Five decades of terrestrial and freshwater research at Ny-Ålesund, Svalbard

For more than five decades, research has been conducted at Ny-Alesund, in Svalbard, Norway, to understand the structure and functioning of High Arctic ecosystems and the profound impacts on them of environmental change. Terrestrial, freshwater, glacial and marine ecosystems are accessible year-round from Ny-Alesund, providing unique opportunities for interdisciplinary observational and experimental studies along physical, chemical, hydrological and climatic gradients. Here, we synthesize terrestrial and freshwater research at Ny-Alesund and review current knowledge of biodiversity patterns, species population dynamics and interactions, ecosystem processes, biogeochemical cycles and anthropogenic impacts. There is now strong evidence of past and ongoing biotic changes caused by climate change, including negative effects on populations of many taxa and impacts of rain-on-snow events across multiple trophic levels. While species-level characteristics and responses are well understood for macro-organisms, major knowledge gaps exist for microbes, invertebrates and ecosystem-level processes. In order to fill current knowledge gaps, we recommend (1) maintaining monitoring efforts, while establishing a longterm ecosystem-based monitoring programme; (2) gaining a mechanistic understanding of environmental change impacts on processes and linkages in food webs; (3) identifying trophic interactions and cascades across ecosystems; and (4) integrating long-term data on microbial, invertebrate and freshwater communities, along with measurements of carbon and nutrient fluxes among soils, atmosphere, freshwaters and the marine environment. The synthesis here shows that the Ny-Alesund study system has the characteristics needed to fill these gaps in knowledge, thereby enhancing our understanding of High-Arctic ecosystems and their responses to environmental variability and change

Five decades of terrestrial and freshwater research at Ny-Ålesund, Svalbard

For more than five decades, research has been conducted at Ny-Ålesund, in Svalbard, Norway, to understand the structure and functioning of High-Arctic ecosystems and the profound impacts on them of environmental change. Terrestrial, freshwater, glacial and marine ecosystems are accessible year-round from Ny-Ålesund, providing unique opportunities for interdisciplinary observational and experimental studies along physical, chemical, hydrological and climatic gradients. Here, we synthesize terrestrial and freshwater research at Ny-Ålesund and review current knowledge of biodiversity patterns, species population dynamics and interactions, ecosystem processes, biogeochemical cycles and anthropogenic impacts. There is now strong evidence of past and ongoing biotic changes caused by climate change, including negative effects on populations of many taxa and impacts of rain-on-snow events across multiple trophic levels. While species-level characteristics and responses are well understood for macro-organisms, major knowledge gaps exist for microbes, invertebrates and ecosystem-level processes. In order to fill current knowledge gaps, we recommend (1) maintaining monitoring efforts, while establishing a long-term ecosystem-based monitoring programme; (2) gaining a mechanistic understanding of environmental change impacts on processes and linkages in food webs; (3) identifying trophic interactions and cascades across ecosystems; and (4) integrating long-term data on microbial, invertebrate and freshwater communities, along with measurements of carbon and nutrient fluxes among soils, atmosphere, freshwaters and the marine environment. The synthesis here shows that the Ny-Ålesund study system has the characteristics needed to fill these gaps in knowledge, thereby enhancing our understanding of High-Arctic ecosystems and their responses to environmental variability and change

Five decades of terrestrial and freshwater research at Ny-Ålesund, Svalbard

For more than five decades, research has been conducted at Ny-Ålesund, in Svalbard, Norway, to understand the structure and functioning of High-Arctic ecosystems and the profound impacts on them of environmental change. Terrestrial, freshwater, glacial and marine ecosystems are accessible year-round from Ny-Ålesund, providing unique opportunities for interdisciplinary observational and experimental studies along physical, chemical, hydrological and climatic gradients. Here, we synthesize terrestrial and freshwater research at Ny-Ålesund and review current knowledge of biodiversity patterns, species population dynamics and interactions, ecosystem processes, biogeochemical cycles and anthropogenic impacts. There is now strong evidence of past and ongoing biotic changes caused by climate change, including negative effects on populations of many taxa and impacts of rain-on-snow events across multiple trophic levels. While species-level characteristics and responses are well understood for macro-organisms, major knowledge gaps exist for microbes, invertebrates and ecosystem-level processes. In order to fill current knowledge gaps, we recommend (1) maintaining monitoring efforts, while establishing a long-term ecosystem-based monitoring programme; (2) gaining a mechanistic understanding of environmental change impacts on processes and linkages in food webs; (3) identifying trophic interactions and cascades across ecosystems; and (4) integrating long-term data on microbial, invertebrate and freshwater communities, along with measurements of carbon and nutrient fluxes among soils, atmosphere, freshwaters and the marine environment. The synthesis here shows that the Ny-Ålesund study system has the characteristics needed to fill these gaps in knowledge, thereby enhancing our understanding of High-Arctic ecosystems and their responses to environmental variability and change

Carbon stock and geological development of a peatland in Karlshaugen nature reserve

Carbon stocks of peatlands is of growing interest due to the ability to store large amounts of carbon. To provide data of this subject this master thesis presents results from a study of a peatland within a forest nature reserve outside of Oslo, Norway. First, peat volume was estimated using a combination of ground penetrating radar survey and GIS tools (EkkoPulse software, ArcMap and Excel). Second, sediment cores retrieved from the peat were analysed in the laboratory to analyse the bulk density and carbon content of the organic material and to calculate the carbon stock of the peatland. The data were also used to explain how this peatland has developed. The volume of the total peatland analysed by the ground penetrating radar was calculated to be 6487 m3. Degree of decomposition, described by the von Post scale, shows similar trends for all four cores; it is low in the shallow peat and increases with depth where they stabilize at level 6-8. Using Loss On Ignition as total amount of organic material gave values well above 90%, except for the samples that visibly contain minerogenic material. These results were consistent with results from total carbon analysis using LECO Truspec instrument finding total carbon content of peat core MM1to be 47-55%. The total carbon content of the remaining three cores were determined by regression analysis to be 50-53% in core MM2, 5154% in core MM3 and 52-54% in core MM4. Carbon stocks in MM1 range from 2 kgC/m2 to 7 kgC/m2. The total amount of carbon stored in this peatland is calculated to be 278 ton. For the top meter the carbon stock is 41.1 kg/m2. The hypothesis for the formation of this peatland being a depression in bedrock filled with water to form a pond, later filled with sediments and organic material was supported by the shape of the peat basin illustrated in the GPR survey, and the fine minerogenic material in the bottom part of peat core MM1. Further field observations support peatland boundary is changing, and it can be predicted that the rise in temperature and changes in precipitation might cause degradation of organic material in the peatland. This process may be part of a positive feedback loop with climate change.Karbonlager i myr er av økende interesse grunnet deres evne til å lagre store mengder karbon. For å belyse dette temaet presenterer denne oppgaven resultater fra en studie av en myr i Karlshaugen naturreservat i Nordmarka, Oslo. Volum av myra ble kartlagt ved en kombinasjon av georadar og GIS-verktøy (EkkoPuls-programvare, ArcMap og Excel). Videre ble fire sediment kjerner hentet opp fra myra, og analysert for tetthet og karboninnhold. Dette er brukt til å estimere mengde karbon lagret i myra. Basert på data fra undersøkelsen er det også utformet en forklaring på hvordan denne myra er dannet og har utviklet seg. Volumet av den delen av myra som er kartlagt med georadar er estimert til 6487 m3. Grad av nedbrytning i materialet, beskrevet ved hjelp an von Post skalaen, viser lignende utvikling i de fire kjernene. I det grunne myrmaterialet er det en lav grad av nedbrytning, mens den øker i dybden, og stabiliserer seg på nivå 6-8. Ved bruk av glødetap er mengde organisk materiale i prøvene bestemt, dette ga resultater på godt over 90%, bortsett fra de prøvene som inneholdt mineralsk materiale. Disse resultatene samsvarer med analysene for karbon innhold gjennomført ved bruk av LECO Truspec instrument. Disse viser karboninnhold på 47-55% for kjerne MM1. Karbon innholdet i de resterende kjernene er bestemt med en regresjonsanalyse, som ga resultater på 50-53% for kjerne MM2, 51-54% for kjerne MM3 og 52-54% for kjerne MM4. Karbonlager utregninger for kjerne MM1 variere fra 2 kgC/m2 til 7kgC/m2. Den totale mengden karbon lagret i denne myra er estimert til 278 tonn. For den øverste meteren i myra er karbonlageret beregnet til 41.1 kg/m2. Hypotesen for hvordan denne myra er dannet går ut på at en nedsenkning i grunnfjellet ble fylt med vann og dannet et tjern, som senere ble fylt med sedimenter og organisk materiale. Denne hypotesen er støttet av formen på myrbassenget som er godt illustrert i georadar undersøkelsen, og funn av mineral materiale i bunnen av den dypeste myrkjernen. Videre så støtter feltobservasjoner tidligere resultater om at denne myra er i endring, det kan antas at økning i temperatur og ening i nedbør kan føre til nedbrytning at organisk materiale og utslipp av karbon. Denne prosessen kan være en del av en positiv tilbakekoblingsmekanisme med globale klimaendringer.M-MIN

Safety barriers to prevent release of hydrocarbons during production of oil and gas

This report documents a set of scenarios related to release of hydrocarbons during production on oil and gas platforms. For each release scenario, initiating events, barrier functions aimed to prevent loss of containment, and barrier systems that realize these barrier functions are identified and described.Safety barriers to prevent release of hydrocarbons during production of oil and ga

Safety Barriers on Oil and Gas Platforms. Means to Prevent Hydrocarbon Releases

The main objective of the PhD project has been to develop concepts and methods that can be used to define, illustrate, analyse, and improve safety barriers in the operational phase of offshore oil and gas production platforms. The main contributions of this thesis are; Clarification of the term safety barrier with respect to definitions, classification, and relevant attributes for analysis of barrier performance Development and discussion of a representative set of hydrocarbon release scenarios Development and testing of a new method, BORA-Release, for qualitative and quantitative risk analysis of hydrocarbon releases Safety barriers are defined as physical and/or non-physical means planned to prevent, control, or mitigate undesired events or accidents. The means may range from a single technical unit or human actions, to a complex socio-technical system. It is useful to distinguish between barrier functions and barrier systems. Barrier functions describe the purpose of safety barriers or what the safety barriers shall do in order to prevent, control, or mitigate undesired events or accidents. Barrier systems describe how a barrier function is realized or executed. If the barrier system is functioning, the barrier function is performed. If a barrier function is performed successfully, it should have a direct and significant effect on the occurrence and/or consequences of an undesired event or accident. It is recommended to address the following attributes to characterize the performance of safety barriers; a) functionality/effectiveness, b) reliability/availability, c) response time, d) robustness, and e) triggering event or condition. For some types of barriers, not all the attributes are relevant or necessary in order to describe the barrier performance. The presented hydrocarbon release scenarios include initiating events, barrier functions introduced to prevent hydrocarbon releases, and barrier systems realizing the barrier functions. Both technical and human/operational safety barriers are considered. The initiating events are divided into five main categories; (1) human and operational errors, (2) technical failures, (3) process upsets, (4) external events, and (5) latent failures from design. The development of the hydrocarbon release scenarios has generated new knowledge about causal factors of hydrocarbon releases and safety barriers introduced to prevent the releases. Collectively, the release scenarios cover the most frequent initiating events and the most important safety barriers introduced to prevent hydrocarbon releases. BORA-Release is a new method for qualitative and quantitative risk analysis of the hydrocarbon release frequency on oil and gas platforms. BORA-Release combines use of barrier block diagrams/event trees, fault trees, and risk influence diagrams in order to analyse the risk of hydrocarbon release from a set of hydrocarbon release scenarios. Use of BORA-Release makes it possible to analyse the effect on the hydrocarbon release frequency of safety barriers introduced to prevent hydrocarbon releases. Further, BORA-Release may be used to analyse the effect on the barrier performance of platform specific conditions of technical, human, operational, and organisational risk influencing factors. Thus, BORA-Release may improve today’s quantitative risk analyses on two weak points; i) analysis of causal factors of the initiating event hydrocarbon release (loss of containment), and ii) analysis of the effect on the risk of human and organisational factors. The main focus of this thesis is safety barriers introduced to prevent hydrocarbon releases on offshore oil and gas production platforms. Thus, the results are primarily useful for the oil and gas industry in their effort to control and reduce the risk of hydrocarbon releases. The Norwegian oil and gas industry can use the results in their work to fulfil the requirements to safety barriers and risk analyses from the Petroleum Safety Authority. However, the concepts and methods may also be applied in other industries (e.g., the process industry) and application areas (e.g., the transport sector) in their effort to reduce the risk.Paper I, II and V are reprodused with kind permission of Elsevier sciencedirect.co

Exploring the capabilities of machine learning (ML) for 1D blood flow: Application to coronary flow

The aim of this thesis is to explore the capabilities of deep neural networks to reproduce 1D computational models for the pressure in a coronary tree. A machine learning algorithm was implemented. The algorithm was trained with a synthetically generated database of coronary trees, where the anatomical data was retrieved from published literature. A grid search was performed to optimize the hyper-parameters in the machine learning model. Two different models were trained to solve a steady state; coronary blood flow model and Young and Tsai's stenosis model. Correlation between the predicted values was excellent for both models with $r^2= 1$ for the steady state coronary blood flow model, and $r^2=0.997$ for Young and Tsai's stenosis model. The established ML models were tested with patient specific data. The prediction on the patient specific data showed that the synthetically generated database did not represent the pathological variation of coronary arteries. For a reduced patient specific database, the model predicted the pressure drop along the healthy vessels with a coefficient of determination of 0.799 and for the reduced database with the patient specific stenoses the coefficient of determination was 0.997