Weather and the City: Machine Learning for Predicting and Attributing Fine Scale Air Quality to Meteorological and Urban Determinants.

Urban air quality persists as a global concern, with critical health implications. This study employs a combination of machine learning (gradient boosting regression, GBR) and spatial analysis to better understand the key drivers behind air pollution and its prediction and mitigation strategies. Focusing on New York City as a representative urban area, we investigate the interplay between urban characteristics and weather factors, showing that urban features, including traffic-related parameters and urban morphology, emerge as crucial predictors for pollutants closely associated with vehicular emissions, such as elemental carbon (EC) and nitrogen oxides (NOx). Conversely, pollutants with secondary formation pathways (e.g., PM2.5) or stemming from nontraffic sources (e.g., sulfur dioxide, SO2) are predominantly influenced by meteorological conditions, particularly wind speed and maximum daily temperature. Urban characteristics are shown to act over spatial scales of 500 × 500 m2, which is thus the footprint needed to effectively capture the impact of urban form, fabric, and function. Our spatial predictive model, needing only meteorological and urban inputs, achieves promising results with mean absolute errors ranging from 8 to 32% when using full-year data. Our approach also yields good performance when applied to the temporal mapping of spatial pollutant variability. Our findings highlight the interacting roles of urban characteristics and weather conditions and can inform urban planning, design, and policy.

A kernel-modulated SIR model for Covid-19 contagious spread from county to continent.

The tempo-spatial patterns of Covid-19 infections are a result of nested personal, societal, and political decisions that involve complicated epidemiological dynamics across overlapping spatial scales. High infection "hotspots" interspersed within regions where infections remained sporadic were ubiquitous early in the outbreak, but the spatial signature of the infection evolved to affect most regions equally, albeit with distinct temporal patterns. The sparseness of Covid-19 infections in the United States was analyzed at scales spanning from 10 to 2,600 km (county to continental scale). Spatial evolution of Covid-19 cases in the United States followed multifractal scaling. A rapid increase in the spatial correlation was identified early in the outbreak (March to April). Then, the increase continued at a slower rate and approached the spatial correlation of human population. Instead of adopting agent-based models that require tracking of individuals, a kernel-modulated approach is developed to characterize the dynamic spreading of disease in a multifractal distributed susceptible population. Multiphase Covid-19 epidemics were reasonably reproduced by the proposed kernel-modulated susceptible-infectious-recovered (SIR) model. The work explained the fact that while the reproduction number was reduced due to nonpharmaceutical interventions (e.g., masks, social distancing, etc.), subsequent multiple epidemic waves still occurred; this was due to an increase in susceptible population flow following a relaxation of travel restrictions and corollary stay-at-home orders. This study provides an original interpretation of Covid-19 spread together with a pragmatic approach that can be imminently used to capture the spatial intermittency at all epidemiologically relevant scales while preserving the "disordered" spatial pattern of infectious cases.

Modeling the Breakup of Oil-Particle Aggregates in Turbulent Environments for Projectile Penetration.

After an oil spill incident, the spilled oil slicks are observed to migrate to the shoreline area. Under the turbulent conditions, they break into small droplets and are suspended in the water column. The dispersed droplets are expected to interact with the suspended particles and form the oil-particle aggregates (OPAs), which significantly changes the transport of the oil. Instead of an earlier assumption that particles cover the oil surface, thus preventing further breakage or aggregation of OPAs, recent studies demonstrated that particles act like projectiles penetrating the oil droplets, resulting in the breakage of OPAs over a longer period of time. A model looking into the OPA breakup through two breakup mechanisms was proposed for the first time. The first method depicted the breakup of one large OPA into two daughter droplets owing to the turbulent nature, while the second method demonstrated the tear of the OPA surface layer caused by particle uprooting. The model was then calibrated by an experimental study targeting crude oil with varied viscosities, along with previous experimental investigations. Three key factors were identified accounting for the breakage of OPAs, where the increase in particle concentration in the natural environment and the increase in turbulent energy of the surrounding flows benefited the breakage of OPAs, and the increase in oil viscosity suppressed the breakage due to large resistance to shear stress. Besides these elements, the impact of the particle shape on the penetration depth was discussed. The model serves as a fundamental theory to describe the evolution of OPAs for fragmentation behavior.

Post-Formation of Oil Particle Aggregates: Breakup and Biodegradation.

Spilled oil slicks are likely to break into droplets in the subtidal and intertidal zones of seashores due to wave energy. The nonliving suspended fine particles in coastal ecosystems can interact with the dispersed oil droplets, resulting in the formation of Oil Particle Aggregates (OPAs). Many investigations assumed that these aggregates will settle due to the particles' high density. Recent studies, however, reported that some particles penetrate the oil droplets, which results in further breakup while forming smaller OPAs that remain suspended in the water column. Here, we investigated the interaction of crude oil droplets with intertidal and subtidal sediments, as well as artificial pure kaolinite, in natural seawater. Results showed that the interaction between oil droplets and intertidal sediments was not particularly stable, with an Oil Trapping Efficiency (OTE) < 25%. When using subtidal sediments, OTE reached 56%. With artificial kaolinite, OPA formation and breakup were more significant (OTE reaching up to 67%) and occurred faster (within 12 h). Oil chemistry analysis showed that the biodegradation of oil in seawater (half-life of 485 h) was significantly enhanced with the addition of sediments, with half-lives of 305, 265, and 150 h when adding intertidal sediments, subtidal sediments, and pure kaolinite, respectively. Such results reveal how the sediments' shape and size affect the various oil-sediment interaction mechanisms, and the subsequent impact on the microbial degradation of petroleum hydrocarbons. Future studies should consider investigating the application of fine (several microns) and sharp (elongated-sheeted) sediments as a nondestructive and nontoxic technique for dispersing marine oil spills.

Optimizing the maintenance strategies for a network of green infrastructure: An agent-based model for stormwater detention basins.

Various stormwater best management practices and green infrastructures (GIs) are recommended to address flooding, stormwater runoff, water quality, and sustainability. While detention basins are considered one of the main GI strategies, their benefits cannot be fully realized without properly maintaining them and making sure that they stay operational. Therefore, this paper used agent-based modeling (ABM) to devise an optimal maintenance program for detention basins to ensure that they function properly and continue to perform their water quality and flood control functions. More specifically, the following 2 agent types were incorporated in the model: 1) the detention basins were considered as static agents, and 2) the service teams responsible for the operation (maintenance, repair, and replacement) of the detention basins were considered as active agents. The developed ABM was applied for the entire network of stormwater detention basins in Newark, NJ. Sensitivity analysis was conducted to identify the most critical variables affecting the total cost of operating the network of detention basins as well as the functioning percentage of detention basins. In addition, optimization was implemented to determine the best maintenance program or policy that minimizes the total cost of operations, while also making sure that a desired functionality level or threshold is achieved for the entire network of detention basins. Finally, the ABM was statistically validated using a total of 10,000 Monte Carlo runs and 99% confidence intervals. The optimization results showed that, in order to minimize the total cost of maintaining the entire network of detention basins and ensure that at least 80% of the basins are in a functioning state at the end of the planning horizon, the decision-maker should implement the following maintenance program or strategy: have 2 service teams for the operations of the detention basins, follow a replacement policy, and replace detention basins after 3 maintenance periods. Also, the identified optimal maintenance program or strategy would result with an average total annual cost of around $4,085,000, where the average annual repair cost is around $2,572,200, the average annual maintenance cost is around $19,700, the average annual replacement cost is around $763,100, and the average annual service team cost is around $730,000. The proposed ABM for detention basins can be extended to other GIs as well as to different geographical areas. The usage of ABM has the advantage to reduce the subjectivity in developing plans for managing GIs.

Bioremediation of Petroleum Hydrocarbons in the Upper Parts of Sandy Beaches.

The biodegradation of dispersed crude oil in the ocean is relatively rapid (a half-life of a few weeks). However, it is often much slower on shorelines, usually attributed to low moisture content, nutrient limitation, and higher oil concentrations in beaches than in dispersed plumes. Another factor may be the increased salinity of the upper intertidal and supratidal zones because these parts of the beach are potentially subject to prolonged evaporation and only intermittent inundation. We have investigated whether such an increase in salinity has inhibitory effects on oil biodegradation in seashores. Lightly weathered Hibernia crude oil was added to beach sand at 1 or 10 mL/kg, and fresh seawater, at salinities of 30, 90, and 160 g/L, was added to 20% saturation. The biodegradation of oil was slower at higher salinities, where the half-life increased from 40 days at 30 g/L salts to 58 and 76 days at 90 and 160 g/L salts, respectively, and adding fertilizers somewhat enhanced oil biodegradation. Increased oil concentration in the sand, from 1 to 10 mL/kg, slowed the half-life by about 10-fold. Consequently, occasional irrigation with fertilization could be a suitable bioremediation strategy for the upper parts of contaminated beaches. However, dispersing oil at sea is probably the most suitable option for the optimal removal of spilled crude oil from the marine environment.

Dispersion modeling of particulate matter from the in-situ burning of spilled oil in the northwest Arctic area of Canada.

In-situ burning can be used to prevent oil spreading in oil spill response. In this study, a steady-state Gaussian plume model was applied to analyze the concentration distribution of fine particulate matter produced by in-situ burning, as well as to assess the health risks associated with different combustion methods and ambient conditions, in reference to three simulation scenarios. The spatial and temporal distribution of emission sources can affect the dispersion pattern. The distribution into an array of different burning locations ensures better dispersion of emissions, thereby preventing the formation of high concentration regions. The wind and atmosphere stability play an important role in pollution dispersion. Lower wind and temperature inversion can seriously hinder the diffusion of pollutants. The health risk to technical staff adjacent to the burning areas is a serious concern, and when the community is more than 20 km away from the burning zone, there is few risks. Through simulation, the influences of combustion methods and natural factors on the concentration and diffusion of pollutants are evaluated. The results can help provide an optimized burning strategy for oil spill response in the Arctic area.

Hypersaline Pore Water in Gulf of Mexico Beaches Prevented Efficient Biodegradation of Deepwater Horizon Beached Oil.

The 2010 Deepwater Horizon (DWH) blowout released 3.19 million barrels (435 000 tons) of crude oil into the Gulf of Mexico. Driven by currents and wind, an estimated 22 000 tons of spilled oil were deposited onto the northeastern Gulf shorelines, adversely impacting the ecosystems and economies of the Gulf coast regions. In this work we present field work conducted at the Gulf beaches in three U.S. States during 2010-2011: Louisiana, Alabama, and Florida, to explore endogenous mechanisms that control persistence and biodegradation of the MC252-oil deposited within beach sediments as deep as 50 cm. The work involved over 1500 measurements incorporating oil chemistry, hydrocarbon-degrading microbial populations, nutrient and DO concentrations, and intrinsic beach properties. We found that intrinsic beach capillarity along with groundwater depth provides primary controls on aeration and infiltration of near-surface sediments, thereby modulating moisture and redox conditions within the oil-contaminated zone. In addition, atmosphere-ocean-groundwater interactions created hypersaline sediment environments near the beach surface at all the studied sites. The fact that the oil-contaminated sediments retained near or above 20% moisture content and were also eutrophic and aerobic suggests that the limiting factor for oil biodegradation is the hypersaline environment due to evaporation, a fact not reported in prior studies. These results highlight the importance of beach porewater hydrodynamics in generating unique hypersaline sediment environments that inhibited oil decomposition along the Gulf shorelines following DWH.

Population agglomeration is a harbinger of the spatial complexity of COVID-19.

The spatial template over which COVID-19 infections operate is a result of nested societal decisions involving complex political and epidemiological processes at a broad range of spatial scales. It is characterized by 'hotspots' of high infections interspersed within regions where infections are sporadic to absent. In this work, the sparseness of COVID-19 infections and their time variations were analyzed across the US at scales ranging from 10 km (county scale) to 2600 km (continental scale). It was found that COVID-19 cases are multi-scaling with a multifractality kernel that monotonically approached that of the underlying population. The spatial correlation of infections between counties increased rapidly in March 2020; that rise continued but at a slower pace subsequently, trending towards the spatial correlation of the population agglomeration. This shows that the disease had already spread across the USA in early March such that travel restriction thereafter (starting on March 15th 2020) had minor impact on the subsequent spatial propagation of COVID-19. The ramifications of targeted interventions on spatial patterns of new infections were explored using the epidemiological susceptible-infectious-recovered (SIR) model mapped onto the population agglomeration template. These revealed that re-opening rural areas would have a smaller impact on the spread and evolution of the disease than re-opening urban (dense) centers which would disturb the system for months. This study provided a novel way for interpreting the spatial spread of COVID-19, along with a practical approach (multifractals/SIR/spectral slope) that could be employed to capture the variability and intermittency at all scales while maintaining the spatial structure.

A framework for the evaluation and selection of shoreline surface washing agents in oil spill response.

The shorelines frequently suffer adverse impacts from oil spill accidents. As one important technique of shoreline cleanup, the application of surface washing agents (SWAs) can help achieve high oil removal from shoreline substrates with less damage to affected zone. In this study, a framework for evaluation and selection of SWAs in oil spill incidents was constructed to better understand and apply this technique. A decision tree was firstly developed to illustrate all possible scenarios which are appropriate to use SWAs in consideration of oil collectability, shoreline character, types and amount of stranded oil, and cleanup requirement. Based on literature review, theoretical modeling, and experts' suggestions, an integrated multi-criteria decision analysis (MCDA) method was then come up to select the most preferred SWA from five aspects of toxicity, effectiveness, minimal dispersion, demonstrated field test, and cost. Its suitability and rationality were proved by a hypothetical case. In addition, sensitivity analysis was performed by changing the weight of each criterion independently to check the priority rank of alternatives, and it also verified the robustness and stability of this model. The presented framework has significant implications for future research and application of SWAs in the shoreline cleanup.

Petroleum dynamics in the sea and influence of subsea dispersant injection during Deepwater Horizon.

During the Deepwater Horizon disaster, a substantial fraction of the 600,000-900,000 tons of released petroleum liquid and natural gas became entrapped below the sea surface, but the quantity entrapped and the sequestration mechanisms have remained unclear. We modeled the buoyant jet of petroleum liquid droplets, gas bubbles, and entrained seawater, using 279 simulated chemical components, for a representative day (June 8, 2010) of the period after the sunken platform's riser pipe was pared at the wellhead (June 4-July 15). The model predicts that 27% of the released mass of petroleum fluids dissolved into the sea during ascent from the pared wellhead (1,505 m depth) to the sea surface, thereby matching observed volatile organic compound (VOC) emissions to the atmosphere. Based on combined results from model simulation and water column measurements, 24% of released petroleum fluid mass became channeled into a stable deep-water intrusion at 900- to 1,300-m depth, as aqueously dissolved compounds (∼23%) and suspended petroleum liquid microdroplets (∼0.8%). Dispersant injection at the wellhead decreased the median initial diameters of simulated petroleum liquid droplets and gas bubbles by 3.2-fold and 3.4-fold, respectively, which increased dissolution of ascending petroleum fluids by 25%. Faster dissolution increased the simulated flows of water-soluble compounds into biologically sparse deep water by 55%, while decreasing the flows of several harmful compounds into biologically rich surface water. Dispersant injection also decreased the simulated emissions of VOCs to the atmosphere by 28%, including a 2,000-fold decrease in emissions of benzene, which lowered health risks for response workers.

A New Mechanism of Sediment Attachment to Oil in Turbulent Flows: Projectile Particles.

The interaction of oil and sediment in the environment determines, to a large extent, the trajectory and fate of oil. Using confocal microscope imaging techniques to obtain detailed 3D structures of oil-particle aggregates (OPAs) formed in turbulent flows, we elucidated a new mechanism of particle attachment, whereby the particles behave as projectiles penetrating the oil droplets to depths varying from ∼2 to 10 µm due to the hydrodynamic forces in the water. This mechanism results in a higher attachment of particles on oil in comparison with adsorption, as commonly assumed. The projectile hypothesis also explains the fragmentation of oil droplets with time, which occurred after long hours of mixing, leading to the formation of massive OPA clusters. Various lines of inquiry strongly suggested that protruding particles get torn from oil droplets and carry oil with them, causing the torn particles to be amphiphillic so that they contribute to the formation of massive OPAs of smaller oil droplets (<∼5-10 µm). Low particle concentration resulted in large, irregularly shaped oil blobs over time, the deformation of which without fragmentation could be due to partial coverage of the oil droplet surface by particles. The findings herein revealed a new pathway for the fate of oil in environments containing non-negligible sediment concentrations.

Characterization of Turbulent Properties in the EPA Baffled Flask for Dispersion Effectiveness Testing.

The baffled flask test (BFT) has been proposed by United States Environmental Protection Agency to be adopted as the official standard protocol for testing dispersant effectiveness. The mixing energy in the baffled flask is investigated in this paper. Particle image velocimetry (PIV) was used to measure the water velocity in the flask placed at an orbital shaker that was rotated at seven rotation speeds: 100, 125, 150, 160, 170, 200, and 250 rpm. Two dimensional velocity fields in large and small vertical cross sections of the flask for each rotation speed were obtained. The one-dimensional (1D) energy spectra indicates the existence of inertial subrange. The estimated average energy dissipation rates were in the range 7.65×10-3 to 4 W/kg for rotation speeds of Ω=100-250 rpm, of which it is larger than the one estimated by prior studies using single-point velocity measurement techniques for Ω=100 and 200 rpm. Factors such as instruments used, velocity components measured, and different analysis methods could contribute to the discrepancies in the results. The Kolmogorov scale estimated in this study for all seven rotation speeds approached the size of oil droplets observed at sea, which is 50-400 µm. The average energy dissipation rate, ε and Kolmogorov microscale, η, in the flasks were correlated to the rotation speed, and it was found that ε ¯ = 9.0 × 10 - 5 Exp (0.043Ω) with R 2 = 0.97 and η ¯ = 1 , 463 Exp (-0.015Ω) with R 2 = 0.98.

Simulation of the landfall of the Deepwater Horizon oil on the shorelines of the Gulf of Mexico.

We conducted simulations of oil transport from the footprint of the Macondo Well on the water surface throughout the Gulf of Mexico, including deposition on the shorelines. We used the U.S. National Oceanic Atmospheric Administration (NOAA) model General NOAA Operational Modeling Environment (GNOME) and the same parameter values and input adopted by NOAA following the Deepwater Horizon (DWH) blowout. We found that the disappearance rate of oil off the water surface was most likely around 20% per day based on satellite-based observations of the disappearance rate of oil detected on the sea surface after the DWH wellhead was capped. The simulations and oil mass estimates suggest that the mass of oil that reached the shorelines was between 10,000 and 30,000 tons, with an expected value of 22,000 tons. More than 90% of the oil deposition occurred on the Louisiana shorelines, and it occurred in two batches. Simulations revealed that capping the well after 2 weeks would have resulted in only 30% of the total oil depositing on the shorelines, while capping after 3 weeks would have resulted in 60% deposition. Additional delay in capping after 3 weeks would have averted little additional shoreline oiling over the ensuing 4 weeks.

Mobilization of per- and poly-fluoroalkyl substances (PFAS) in soils with different organic matter contents.

There is considerable interest in addressing soils contaminated with per- and polyfluoroalkyl substances (PFAS) because of the PFAS in the environment and associated health risks. The neutralization of PFAS in situ is challenging. Consequently, mobilizing the PFAS from the contaminated soils into an aqueous solution for subsequent handling has been pursued. Nonetheless, the efficiency of mobilization methods for removing PFAS can vary depending on site-specific factors, including the types and concentrations of PFAS compounds, soil characteristics. In the present study, the removal of perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) from artificially contaminated soils was investigated in a 2D laboratory setup using electrokinetic (EK) remediation and hydraulic flushing by applying a hydraulic gradient (HG) for a duration of 15 days. The percent removal of PFOA by EK was consistent (∼80%) after a 15-day treatment for all soils. The removal efficiency of PFOS by EK significantly varied with the OM content, where the PFOS removal increased from 14% at 5% OM to 60% at 50% OM. With HG, the percent removal increased for both PFOA and PFOS from about 20% at 5% OM up to 80% at 75% OM. Based on the results, the mobilization of PFAS from organic soil would be appropriate using both hydraulic flushing and EK considering their applicability and advantages over each other for site-specific factors and requirements.

Repurposing spent biomass of vetiver grass used for stormwater treatment to generate biochar and ethanol.

Stormwater pollution is a key factor contributing to water quality degradation, posing substantial environmental and human health risks. Although stormwater retention ponds, also referred to as wet ponds, are commonly implemented to alleviate stormwater challenges by reducing peak flow and removing suspended solids, their effectiveness in removing heavy metals and nutrients is limited. This study evaluated the performance of floating treatment platforms (FTPs) featuring vetiver grass (Chrysopogon zizanioides), a non-invasive, nutrient- and metal-accumulating perennial grass, in removing heavy metals (Cu, Pb, and Zn) and nutrients (P and N) in stormwater retention ponds. Furthermore, the potential for utilizing the spent vetiver biomass for generating biochar and bioethanol was investigated. The study was conducted in a greenhouse setup under simulated wet and dry weather conditions using pond water collected from a retention pond in Stafford Township, New Jersey, USA. Two FTPs with vetiver (vegetated FTPs) were compared with two FTPs without vetiver (non-vegetated FTPs), which served as controls. Results showed that the removal of heavy metals and nutrients by the FTPs with vetiver was significantly higher (p < 0.05) than the FTPs without vetiver. Notably, vetiver showed resilience to stormwater pollutants and hydroponic conditions, displaying no visible stress symptoms. The biochar and bioethanol generated from the spent vetiver exhibited desirable yield and quality, without raising concerns regarding pollutant leaching, indicated by very low TCLP and SPLP concentrations. This study provides compelling evidence that the implementation of vetiver-based FTPs offers a cost-effective and environment-friendly solution for mitigating stormwater pollution in retention ponds. Furthermore, the utilization of vetiver biomass for biofuel and biochar production supports clean production and fostering circular economy efforts.

Temporal and spatial distribution of microplastics in green infrastructures: Rain gardens.

Rain gardens, a type of green infrastructure (GI), have been recognized for mitigating flooding and improving water quality from minor storms by trapping stormwater pollutants. Yet, the capability of these systems to retain microplastics (MPs) from stormwater, especially in size <125 µm, remains inadequately understood. This study investigated the spatial and temporal distributions of MPs in three rain gardens located in Newark, New Jersey, USA. The rain gardens have been in operation for ∼7 years and located in different land uses: low-density residential (Site 1), commercial (Site 2), and high-density residential (Site 3). The sediment samples were collected during May 2022, August 2022, and February 2023 at various soil depths and horizontal distances of rain gardens. The MPs were quantified and characterized using Fourier transform infrared (FTIR) spectrometer and a Raman microscope. The overall mean concentration varied between sampling sites, with 469 ± 89.8 pkg-1 in Site 1, 604 ± 91.4 pkg-1 in Site 2, and 997 ± 64.3 pkg-1 in Site 3, with Polypropylene as the dominant polymer, followed by nylon and polyethylene. In the vertical direction, larger MPs (250 µm-5 mm) were effectively retained within the top 5 cm and their concentration declined exponentially with the increasing depths. Small-sized MPs (1-250 µm) were prevalent at deeper depths (≥ 10 cm), and no MPs were found below 15 cm. In the horizontal direction, the highest MP concentration was observed near the stormwater inlet, and the concentration decreased away from the inlet. Over the nine-month period, a notable increase in concentration was observed at all sites. These findings contribute valuable knowledge towards developing effective measures for retaining MPs from stormwater and monitoring GIs in urban environments.

IMPACT: Innovative (nano)Materials and processes for advanced catalytic technologies to degrade PFOA in water.

We hereby report the development of a novel electrochemical method to degrade perfluorooctanoic acid (C7F15COOH, PFOA). At the center of the approach are bimetallic Pd-Ru nano-catalyst materials called IMPACT: Innovative (nano)Materials and Processes for Advanced Catalytic Technologies. IMPACT uses flavonoid-sequestered Pd-Ru, allowing the development of specialized electrodes with tunable properties to sequentially degrade PFOA in wastewater samples into a sustainable byproduct via an indirect electrochemical method. Electron transfers at RuOxHy species stabilize the Pd component of the nano-catalysts, enabling the degradation process via PFOA deprotonation, chain shortening, decarboxylation, hydrolysis, fluoride elimination, and CF2 flake-off mechanism. IMPACT enabled the observation of redox peaks at -0.26 V and 0.56 V for the first time, with accompanying reduction peaks at -0.5V and 0.29 V, respectively. These redox peaks, which correlated with the concentrations of PFOA (20, 50, 100, 200, and 400. mg L-1), were verified and confirmed using electrochemical simulations. Control experiments did not show degradation of PFOA in the absence of Pd-Ru nano-catalyst. The degradation in wastewater was obtained within 3 h with an efficiency of 98.5%. The electrochemical degradation products of PFOA were identified using High-resolution desalting paper spray mass spectrometry (DPS-MS) and collision-induced dissociation (CID) analysis. The results yielded C2F5COOH, C3F7COOH, and C6F13OH with dissociation losses of CF2O or CO2. IMPACT introduces a novel nano-catalyst with high efficiency and a reliable capability that defluorinates strong C-F bonds that are components of recalcitrant organics in myriad environmental matrices.

Unrefined and Milled Ilmenite as a Cost-Effective Photocatalyst for UV-Assisted Destruction and Mineralization of PFAS.

Per- and polyfluoroalkyl substances (PFAS) are fluorinated and refractory pollutants that are ubiquitous in industrial wastewater. Photocatalytic destruction of such pollutants with catalysts such as TiO2 and ZnO is an attractive avenue for removal of PFAS, but refined forms of such photocatalysts are expensive. This study, for the first time, utilized milled unrefined raw mineral ilmenite, coupled to UV-C irradiation to achieve mineralization of the two model PFAS compounds perfluorooctanoic acid (PFOA) and perfluoro octane sulfonic acid (PFOS). Results obtained using a bench-scale photocatalytic reactor system demonstrated rapid removal kinetics of PFAS compounds (>90% removal in less than 10 h) in environmentally-relevant concentrations (200-1000 ppb). Raw ilmenite was reused over three consecutive degradation cycles of PFAS, retaining >80% removal efficiency. Analysis of degradation products indicated defluorination and the presence of shorter-chain PFAS intermediates in the initial samples. End samples indicated the disappearance of short-chain PFAS intermediates and further accumulation of fluoride ions, suggesting that original PFAS compounds underwent mineralization due to an oxygen-radical-based photocatalytic destruction mechanism induced by TiO2 present in ilmenite and UV irradiation. The outcome of this study implies that raw ilmenite coupled to UV-C is suitable for cost-effective reactor operation and efficient photocatalytic destruction of PFAS compounds.

Mathematical modeling of the biodegradation of residual hydrocarbon in a variably-saturated sand column.

The biodegradation of heptadecane in five sand columns was modeled using a multiplicative Monod approach. Each column contained 1.0 kg of sand and 2 g of heptadecane, and was supplied with an artificial seawater solution containing nutrients at a flow rate that resulted in unsaturated flow through the column. All nutrients were provided in excess with the exception of nitrate whose influent concentration was 0.1, 0.5, 1.0, 2.5, or 5.0 mg N/L. The experiment was run around 912 h until no measurable oxygen consumption or CO2 production was observed. The residual mass of heptadecane was measured at the end of the experiments and the biodegradation was monitored based on oxygen consumption and CO2 production. Biodegradation kinetic parameters were estimated by fitting the model to experimental data of oxygen, CO2, and residual mass of heptadecane obtained from the two columns having influent nitrate-N concentration of 0.5 and 2.5 mg/L. Noting that the oxygen and CO2 measurements leveled off at around 450 h, we fitted the model to these data for that range. The estimated parameters fell in within the range reported in the literature. In particular, the half-saturation constant for nitrate utilization, [Formula: see text], was estimated to be 0.45 mg N/L, and the yield coefficient was found to be 0.15 mg biomass/mg heptadecane. Using these values, the rest of experimental data from the five columns was predicted, and the model agreed with the observations. There were some consistent discrepancies at large times between the model simulation and observed data in the cases with higher nitrate concentration. One plausible explanation for these differences could be limitation of biodegradation by reduction of the heptadecane-water interfacial area in these columns while the model uses a constant interfacial area.