The Experts below are selected from a list of 15900 Experts worldwide ranked by ideXlab platform
Rajandrea Sethi - One of the best experts on this subject based on the ideXlab platform.
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Nanoscale zerovalent iron particles for Groundwater Remediation: a review
Journal of Cleaner Production, 2014Co-Authors: Tiziana Anna Elisabetta Tosco, Marco Petrangeli Papini, Carolina Cruz Viggi, Rajandrea SethiAbstract:Abstract Nanoscale zero-valent iron particles (nZVI) have been studied in recent years as a promising technology for the Remediation of contaminated aquifers. Specific positive features of nZVI are the high reactivity towards a broad range of contaminants and the possibility of injecting in aqueous slurries for a targeted Remediation of contaminated areas. However, crucial points to be addressed are stability against aggregation, mobility in subsurface environments, and longevity. In this work a review is presented on the current knowledge on the properties, reactivity and mobility in porous media of nZVI and their application to Groundwater Remediation. A specific focus is devoted to the methodologies to the colloidal stability of the nZVI slurries and to the available numerical tools for the simulation of laboratory and field scale mobility of the particles when injected in porous media.
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Characterization and mobility enhanchement of iron nanopowders suspensions for Groundwater Remediation
2008Co-Authors: Rajandrea Sethi, Alberto Tiraferri, Antonio Di MolfettaAbstract:In the context of Groundwater Remediation, the use of zero-valent metals has been shown promising for the degradation of a wide range of contaminants. In particular, granular iron filings in permeable reactive barriers (PRBs) are a consolidated technology applied on a number of sites. Nanoscale zerovalent iron is characterized by tiny particles (1-100 nm) and by a specific surface area that is up to a hundred times higher than millimetric iron, thus also its reactivity is much higher. These particles can be suspended into a slurry and injected directly into the source of contamination in order to treat a wide variety of contaminants and bypassing most of the limitation related to PRBs. However, very limited or no mobility of the nanoparticles has been shown in both laboratory studies and field-scale tests. In the present study, after a description of the characterization of a commercial NZVI, the stabilizing effects and mobility enhancements deriving from dosing of biodegradable hydrocolloids on nanoscale iron suspensions will be investigated
Raymond L.d. Whitby - One of the best experts on this subject based on the ideXlab platform.
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Use of iron-based technologies in contaminated land and Groundwater Remediation: a review
Science of The Total Environment, 2008Co-Authors: Andrew B. Cundy, Laurence Hopkinson, Raymond L.d. WhitbyAbstract:Reactions involving iron play a major role in the environmental cycling of a wide range of important organic, inorganic and radioactive contaminants. Consequently, a range of environmental clean-up technologies have been proposed or developed which utilise iron chemistry to remediate contaminated land and surface and subsurface waters, e.g. the use of injected zero zero-valent iron nanoparticles to remediate organic contaminant plumes; the generation of iron oxyhydroxide-based substrates for arsenic removal from contaminated waters; etc. This paper reviews some of the latest iron-based technologies in contaminated land and Groundwater Remediation, their current state of development, and their potential applications and limitations.
Yizhong Chen - One of the best experts on this subject based on the ideXlab platform.
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A multi-level method for Groundwater Remediation management accommodating non-competitive objectives
Journal of Hydrology, 2019Co-Authors: Yizhong ChenAbstract:Abstract No attempts have been found on dealing with a set of non-competitive (or leader-follower-interactive) objectives when performing optimal Groundwater Remediation management. This study presents a multi-level nonlinear simulation-optimization (ML-NSO) model for Groundwater Remediation management when objectives should be satisfied at multiple levels. This model is formulated by integrating health-risk assessment (at the residential concern level), energy assessment (at the energy concern level) and contamination forecasting (at the environmental concern level) within a general framework. The capabilities and effectiveness of the developed model are illustrated through a real-world case located at Cantuar, Saskatchewan in Canada. Results facilitate (a) generating non-compromised solutions in association with the optimal strategies regarding Groundwater injection and extraction, (b) displaying the distribution of contaminant concentration and carcinogenic risks for human health, and estimating the corresponding energy consumption, (c) resolving of conflicts and interactions among residential, energy, and environmental requirements. Moreover, the performance of ML-NSO model is enhanced by comparing with the single-level and multi-objective (SL-NSO and MO-NSO) models. Results show that ML-NSO model would assign higher priority on the residential and environmental concerns by tolerating a slight rise in energy cost. The ML-NSO model would provide more comprehensive and systematic policies with considering the leader-follower relationship within system.
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Human health risk constrained naphthalene-contaminated Groundwater Remediation management through an improved credibility method
Environmental science and pollution research international, 2017Co-Authors: Xing Fan, Yizhong ChenAbstract:In this study, a human health risk constrained Groundwater Remediation management program based on the improved credibility is developed for naphthalene contamination. The program integrates simulation, multivariate regression analysis, health risk assessment, uncertainty analysis, and nonlinear optimization into a general framework. The improved credibility-based optimization model for Groundwater Remediation management with consideration of human health risk (ICOM-HHR) is capable of not only effectively addressing parameter uncertainties and risk-exceeding possibility in human health risk but also providing a credibility level that indicates the satisfaction of the optimal Groundwater Remediation strategies with multiple contributions of possibility and necessity. The capabilities and effectiveness of ICOM-HHR are illustrated through a real-world case study in Anhui Province, China. Results indicate that the ICOM-HHR would generate double Remediation cost yet reduce approximately 10 times of the naphthalene concentrations at monitoring wells, i.e., mostly less than 1 μg/L, which implies that the ICOM-HHR usually results in better environmental and health risk benefits. And it is acceptable to obtain a better environmental quality and a lower health risk level with sacrificing a certain economic benefit.
Xing Fan - One of the best experts on this subject based on the ideXlab platform.
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Human health risk constrained naphthalene-contaminated Groundwater Remediation management through an improved credibility method
Environmental science and pollution research international, 2017Co-Authors: Xing Fan, Yizhong ChenAbstract:In this study, a human health risk constrained Groundwater Remediation management program based on the improved credibility is developed for naphthalene contamination. The program integrates simulation, multivariate regression analysis, health risk assessment, uncertainty analysis, and nonlinear optimization into a general framework. The improved credibility-based optimization model for Groundwater Remediation management with consideration of human health risk (ICOM-HHR) is capable of not only effectively addressing parameter uncertainties and risk-exceeding possibility in human health risk but also providing a credibility level that indicates the satisfaction of the optimal Groundwater Remediation strategies with multiple contributions of possibility and necessity. The capabilities and effectiveness of ICOM-HHR are illustrated through a real-world case study in Anhui Province, China. Results indicate that the ICOM-HHR would generate double Remediation cost yet reduce approximately 10 times of the naphthalene concentrations at monitoring wells, i.e., mostly less than 1 μg/L, which implies that the ICOM-HHR usually results in better environmental and health risk benefits. And it is acceptable to obtain a better environmental quality and a lower health risk level with sacrificing a certain economic benefit.
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Control of stochastic carcinogenic and noncarcinogenic risks in Groundwater Remediation through an integrated optimization design model
Stochastic Environmental Research and Risk Assessment, 2015Co-Authors: Xing FanAbstract:This study presents an integrated optimal Groundwater Remediation design approach. It incorporates numerical simulation, health risk assessment, uncertainty analysis, and nonlinear optimization within a general framework. It is capable of dealing with not only health risk itself (generally caused by uncertainty), but also parameter uncertainty (e.g., slope factor and reference dose) in health risk assessment. This approach is applied to a contaminated site in western Canada for creating a set of optimal Remediation strategies. Carcinogenic and noncarcinogenic risks associated with the strategies are further evaluated under four confidence levels (68.26, 90, 95 and 99.72 %). Results from the case study indicate that (i) the wells have varied contributions to Groundwater Remediation under different Remediation periods and environmental standards; (ii) total pumping rate is mainly controlled by health risk constraints and a stringent health risk standard leads to a high total pumping rate; (iii) Remediation period has a significant impact on health risk mitigation, but the marginal impact does not always increase; (iv) the impact of confidence level of slope factor on health risk is obvious, i.e., the larger the confidence level, the higher the health risk.
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Design of optimal Groundwater Remediation systems under flexible environmental-standard constraints.
Environmental science and pollution research international, 2014Co-Authors: Xing FanAbstract:In developing optimal Groundwater Remediation strategies, limited effort has been exerted to solve the uncertainty in environmental quality standards. When such uncertainty is not considered, either over optimistic or over pessimistic optimization strategies may be developed, probably leading to the formulation of rigid Remediation strategies. This study advances a mathematical programming modeling approach for optimizing Groundwater Remediation design. This approach not only prevents the formulation of over optimistic and over pessimistic optimization strategies but also provides a satisfaction level that indicates the degree to which the environmental quality standard is satisfied. Therefore the approach may be expected to be significantly more acknowledged by the decision maker than those who do not consider standard uncertainty. The proposed approach is applied to a petroleum-contaminated site in western Canada. Results from the case study show that (1) the peak benzene concentrations can always satisfy the environmental standard under the optimal strategy, (2) the pumping rates of all wells decrease under a relaxed standard or long-term Remediation approach, (3) the pumping rates are less affected by environmental quality constraints under short-term Remediation, and (4) increased flexible environmental standards have a reduced effect on the optimal Remediation strategy.
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Health-Risk-Included Optimal Model for Groundwater Remediation Design under Uncertainty: A Case Study in Western Canada
Advanced Materials Research, 2014Co-Authors: Xing Fan, Jiaqi ZhangAbstract:Groundwater has been polluted in different countries, and the pollutants threat to public health. In Groundwater Remediation design, it is necessary to take health risk level into consideration, which should be as important as the environmental standards. This study advances a health-risk-included optimal model for Groundwater Remediation design under relaxed environmental standard constraints. It can simulate and optimize the Groundwater Remediation strategies, and help the decision makers to obtain optimal strategies from various Remediation alternatives. The model is applied for a petroleum contaminated site in western Canada to simulate the Pump and Treat system.
T. I. Eldho - One of the best experts on this subject based on the ideXlab platform.
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Artificial Neural Network and Grey Wolf Optimizer Based Surrogate Simulation-Optimization Model for Groundwater Remediation
Water Resources Management, 2020Co-Authors: Partha Majumder, T. I. EldhoAbstract:Abstract We herein propose a simulation-optimization model for Groundwater Remediation, using PAT (pump and treat), by coupling artificial neural network (ANN) with the grey wolf optimizer (GWO). The input and output datasets to train and validate the ANN model are generated by repetitively simulating the Groundwater flow and solute transport processes using the analytic element method (AEM) and random walk particle tracking (RWPT). The input dataset is the different realization of the pumping strategy and output dataset are hydraulic head and contaminant concentration at predefined locations. The ANN model is used to approximate the flow and transport processes of two unconfined aquifer case studies. The performance evaluation of the ANN model showed that the value of mean squared error (MSE) is close to zero and the value of the correlation coefficient (R) is close to 0.99. These results certainly depict high accuracy of the ANN model in approximating the AEM-RWPT model. Further, the ANN model is coupled with the GWO and it is used for Remediation design using PAT. A comparison of the results of the ANN-GWO model with solutions of ANN-PSO (ANN-Particle Swarm Optimization) and ANN-DE (ANN-Differential Evolution) models illustrates the better stability and convergence behaviour of the proposed methodology for Groundwater Remediation.
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Groundwater Remediation optimization using a point collocation method and particle swarm optimization
Environmental Modelling & Software, 2012Co-Authors: M. Mategaonkar, T. I. EldhoAbstract:Groundwater contamination is a major problem in many parts of the world. Remediation of contaminated Groundwater is a tedious, time consuming and expensive process. Pump and treat (PAT) is one of the commonly used techniques for Groundwater Remediation. Simulation-optimization (S/O) models are very useful in appropriate design of an effective PAT Remediation system. Simulation models can be employed to predict the spatial and temporal variation of contaminant plumes. Optimization models, on the other hand, can be used to minimize the cost of pumping or recharge. Generally, grid or mesh based models using Finite Difference Methods (FDM) or Finite Element Methods (FEM) are used for Groundwater flow and transport simulation. Recently, Meshfree (MFree) based numerical models have been developed due to the difficulty of meshing and remeshing in these methods. The MFree Point Collocation Method (PCM) is a simple MFree method to simulate coupled Groundwater flow and contaminant transport. It saves time for pre-processing such as meshing or remeshing. Evolutionary algorithm based techniques such as for particle swarm optimization (PSO) and genetic algorithms (GA) have been found to be very effective for Groundwater optimization problems. In this paper, a simulation model using MFree PCM for unconfined Groundwater flow and transport and a PSO based optimization model are developed. These models are coupled to get an effective S/O model for the Groundwater Remediation design using PAT. The S/O model is applied to the Remediation design of an unconfined field aquifer polluted by Total Dissolved Solids (TDS) by using pump and treat and flushing. The model provides an effective Remediation design of pumping rate for the selected wells and costs of Remediation.