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Cyanobacterial harmful algal blooms (cyanoHAB) cause human and ecological health problems in lakes worldwide. The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management and for targeted deployment of water quality monitoring resources. Software platforms that permit timely, useful, and cost-effective delivery of information from satellites are required to help managers respond to cyanoHABs. The Cyanobacteria Assessment Network (CyAN) mobile device application (app) uses data from the European Space Agency Copernicus Sentinel-3 satellite Ocean and Land Colour Instrument (OLCI) in near real-time to make initial water quality assessments and quickly alert managers to potential problems and emerging threats related to cyanobacteria. App functionality and satellite data were validated with 25 state health advisories issued in 2017. The CyAN app provides water quality managers with a user-friendly platform that reduces the complexities associated with accessing satellite data to allow fast, efficient, initial assessments across lakes.

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.

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

A new laboratory testing protocol for evaluating effectiveness of solidifiers in removing crude oil slicks on the water surface has been developed by the U.S. Environmental Protection Agency (EPA). Since an assessment of a testing protocol requires validation through an inter laboratory study with several independent research partners, a round-robin test was performed by five operators across two laboratories. The protocol was qualitatively and quantitatively evaluated to determine if it can satisfactorily differentiate product effectiveness, while still accounting for experimental and operational errors. Each operator evaluated the efficiency of six solidifier products with Arabian Light, Endicott and IFO 120 crude oils. All the experiments were carried out in triplicates and, additionally, an oil alone control sample was run for quality control purposes. The five operators were provided with all the supplies required to conduct the experiment and a detailed standard operating procedure. The results were collected and analyzed statistically to quantify repeatability and reproducibility. The average repeatability and reproducibility standard deviations were 5.1, 2.7, and 3.3% and 11.2, 10.1, and 13.1% for Arabian Light, Endicott and IFO, respectively. The within-operator error was ≤ 5% regardless of operator and oil type. Due to the difficulty and uncertainty associated with the separation of the solidified and un-solidified mass, the between-operator error was around 10%. The oil alone control had an average repeatability and reproducibility standard deviation of 4.8 and 6.1%, respectively. The variability among operators was also examined with h-statistics and the differences in operator means were found to be statistically insignificant. The variability is deemed acceptable for purposes of differentiating effective from ineffective solidifier products in the laboratory. The results from this round robin experiment will serve as an initial screening tool for the solidifier products in the market and will also help response teams determine the desirability and appropriateness of using a specific solidifier for oil spill remediation.

The majority of aquatic toxicity data for petroleum products has been limited to a few intensively studied crude oils and Corexit chemical dispersants, and acute toxicity testing in two standard estuarine test species: mysids (Americamysis bahia) and inland silversides (Menidia beryllina). This study compared the toxicity of two chemical dispersants commonly stock piled for spill response (Corexit EC9500A®, Finasol®OSR 52), three less studied agents (Accell Clean®DWD dispersant; CytoSol® surface washing agent; Gelco200® solidifier), and three crude oils differing in hydrocarbon composition (Dorado, Endicott, Alaska North Slope). Consistent with listings on the U.S. National Contingency Plan Product Schedule, general rank order toxicity was greatest for dispersants and lowest for the solidifier. The results indicate that freshwater species can have similar sensitivity as the conventionally tested mysids and silversides, and that the sea urchin (Arbacia punctulata) appears to be a reasonable addition to increase taxa diversity in standardized oil agent testing.

A controlled laboratory study was conducted to measure the dispersion effectiveness of Corexit 9500 on 23 different crude oils. This study was a part of a larger project initiated by the Bureau of Safety and Environmental Enforcement (BSEE) testing 20 oils to compare the predictive value of laboratory dispersant effectiveness tests with their larger scale test conducted at Ohmsett, BSEE’s national oil spill response test facility located in Leonardo, NJ. The test used in this study was the Baffled Flask Test (BFT), which is planned for adoption as EPA’s official testing protocol for listing commercial dispersant products on the National Contingency Plan Product Schedule, replacing the current Swirling Flask Test (SFT) [1]. In addition, the results of 3 additional oils, the 2 used in the SFT and BFT as currently written plus another reference oil, are presented. The temperature used for the tests was 15°C, to match the temperature used at Ohmsett. The dispersion effectiveness ranged from 3.4% to 93%. The BFT is a laboratory test with results that are inversely correlated with oil viscosity and therefore has predictive value in the decision to use a dispersant in the event of a spill.

In situ fluorometers were deployed during the Deepwater Horizon (DWH) Gulf of Mexico oil spill to track the subsea oil plume. Uncertainties regarding instrument specifications and capabilities necessitated performance testing of sensors exposed to simulated, dispersed oil plumes. Dynamic ranges of the Chelsea Technologies Group AQUAtracka, Turner Designs Cyclops, Satlantic SUNA and WET Labs, Inc. ECO, exposed to fresh and artificially weathered crude oil, were determined. Sensors were standardized against known oil volumes and total petroleum hydrocarbons and benzene-toluene-ethylbenzene-xylene measurements-both collected during spills, providing oil estimates during wave tank dilution experiments. All sensors estimated oil concentrations down to 300 ppb oil, refuting previous reports. Sensor performance results assist interpretation of DWH oil spill data and formulating future protocols.

Sustainable practices require a long-term commitment to creating solutions to environmental, social, and economic issues. The most direct way to ensure that management practices achieve sustainability is to monitor the environment. Remote sensing technology has the potential to accelerate the engagement of communities and managers in the implementation and performance of best management practices. Over the last few decades, satellite technology has allowed measurements on a global scale over long time periods, and is now proving useful in coastal waters, estuaries, lakes, and reservoirs, which are relevant to water quality managers. Comprehensive water quality climate data records have the potential to provide rapid water quality assessments, thus providing new and enhanced decision analysis methodologies and improved temporal/spatial diagnostics. To best realize the full application potential of these emerging technologies an open and effective dialogue is needed between scientists, policy makers, environmental managers, and stakeholders at the federal, state, and local levels. Results from an internal US Environmental Protection Agency qualitative survey were used to determine perceptions regarding the use of satellite remote sensing for monitoring water quality. The goal of the survey was to begin understanding why management decisions do not typically rely on satellite-derived water quality products.

The increasing level of commercial marine activity in high latitudes creates an ever growing risk of oil spills. Even in logistically accessible, ice-free oceans, characterizing the extent and nature of a spill can be challenging as highlighted by the Deepwater Horizon incident. We propose to develop an AUV-based approach inspired by an existing small, long-range system, called the Tethys Long-Range AUV (LRAUV), in order to support the Arctic Doman Awareness Center (ADAC) for spill preparedness.

This study was aimed at testing the applicability of modified Weber number scaling with Alaska North Slope (ANS) crude oil, and developing a Reynolds number scaling approach for oil droplet size prediction for high viscosity oils. Dispersant to oil ratio and empirical coefficients were also quantified. Finally, a two-step Rosin-Rammler scheme was introduced for the determination of droplet size distribution. This new approach appeared more advantageous in avoiding the inconsistency in interfacial tension measurements, and consequently delivered concise droplet size prediction. Calculated and observed data correlated well based on Reynolds number scaling. The relation indicated that chemical dispersant played an important role in reducing the droplet size of ANS under different seasonal conditions. The proposed Reynolds number scaling and two-step Rosin-Rammler approaches provide a concise, reliable way to predict droplet size distribution, supporting decision making in chemical dispersant application during an offshore oil spill.

The development of multispectral in situ fluorescence instruments greatly enhances the study of the optical properties of Colored Organic Matter (COM). Here, we tested the inter-instrument variability of three WetLabs, Inc. SAFIres using quinine sulfate standards. As with any fluorometer, intensity and spectral biases in fluorescence output due to properties of the SAFIre's optical components necessitate corrections. Low response of the instrument to quinine sulfate and lack of an excitation/emission channel at the fluorescence maximum of this standard precluded direct spectral calibration. Calibrations conducted using seawater as a secondary standard provided an acceptable alternative. The field performance of the SAFIre from two experiments is presented here. Time series contour plots show that the instrument has the ability to detect small differences in COM optical properties, and observed fluorescence emission ratios are indicative of changes in sources of the material over the course of the study. The SAFIre was found to extend multispectral measurements to include high spatial and high temporal resolution.

In situ fluorometers were deployed during the Deepwater Horizon (DWH) Gulf of Mexico oil spill to provide critical measurements for tracking the subsea oil plume. In the wake of the spill, uncertainties regarding instrument specifications, capabilities and reliability necessitated performance testing of sensors (commonly used during spill response) exposed to simulated, dispersed oil plumes. Moreover, concerns on the applicability of laboratory calibrations (at high concentrations and insufficient mixing energies) to field conditions and on sensor reliability to detect dispersed oil persist. To address these uncertainties the performance of select commercially-available sensors (from Chelsea Technologies Group, Satlantic, Turner Designs, WetLabs Inc) was evaluated using a wave tank facility at the Bedford Institute of Oceanography in Halifax, Nova Scotia. Breaking waves were generated within the tank to simulate mixing energies and achieve dispersant effectiveness observed in the field. Presented here are the results of the sensors exposed to chemically-dispersed MC252 crude oil using Corexit 9500, DOR=1:20. Stepwise additions of dispersed oil (0.3 – 12 ppm) to the tank were used to establish linearity. Model 1 linear least squares regressions were calculated and applied to sensor data during validation experiments to simulate dilution of an oil plume. Dynamic ranges of the sensors, exposed to fresh and artificially weathered crude oil, were determined. Sensors were standardized against known oil volumes and measured Total Petroleum Hydrocarbons (TPH) and Benzene-Toluene-Ethylbenzene-Xylene (BTEX) values – both collected during spills, providing oil estimates during dilution experiments. Results were validated against particle size data (Sequoia LISST). All sensors estimated oil concentrations down to 300 ppb oil, refuting previous reports. Low percent differences and absolute errors between chemistry and sensor results were metrics to evaluate performance. Discussed will be the application of this vicarious calibration approach as a means to calibrate the DWH fine-scale fluorescence data into oil concentrations. This allows for filling in coarse-scale field chemistry data, improved assessment of DWH spill measurements mined from the NOAA NODC, and understanding the fate and transport of the DWH oil plume.