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.

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.

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.

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.

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.

Modeling impacts of river hydrodynamics on fate and transport of microplastics in riverine environments.

Microplastics pose a significant and growing threat to marine ecosystems and human health. Rivers serve as critical pathways for the entry of inland-produced microplastics into marine environments. In this paper, we developed a numerical modeling scheme using OpenFOAM to investigate the fate and transport of microplastics in a river system. Our simulation results show that microplastics undergo significant aggregation and breakage as they are transported downstream by river flows. This significantly alters the particle size distribution of microplastics. The aggregation-breakage process is mainly controlled by river hydrodynamics and pollution scale. Our findings suggest that a significant extent of particle aggregation occurs at an early stage of the release of microplastics in the river, while the aggregation-breakage process becomes limited as the microplastic plume is gradually dispersed and diluted downstream. Eddy diffusivity drives the dispersion of the microplastic plume in the river, and its spatial patterns affect the aggregation-breakage process.

Oil Transport Following the Deepwater Horizon Blowout.

The Deepwater Horizon oil spill in the Gulf of Mexico in 2010 was the largest in US history, covering more than 1,000 km of shorelines and causing losses that exceeded $50 billion. While oil transformation processes are understood at the laboratory scale, the extent of the Deepwater Horizon spill made it challenging to integrate these processes in the field. This review tracks the Deepwater Horizon oil during its journey from the Mississippi Canyon block 252 (MC252) wellhead, first discussing the formation of the oil and gas plume and the ensuing oil droplet size distribution, then focusing on the behavior of the oil on the water surface with and without waves. It then reports on massive drifter experiments in the Gulf of Mexico and the impact of the Mississippi River on the oil transport. Finally, it concludes by addressing the formation of oil-particle aggregates. Although physical processes lend themselves to numerical modeling, we attempted to elucidate them without using advanced modeling, as our goal is to enhance communication among scientists, engineers, and other entities interested in oil spills.

Effect of clay content on the mobilization efficiency of per- and polyfluoroalkyl substances (PFAS) from soils by electrokinetics and hydraulic flushing.

The need for the efficient remediation of soils impacted by per- and polyfluoroalkyl substances (PFAS) is substantially growing because of the notable upsurge in societal and regulatory awareness of this class of chemicals. To remediate PFAS-contaminated soils using mobilization approaches, the choice of appropriate techniques highly depends on the soil's composition, particularly the clay content, which significantly affects the soil's permeability. Here, we investigated the PFAS mobilization efficiency from soils with different clay contents by using two techniques: electrokinetic (EK) remediation and hydraulic flushing. Artificial kaolinite was added to a loamy sand soil to prepare four soil blends with clay contents of 5, 25, 50, and 75%, each contaminated with perfluorooctanoic acid (PFOA) and perfulorooctanesulfonic acid (PFOA) at 10,000 µg/kg. EK remediation was conducted by applying a low voltage (30 V) with a current of 100 mA, and hydraulic flushing was carried out by applying a hydraulic gradient (HG) with a slope of 6.7%. Results show that, with a 14-day treatment duration, the EK-mobilization efficiency was enhanced substantially with the increase of clay content (removal of PFOS increased from 20% at 5% clay to 80% at 75% clay), most likely due to the increase of electroosmotic flow due to the higher content of particles having a zeta potential (i.e., clay). For HG, increasing the clay content significantly suppressed the mobilization of PFAS (removal of PFOS decreased from 40% at 5% clay to 10% at 75% clay) due to a notable decrease in the soil's permeability. Based on the results, applying hydraulic flushing and washing techniques for mobilizing PFAS would be appropriate when treating permeable soils with a maximum clay content of about 25%; otherwise, other suitable mobilization techniques such as EKs should be considered.

A perspective on quantifying resilience: Combining community and infrastructure capitals.

The resilience of communities has emerged as a major goal in policy and practice. Cities, states, and counties within the United States and around the world are passing laws requiring the incorporation of climate-related hazard vulnerability assessments within their master plan updates for resilience planning and design. The resilience of communities under present and future scenarios is thus becoming a cornerstone of decision making and actions. Decisions that would enhance resilience, however, span multiple sectors and involve various stakeholders. Quantifying community resilience is a key step in order to describe the preparedness level of communities, and subsequently locating non-resilient areas to further enhance their capacity to endure disasters. Two main approaches are currently being pursued to evaluate resilience. The first approach is the "community resilience" developed mainly by social scientists and planners, and it captures social resilience using numerous pre-disaster attributes to describe the functioning of a community. This approach subsumes that pre-disaster attributes can predict the community resilience to a disaster. The second approach is adopted for infrastructure resilience, mostly used by engineers, and it focuses on robustness, redundancy, resourcefulness, and rapidity. This approach is appropriate for systems that are operated by highly skilled personnel and where the actions are of engineering type. In this paper, we provide an overview of the two approaches, and we leverage their limitations to propose a hybrid approach that combines community and infrastructure capitals into an Area Resilience metric, called ARez. ARez captures the role/impact of both infrastructure and community and combines five sectors: energy, public health, natural ecosystem, socio-economic, and transportation. We present a proof-of-concept for the ARez metric, showing its practicality and applicability as a direct measure for resilience, over various time scales.

A generic approach to construct pseudo components for oil weathering models.

Oil weathering models are essential for predicting the behavior of spilled oil in the environment. Most models use a "Pseudo Component" (PC) approach to represent the wide range of compounds found in petroleum products. Within the approach, rather than modeling each individual compound in an oil, a manageable number of PCs are developed that represent whole classes of compounds. However, previous studies focused mainly on traditional crude oils and did not develop a generic approach to create an optimal set of PCs for a variety of oils. In developing the updates to the NOAA oil weathering model, we propose herein a generic approach to construct PCs using oil distillation data to capture the complexity of oil evaporative weathering. We validated our approach with 899 oils from the Automated Data Inquiry for Oil Spills (ADIOS) oil library and found that an optimal set of sixteen PCs should be used. These PCs include two with low boiling point (below 144 °C), one with a high boiling point (above 400 °C), and thirteen constructed within a middle range of boiling points with a temperature resolution of 20 °C. Our simulation tests suggested that this set of sixteen PCs adequately characterizes oil evaporation processes for a wide variety of oils.

Relative sensitivity of hydrodynamic, thermodynamic, and chemical processes for simulating the buoyant multiphase plume and surfacing flows of an oil and gas blowout.

Deepwater hydrocarbon releases experience complex chemical and physical processes. To assess simplifications of these processes on model predictions, we present a sensitivity analysis using simulations for the Deepwater Horizon oil spill. We compare the buoyant multiphase plume metrics (trap height, rise time etc), the hydrocarbon mass flowrates at the near-field plume termination and their mass fractions dissolved in the water column and reaching the water surface. The baseline simulation utilizes a 19-component hydrocarbon model, live-fluid state equations, hydrate dynamics, and heat and mass transfer. Other simulations turn-off each of these processes, with the simplest one using inert oil and methane gas. Plume metrics are the least sensitive to the modeled processes and can be matched by adjusting the release buoyancy flux. The mass flowrate metrics are more sensitive. Both liquid- and gas-phase mass transfer should be modeled for accurate tracking of soluble components (e.g. C1 - C7 hydrocarbons) in the environment.

Field fluorometers for assessing oil dispersion at sea.

Oil dispersion by the application of chemical dispersants is an important tool in oil spill response, but it is difficult to quantify in the field in a timely fashion that is useful for coordinators and decision-makers. One option is the use of rugged portable field fluorometers that can deliver essentially instantaneous results if access is attainable. The United States Coast Guard has suggested, in their Special Monitoring of Applied Response Technologies (SMART) protocols, that successful oil dispersion can be identified by a five-fold increase in oil fluorescence. Here we test three commercial fluorometers with different excitation/emission windows (SeaOWL, Cyclops 7FO, and Cyclops 7F-G) that might prove useful for such applications. Results show that they have significantly different dynamic ranges for detecting oil and that using them (or similar instruments) in combination is probably the best option for successfully assessing the effectiveness of oil dispersion operations. Nevertheless, the rapid dilution of dispersed oil means that measurements must be made within an hour or two of dispersion, suggesting that one feasible scenario would be monitoring ship-applied dispersants by vessels following close behind the dispersant application vessel. Alternatively, autonomous submersibles might be pre-deployed to monitor aerial dispersant application, although the logistical challenges in a real spill would be substantial.

Oil droplet formation and vertical transport in the upper ocean.

The dispersion of oil droplets near ocean surface is important for evaluating the impact to the environment. Under breaking wave conditions, the surface oil experiences mainly two processes: the generation of oil droplets at/near the water surface, and the transport of oil droplets due to ocean dynamics. We investigated the vertical behavior by incorporating the transport equation and the VDROP model. The transport equation adopted the ocean dynamics by K-profile parameterization (KPP) and the impact of additional turbulence by imposing the energy dissipation rate on the ocean surface. The oil droplet distribution was obtained, and the entrained distribution and entrainment rate was computed. The results shows that although the entrained distribution and the entrainment rate shares certain consistency with previous studies, divergences are also noticed. Accordingly, the model that describes the physics should be adopted to avoid incorrect qualification of the oil concentration dispersed in the ocean.

Proof of concept study for in-situ burn application using conventional containment booms - Design of Burning Tongue.

In situ burning (ISB) hasn't been widely used for offshore oil spill response for various reasons. We present a feasibility study for a new ISB method - the Burning Tongue (BT) concept. We conducted scaled experiments in the Ohmsett wave tank to demonstrate its feasibility. We produced a 35-m long "tongue" of burnable oil (average oil thickness 4.2 mm - above the thickness needed for ISB) by towing a conventional boom (with a 12″ (0.3 m) deep skirt) partially filled with crude oil and then released the oil through a 6″ (0.15 m) wide opening at the apex. We found that the boom movement produced a convergence zone just downstream that kept released oil thick and also pulled oil that entrained under the boom skirt into the thick "tongue" of oil. CFD modeling was performed to explain the flow hydrodynamics and the formation of the convergence zone, which indicates the phenomenon is universal. We used small harbor boom only partially filled with oil for this study and believe that a full-scale marine boom filled with oil would achieve an even thicker "burning tongue." The BT concept could make ISB more widely used for oil spill response in offshore areas.