Studies on coliform bacteria discharged from the Hyperion outfall : final bacteriological report /

Mode of access: Internet.

A coliform bacteria survey of Monterey Bay off Del Monte Beach /

Mode of access: Internet.

Modelling of saline intrusion in marine outfalls

Since their introduction in the 1950s, marine outfalls with diffusers have been prone to saline intrusion, a process in which seawater ingresses into the outfall. This can greatly reduce the dilution and subsequent dispersion of wastewater discharged, sometimes resulting in serious deterioration of coastal water quality. Although long aware of the difficulties posed by saline intrusion, engineers still lack satisfactory methods for its prediction and robust design methods for its alleviation. However, with recent developments in numerical methods and computer power, it has been suggested that commercially available computational fluid dynamics (CFD) software may be a useful aid in combating this phenomenon by improving understanding through synthesising likely behaviour. This document reviews current knowledge on saline intrusion and its implications and then outlines a model-scale investigation of the process undertaken at Queen's University Belfast, using both physical and CFD methods. Results are presented for a simple outfall configuration, incorporating several outlets. The features observed agree with general observations from full-scale marine outfalls, and quantify the intricate internal flow mechanisms associated with saline intrusion. The two-dimensional numerical model was found to represent saline intrusion, but in a qualitative manner, not yet adequate for design purposes. Specific areas requiring further development were identified. The ultimate aim is to provide a reliable, practical and cost effective means by which engineers can minimise saline intrusion through optimised outfall design.

Geostatistical Prediction of Ocean Outfall Plume Characteristics Based on an Autonomous Underwater Vehicle

Geostatistics has been successfully used to analyze and characterize the spatial variability of environmental properties. Besides giving estimated values at unsampled locations, it provides a measure of the accuracy of the estimate, which is a significant advantage over traditional methods used to assess pollution. In this work universal block kriging is novelty used to model and map the spatial distribution of salinity measurements gathered by an Autonomous Underwater Vehicle in a sea outfall monitoring campaign, with the aim of distinguishing the effluent plume from the receiving waters, characterizing its spatial variability in the vicinity of the discharge and estimating dilution. The results demonstrate that geostatistical methodology can provide good estimates of the dispersion of effluents that are very valuable in assessing the environmental impact and managing sea outfalls. Moreover, since accurate measurements of the plume’s dilution are rare, these studies might be very helpful in the future to validate dispersion models.

The environmental impact of sewage and wastewater outfalls in Antarctica: an example from Davis station, East Antarctica

We present a comprehensive scientific assessment of the environmental impacts of an Antarctic wastewater ocean outfall, at Davis station in East Antarctica. We assessed the effectiveness of current wastewater treatment and disposal requirements under the Protocol on Environmental Protection to the Antarctic Treaty. Macerated wastewater has been discharged from an outfall at Davis since the failure of the secondary treatment plant in 2005. Water, sediment and wildlife were tested for presence of human enteric bacteria and antibiotic resistance mechanisms. Epibiotic and sediment macrofaunal communities were tested for differences between sites near the outfall and controls. Local fish were examined for evidence of histopathological abnormalities. Sediments, fish and gastropods were tested for uptake of sewage as measured by stable isotopes of N and C. Escherichia coli carrying antibiotic resistance determinants were found in water, sediments and wildlife (the filter feeding bivalve Laternula eliptica). Fish (Trematomus bernacchii) within close proximity to the outfall had significantly more severe and greater occurrences of histopathological abnormalities than at controls, consistent with exposure to sewage. There was significant enrichment of (15)N in T. bernacchii and the predatory gastropod Neobuccinum eatoni around the outfall, providing evidence of uptake of sewage. There were significant differences between epibiotic and sediment macrofaunal communities at control and outfall sites (<1.5 km), when sites were separated into groups of similar habitat types. Benthic community composition was also strongly related to habitat and environmental drivers such as sea ice. The combined evidence indicated that the discharge of wastewater from the Davis outfall is causing environmental impacts. These findings suggest that conditions in Antarctic coastal locations, such as Davis, are unlikely to be conducive to initial dilution and rapid dispersal of wastewater as required under the Protocol on Environmental Protection to the Antarctic Treaty. Current minimum requirements for wastewater treatment and disposal in Antarctica are insufficient to ameliorate these risks and are likely to lead to accumulation of contaminants and introduction of non-native microbes and associated genetic elements. This new understanding suggests that modernised approaches to the treatment and disposal of wastewater are required in Antarctica. The most effective solution is advanced levels of wastewater treatment, which are now possible, feasible and a high priority for installation. As a direct outcome of the study, a new advanced treatment system is being installed at Davis, effectively avoiding environmental risks.

Volcanic sulphate and Arctic dust plumes over the North Atlantic Ocean

High time resolution aerosol mass spectrometry measurements were conducted during a field campaign at Mace Head Research Station, Ireland, in June 2007. Observations on one particular day of the campaign clearly indicated advection of aerosol from volcanoes and desert plains in Iceland which could be traced with NOAA Hysplit air mass back trajectories and satellite images. In conjunction with this event, elevated levels of sulphate and light absorbing particles were encountered at Mace Head. While sulphate concentration was continuously increasing, nitrate levels remained low indicating no significant contribution from anthropogenic pollutants. Sulphate concentration increased about 3.8 g/m3 in comparison with the background conditions. Corresponding sulphur flux from volcanic emissions was estimated to about 0.3 TgS/yr, suggesting that a large amount of sulphur released from Icelandic volcanoes may be distributed over distances larger than 1000 km. Overall, our results corroborate that transport of volcanogenic sulphate and dust particles can significantly change the chemical composition, size distribution, and optical properties of aerosol over the North Atlantic Ocean and should be considered accordingly by regional climate models.

Persistent ocean monitoring with underwater gliders : towards accurate reconstruction of dynamic ocean processes

Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.

Planning and implementing trajectories for autonomous underwater vehicles to track evolving ocean processes based on predictions from a regional ocean model

Path planning and trajectory design for autonomous underwater vehicles (AUVs) is of great importance to the oceanographic research community because automated data collection is becoming more prevalent. Intelligent planning is required to maneuver a vehicle to high-valued locations to perform data collection. In this paper, we present algorithms that determine paths for AUVs to track evolving features of interest in the ocean by considering the output of predictive ocean models. While traversing the computed path, the vehicle provides near-real-time, in situ measurements back to the model, with the intent to increase the skill of future predictions in the local region. The results presented here extend prelim- inary developments of the path planning portion of an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. This extension is the incorporation of multiple vehicles to track the centroid and the boundary of the extent of a feature of interest. Similar algorithms to those presented here are under development to consider additional locations for multiple types of features. The primary focus here is on algorithm development utilizing model predictions to assist in solving the motion planning problem of steering an AUV to high-valued locations, with respect to the data desired. We discuss the design technique to generate the paths, present simulation results and provide experimental data from field deployments for tracking dynamic features by use of an AUV in the Southern California coastal ocean.

Towards improvement of autonomous glider navigation accuracy through the use of regional ocean models

Autonomous underwater gliders are robust and widely-used ocean sampling platforms that are characterized by their endurance, and are one of the best approaches to gather subsurface data at the appropriate spatial resolution to advance our knowledge of the ocean environment. Gliders generally do not employ sophisticated sensors for underwater localization, but instead dead-reckon between set waypoints. Thus, these vehicles are subject to large positional errors between prescribed and actual surfacing locations. Here, we investigate the implementation of a large-scale, regional ocean model into the trajectory design for autonomous gliders to improve their navigational accuracy. We compute the dead-reckoning error for our Slocum gliders, and compare this to the average positional error recorded from multiple deployments conducted over the past year. We then compare trajectory plans computed on-board the vehicle during recent deployments to our prediction-based trajectory plans for 140 surfacing occurrences.

Cooperative multi-AUV tracking of phytoplankton blooms based on ocean model predictions

In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor plat- forms. Currently, most AUV deployments execute a lawnmower- type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.

Autonomous underwater vehicle trajectory design coupled with predictive ocean models : a case study

Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

Trajectory design for autonomous underwater vehicles based on ocean model predictions for feature tracking

Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.