A comparative assessment of the risks of the three current wastewater effluent disposal options and three other potential options was conducted for Southeast Florida communities. The question was how the risk to humans from the use of potable reuse compares to the other five available wastewater disposal alternatives. The need for this type of risk assessment is due to the potential to use potable reuse as a water supply and the potential resistance from the public as a result of such a proposal. Water quality data relevant to disposal of wastewater treatment plant effluent from South Florida utilities along with water quality data on the receiving waters and drinking water standards were obtained for the project. The comparison of the public health risks associated with these disposal alternatives indicated that health risks associated with deep wells and direct potable reuse were generally lower than those of the other alternatives.

Predictive Bayesian methods were used to develop a comparative assessment of the risks of six effluent disposal alternatives currently or potentially available to wastewater utilities in Southeast Florida. The alternatives are: 1) deep well injection 2) ocean outfalls following secondary treatment, 3) surface water (canal) discharges following secondary wastewater treatment, filtration and nutrient removal, 4) reclaimed water (secondary treatment plus filtration and high-level disinfection, 5) indirect potable reuse (full treatment with reverse osmosis, plus ultraviolet light and advanced oxidation) and 6) direct potable reuse using reverse osmosis, ultraviolet light and advanced oxidation. Water quality data was gathered from a series of south Florid utilities, south Florida test facilities, receiving waters and other relevant locations to south Florida wastewater effluent disposal. This paper presents the conclusions regarding relative health concerns associated with these disposal alternatives. The results indicated that health risks associated with deep wells and direct potable reuse were generally lower than those of the other alternatives.

Since the 2010 Deepwater Horizon (DWH) oil spill, the Gulf of Mexico Research Initiative (GOMRI) has studied the oil spill from the perspectives of ocean environment, ecosystems, socioeconomics and human health. As GOMRI sunsets in its tenth year after the DWH oil spill, synthesis efforts recently took place to assess the accomplishments of the program. In this paper, we report on DWH modeling as part of GOMRI's Synthesis and Legacy effort. We compile a list of 330 published applications by GOMRI, the Natural Resource Damage Assessment (NRDA), and others studying the DWH oil spill and look at a wide range of subjects, tools, achievements, and integration with field research. We offer highlights and synthesis based on discussions and public webinars held in 2019 and 2020. We synthesize the significant achievements and advancements that have been made in integrating the various disciplines and domains from a modeling perspective. There was a large diversity of tools used, including at least 74 unique modeling systems. Most studies employed circulation models. These hydrodynamic models were often coupled to wave, river, and atmosphere models, as well as representations of high pressure physics and oil chemistry. Several research groups used Lagrangian transport models and statistical inference to track subsurface oil. Some coupled biophysical models were also employed to study oil fate and weathering, larval transport, biological effects, and population dynamics. In a few cases, such biophysical models were linked to marine populations and to humans through socioeconomics effects and ecosystem services. We consider models made for response planning and remediation, damage assessment, and restoration planning. There are relatively few socioeconomic or human health models, although those few examples make good use of biophysical modeling products. Our conclusions offer some insights on how the development of new tools has better prepared us for studying environmental management challenges in the Gulf of Mexico.

Sunken oil is often difficult to detect, and few oil spill models are designed to locate and track such oil. Therefore, the multi-modal Bayesian inferential sunken oil model, SOSim (Subsurface Oil Simulator), was expanded in this work for use during emergency response and damage assessment. Rather than requiring hydrodynamic data as input, SOSim v2 accepts available field concentration data, along with default or custom bathymetric data, for inference of the location and trajectory of sunken oil. Novel aspects include inference based on bathymetry and the Coriolis Effect, by constructing a prior likelihood function from sampled bathymetric data, scaled proportionally with field concentration data. SOSim v2 is demonstrated versus field data on the ITB DBL-152 oil spill in the Gulf of Mexico, with sensitivity analysis. Results suggest that the inferential approach presented can be effective for modeling relatively slow-moving pollutant masses such as sunken oil, when field concentration data are available.

When spilled oil collects at depth, questions as to where and when to dispatch response equipment become daunting, because such oil may be invisible by air, and underwater sensing technology is limited in coverage and by underwater visibility. Further, trajectory modeling based on previously recorded flow field data may show mixed results. In this work, the Bayesian model, SOSim, is modified to locate and forecast the movement of submerged oil, with confidence bound, by inferring model parameters based on any available field concentration data and the output of one or more deterministic trajectory models. Novel aspects include specification of a prior likelihood function, and generation of results in 3-D from data in the 2-D density space of the isopycnal layer containing oil. The model is demonstrated versus data collected following the Deepwater Horizon spill. This new inferential modeling approach appears complimentary to deterministic methods when field concentration data are available.

A rise in the shipping of heavier hydrocarbon products increases the potential for an oil to sink after a spill. Further, sunken oil is difficult to locate and recover, and appropriate response technologies depend on the sinking mechanism. In this review, principal sinking mechanisms for oil are described and appropriate response technologies are suggested. Then, models appropriate for tracking sunken oil are compared. Oil may sink as burn residue, microscopic oil-particle aggregates (OPAs) or macroscopic oil-sediment mixtures (OSMs), marine oil snow during a MOSSFA event, or due to its high density. The most common mechanism is by sediment en-trainment, and in such scenarios manual recovery has been reported as a successful response option. Among oil tracking models, trajectory models and Bayesian oil search models are compared for sunken oil capabilities. Many oil spill models require hydrodynamic inputs, whereas Bayesian models infer parameters based on available field concentration and bathymetric data.

The manufacture and use of chemical fertilizers has led to surface water eutrophication, mining-related environmental effects, and consumption of 1-2% of global energy supplies for commercial production of nitrogen (N) fertilizer by the Haber-Bosch process. However, recovery of nutrients from wastewater can help to close the nutrient cycle, from farm to food to municipal wastewater. In this work, we demonstrate simultaneous N and P recovery from settled sewage in a continuous-flow reactor, by precipitation of Ca-3(PO4)(2) and stripping of NH3(g) following electrochemical pH shifting, termed electrohydromodulation (EHM). pH was dropped anodically to similar to 6 for stripping of CO2, to address subsequent buffering and calcite precipitation, then raised cathodically to similar to 11 for Ca-3(PO4)(2) precipitation and NH3(g) stripping, and neutralized prior to discharge. Ammonia recovery by stripping under vacuum using 0.3 m (1 ft) of glass Raschig Rings packing material was found most efficient. Recovery of 89% and 97% of average total N & P from municipal primary effluent was achieved in the continuous-flow bench reactor, at an electrochemical energy demand of 0.623 kWh/m(3). Total energy demand, including energy for EHM, filtration, ammonia stripping and absorption was projected at 1.21 kWh/m(3). Precipitates were found to be amorphous with a Ca/P ratio of similar to 3.66, with the ratio depending somewhat on flow rate at a constant voltage. Results suggest that 0.91 L (0.24 Gal) of 5.8 M H2SO4 can recover 90% of ammonia in 3.785 m(3) (1000 Gal) of wastewater containing 25 mg-N/L. Overall, the process appears economical relative to competing recovery processes and commercial fertilizer production.

Locating and tracking submerged oil in the mid depths of the ocean is challenging during an oil spill response, due to the deep, wide-spread and long-lasting distributions of submerged oil. Due to the limited area that a ship or AUV can visit, efficient sampling methods are needed to reveal the real distributions of submerged oil. In this paper, several sampling plans are developed for collecting submerged oil samples using different sampling methods combined with forecasts by a submerged oil model, SOSim (Subsurface Oil Simulator). SOSim is a Bayesian probabilistic model that uses real time field oil concentration data as input to locate and forecast the movement of submerged oil. Sampling plans comprise two phases: the first phase for initial field data collection prior to SOSim assessments, and the second phase based on the SOSim assessments. Several environmental sampling techniques including the systematic random, modified station plans as well zig-zag patterns are evaluated for the first phase. The data using the first phase sampling plan are then input to SOSim to produce submerged oil distributions in time. The second phase sampling methods (systematic random combined with the kriging-based sampling method and naive zig-zag sampling method) are applied to design the sampling plans within the submerged oil area predicted by SOSim. The sampled data obtained using the second phase sampling methods are input to SOSim to update the model’s assessments. The performance of the sampling methods is evaluated by comparing SOSim predictions using the sampled data from the proposed sampling methods with simulated submerged oil distributions during the Deepwater Horizon spill by the OSCAR (oil spill contingency and response) oil spill model. The proposed sampling methods, coupled with the use of the SOSim model, are shown to provide an efficient approach to guide oil spill response efforts.

Sunken oil transport processes in rivers differ from those in oceans, and currently available models may not be generally applicable to sunken oil in river settings. The open-source Subsurface Oil Simulator (SOSim) model has been expanded to handle spills of sunken oil in navigable rivers, utilizing Bayesian inference to integrate field concentration data with bathymetric data to predict the location and movement of sunken oil. A novel prior likelihood function incorporates bathymetric input, with sampling grid and default parameters adapted appropriately for rivers. SOSim v2 was demonstrated versus field observations taken following the M/T (Motor Tanker) Athos I oil spill. The model was also modified to operate in 1-D, to assess the longitudinal distribution of sunken oil in a non-navigable river using available poling data collected following the Enbridge Kalamazoo River oil spill in 2010. Results of both case studies were consistent with observed data and local bathymetry in 2-D and 1-D, and the model is suggested as a complement to deterministic models for oil spill emergency response in rivers.

The mining of phosphate rock to produce fertilizer, and subsequent disposal of the municipal wastewater containing a significant fraction of the phosphate applied agriculturally, has led to environmental impacts of phosphate mining as well as surface water eutrophication. However, recovery of phosphate (H2PO4-, HPO42-, PO43-) from wastewater, either chemically or biologically, has not been sufficiently economical at low phosphate concentrations in raw wastewater (similar to 2.4 mg.P l(-1)) to motivate widespread adoption. In this work, we demonstrate phosphate recovery directly from raw and mineral-spiked septic tank effluent by electrochemical pH shifting, termed electrohydromodulation (EHM), without expensive chemical addition. EHM using a CMI-7000 multivalent cation exchange membrane (MCEM) at 5 V at 1.347 mA/cm(2) resulted in the highest efficiency at lowest energy consumption. 94 and 95% phosphate were recovered from mineral-spiked septic tank effluent (simulating advanced oxidation-based direct potable reuse water), and raw septic tank effluent, at an energy demand of 1.046 kWh/m(3) (3.960 kWh/1000 Gal) and 1.863 kWh/m(3) (7.054 kWh/1000 Gal), respectively, low despite use of non-toxic, inexpensive graphite electrodes. Results from scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and X-ray powder diffraction (XRD) indicated that recovered precipitates consisted principally of amorphous calcium phosphate (ACP), with minor amounts of amorphous calcium carbonate (ACC), having an overall Ca:P ratio of 2. CO2 stripping at low pH prior to pH shifting was found to minimize competitive calcite precipitation to improve product purity. Electrodes used intermittently, with polarity reversal, over 1.5 years of experiments were intact from fouling.

Submerged oil, oil in the water column (neither at the surface nor on the bottom), was found in the form of oil droplet layers in the mid depths between 900–1300 m in the Gulf of Mexico during and following the Deepwater Horizon oil spill. The subsurface peeling layers of submerged oil droplets were released from the well blowout plume and moved along constant density layers (also known as isopycnals) in the ocean. The submerged oil layers were a challenge to locate during the oil spill response. To better understand and find submerged oil layers, we review the mechanisms of submerged oil formation, along with detection methods and modeling techniques. The principle formation mechanisms under stratified and cross-current conditions and the concepts for determining the depths of the submerged oil layers are reviewed. Real-time in situ detection methods and various sensors were used to reveal submerged oil characteristics, e.g., colored dissolved organic matter and dissolved oxygen levels. Models are used to locate and to predict the trajectories and concentrations of submerged oil. These include deterministic models based on hydrodynamical theory, and probabilistic models exploiting statistical theory. The theoretical foundations, model inputs and the applicability of these models during the Deepwater Horizon oil spill are reviewed, including the pros and cons of these two types of models. Deterministic models provide a comprehensive prediction on the concentrations of the submerged oil and may be calibrated using the field data. Probabilistic models utilize the field observations but only provide the relative concentrations of the submerged oil and potential future locations. We find that the combination of a probabilistic integration of real-time detection with trajectory model output appears to be a promising approach to support emergency response efforts in locating and tracking submerged oil in the field.

Phosphorus (P) is a non-renewable resource, production of nitrogen (N) fertilizer is energy intensive, and discharge of these nutrients in treated wastewater causes environmental eutrophication. Hence, recovery of nutrients from municipal wastewater has attracted attention. In this article, current technologies for such recovery are reviewed, with synthesis in terms of wastewater characteristics, recovery goals, effluent discharge limits, constraints on chemical usage, treatment plant scale, operational complexity and applicability, and analysis of energy demands. Phosphorus recovery processes applicable for centralized plants include enhanced biological phosphorus removal (EBPR) combined with chemical and electrochemical struvite precipitation and chemical precipitation alone, whereas electrochemical and chemical precipitation and ion exchange (IE) may be adapted to onsite and packaged treatment plants. Many processes can be used for N concentration; however, N recovery has been reported only by struvite precipitation and acid absorption following separation by gas stripping or gas permeable membrane. Only chemical and electrochemical precipitation can produce fertilizer requiring minimal post-processing beyond filtration. Electrochemical precipitation of struvite and calcium phosphate is further capable of such recovery with minimal chemical addition. Direct microbiological recovery as protein is an emerging technology, and algal recovery is being developed for livestock and fuel production. Although reactive filtration can achieve very low P discharge concentrations, the only processes reported to be capable individually of removing P in secondary effluent to below 10 mu g/L, for example, for discharge to surficial waters, were adsorption and IE. Several authors point to EBPR as a currently preferred approach, and further development of electrochemical processes appears warranted.

Current efforts to assess human health response to chemicals based on high-throughput in vitro assay data on intra-cellular changes have been hindered for some illnesses by lack of information on higher-level extracellular, inter-organ, and organism-level interactions. However, a dose-response function (DRF), informed by various levels of information including apical health response, can represent a template for convergent top-down, bottom-up analysis. In this paper, a general DRF for chronic chemical and other health stressors and mixtures is derived based on a general first-order model previously derived and demonstrated for illness progression. The derivation accounts for essential autocorrelation among initiating event magnitudes along a toxicological mode of action, typical of complex processes in general, and reveals the inverse relationship between the minimum illness-inducing dose, and the illness severity per unit dose (both variable across a population). The resulting emergent DRF is theoretically scale-inclusive and amenable to low-dose extrapolation. The two-parameter single-toxicant version can be monotonic or sigmoidal, and is demonstrated preferable to traditional models (multistage, lognormal, generalized linear) for the published cancer and non-cancer datasets analyzed: chloroform (induced liver necrosis in female mice); bromate (induced dysplastic focia in male inbred rats); and 2-acetylaminofluorene (induced liver neoplasms and bladder carcinomas in 20,328 female mice). Common- and dissimilar-mode mixture models are demonstrated versus orthogonal data on toluene/benzene mixtures (mortality in Japanese medaka, Oryzias latipes, following embryonic exposure). Findings support previous empirical demonstration, and also reveal how a chemical with a typical monotonically-increasing DRF can display a J-shaped DRF when a second, antagonistic common-mode chemical is present. Overall, the general DRF derived here based on an autocorrelated first-order model appears to provide both a strong theoretical/biological basis for, as well as an accurate statistical description of, a diverse, albeit small, sample of observed dose-response data. The further generalizability of this conclusion can be tested in future analyses comparing with traditional modeling approaches across a broader range of datasets.

Correction for ‘Ozone–UV net-zero water wash station for remote emergency response healthcare units: design, operation, and results’ by Lucien W. Gassie et al., Environ. Sci.: Water Res. Technol., 2019, 5, 1971–1984, DOI: 10.1039/C9EW00126C.

A novel ozone-UV kinetic model provides insight into ozone-UV organic mineralization, in particular, varying the organic load and pH during treatment.

Challenges of water and wastewater management in Alaska include the potential need for above-grade and freeze-protected piping, high unit energy costs and, in many rural areas, low population density and median annual income. However, recently developed net-zero water (NZW), i.e., nearly closed-loop, direct potable water reuse systems, can retain the thermal energy in municipal wastewater, producing warm treated potable water without the need for substantial water re-heating, heat pumping or transfer, or additional energy conversion. Consequently, these systems are projected to be capable of saving more energy than they use in water treatment and conveyance, in the temperate USA. In this paper, NZW technology is reviewed in terms of potential applicability in Alaska by performing a hypothetical case study for the city of Fairbanks, Alaska. Results of this paper study indicate that in municipalities of Alaska with local engineering and road access, the use of NZW systems may provide an energy-efficient water service option. In particular, case study modeling suggests hot water energy savings are equivalent to five times the energy used for treatment, much greater savings than in mid-latitudes, due largely to the substantially higher energy needed for heating water from a conventional treatment system and lack of need for freeze-protected piping. Further study of the applicability of NZW technology in cold regions, with expanded evaluation in terms of system-wide lifecycle cost, is recommended.