Global patterns and temporal trends of perfluoroalkyl substances in municipal wastewater: A meta-analysis.

Despite increasing regulatory efforts to reduce production of per- and polyfluoroalkyl substances (PFAS), continued human and ecological exposure to PFAS has led to concerns about historical releases. Municipal wastewater treatment plants (WWTPs) provide important conduits between waste sources and the environment. We present a meta-analysis of results reported in 44 peer-reviewed publications that include 460 influent and 528 effluent samples, collected from 21 countries, for which some or all of five perfluorinated carboxylic acids (PFCAs) and three perfluorinated sulfonic acids (PFSAs) were measured. Our meta analysis revealed global patterns and trends that, to our knowledge, have not been reported elsewhere. Regression analyses of samples collected from 2004 to 2020 quantified the temporal trends of global wastewater effluent concentrations of each of the PFAS and the corresponding mean concentration for each country. Although legacy compounds, perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), have been reported with the highest measured concentrations, their global temporal trends are lowest of all PFAS considered. Concentrations of most PFAS analyzed in wastewater in the United States have not changed significantly with time, whereas reported PFAS concentrations in wastewater effluent from China have increased from 11% to 37% per year. In addition, our results show significant positive correlations between previous wastewater effluent concentrations of individual PFAS and the gross domestic product per capita of each country. Our analysis of this global data set also confirmed conclusions from previous studies on smaller data sets: (i) none of the PFAS studied are effectively removed by conventional treatment processes; (ii) effluents from treatment plants that include a significant industrial component to their influent tend to have higher PFAS concentrations; and (iii) the few studies that measured both aqueous concentrations and concentrations adsorbed to suspended particulate matter (SPM) indicate that PFAS adsorbed to SPM can contribute significantly to the total PFAS load.

Environmental fate and transport modeling for perfluorooctanoic acid emitted from the Washington Works Facility in West Virginia.

Perfluorooctanoic acid (PFOA) has been detected in environmental samples in Ohio and West Virginia near the Washington Works Plant in Parkersburg, West Virginia. This paper describes retrospective fate and transport modeling of PFOA concentrations in local air, surface water, groundwater, and six municipal water systems based on estimates of historic emission rates from the facility, physicochemical properties of PFOA, and local geologic and meteorological data beginning in 1951. We linked several environmental fate and transport modeling systems to model PFOA air dispersion, transit through the vadose zone, surface water transport, and groundwater flow and transport. These include AERMOD, PRZM-3, BreZo, MODFLOW, and MT3DMS. Several thousand PFOA measurements in municipal well water have been collected in this region since 1998. Our linked modeling system performs better than expected, predicting water concentrations within a factor of 2.1 of the average observed water concentration for each of the six municipal water districts after adjusting the organic carbon partition coefficient to fit the observed data. After model calibration, the Spearman's rank correlation coefficient for predicted versus observed water concentrations is 0.87. These models may be useful for estimating past and future public well water PFOA concentrations in this region.

Accurate and reliable estimation of kinetic parameters for environmental engineering applications: A global, multi objective, Bayesian optimization approach.

Accurate and reliable predictions of bacterial growth and metabolism from unstructured kinetic models are critical to the proper operation and design of engineered biological treatment and remediation systems. As such, parameter estimation has progressed into a routine challenge in the field of Environmental Engineering. Among the main issues identified with parameter estimation, the model-data calibration approach is a crucial, yet an often overlooked and difficult optimization problem. Here, a novel and rigorous global, multi objective, and fully Bayesian optimization approach that overcomes challenges associated with multi-variate, sparse and noisy data, as well as highly non-linear model structures commonly encountered in Environmental Engineering practice is presented. This optimization approach allows an improved definition and targeting of the compromise solution space for all multivariate problems, allowing efficient convergence, and a Bayesian component to thoroughly explore parameter and model prediction uncertainty. This global optimization approach outperformed, in terms of parameter accuracy and precision, standard, local non-linear regression routines and overcomes issues associated with premature convergence and addresses overfitting of different variables in the calibration process. •A sequential single, multi-objective, and Bayesian optimization workflow was developed to accurately and reliably estimate unstructured kinetic model parameters.•The global, single objective approach defines the global optimum (the best compromise solution) and "extreme" parameter solutions for each variable, while the global, multi-objective approach confirms the "best" compromise solution space for the Bayesian search to target and convergence is assessed using the single objective results.•The Approximate Bayesian Computational approach fully explores parameter and model prediction uncertainty targeting the compromise solution space previously identified.

Application of unstructured kinetic models to predict microcystin biodegradation: Towards a practical approach for drinking water treatment.

Biological drinking water treatment technologies offer a cost-effective and sustainable approach to mitigate microcystin (MC) toxins from harmful algal blooms. To effectively engineer these systems, an improved predictive understanding of the bacteria degrading these toxins is required. This study reports an initial comparison of several unstructured kinetic models to describe MC microbial metabolism by isolated degrading populations. Experimental data was acquired from the literature describing both MC removal and cell growth kinetics when MC was utilized as the primary carbon and energy source. A novel model-data calibration approach melding global single-objective, multi-objective, and Bayesian optimization in addition to a fully Bayesian approach to model selection and hypothesis testing were applied to identify and compare parameter and predictive uncertainties associated with each model structure. The results indicated that models incorporating mechanisms of enzyme-MC saturation, affinity, and cooperative binding interactions of a theoretical single, rate limiting reaction accurately and reliably predicted MC degradation and bacterial growth kinetics. Diverse growth characteristics were observed among MC degraders, including moderate to high maximum specific growth rates, very low to substantial affinities for MC, high yield of new biomass, and varying degrees of cooperative enzyme-MC binding. Model predictions suggest that low specific growth rates and MC removal rates of degraders are expected in practice, as MC concentrations in the environment are well below saturating levels for optimal growth. Overall, this study represents an initial step towards the development of a practical and comprehensive kinetic model to describe MC biodegradation in the environment.

Satiated relative permeability of variable-aperture fractures.

Experimental studies of capillary-dominated displacements in variable-aperture fractures have demonstrated the occurrence of a satiated state at the end of invasion, where significant entrapment of the displaced phase occurs. The structure of this entrapped phase controls the behavior of flow and transport processes in the flowing phase. Recent studies have shown that the areal saturation of the flowing phase at satiation (S(f) ) is largely controlled by a single parameter C/delta , where C , the curvature number, weighs the mean in-plane interfacial curvature relative to the mean out-of-plane interfacial curvature, and delta , the coefficient of variation of the aperture field, represents the strength of interface roughening induced by aperture variations. Here we consider the satiated relative permeability (k(rs)) to the flowing phase, which is defined as the relative permeability when the defending phase is fully entrapped. The satiated relative permeability is shown to be a well-defined function of S(f) over a wide range of C/delta , ranging from capillary fingering with significant entrapment (C/delta-->0) to smooth invasion with very little entrapment (C/delta > 1) . We develop a relationship for k(rs) as a function of S(f), by combining theoretical results for the effective permeability in a spatially correlated random permeability field, with results from continuum percolation theory for quantifying the influence of the entrapped phase. The resulting model for k(rs) also involves a dependence on delta . The predicted relative permeability values are accurate across the entire range of phase structures representative of capillary-dominated displacements in variable-aperture fractures.

Immiscible displacements in rough-walled fractures: competition between roughening by random aperture variations and smoothing by in-plane curvature.

Phase structure during capillary displacement of fluid phases within rough-walled fractures is controlled by the competition between random aperture variability which tends to roughen the interface and in-plane curvature which tends to smooth it. We show that the phase structure and corresponding areal saturation at the end of displacement depend primarily on the ratio of two dimensionless parameters: one that controls roughening (the coefficient of variation of the aperture field, delta) and another that controls smoothing (the curvature number C, which weighs the mean influences of aperture induced and in-plane curvature). Interestingly, for C/delta above approximately 0.5, areal saturation for wetting and nonwetting invasion first diverges and then converges to create an envelope, whose width increases with delta. This nonunique behavior with respect to wettability is fundamental to capillary displacements in rough-walled fractures and is due to an asymmetry in capillary competition in wetting versus nonwetting invasions.

Comparison of an algebraic multigrid algorithm to two iterative solvers used for modeling ground water flow and transport.

Numerical solution of large-scale ground water flow and transport problems is often constrained by the convergence behavior of the iterative solvers used to solve the resulting systems of equations. We demonstrate the ability of an algebraic multigrid algorithm (AMG) to efficiently solve the large, sparse systems of equations that result from computational models of ground water flow and transport in large and complex domains. Unlike geometric multigrid methods, this algorithm is applicable to problems in complex flow geometries, such as those encountered in pore-scale modeling of two-phase flow and transport. We integrated AMG into MODFLOW 2000 to compare two- and three-dimensional flow simulations using AMG to simulations using PCG2, a preconditioned conjugate gradient solver that uses the modified incomplete Cholesky preconditioner and is included with MODFLOW 2000. CPU times required for convergence with AMG were up to 140 times faster than those for PCG2. The cost of this increased speed was up to a nine-fold increase in required random access memory (RAM) for the three-dimensional problems and up to a four-fold increase in required RAM for the two-dimensional problems. We also compared two-dimensional numerical simulations of steady-state transport using AMG and the generalized minimum residual method with an incomplete LU-decomposition preconditioner. For these transport simulations, AMG yielded increased speeds of up to 17 times with only a 20% increase in required RAM. The ability of AMG to solve flow and transport problems in large, complex flow systems and its ready availability make it an ideal solver for use in both field-scale and pore-scale modeling.

Dissolution of dense non-aqueous phase liquids in vertical fractures: effect of finger residuals and dead-end pools.

Understanding the dissolution behavior of dense non-aqueous phase liquids (DNAPLs) in rock fractures under different entrapment conditions is important for remediation activities and any related predictive modeling. This study investigates DNAPL dissolution in variable aperture fractures under two important entrapment configurations, namely, entrapped residual blobs from gravity fingering and pooling in a dead-end fracture. We performed a physical dissolution experiment of residual DNAPL blobs in a vertical analog fracture using light transmission techniques. A high-resolution mechanistic (physically-based) numerical model has been developed which is shown to excellently reproduce the experimentally observed DNAPL dissolution. We subsequently applied the model to simulate dissolution of the residual blobs under different water flushing velocities. The simulated relationship between the Sherwood number Sh and Peclet number Pe could be well fitted with a simple power-law function (Sh=1.43Pe°·4³). To investigate mass transfer from dead-end pools, another type of trapping in rock fractures, entrapment and dissolution of DNAPL in a vertical dead-end fracture was simulated. As the entrapped pool dissolves, the depth of the interface between the DNAPL and the flowing water increases linearly with decreasing DNAPL saturation. The interfacial area remains more or less constant as DNAPL saturation decreases, unlike in the case of residual DNAPL blobs. The decreasing depth of the contact interface changes the flow field and causes decreasing water flow velocity above the top of the DNAPL pool, suggesting the dependence of the mass transfer rate on the depth of the interface, or alternatively, the remaining mass percentage in the fracture. Simulation results show that the resultant Sherwood number Sh is significantly smaller than in the case of residual blobs for any given Peclet number, indicating slower mass transfer. The results also show that the Sh can be well fitted with a power-law function of Pe and remaining mass percentage. The obtained relationships of dimensionless groups concerning the mass transfer characteristics at the level of individual fractures can be further used in predictive modeling of dissolution at a larger (fracture network) scale.