有效的污染场地地下水修复技术,建立了基于层次分析法(AHP)与蒙特卡罗法(MC)的污染场地地下水修复技术筛选方法。该方法利用AHP构建指标体系,结合MC进行抽样,避免了定性描述和单一数值评价带来的不确定性。将该方法用于某铬渣污染场地地下水修复技术的筛选,发现化学氧化/还原是最适宜的修复技术,筛选结果符合实际。     

大气最佳采样时间及其布点的探讨研究

大气污染的因素多种多样,污染物的时空分布也千变万化。要使监测数据客观地反映大气污染的状况和动态,需选择最优监测时间和合理的布点位置,使之充分反映这一区域大气污染现状。本文就大气最佳采样时间及其布点进行研究。一、大气采样最佳时间的探讨大气监测的时间主要指采样时机,它包括时间尺度和采样频率。根据我国现有的监测手段,国家环保局规定:每年冬季1月、春季4月、夏季7月、秋季10月的中旬,各有效监测5天以上,每天监测不得少于4次,每次30分钟。具体时间的选择,应根据本地区污染浓度的变化规律来确定。     

基于MCDA的沙漠地区污染场地地下水修复技术优化方法

针对近年来频频出现的污染企业向沙漠地区地下排污造成地下水污染这一问题,以腾格里沙漠地区某化工厂地下水污染为研究案例,提出适合沙漠地区地下水污染修复技术的优选方法。在综合考虑修复技术的经济、技术和社会效益基础上,利用层次分析法建立修复技术优化指标体系,运用多准则决策分析模型(multiple criteria decision analysis,MCDA)中的消去和选择转换法(ELECTREII)对修复技术组合进行优选排序,确定适合该地区的最优修复技术方案。结果表明,5种地下水修复备选技术中可渗透反应墙、抽出-处理、监测自然衰减技术较为理想,综合考虑该污染场地特征以及地下水治理要求,得出最佳修复方案为:对高污染浓度区域采用抽出-处理技术+可渗透反应墙技术联合修复;对于低污染区域采用监测自然衰减技术。该优化方法可为沙漠地区地下水污染修复技术的选取提供借鉴。     

基于时序蒙特卡罗方法的某铬盐场污染地下水泄漏风险

突发性污染地下水泄漏对周围水环境的影响具有重要研究意义。借鉴时序蒙特卡罗(SMC)方法来模拟污染源运行状态,并结合相应的河流水质模型,对污染地下水泄漏后造成的河流水质超标风险概率进行研究;利用健康风险评价模型,对污染物泄漏时水环境造成的人体健康风险进行评价。以某铬盐场为例验证该方法的稳定性和实用性。结果表明,该场地受污染的地下水对人体健康产生的危害程度为中级,其超标风险概率随模拟时间的增加而趋于稳定。     

吉林省某垃圾填埋场地下水有机污染风险评价

以吉林省某垃圾填埋场地下水为研究对象,监测其中的有机污染物,并进行风险评价。结果表明:(1)有机污染物总计检出18种,5种检出率大于50%。其中,三氯甲烷检出率最高,达到85.7%,质量浓度高达0.217mg/L,超过《生活饮用水卫生标准》(GB 5749—2006)限值(0.06mg/L)。(2)地下水污染指数表明,10种有机污染物具有高淋溶迁移性。(3)以三氯甲烷为典型污染物,14个采样点中,非致癌风险指数均未超过1,12个采样点致癌风险指数超过10~(-6),不在可接受范围。主要暴露途径为饮水摄入。     

土地利用变更的土壤及地下水污染调查方法及实例

以南京大厂区某地块的土壤及地下水污染调查为实例,提出了资料收集、源项分析、监测因子筛选、监测布点．场地地质水文勘探和土壤及地下水采样分析的土壤及地下水污染调查方法,探讨了评价标准和确定土壤及地下水污染范围的方法。     

某矿区土壤和地下水重金属污染调查与评价

为了解湘南某矿区土壤和地下水重金属污染状况，对该矿区东河流域附近重金属污染源进行了调查，同时，对地下水和土壤样品进行了采样分析，结果表明：（1）该矿区东河流域附近的主要污染源有18个，其中有色金属选厂、尾矿库、采矿场和冶炼厂是排放重金属较多的污染源；（2）20个采样点中土壤重金属Pb、Cd、Zn、As和Hg大部分超过国家土壤环境质量标准（GB15618-1995），综合污染指数P综〉1，该矿区主要的重金属污染元素为Cd、As和Hg，且土壤中Cd、Zn和As的含量两两之间存在着极显著的正线性相关关系；（3）重金属元素在土壤中的纵向迁移不明显，该矿区附近20个采样点的地下水并未受到污染，综合污染指数P综〈1。20个采样点地下水Pb、Cd、Zn、As、Hg浓度均能达到地下水质量标准（GB／T14848．9）中的Ⅲ类标准。     

Spatial distribution of pollution in an urban stormwater infiltration basin

Infiltration basins are frequently used for stormwater drainage. Because stormwater is polluted in highly toxic compounds, assessment of pollution retention by infiltration basins is necessary. Indeed, if basins are not effective in trapping pollution, deep soil and groundwater may be contaminated. This study's objective is to investigate soil pollution in infiltration basins: spatial distribution of soil pollution, optimisation of the number of soil samples and a contamination indicator are presented. It is part of a global project on long-term impact of stormwater infiltration on groundwater. Soil sampling was done on a basin in suburban Lyon (France). Samples were collected at different depths and analysed for nutrients, heavy metals, hydrocarbons and grain size. Pollutant concentrations decrease rapidly with depth while pH, mineralisation and grain size increase. Sustainable metal concentrations are reached at a 30-cm depth, even after 14 years of operation; hydrocarbon pollution is deeper. Principal component analysis shows how pollutants affect each level. The topsoil is different from other levels. Three specifically located points are enough to estimate the mass of pollution trapped by the basin with a 26% error. The proposed contamination indicator is calculated using either average level concentrations or maximum level concentrations. In both cases, the topsoil layer appears polluted but evaluation of lower levels is dependent on the choice of input concentrations.     

突发性场地污染应急控制技术研究进展

随着中国社会经济水平的加速发展,近年来各类突发性场地污染事故频发,如何有效地在第一时间对污染物进行应急控制及场地修复显得尤为重要.以突发性场地污染为研究对象,探讨了土壤及地下水中污染物的应急控制及场地修复技术的研究状况,给出了各项应急控制技术在突发性场地污染事故中适用的目标污染物及土壤类型,以便在实际运用中根据场地的污染类型和土壤性质快速做出响应.最后还指出,应急控制技术作为一种暂时性处理手段,可在场地污染事故发生后对污染物扩散进行快速控制,但不可作为一种长期处置措施.     

Breakthrough Curves Characterization and Identification of an Unknown Pollution Source in Groundwater System Using an Artificial Neural Network (ANN)

Contamination of groundwater constrains its uses and poses a serious threat to the environment. Once groundwater is contaminated, the cleanup may be difficult and expensive. Identification of unknown pollution sources is the first step toward adopting any remediation strategy. The proposed methodology exploits the capability of a universal function approximation by a feed-forward multilayer artificial neural network (ANN) to identify the sources in terms of its location, magnitudes, and duration of activity. The back-propagation algorithm is utilized for training the ANN to identify the source characteristics based on simulated concentration data at specified observation locations in the aquifer. Uniform random generation and the Latin hypercube sampling method of random generation are used to generate temporal varying source fluxes. These source fluxes are used in groundwater flow and the transport simulation model to generate necessary data for the ANN model-building processes. Breakthrough curves obtained for the specified pollution scenario are characterized by different methods. The characterized breakthrough curves parameters serve as inputs to ANN model. Unknown pollution source characteristics are outputs for ANN model. Experimentation is also performed with different number of training and testing patterns. In addition, the effects of measurement errors in concentration measurements values are used to show the robustness of ANN based methodology for source identification in case of erroneous data.     

Validation of regression models for nitrate concentrations in the upper groundwater in sandy soils

For Dutch sandy regions, linear regression models have been developed that predict nitrate concentrations in the upper groundwater on the basis of residual nitrate contents in the soil in autumn. The objective of our study was to validate these regression models for one particular sandy region dominated by dairy farming. No data from this area were used for calibrating the regression models. The model was validated by additional probability sampling. This sample was used to estimate errors in 1) the predicted areal fractions where the EU standard of 50 mg l⁻¹ is exceeded for farms with low N surpluses (ALT) and farms with higher N surpluses (REF); 2) predicted cumulative frequency distributions of nitrate concentration for both groups of farms.Both the errors in the predicted areal fractions as well as the errors in the predicted cumulative frequency distributions indicate that the regression models are invalid for the sandy soils of this study area.     

Spatial variability of arsenic and chromium in the soil water at a former wood preserving site

Contamination of industrial sites by wood preservatives such as chromated copper arsenate (CCA) may pose a serious threat to groundwater quality. The objective of this study was to characterise the spatial variability of As and Cr concentrations in the solid phase and in the soil water at a former wood impregnation plant and to reveal the fundamental transport processes. The soil was sampled down to a depth of 2m. The soil water was extracted in situ from the vadose zone over a period of 10 months at depths of 1 and 1.5m, using large horizontally installed suction tubes. Groundwater was sampled from a depth of 4.5m. Results showed that arsenic and chromium had accumulated in the upper region of the profile and exhibited a high spatial variability (As: 21-621 mg kg(-1); Cr: 74-2872 mg kg(-1)). Concentrations in the soil water were high (mean As 167 microg L(-1); Cr: 62 microg L(-1)) and also showed a distinct spatial variability, covering concentration ranges up to three orders of magnitude. The variability was caused by the severe water-repellency of the surface soil, induced by the concurrent application of creosote wood preservatives, which leads to strong preferential flow as evident from a dye experiment. In contrast to soil water concentrations, only low As concentrations (<12 microg L(-1)) were detected in the groundwater. High Cr concentrations in the groundwater (approx. 300 microg L(-1)), however, illustrated the pronounced mobility of chromium. Our study shows that at sites with a heterogeneous flow system in the vadose zone a disparity between flux-averaged and volume-averaged concentrations may occur, and sampling of soil water might not be adequate for assessing groundwater concentrations. In these cases long-term monitoring of the groundwater appears to be the best strategy for a groundwater risk assessment.     

Groundwater pollution source apportionment using principal component analysis in a multiple land-use area in southwestern China

Identification of different pollution sources in groundwater is challenging, especially in areas with diverse land uses and receiving multiple inputs. In this study, principal component analysis (PCA) was combined with geographic information system (GIS) to explore the spatial and temporal variation of groundwater quality and to identify the sources of pollution and main factors governing the quality of groundwater in a multiple land-use area in southwestern China. Groundwater samples collected from 26 wells in 2012 and 38 wells in 2018 were analyzed for 13 water quality parameters. The PCA results showed that the hydro-geochemical process was the predominant factor determining groundwater quality, followed by agricultural activities, domestic sewage discharges, and industrial sewage discharges. Agriculture expansion from 2012 to 2018 resulted in increased apportionment of agricultural pollution. In contrast, economic restructure and infrastructure improvement reduced the contributions of domestic sewage and industrial pollution. Anthropogenic activities were found the major causes of elevated nitrogen concentrations (NO₃^?, NO₂^?, NH₄⁺) in groundwater, highlighting the necessity of controlling N sources through effective fertilizer managements in agricultural areas and reducing sewage discharges in urban areas. The applications of GIS and PCA successfully identified the sources of pollutants and major factors driving the variations of groundwater quality in tested years.

     

Field demonstration and evaluation of the Passive Flux Meter on a CAH groundwater plume

This study comprises the first application of the Passive Flux Meter (PFM) for the measurement of chlorinated aliphatic hydrocarbon (CAH) mass fluxes and Darcy water fluxes in groundwater at a European field site. The PFM was originally developed and applied to measurements near source zones. The focus of the PFM is extended from near source to plume zones. For this purpose, 48 PFMs of 1.4 m length were constructed and installed in eight different monitoring wells in the source and plume zone of a CAH-contaminated field site located in France. The PFMs were retrieved, sampled, and analyzed after 3 to 11 weeks of exposure time, depending on the expected contaminant flux. PFM evaluation criteria include analytical, technical, and practical aspects as well as conditions and applicability. PFM flux data were compared with so-called traditional soil and groundwater concentration data obtained using active sampling methods. The PFMs deliver reasonable results for source as well as plume zones. The limiting factor in the PFM applicability is the exposure time together with the groundwater flux. Measured groundwater velocities at the field site range from 2 to 41 cm/day. Measured contaminant flux data raise up to 13 g/m²/day for perchloroethylene in the plume zone. Calculated PFM flux averaged concentration data and traditional concentration data were of similar magnitude for most wells. However, both datasets need to be compared with reservation because of the different sampling nature and time. Two important issues are the PFM tracer loss during installation/extraction and the deviation of the groundwater flow field when passing the monitoring well and PFM. The demonstration of the PFM at a CAH-contaminated field site in Europe confirmed the efficiency of the flux measurement technique for source as well as plume zones. The PFM can be applied without concerns in monitoring wells with European standards. The acquired flux data are of great value for the purpose of site characterization and mass discharge modeling, and can be used in combination with traditional soil and groundwater sampling methods.