Integrated environmental monitoring and multivariate data analysis-A case study.

The present article describes integration of environmental monitoring and discharge data and interpretation using multivariate statistics, principal component analysis (PCA), and partial least squares (PLS) regression. The monitoring was carried out at the Peregrino oil field off the coast of Brazil. One sensor platform and 3 sediment traps were placed on the seabed. The sensors measured current speed and direction, turbidity, temperature, and conductivity. The sediment trap samples were used to determine suspended particulate matter that was characterized with respect to a number of chemical parameters (26 alkanes, 16 PAHs, N, C, calcium carbonate, and Ba). Data on discharges of drill cuttings and water-based drilling fluid were provided on a daily basis. The monitoring was carried out during 7 campaigns from June 2010 to October 2012, each lasting 2 to 3 months due to the capacity of the sediment traps. The data from the campaigns were preprocessed, combined, and interpreted using multivariate statistics. No systematic difference could be observed between campaigns or traps despite the fact that the first campaign was carried out before drilling, and 1 of 3 sediment traps was located in an area not expected to be influenced by the discharges. There was a strong covariation between suspended particulate matter and total N and organic C suggesting that the majority of the sediment samples had a natural and biogenic origin. Furthermore, the multivariate regression showed no correlation between discharges of drill cuttings and sediment trap or turbidity data taking current speed and direction into consideration. Because of this lack of correlation with discharges from the drilling location, a more detailed evaluation of chemical indicators providing information about origin was carried out in addition to numerical modeling of dispersion and deposition. The chemical indicators and the modeling of dispersion and deposition support the conclusions from the multivariate statistics. Integr Environ Assess Manag 2017;13:387-395. © 2016 SETAC.

Assessing the potential impact of water-based drill cuttings on deep-water calcareous red algae using species specific impact categories and measured oceanographic and discharge data.

The potential impact of drill cuttings on the two deep water calcareous red algae Mesophyllum engelhartii and Lithothamnion sp. from the Peregrino oil field was assessed. Dispersion modelling of drill cuttings was performed for a two year period using measured oceanographic and discharge data with 24 h resolution. The model was also used to assess the impact on the two algae species using four species specific impact categories: No, minor, medium and severe impact. The corresponding intervals for photosynthetic efficiency (ΦPSIImax) and sediment coverage were obtained from exposure-response relationship for photosynthetic efficiency as function of sediment coverage for the two algae species. The temporal resolution enabled more accurate model predictions as short-term changes in discharges and environmental conditions could be detected. The assessment shows that there is a patchy risk for severe impact on the calcareous algae stretching across the transitional zone and into the calcareous algae bed at Peregrino.

The effect of sediment mimicking drill cuttings on deep water rhodoliths in a flow-through system: Experimental work and modeling.

The impact of sediment coverage on two rhodolith-forming calcareous algae species collected at 100m water depth off the coast of Brazil was studied in an experimental flow-through system. Natural sediment mimicking drill cuttings with respect to size distribution was used. Sediment coverage and photosynthetic efficiency (maximum quantum yield of charge separation in photosystem II, ϕPSIImax) were measured as functions of light intensity, flow rate and added amount of sediment once a week for nine weeks. Statistical experimental design and multivariate data analysis provided statistically significant regression models which subsequently were used to establish exposure-response relationship for photosynthetic efficiency as function of sediment coverage. For example, at 70% sediment coverage the photosynthetic efficiency was reduced 50% after 1-2weeks of exposure, most likely due to reduced gas exchange. The exposure-response relationship can be used to establish threshold levels and impact categories for environmental monitoring.

Achievements of risk-based produced water management on the Norwegian continental shelf (2002-2008).

In 1996, the Norwegian government issued a White Paper requiring the Norwegian oil industry to reach the goal of "zero discharge" for the marine environment by 2005. To achieve this goal, the Norwegian oil and gas industry initiated the Zero Discharge Programme for discharges of produced formation water from the hydrocarbon-containing reservoir, in close communication with regulators. The environmental impact factor (EIF), a risk-based management tool, was developed by the industry to quantify and document the environmental risks from produced water discharges. The EIF represents a volume of recipient water containing concentrations of one or more substances to a level exceeding a generic threshold for ecotoxicological effects. In addition, this tool facilitates the identification and selection of cost-effective risk mitigation measures. The EIF tool has been used by all operators on the Norwegian continental shelf since 2002 to report progress toward the goal of "zero discharge," interpreted as "zero harmful discharges," to the regulators. Even though produced water volumes have increased by approximately 30% between 2002 and 2008 on the Norwegian continental shelf, the total environmental risk from produced water discharges expressed by the summed EIF for all installations has been reduced by approximately 55%. The total amount of oil discharged to the sea has been reduced by 18% over the period 2000 to 2006. The experience from the Zero Discharge Programme shows that a risk-based approach is an excellent working tool to reduce discharges of potential harmful substances from offshore oil and gas installations.

Development of a risk-based environmental management tool for drilling discharges. Summary of a four-year project.

This paper briefly summarizes the ERMS project and presents the developed model by showing results from environmental fates and risk calculations of a discharge from offshore drilling operations. The developed model calculates environmental risks for the water column and sediments resulting from exposure to toxic stressors (e.g., chemicals) and nontoxic stressors (e.g., suspended particles, sediment burial). The approach is based on existing risk assessment techniques described in the European Union technical guidance document on risk assessment and species sensitivity distributions. The model calculates an environmental impact factor, which characterizes the overall potential impact on the marine environment in terms of potentially impacted water volume and sediment area. The ERMS project started in 2003 and was finalized in 2007. In total, 28 scientific reports and 9 scientific papers have been delivered from the ERMS project (http://www.sintef.no/erms).

Water column monitoring near oil installations in the North Sea 2001-2004.

Fisheries have been vital to coastal communities around the North Sea for centuries, but this semi-enclosed sea also receives large amounts of waste. It is therefore important to monitor and control inputs of contaminants into the North Sea. Inputs of effluents from offshore oil and gas production platforms (produced water) in the Norwegian sector have been monitored through an integrated chemical and biological effects programme since 2001. The programme has used caged Atlantic cod and blue mussels. PAH tissue residues in blue mussels and PAH bile metabolites in cod have confirmed exposure to effluents, but there was variation between years. Results for a range of biological effects methods reflected exposure gradients and indicated that exposure levels were low and caused minor environmental impact at the deployment locations. There is a need to develop methods that are sufficiently sensitive to components in produced water at levels found in marine ecosystems.

Oil well produced water discharges to the North Sea. Part I: comparison of deployed mussels (Mytilus edulis), semi-permeable membrane devices, and the DREAM model predictions to estimate the dispersion of polycyclic aromatic hydrocarbons.

The oil companies operating in the Norwegian sector of the North Sea have conducted field studies since the mid-1990s to monitor produced water discharges to the ocean. These studies have been used to refine monitoring methods, and to develop and validate a dispersion and impact assessment model. This paper summarizes monitoring data from surveys conducted in two major oil and gas production areas, and compares the results to concentrations of polycyclic aromatic hydrocarbons (PAH) in surface waters predicted by the dose-related risk and effect assessment model (DREAM). Blue mussels and semi-permeable membrane devices (SPMDs) were deployed in the Ekofisk and Tampen Regions and analyzed for more than 50 PAH. PAH concentrations in ambient seawater were estimated based on the mussels and SPMD concentrations, and compared to model predictions. Surface water total PAH concentrations ranged from 25 to 350 ng/L within 1 km of the platform discharges and reached background levels of 4-8 ng/L within 5-10 km of the discharge; a 100,000-fold dilution of the PAH in the discharge water. The PAH concentrations in surface water, predicted by three methods, compared well for the Ekofisk Region. The model predicted higher concentrations than the field-based methods for parts of the Tampen Region; particularly the most tidally influenced areas. Tidally-mediated fluctuations in PAH concentrations in surface water must be considered because they affect the estimation of PAH concentrations from mussel and SPMD residue data, and the predictions by the DREAM model. Predictions using mussels, SPMDs, and modeling support and complement each other; all are valuable tools for estimating the fate and impact of chemical contaminants in produced water that are discharged to the ocean.

Oil well produced water discharges to the North Sea. Part II: comparison of deployed mussels (Mytilus edulis) and the DREAM model to predict ecological risk.

Large volumes of water often are produced with oil and gas from offshore platforms. The produced water is separated from the oil and gas and either reinjected into a deep formation or discharged to the ocean. The Norwegian oil and gas industry advocates ecological risk assessment as the basis for managing produced water discharges to the North Sea. In this paper, we compare estimates of ecological risks to water-column communities based on data on hydrocarbon residues in soft tissues of blue mussels deployed for a month near offshore platforms and based on predictions of the Dose related Risk and Effect Assessment Model (DREAM). The study was performed near produced water discharges to the Tampen and Ekofisk Regions of the Norwegian Sector of the North Sea. Because polycyclic aromatic hydrocarbons (PAH) are considered the most important contributors to the ecological hazard posed by produced water discharges, comparisons made here focus on this group of compounds. The mussel approach is based on predicted environmental concentrations (PECs) of individual PAH, estimated from PAH residues in mussels following deployment for a month near several produced water discharges, and predicted no effects concentrations (PNECs) based on a K(ow) regression model. In the DREAM method, PECs for three PAH fractions are estimated in the three-dimensional area around produced water discharge with the DREAM model. PNECs for each fraction are based on the chronic toxicity of a representative PAH from each fraction divided by an assessment factor to account for uncertainty in the chronic value. The mussel method gives much lower estimates of ecological risk than the DREAM method. The differences are caused by the much lower PNECs used in DREAM than derived from the regression model, and by the lower concentrations of aqueous PAH predicted by DREAM than estimated from PAH residues in mussel tissues. However, the two methods rank stations at different distances from produced water discharges in the same order and both identify 2- and 3-ring PAHs as the main contributors to the ecological risk of produced water discharges. Neither method identifies a significant ecological risk of PAH in the upper water column of the oil fields. The DREAM model may produce an overly conservative estimate of ecological risk of produced water discharges to the North Sea.