Human health risk constrained naphthalene-contaminated groundwater remediation management through an improved credibility method

Biodegradation of hazardous naphthalene and cleaner production of rhamnolipids - Green approaches of pollution mitigation

Toxic and hazardous waste poses a serious threat to human health and the environment. Green remediation technologies are required to manage such waste materials, which is a demanding and difficult task. Here, effort was made to explore the role of Pseudomonas aeruginosa SR17 in alleviating naphthalene via catabolism and simultaneously producing biosurfactant. The results showed up to 89.2% naphthalene degradation at 35 °C and pH 7. The GC/MS analysis revealed the generation of naphthalene degradation intermediates. Biosurfactant production led to the reduction of surface tension of the culture medium to 34.5 mN/m. The biosurfactant was further characterized as rhamnolipids. LC-MS of the column purified biosurfactant revealed the presence of both mono and di rhamnolipid congeners. Rhamnolipid find tremendous application in medical field and as well as in detergent industry and since they are of biological origin, they can be used as favorable alternative against their chemical counterparts. The study demonstrated that catabolism of naphthalene and concurrent formation of rhamnolipid can result in a dual activity process, namely environmental cleanup and production of a valuable microbial metabolite. Additionally, the present-day application of rhamnolipids is highlighted.

Energy information flow-based ecological risk transmission among communities within the heavy metals contaminated soil system

An energy information flow-based ecological risk assessment framework (EIF-ERA) is developed for identifying ecological risk transmission rules among communities (i.e., vegetation E1, herbivorous animals E2, soil microorganisms E3, and carnivorous animals E4) within the heavy metals contaminated soil system. This framework is integrated with numerous techniques of carcinogenic risk evaluation, ecological risk assessment (ERA), and Monte Carlo simulation. Stepwise quadratic response surface analysis (SQRSA) is employed for reflecting the relation between contaminants' concentration and comprehensive risk. Two scenarios with respect to the environmental quality standards (scenarios 1) and carcinogenic risk reversion (scenarios 2) are merged into the EIF-ERA. A real-world mining area in Xinglong County in Chengde is selected to verify the developed framework's effectiveness. Results reveal that E3 is considered as the most sensitive community when contaminant interference occurs, and its 62.3% and 37.7% of comprehensive risk are contributed by initial and direct risks, respectively. Other communities can receive direct risk through control allocation (CA). Monte Carlo anlysis shows that there are 7.68% and 20.25% increase in the initial risk of Cd and Pb when their quantile statistics increase from 70% to 90%. Determination of an appropriate screening value is vital for contaminated mining soil remediation due to its inefficiency of remediation funds, especially when considering the trict standards of contaminants' concentration within scenarios 1. The surrogates obtained from the SQRSA display the relation of contaminant concentration and comprehensive risks with the adjusted R² greater than 0.77. These findings can be in support of system design, risk assessment, and site remediation.

Fate and contaminant transport model-driven probabilistic human health risk assessment of DNAPL-contaminated site

In this study, fate and contaminant transport model-driven human health risk indexes were calculated due to the presence of dense non-aqueous phase liquids (DNAPLs) in the subsurface environment of air force base area in Florida, USA. Source concentration data of DNAPLs was used for the calculation of transport model-driven health risk indexes for the children and adult sub-population via direct oral ingestion and skin dermal contact exposure scenario using 10,000 Monte Carlo type simulations. The highest variation in the probability distribution of transformed DNAPL compound (cis-dichloroethene (cis-DCE) > vinyl chloride (VC)) was observed as compared to parent DNAPL (tetrachloroethene (PCE)) based on the 50-year simulation timespan. Transformed DNAPL compounds (VC, cis-DCE) posed the highest risk to human health for a longer duration (up to 15 years) in comparison to parent DNAPL (PCE), as non-carcinogenic hazard quotient varied from 400 to 1100. Carcinogenic health risks were observed as 3-order of magnitude higher than safe limit (HQ_Safe < 10^-6) from 2nd to 5th year timespan and fall in the high-risk zone, indicating the need for a remediation plan for a contaminated site. Variance attribution analysis revealed that concentration, body weight, and exposure duration (contribution percentage - 70 to 95%) were the most important parameters, highlighting the impact of dispersivity and exposure model in the estimation of risk indexes. This approach can help decision-makers when a contaminated site with partial data on hydrogeological properties and with higher uncertainty in model parameters is to be assessed for the formulation of remediation measures.

Enhanced Cd transport in the soil-plant-atmosphere continuum (SPAC) system by tobacco (Nicotiana tabacum L.)

The optimal treatment designs of the heavy metal pollution sites and the calculation of the recovery capacity are important in recent studies. In this paper, we aimed to model the accumulation of heavy metals under different artificially Cd added concentrations, and analyzed the various tobacco solute adsorption and fluid flow properties. The finite difference method was used to simulate the heavy metals flux and root absorption in the soil, and the model simulation was compared with the measured values to quantify the uncertainty of the metal transport and modeling parameters. Treatments with different Cd levels were compared, e.g., control tillage (CT), low Cd tillage (LT, 2.0 mg/kg), high Cd tillage (HT, 20.0 mg/kg), ultra-high Cd tillage (UHT, 80.0 mg/kg). The predicted soil water content (SWC) was consistent with observed data. Predicted cumulative root water uptake (mm) ranked as follows: CT (196)>LT (178)>HT (134)>UHT (117). Potential transpiration rates (T r p) under HT and UHT were lower than that of other treatment, because of their lower leaf Area Index (LAI). The predicted root Cd uptake showed a strong correlation within the actual Cd uptake. The predicted root absorption of Cdmax was UHT (180.17)> HT (106.52)> LT (53.20) >CT (0.610). However, deviation of models was added by the Cd effluent trend and the performance of root exudates. This finding would be useful for further investigation into bio-remediation in the agricultural area, not only for Cd ion but for a range of other heavy metal contaminants.

Coupled Monte Carlo simulation and Copula theory for uncertainty analysis of multiphase flow simulation models

Simulation-optimization techniques are effective in identifying an optimal remediation strategy. Simulation models with uncertainty, primarily in the form of parameter uncertainty with different degrees of correlation, influence the reliability of the optimal remediation strategy. In this study, a coupled Monte Carlo simulation and Copula theory is proposed for uncertainty analysis of a simulation model when parameters are correlated. Using the self-adaptive weight particle swarm optimization Kriging method, a surrogate model was constructed to replace the simulation model and reduce the computational burden and time consumption resulting from repeated and multiple Monte Carlo simulations. The Akaike information criterion (AIC) and the Bayesian information criterion (BIC) were employed to identify whether the t Copula function or the Gaussian Copula is the optimal Copula function to match the relevant structure of the parameters. The results show that both the AIC and BIC values of the t Copula function are less than those of the Gaussian Copula function. This indicates that the t Copula function is the optimal function for matching the relevant structure of the parameters. The outputs of the simulation model when parameter correlation was considered and when it was ignored were compared. The results show that the amplitude of the fluctuation interval when parameter correlation was considered is less than the corresponding amplitude when parameter estimation was ignored. Moreover, it was demonstrated that considering the correlation among parameters is essential for uncertainty analysis of a simulation model, and the results of uncertainty analysis should be incorporated into the remediation strategy optimization process.