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During time-periods oil slicks are in the marine environment (age-at-sea), weathering causes significant changes in composition and mass loss (depletion) of oil spill chemicals including the more toxic polycyclic aromatic hydrocarbons (PAHs). The goal of this study was to estimate the age-at-sea of weathered oil slicks using the oil spill module of the Connectivity Modeling System and to use this age to interpret PAH concentration measurements. Percent depletion (PD) for each measurement was computed as the percentage difference between the original and measured PAH concentration in the crude oil and weathered oil slicks, normalized upon the mass losses relative to hopane. Mean PD increased with estimated age-at-sea for all PAHs. Less PD was observed for alkylated than for parent PAHs, likely due to decreasing vapor pressure with increasing degree of alkylation. We conclude that estimated age-at-sea can be used to explain PAH depletion in weathered oil slicks. We propose PAH vapor pressure can be coupled with the model to expand capacity for predicting concentration distributions of individual parent and alkylated PAHs in weathered oil along the coastline. This new module will advance the science supporting oil spill response by providing more certain estimates of health risks from oil spills. [Display omitted] • Evaluated relationship between age-at-sea and PAH depletion. • PAH depletion increased with estimated age-at-sea. • PAH vapor pressure decreased with increasing alkylation. • A new module to predict PAH concentration distributions is recommended. • Improved oil spill response through better estimates of health risks. [ABSTRACT FROM AUTHOR]

The 2010 DWH disaster generated atmospheric pollutants of health concern which reached the Gulf Coast. This study evaluated whether changes in coastal air quality due to the disaster were captured by aerosol optical depth (AOD) estimated using satellite data and by ground-based monitoring of air pollution, including fine particulate matter ≤2.5 μm in aerodynamic diameter (PM 2.5), benzene and naphthalene. Mean monthly AOD levels were higher in May 2010 [during oil spill time], (mean AOD = 0.355), than for the prior (mean AOD = 0.258) and following years (mean AOD = 0.252) (p < 0.05). PM 2.5 concentrations and AOD were significantly correlated (R2 = 0.59, p < 0.05), for one study area. Elevated PM 2.5 , benzene, and naphthalene concentrations coincided with downwind directions from the location of the oil slicks. A fully-coupled oil fate and transport atmospheric transport model of oil spill emissions, integrated with AOD and more extensive ground-based measurements, is recommended to predict coastal population exposures during oil spills. [Display omitted] • Evaluated coastal air quality impacts during an oil spill. • AOD levels were higher at times of active spill than prior and following years. • PM 2.5 and AOD were significantly correlated for one study area. • PM 2.5 , naphthalene and benzene in coastal areas peaked downwind from oil slicks. • A fully-coupled ocean-atmospheric model of oil spill emissions is recommended. [ABSTRACT FROM AUTHOR]

Although great progress has been made to advance the scientific understanding of oil spills, tools for integrated assessment modeling of the long-term impacts on ecosystems, socioeconomics and human health are lacking. The objective of this study was to develop a conceptual framework that could be used to answer stakeholder questions about oil spill impacts and to identify knowledge gaps and future integration priorities. The framework was initially separated into four knowledge domains (ocean environment, biological ecosystems, socioeconomics, and human health) whose interactions were explored by gathering stakeholder questions through public engagement, assimilating expert input about existing models, and consolidating information through a system dynamics approach. This synthesis resulted in a causal loop diagram from which the interconnectivity of the system could be visualized. Results of this analysis indicate that the system naturally separates into two tiers, ocean environment and biological ecosystems versus socioeconomics and human health. As a result, ocean environment and ecosystem models could be used to provide input to explore human health and socioeconomic variables in hypothetical scenarios. At decadal-plus time scales, the analysis emphasized that human domains influence the natural domains through changes in oil-spill related laws and regulations. Although data gaps were identified in all four model domains, the socioeconomics and human health domains are the least established. Considerable future work is needed to address research gaps and to create fully coupled quantitative integrative assessment models that can be used in strategic decision-making that will optimize recoveries from future large oil spills. [Display omitted] • A conceptual framework was developed for an integrated oil spill model that can be used to answer societal level questions. • Framework includes four knowledge domains: ocean environment, biological ecosystems, socioeconomics, and human health. • A causal loop diagram was developed to evaluate linkages and data gaps. • System separates into two tiers, the natural systems and human systems. • The largest knowledge gaps correspond to the socioeconomics and human health domains. [ABSTRACT FROM AUTHOR]

Oil spills can result in changes in chemical concentrations along coastlines. In prior work, these concentration changes were used to evaluate the date sediment was impacted by oil (i.e., oil exposure date). The objective of the current study was to build upon prior work by using the oil exposure date to compute oil spill chemical (OSC) concentrations in shoreline sediments before and after exposure. The new method was applied to OSC concentration measures collected during the Deepwater Horizon oil spill with an emphasis on evaluating before and after concentrations in muddy versus sandy regions. The procedure defined a grid that overlaid coastal areas with chemical concentration measurement locations. These grids were then aggregated into clusters to allow the assignment of chemical concentration measurements to a uniform coastal type. Performance of the method was illustrated for ten chemicals individually by cluster, and collectively for all chemicals and all clusters. Results show statistically significant differences between chemical concentrations before and after the calculated oil exposure dates (p < 0.04 for each of the 10 chemicals within the identified clusters). When aggregating all chemical measures collectively across all clusters, chemical concentrations were lower before oil exposure in comparison to after (p < 0.0001). Sandy coastlines exhibited lower chemical concentrations relative to muddy coastlines (p < 0.0001). Overall, the method developed is a useful first step for establishing baseline chemical concentrations and for assessing the impacts of disasters on sediment quality within different coastline types. Results may be also useful for assessing added ecological and human health risks associated with oil spills. Image 1 • A novel method was developed to quantify oil impact on chemical concentrations. • The method can be used to evaluate muddy versus sandy regions. • Coast types were identified by superimposing a grid on remote sensing images. • Concentration differences between muddy and sandy regions were computed. • 10 indicator chemicals were identified as potential tracers of oil impact level. A new method is developed and applied to the Deepwater Horizon oil dataset to evaluate chemical concentrations in coastline sediments before and after oil exposures. [ABSTRACT FROM AUTHOR]

Oil spills can result in changes in chemical contaminant concentrations along coastlines. When concentrations are measured along the Gulf of Mexico over time, this information can be used to evaluate oil spill shoreline exposure dates. The objective of this research was to identify more accurate oil exposure dates based on oil spill chemical concentrations changes (CCC) within sediments in coastal zones after oil spills. The results could be used to help improve oil transport models and to improve estimates of oil landings within the nearshore. The CCC method was based on separating the target coastal zone into segments and then documenting the timing of large increases in concentration for specific oil spill chemicals (OSCs) within each segment. The dataset from the Deepwater Horizon (DWH) oil spill was used to illustrate the application of the method. Some differences in exposure dates were observed between the CCC method and between oil spill trajectories. Differences may have been caused by mixing at the freshwater and sea water interface, nearshore circulation features, and the possible influence of submerged oil that is unaccounted for by oil spill trajectories. Overall, this research highlights the benefit of using an integrated approach to confirm the timing of shoreline exposure. Image 1 • A new method is developed to compute oil exposure dates and regions. • Dates and regions were computed from concentrations of shoreline sediments. • Differences were observed against exposure dates predicted by oil spill trajectories. • Nearshore circulation features appear to account for some differences. • Cyclones also appear to influence exposure dates. Shoreline oil exposure dates were computed from concentrations of shoreline sediments measured during an oil spill. [ABSTRACT FROM AUTHOR]

Oil Spill Chemicals (OSCs) represent a risk to the environment and human health, especially in nearshore environments used for recreational purposes. Importantly, the starting point for human health risk assessment is to define the concentration of OSCs at nearshore locations. The objective of this study was to evaluate nearshore sampling data of OSC concentrations in different environmental matrices within time-space specific categories. The categories correspond to OSC concentration values for samples collected prior to nearshore oiling, post nearshore oiling and at no time impacted by oil as predicted by historic oil spill trajectories generated by an Oil Spill Trajectory Model. In general, concentration values for the post category were higher than prior which were higher than unimpacted. Results show differences in PAH concentration patterns within each matrix and for each category. Concentration frequency distributions for most chemicals in each category were log-normally distributed. Unlabelled Image • Toxic Oil Spill Chemicals (OSCs) represent a risk to human health. • OSC distributions were categorized in a spatial and temporal context. • Two spatial-temporal categories had statistically higher mean concentrations. • Results show differences in concentration patterns for each category. • Concentration frequency distributions for most OSCs were log-normally distributed. [ABSTRACT FROM AUTHOR]