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Monitoring the marine environment for leaks from geological storage projects is a challenge due to the variability of the environment and the extent of the area that migrating CO2 might seep through the seafloor. Due to the environmental risk associated leaks should not be allowed to continue undetected. There is also a cost issue since marine operations are expensive, so false alarms should be avoided. The main question is then: how large a deviation in the monitoring data should cause mobilization of confirmation and localization procedures? Here Baye's theorem and Bayesian decision theory is suggested as a tool for quantifying certainties and to implement costs for false positives (false alarms) and false negatives (undetected leaks) in the decision procedure. The procedure is exemplified using modeled natural CO2 content variability and the predicted CO2 signal from a simulated leak. [ABSTRACT FROM AUTHOR]

We produced 204 monthly maps of the air–sea CO 2 flux in the Arctic north of 60°N, including the Arctic Ocean and its adjacent seas, from January 1997 to December 2013 by using a self-organizing map technique. The partial pressure of CO 2 ( p CO 2 ) in surface water data were obtained by shipboard underway measurements or calculated from alkalinity and total inorganic carbon of surface water samples. Subsequently, we investigated the basin-wide distribution and seasonal to interannual variability of the CO 2 fluxes. The 17-year annual mean CO 2 flux shows that all areas of the Arctic Ocean and its adjacent seas were net CO 2 sinks. The estimated annual CO 2 uptake by the Arctic Ocean was 180 TgC yr −1 . The CO 2 influx was strongest in winter in the Greenland/Norwegian Seas (>15 mmol m −2 day −1 ) and the Barents Sea (>12 mmol m −2 day −1 ) because of strong winds, and strongest in summer in the Chukchi Sea (∼10 mmol m −2 day −1 ) because of the sea-ice retreat. In recent years, the CO 2 uptake has increased in the Greenland/Norwegian Sea and decreased in the southern Barents Sea, owing to increased and decreased air–sea p CO 2 differences, respectively. [ABSTRACT FROM AUTHOR]

Annular pancreas is an uncommon congenital abnormality characterized by a ring of pancreatic tissue around the duodenum descending part. It is exceptionally rare in adults and is increasingly detected after the investigation of symptoms caused by its consequences, which include recurrent pancreatitis, duodenal stenosis at the site of the annulus, or duodenal or gastric ulcers. In this study, we present a case report of symptomatic annular pancreas in an adult patient. A 23-year-old woman hospitalized for epigastric pain and recurrent vomiting. Radiological examination was consistent with an annular pancreas. At operation, a partial obstruction of the second part of the duodenum was found, caused by an annular pancreas. No other congenital anomaly of the intra-abdominal organs was noted. A gastrojejunostomy was performed and she was discharged after 8 days with good recovery. Because annular pancreas in adults is a rare clinical scenario, it should be included in the differential diagnosis of adult patients with gastrointestinal obstructive symptoms for a prolonged period of time, given that surgical intervention has a reliable outcome. • Annular pancreas in adults is a rare condition. • Symptomatic patients will develop symptoms of proximal bowel obstruction. • A CT scan can confirm the diagnosis after a gastroduodenoscopy. • Symptomatic patients need to actively pursue surgical intervention. [ABSTRACT FROM AUTHOR]

• Approaches for CO 2 leakage detection, attribution and quantification monitoring exist. • Many approaches cover multiple monitoring tasks simultaneously. • Sonars and chemical sensors on ships or AUVs can cover large areas. • Newer, more specific technologies can detect, verify and quantify smaller, localised leaks. Environmental monitoring of offshore Carbon Capture and Storage (CCS) complexes requires robust methodologies and cost-effective tools to detect, attribute and quantify CO 2 leakage in the unlikely event it occurs from a sub-seafloor reservoir. Various approaches can be utilised for environmental CCS monitoring, but their capabilities are often undemonstrated and more detailed monitoring strategies need to be developed. We tested and compared different approaches in an offshore setting using a CO 2 release experiment conducted at 120 m water depth in the Central North Sea. Tests were carried out over a range of CO 2 injection rates (6 - 143 kg d−1) comparable to emission rates observed from abandoned wells. Here, we discuss the benefits and challenges of the tested approaches and compare their relative cost, temporal and spatial resolution, technology readiness level and sensitivity to leakage. The individual approaches demonstrate a high level of sensitivity and certainty and cover a wide range of operational requirements. Additionally, we refer to a set of generic requirements for site-specific baseline surveys that will aid in the interpretation of the results. Critically, we show that the capability of most techniques to detect and quantify leakage exceeds the currently existing legal requirements. [ABSTRACT FROM AUTHOR]

• A novel stoichiometric approach called the Cseep method was developed and used to. • Predict natural DIC variations around the Goldeneye site in the north-western North Sea. • Establish a process-based baseline DIC concentration (Cb) with minimal variability. • Determine CO2 seepage detection threshold (DT) to reliably differentiate subsea released−CO 2 signal from natural variability. • Quantify DIC concentration of subsea released−CO 2 dissolved in the sampled seawater. Carbon Capture and Storage (CCS) is a potential significant mitigation strategy to combat climate change and ocean acidification. The technology is well understood but its current implementation must be scaled up nearly by a hundredfold to become an effective tool that helps meet mitigation targets. Regulations require monitoring and verification at storage sites, and reliable monitoring strategies for detection and quantification of seepage of the stored carbon need to be developed. The C seep method was developed for reliable determination of CO 2 seepage signal in seawater by estimating and filtering out natural variations in dissolved inorganic carbon (C). In this work, we analysed data from the first-ever subsea CO 2 release experiment performed in the north-western North Sea by the EU STEMM−CCS project. We successfully demonstrated the ability of the C seep method to (i) predict natural C variations around the Goldeneye site over seasonal to interannual time scales; (ii) establish a process-based baseline C concentration with minimal variability; (iii) determine CO 2 seepage detection threshold (DT) to reliably differentiate released−CO 2 signal from natural variability and quantify released−CO 2 dissolved in the sampled seawater. DT values were around 20 % of the natural C variations indicating high sensitivity of the method. Moreover, with the availability of DT value, the identification of released−CO 2 required no pre-knowledge of seepage occurrence, but we used additional available information to assess the confidence of the results. Overall, the C seep method features high sensitivity, automation suitability, and represents a powerful future monitoring tool both for large and confined marine areas. [ABSTRACT FROM AUTHOR]

• The classical set cover problem was used to optimize chemical sensors layout on the seafloor. • Multiple leak scenarios were simulated using an advection–diffusion equation with the currents data obtained from GCM. • The anomaly threshold was calculated using the C-seep method. • Different costs were incorporated in the monitoring design and the results were compared. Assurance monitoring of the marine environment is a required and intrinsic part of CO 2 storage project. To reduce the costs related to the monitoring effort, the monitoring program must be designed with optimal use of instrumentation. Here we use solution of a classical set cover problem to design placement of an array of fixed chemical sensors with the purpose of detecting a seep of CO 2 through the seafloor from an unknown location. The solution of the problem is not unique and different aspects, such as cost or existing infrastructure, can be added to define an optimal solution. We formulate an optimization problem and propose a method to generate footprints of potential seeps using an advection–diffusion model and a stoichiometric method for detection of small seepage CO 2 signals. We provide some numerical experiments to illustrate the concepts. [ABSTRACT FROM AUTHOR]