In situ Remediation of Petroleum Contaminated Groundwater by Permeable Reactive Barrier with Hydrothermal Palygorskite as Medium

The permeable reactive barrier（PRB） has proven to be a costeffective technique to remediate the petro leum contaminated groundwater at a northeast field site in China. In this study, the geology, hydrogeology and con tamination characterization of the field site were investigated and the natural hydrothermal palygorskite was chosen as a reactive medium. Furthermore, the adsorption of the total petroleum hydrocarbons（TPH） in the groundwater onto hydrothermal palygorskite and the adsorption kinetics were investigated. The results indicate that the removal rates of TPH, benzene, naphthalene and phenantharene could all reach up to 90% by hydrothermal palygorskite with a diameter of 0.25-2.00 mm that had been thermally pretreated at 140 ℃. The adsorption of TPH onto hydrothermal palygorskite after pretreatment followed a pseudosecondorder kinetic model and a Langmuir adsorption isotherm, suggesting that the theoretic adsorption capacity of hydrothermal palygorskite for adsorbate could be 4.2 g/g. Scan ning electron microscopy（SEM）, infrared spectroscopy（IR）, Xray diffraction（XRD） and Xray fluorescence spec troscopy（XRF） were carried out to analyze the adsorption mechanism. The results reveal that hydrothermal palygors kite is a fibrous silicate mineral enriched in Mg and A1 with large surface area and porosity. The dense cluster acicular and fibrous crystal of hydrothermal palygorskite, and its effect polar group OH played an important role in the physical and chemical adsorption processes of it for contaminants. This study has demonstrated hydrothermal paly gorskite is a reliable reactive medium for in situ remediation of petroleum contaminated groundwater at field sites.

Applications of Monitored Natural Attenuation in Contaminated Soil and Groundwater

Restoration of contaminated soil and groundwater could be divided into two phases. The first phase takes aim at reducing human being＇s health risks by active remediation, while the second phase aims at eliminating ecological risks by natural attenuation （NA）. Because of cost-effective and sustainable cleanup, monitored natural attenuation （MNA） and enhanced natural attenuation （ENA） have been gaining more attention recently, especially in the respects of ecological risk-oriented contaminated land management and a follow-up measure after active remediation. The uses and procedures of MNA for contaminated site cleanup and remediation in USA and EU were introduced firstly, and then possible applications of MNA in China were suggested. More developments and practices of MNA and ENA for managing contaminated sites in China are expected.

Machine learning prediction of methane,ethane,and propane solubility in pure water and electrolyte solutions:Implications for stray gas migration modeling

Hydraulic fracturing is an effective technology for hydrocarbon extraction from unconventional shale and tight gas reservoirs.A potential risk of hydraulic fracturing is the upward migration of stray gas from the deep subsurface to shallow aquifers.The stray gas can dissolve in groundwater leading to chemical and biological reactions,which could negatively affect groundwater quality and contribute to atmospheric emissions.The knowledge oflight hydrocarbon solubility in the aqueous environment is essential for the numerical modelling offlow and transport in the subsurface.Herein,we compiled a database containing 2129experimental data of methane,ethane,and propane solubility in pure water and various electrolyte solutions over wide ranges of operating temperature and pressure.Two machine learning algorithms,namely regression tree(RT)and boosted regression tree(BRT)tuned with a Bayesian optimization algorithm(BO)were employed to determine the solubility of gases.The predictions were compared with the experimental data as well as four well-established thermodynamic models.Our analysis shows that the BRT-BO is sufficiently accurate,and the predicted values agree well with those obtained from the thermodynamic models.The coefficient of determination(R2)between experimental and predicted values is 0.99 and the mean squared error(MSE)is 9.97×10^(-8).The leverage statistical approach further confirmed the validity of the model developed.

Progress in enhancing the remediation performance of microbial fuel cells for contaminated groundwater

Microbial fuel cells(MFCs)have become more prevalent in groundwater remediation due to their capacity for power generation,removal of pollution,ease of assembly,and low secondary contamination.It is currently being evaluated for practical application in an effort to eliminate groundwater pollution.However,a considerable majority of research was conducted in laboratories.But the operational circumstances including anaerobic characteristics,pH,and temperature vary at different sites.In addition,the complexity of contaminants and the positioning of MFCs significantly affect remediation performance.Taking the aforementioned factors into consideration,this reviewsummarizes a bibliography on the application of MFCs for the remediation of groundwater contamination during the last ten decades and assesses the impact of environmental conditions on the treatment performance.The design of the reactor,including configuration,dimensions,electrodes,membranes,separators,and target contaminants are discussed.This review aims to provide practical guidance for the future application of MFCs in groundwater remediation.

Groundwater Contamination with NO_3-N in a Wheat-Corn Cropping System in the North China Plain

The North China Plain,where summer corn(Zea mays L.)and winter wheat(Triticum aestivum L.)are the major crops grown,is a major agricultural area in China.Permeable soils make the region susceptible to groundwater pollution by NO_3-N,which is applied to fields in large amounts of more than 400 kg NO_3-N ha^(-1)as fertilizer.A field experiment was established in 2002 to examine the relationship among N fertilization rate,soil NO_3-N,and NO_3-N groundwater contamination.Two adjacent fields were fertilized with local farmers' N fertilization rate(LN)and double the normal application rate(HN),respectively,and managed under otherwise identical conditions.The fields were under a traditional summer corn/winter wheat rotation.Over a 22-month period,we monitored NO_3-N concentrations in both bulk soil and soil pore water in 20-40 cm increments up to 180 cm depth.We also monitored NO_3-N concentrations in groundwater and the depth of the groundwater table.No significant differences in soil NO_3-N were observed between the LN and HN treatment.We identified NO_3-N plumes moving downward through the soil profile.The HN treatment resulted in significantly higher groundwater NO_3-N,relative to the LN treatment,with groundwater NO_3-N consistently exceeding the maximum safe level of 10 mg L^(-1),but groundwater NO_3-N above the maximum safe level was also observed in the LN treatment after heavy rain.Heavy rain in June,July,and August 2003 caused increased NO_3-N leaching through the soil and elevated NO_3-N concentrations in the groundwater.Concurrent rise of the groundwater table into NO_3-N- rich soil layers also contributed to the increased NO_3-N concentrations in the groundwater.Our results indicate that under conditions of average rainfall,soil NO_3-N was accumulated in the soil profile.The subsequent significantly higher- than-average rainfalls continuously flushed the soil NO_3-N into deeper layers and raised the groundwater table,which caused continuous groundwater contamination with NO_3-N.The results suggest that under common farming practices in the North China Plain,groundwater contamination with NO_3-N was likely,especially during heavy rainfalls,and the degree of groundwater contamination appeared to be proportional to the N application rates.Decreasing fertilization rates, splitting fertilizer inputs,and optimizing irrigation scheduling had potential to reduce groundwater NO_3-N contamination.

Acid mine drainage and heavy metal contamination in groundwater of metal sulfide mine at arid territory (BS mine,Western Australia)

The issues of acid mine drainage （AMD） and heavy metals contamination in the metal sulfide mine in the add district were explored, through studying the acidification and the heavy metals distribution and evolution of groundwater in the black swan （BS） nickel sulfide mine （Western Australia）. The groundwater samples were collected from the drilling holes situated in the vicinity of tailings storage facility （TSF） and in the background of the mine （away from TSF）, respectively, and the pH and electric conductivity （Ec） were measured in site and the metal contents were analysed by ICP-MS and ICP-AES, quarterly in one hydrological year. The results disclose that the TSF groundwater is remarkably acidified （.pHmean=5, pHmin=3）, and the average contents of heavy metals （Co, Cu, Zn, Cd） and Al, Mn are of 1-2 orders of magnitude higher in TSF groundwater than in background groundwater. It may be due to the percolation of tailings waste water from miU process, which leads the tailings to oxidize and the deep groundwater to acidify and contaminate with heavy metals. Besides, the heavy metals concentration in groundwater may be controlled by pH mainly.

Fluoride contamination in groundwater resources of Alleppey,southern India

Alleppey is one of the thickly populated coastal towns of the Kerala state in southern India.Groundwater is the main source of drinking water for the 240,991 people living in this region.The groundwater is being extracted from a multi-layer aquifer system of unconsolidated to semi-consolidated sedimentary formations,which range in age from Recent to Tertiary.The public water distribution system uses dug and tube wells.Though there were reports on fluoride contamination,this study reports for the first time excess fluoride and excess salinity in the drinking water of the region.The quality parameters,like Electrical Conductivity（EC） ranges from 266 to 3900 μs/cm,the fluoride content ranges from 0.68 to2.88 mg/L,and the chloride ranges between the 5.7 to 1253 mg/L.The main water types are Na-HC03,NaCO3 and Na-Cl.The aqueous concentrations of F- and CO32- show positive correlation whereas F- and Ca2＋ show negative correlation.The source of fluoride in the groundwater could be from dissolution of fluorapatite,which is a common mineral in the Tertiary sediments of the area.Long residence time,sediment-groundwater interaction and facies changes（Ca-HCO3 to Na-HCO3） during groundwater flow regime are the major factors responsible for the high fluoride content in the groundwater of the area.High strontium content and high EC in some of the wells indicate saline water intrusion that could be due to the excess pumping from the deeper aquifers of the area.The water quality index computation has revealed that 62%of groundwater belongs to poor quality and is not suitable for domestic purposes as per BIS and WHO standards.Since the groundwater is the only source of drinking water in the area,proper treatment strategies and regulating the groundwater extraction are required as the quality deterioration poses serious threat to human health.

Groundwater modelling to help diagnose contamination problems

Aquifer remediation for a contaminated site is complex, expensive, and long-term. Groundwater modelling is often used as a tool to evaluate remedial alternatives and to design a groundwater remediation system. Groundwater modelling can also be used as a useful process to identify aquifer characteristics and contaminant behaviour that are not realized prior to modelling, to help diagnose what happened and why it happened at contaminant sites. Three real-world modelling cases are presented to demonstrate how groundwater modelling is applied to help understand contamination problems and how valuable the improved understanding is to decision-making and/or to remedial design.

Preliminary Hydrogeologic Modeling and Optimal Monitoring Network Design for a Contaminated Abandoned Mine Site Area: Application of Developed Monitoring Network Design Software

In abandoned mine sites, i.e., mine sites where mining operations have ended, wide spread contaminations are often evident, but the potential sources and pathways of contamination especially through the subsurface, are difficult to identify due to inadequate and sparse geochemical measurements available. Therefore, it is essential to design and implement a planned monitoring net-work to obtain essential information required for establishing the potential contamination source locations, i.e., waste dumps, tailing dams, pits and possible pathways through the subsurface, and to design a remediation strategy for rehabilitation. This study presents an illustrative application of modeling the flow and transport processes and monitoring network design in a study area hydrogeologically resembling an abandoned mine site in Queensland, Australia. In this preliminary study, the contaminant transport process modeled does not incorporate the reactive geochemistry of the contaminants. The transport process is modeled considering a generic conservative contaminant for the illustrative purpose of showing the potential application of an optimal monitoring design methodology. This study aims to design optimal monitoring network to: 1) minimize the contaminant solute mass estimation error;2) locate the plume boundary;3) select the monitoring locations with (potentially) high concentrations. A linked simulation optimization based methodology is utilized for optimal monitoring network design. The methodology is applied utilizing a recently developed software package CARE-GWMND, developed at James Cook University for optimal monitoring network design. Given the complexity of the groundwater systems and the sparsity of pollutant concentration observation data from the field, this software is capable of simulating the groundwater flow and solute transport with spatial interpolation of data from a sparse set of available data, and it utilizes the optimization algorithm to determine optimum locations for implementing monitoring wells.

Physicochemical and Bacteriological Quality of Groundwater, East of Nile Delta of Egypt

Groundwater is an important source of freshwater for drinking and irrigation purposes, and hence protecting it against depletion and deterioration is extremely required. Groundwater could get contaminated physically, chemically, or microbiologically. Each type of contamination is linked to different sources and in turn imposes different types of health problems and consequences. A water sample from Bahr Al-Baqar Wastewater drain and 13 groundwater samples were collected for physiochemical and bacteriological analyses to evaluate groundwater contamination in As-Salihiyyah and adjacent areas, east of Nile Delta of Egypt. Nitrate, COD, and BOD values collected from Bahr Al-Baqr drain and groundwater exceeded the Egyptian maximum permissible limit for drinking water (0.5, 6, 10, respectively). The total number of viable microorganisms (TVC) test for Bahr Al-Baqar drain was recorded as more than 300 CFU/mL, and the total coliform recorded 1100 MPN/100ml, indicating high level of contamination. The high count of the TVC (16-↑300 CFU/mL) for groundwater and the total coliform (3 - 1100 MPN/100ml) indicated that groundwater is contaminated and unsafe for drinking and might be affected by Bahr Al-Baqar wastewater drain.

Groundwater contaminant source identification based on iterative local update ensemble smoother

Identification of the location and intensity of groundwater pollution source contributes to the effect of pollution remediation,and is called groundwater contaminant source identification.This is a kind of typical groundwater inverse problem,and the solution is usually ill-posed.Especially considering the spatial variability of hydraulic conductivity field,the identification process is more challenging.In this paper,the solution framework of groundwater contaminant source identification is composed with groundwater pollutant transport model(MT3DMS)and a data assimilation method(Iterative local update ensemble smoother,ILUES).In addition,Karhunen-Loève expansion technique is adopted as a PCA method to realize dimension reduction.In practical problems,the geostatistical method is usually used to characterize the hydraulic conductivity field,and only the contaminant source information is inversely calculated in the identification process.In this study,the identification of contaminant source information under Kriging K-field is compared with simultaneous identification of source information and K-field.The results indicate that it is necessary to carry out simultaneous identification under heterogeneous site,and ILUES has good performance in solving high-dimensional parameter inversion problems.

Contamination of Groundwater Sources with Common Waterborne Pathogens and Heficobacter pylori in the West Bank： Case Study of Wadi AI Arroub, Tulkarem and Jericho

Detection of waterborne pathogens in drinking water via rapid DNA amplification assays is an important and crucial public health method. The aim of this study is to investigate the presence of waterborne pathogens in groundwater resources in Al Arroub, Tulkarem and Jericho areas using direct PCR （polymerase chain reaction） analysis. Forty-six groundwater samples were collected. The total DNA was extracted from each sample and subjected to PCR analysis directed to specific genes of enteric bacteria, β-lactamases producing bacteria, L. pneumophila （Legionella pneumophila） and H. pylori （Helicobacter pylori）. Enteric bacteria were detected with high frequency in Palestinian water sources followed by 13% occurrence of β-lactamases producing bacteria, 9% of H. pylori and 4% of L. pneumophila. The study shows that shallow groundwater wells and water taped from karstic aquifer is potential for contamination and could not be reliable sources of potable water.

Soil Explorations and Groundwater Monitoring to Evaluate Subsurface Contamination Due to Chromium in District Kasur, Pakistan

Due to improper tannery wastewater management in district Kasur Pakistan, groundwater has been reported to be highly contaminated. It was aimed to find out the extent up to which subsurface has contaminated due to chromium in areas adjacent to the tannery units. Eight （8） soil bores were conducted up to the depth of 30.5 meters and soil samples were tested for total and hexavalent chromium concentrations retained in soil by aqua regia digestion at the every depth of 1.5 meters. Afterwards monitoring wells were installed in these eight （8） bores so as to monitor chromium concentrations in the groundwater on monthly basis. The main source of contamination was considered to be the four （4） drains carrying tanneries effluent therefore samples were collected from these drains so as to observe seasonal variation in chromium concentration.

Groundwater contaminant source identification considering unknown boundary condition based on an automated machine learning surrogate

Groundwater contamination source identification(GCSI)is a prerequisite for contamination risk evaluation and efficient groundwater contamination remediation programs.The boundary condition generally is set as known variables in previous GCSI studies.However,in many practical cases,the boundary condition is complicated and cannot be estimated accurately in advance.Setting the boundary condition as known variables may seriously deviate from the actual situation and lead to distorted identification results.And the results of GCSI are affected by multiple factors,including contaminant source information,model parameters,boundary condition,etc.Therefore,if the boundary condition is not estimated accurately,other factors will also be estimated inaccurately.This study focuses on the unknown boundary condition and proposed to identify three types of unknown variables(contaminant source information,model parameters and boundary condition)innovatively.When simulation-optimization(S-O)method is applied to GCSI,the huge computational load is usually reduced by building surrogate models.However,when building surrogate models,the researchers need to select the models and optimize the hyperparameters to make the model powerful,which can be a lengthy process.The automated machine learning(AutoML)method was used to build surrogate model,which automates the model selection and hyperparameter optimization in machine learning engineering,largely reducing human operations and saving time.The accuracy of AutoML surrogate model is compared with the surrogate model used in eXtreme Gradient Boosting method(XGBoost),random forest method(RF),extra trees regressor method(ETR)and elasticnet method(EN)respectively,which are automatically selected in AutoML engineering.The results show that the surrogate model constructed by AutoML method has the best accuracy compared with the other four methods.This study provides reliable and strong support for GCSI.

Assessment of the environmental impact of artificial effluent lagoon in Jiayuguan City of China

An artificial effluent lagoon for storing wastewater were excavated in Jiayuguan City since 1994. As a part of a demonstration project of Sino Australia cooperation, an assessment of the environmental impact of the lagoon was carried out. The assessment was based on field and laboratory tests and predictive model. The main impacts from the lagoon site are likely to be on the groundwater system, and, to a lesser extent, on ambient air quality in the vicinity. Currently it is expected that groundwater is being polluted with effluent from the effluent lagoon. Air pollution(odor nuisance) is mainly caused by untreated effluent in the irrigation channel. The impact of high total dissolved salt(TDS) on groundwater is likely to be significant in the long run if the lagoon is continuously used. There is, consequently, no likelihood of contamination of surface water system, particularly of the city water supply system, from infiltration of effluent at the lagoon.

Investigation of Subsurface Contamination due to Chromium from Tannery Effluent in Kasur District of Pakistan

The present study is conducted in the scenario of the tannery waste hazards in Kasur district of Pakistan where the tannery industry is considered as major cause of groundwater quality deterioration, Area focused in this research constitutes the surroundings of the effluent carrying drains near tannery units. This study includes soil explorations, groundwater monitoring and wastewater analysis in the research area so as to find out the contamination extent of chromium in subsurface. Initial groundwater monitoring exhibited chromium concentrations as high as 90 mg/L in the tannery area. Even groundwater sampling from monitoring wells installed in the adjacent areas of effluent carrying drains, showed concentrations up to 10.4 mg/L. Wastewater analysis of all the drains in the research area has evidenced potential risk of contaminant seepage into soil and groundwater as level of chromium in wastewater samples has reported to be immensely high and varies from 68 mg/L to 2,152 mg/L. However the 30 soil samples collected from two soil bores did not show any significant results as the maximum values obtained for hexavalent chromium for leaching and retained in soil are 0.02 mg/L and 8.1 mg/kg, respectively. These low concentrations of soil samples suggest that the soil contamination may not be a main environmental issue in the areas adjacent to the effluent carrying drains, The research concludes as possibility of direct interference of the tannery wastewater with groundwater through damaged structures and sewers.