WaterMet2: a tool for integrated analysis of sustainability-based performance of urban water systems

This paper presents the "WaterMet2" model for long-term assessment of urban water system (UWS) performance which will be used for strategic planning of the integrated UWS. WaterMet2 quantifies the principal water-related flows and other metabolism-based fluxes in the UWS such as materials, chemicals, energy and greenhouse gas emissions. The suggested model is demonstrated through sustainability-based assessment of an integrated real-life UWS for a daily time-step over a 30-year planning horizon. The integrated UWS modelled by WaterMet2 includes both water supply and wastewater systems. Given a rapid population growth, WaterMet2 calculates six quantitative sustainability-based indicators of the UWS. The result of the water supply reliability (94%) shows the need for appropriate intervention options over the planning horizon. Five intervention strategies are analysed in WaterMet2 and their quantified performance is compared with respect to the criteria. Multi-criteria decision analysis is then used to rank the intervention strategies based on different weights from the involved stakeholders' perspectives. The results demonstrate that the best and robust strategies are those which improve the performance of both water supply and wastewater systems

A spatially-resolved material flow model: of the Lisbon metropolitan area

Urban systems are the locus of consumption and engines of economic growth in a globalized world. Major cities offer then the most striking examples of the environmental and energy problems that accompany intense urbanization: as cities grow the flow of energy and materials increase and pose serious problems to global sustainability. It is therefore critical to understand the interactions between the socio-economic urban development and environmental pressures, and to develop models that may explain these interactions. Early efforts led to conceptual models of cities as urban ecosystems. Ecologists have described the city as a heterotrophic ecosystem highly dependent on large inputs of energy and materials and a vast capacity to absorb emissions and waste [1,3]. Wolman was the first to apply an urban metabolism approach to quantify the flows of energy and materials into and out of a hypothetical American city with a population of one million. Systems ecologists provided formal equations to describe the energy balance and the cycling of materials . Although these efforts have never been translated into operational simulation models, they have laid out the basis for urban-ecological research. A critical challenge in this context is how to balance service levels, asset management (at times with a growing maintenance backlog), and resource efficiency with respect to materials, energy and cost. In this paper the outline of a spatially resolved model of urban systems is described.Peer Reviewe

Scenario 2040 for Oslo as model city

This report – D34.2, authored by NTNU, is a sequel to D34.1 in which interventions suggested by the water-sanitation utility in Oslo - Oslo Vann og Avløpsetaten, had been tested using both the models – the WaterMet 2 (WM2) model developed by Exeter and the Dynamic Metabolism Model (DMM) developed at NTNU, as part of TRUST. The report starts off by emphasising the need for a holistic long-term sustainability approach in decision-making in water and wastewater utilities around the world. The models referred to above, are proposed as aids in meeting this need. With the help of references to earlier published works and TRUST deliverables related to these models, as well as some new tests carried out using one of them (DMM), the usability of the same has been demonstrated. ‘Usability’ here refers to understanding the impact of interventions on selected metrics/indicators in year-2040 (in keeping with the title of the deliverable; and the timeframe which has been considered for the TRUST project); and subsequent choices/selections which utilities would like to make depending on their priorities, targets and benchmarks they would set for themselves. As concluded in D34.1, there are differences between WM2 and DMM – which make them useful in different contexts – situational, circumstantial etc. These differences are recounted here again, in order to make it clear to the readers and end-users that one model is not meant to substitute the other, per se. Simply put, depending on what the end-users’ needs, goals, objectives and constraints are, one or the other would be preferable. The models have been extensively tested at Oslo VAV. A brief summary of the initial feedback from personnel at Oslo VAV is provided. The models were also introduced to pilot cities to understand their points of view, which have been presented in brief.Venkatesh, G.; Sægrov, S.; Brattebø, H. (2014). Scenario 2040 for Oslo as model city. http://hdl.handle.net/10251/4662

Quantifying energy demand and greenhouse gas emissions of road infrastructure projects: An LCA case study of the Oslo fjord crossing in Norway

The road sector consumes large amounts of materials and energy and produces large quantities of greenhouse gas emissions, which can be reduced with correct information in the early planning stages of road project. An important aspect in the early planning stages is the choice between alternative road corridors that will determine the route distance and the subsequent need for different road infrastructure elements, such as bridges and tunnels. Together, these factors may heavily influence the life cycle environmental impacts of the road project. This paper presents a case study for two prospective road corridor alternatives for the Oslo fjord crossing in Norway and utilizes in a streamlined model based on life cycle assessment principles to quantify cumulative energy demand and greenhouse gas emissions for each route. This technique can be used to determine potential environmental impacts of road projects by overcoming several challenges in the early planning stages, such as the limited availability of detailed life cycle inventory data on the consumption of material and energy inputs, large uncertainty in the design and demand for road infrastructure elements, as well as in future traffic and future vehicle technologies. The results show the importance of assessing different life cycle activities, input materials, fuels and the critical components of such a system. For the Oslo fjord case, traffic during operation contributes about 94 % and 89 % of the annual CED and about 98 % and 92 % of the annual GHG emissions, for a tunnel and a bridge fjord crossing alternative respectively

Teamwork skills, shared mental models, and performance in simulated trauma teams: an independent group design

<p>Abstract</p> <p>Background</p> <p>Non-technical skills are seen as an important contributor to reducing adverse events and improving medical management in healthcare teams. Previous research on the effectiveness of teams has suggested that shared mental models facilitate coordination and team performance. The purpose of the study was to investigate whether demonstrated teamwork skills and behaviour indicating shared mental models would be associated with observed improved medical management in trauma team simulations.</p> <p>Methods</p> <p>Revised versions of the 'Anesthetists' Non-Technical Skills Behavioural marker system' and 'Anti-Air Teamwork Observation Measure' were field tested in moment-to-moment observation of 27 trauma team simulations in Norwegian hospitals. Independent subject matter experts rated medical management in the teams. An independent group design was used to explore differences in teamwork skills between higher-performing and lower-performing teams.</p> <p>Results</p> <p>Specific teamwork skills and behavioural markers were associated with indicators of good team performance. Higher and lower-performing teams differed in information exchange, supporting behaviour and communication, with higher performing teams showing more effective information exchange and communication, and less supporting behaviours. Behavioural markers of shared mental models predicted effective medical management better than teamwork skills.</p> <p>Conclusions</p> <p>The present study replicates and extends previous research by providing new empirical evidence of the significance of specific teamwork skills and a shared mental model for the effective medical management of trauma teams. In addition, the study underlines the generic nature of teamwork skills by demonstrating their transferability from different clinical simulations like the anaesthesia environment to trauma care, as well as the potential usefulness of behavioural frequency analysis in future research on non-technical skills.</p

Resource recovery and life cycle assessment in co‐treatment of organic waste substrates for biogas versus incineration value chains in Poland and Norway

Present waste management policies are characterized by some main shifts compared to previous practices; such as increased focus on resources recovery, banning of landfilling of organic waste fractions, waste-to-energy value chains optimization, and environmental life cycle impact optimization. In order to comply with such new policies there is a need for research on methodological and empirical aspects of LCA for value chains for co-treatment and resource recovery from organic waste substrates; including processes from generation, treatment, energy conversion and final use of products and byproducts. This study examines two generic value chains (aiming at what are common solutions) for co-treatment of selected organic waste substrates, converted to energy, in Norway and Poland. The waste substrates that are studied are sewage sludge (46% dry matter), organic fractions of municipal solid waste (27.1%), and fat (26.9), in different combinations of quantity mix. Chemical properties for these substrates are gathered from a newly executed state-of-the-art analysis in addition to comprehensive laboratory experiments to find methane yield characteristics of different co-treatment substrate mix situations. Technologies examined in this study include pretreatment, anaerobic digestion, biogas upgrading to CHP-generation or to biofuel for use in transport, bioresiduals separation or upgrading to compost for use in agriculture or as soil amendment, all as part of an anaerobic route, compared to waste incineration with energy recovery to CHP-generation as alternative to the anaerobic route. Products and byproducts of both treatment options are substituting mineral fertilizers, fossil fuels and electricity grid mixes common of today, by system expansion, to determine possible avoided impacts when comparing alternative technologies. The LCA model is based on input from a feedstock-driven and mass-balance consistent MFA model that estimates the life cycle inventory. This provides increased flexibility and accuracy regarding system and technology assumptions, on the basis of a given set of transfer coefficients and parameters that can be altered according to what value chain and technologies are to be examined. This study presents LCA results from two defined and alternative value chains, based on what are typical assumptions and input variable values for applications in a Norwegian and in a Polish setting. The study account for the differences in technologies and practices in the typical waste systems, the typical energy systems and the typical transportation systems in each country, where the main differences between the two systems are that bioresidual is used as fertilizer in Norway and not in Poland additional to the different electricity mixes. LCA calculations are performed using different mix ratios of incoming waste substrates (sewage sludge, organic waste, fat), and assessing the corresponding energy recovery efficiency, nutrient recovery efficiency, and the associated impacts affected by applied technologies, transport distances, carbon capture potential, as well as estimating direct emissions for CH4, N2O and NH3, according to chosen end-use practices within the systems. The study shows what are the main important system processes and elements and what turn to be the critical variables and assumptions in the LCA modeling. It also gives recommendations for what factors to focus when trying to improve the resource recovery for energy and nutrients and the life-cycle environmental impacts of organic waste-to-energy value chains

Framework for Sustainability Assessment of UWCS and development of a self-assessment tool

This report provides a comprehensive definition of sustainability aimed to provide a reference framework within the TRUST project. Sustainability for the Urban Water Cycle Services (UWCS) is defined in 5 dimensions (including the classial tripple bottom line plus two additional enabling dimensions) and includes the detail of objectives and assessment criteria that should be used to define assessment systems within TRUST. In other words, the TRUST sustainability framework defined in this report should be used as a reference when developing any performance assessment system within TRUST, as it provides the basic objectives and assessment criteria that should lead to adequate performance metrics. A practical implementation of this approach is the development of the online self-assessment tool which constitutes TRUST Deliverable D312. The self-assessment tool makes use of the framework developed for the whole project and develops it into a set of performance metrics to perform a quick and initial assessment of the sustainability of the system. The second part of this report provides the details on how the self-assessment tool operates, the metrics used and how the assessment is provided. As a matter of fact, D311 should be seen as the document providing the technical insight on the self-assessment tool presented in D312.Alegre, H.; Cabrera Rochera, E.; Hein, A.; Brattebø, H. (2014). Framework for Sustainability Assessment of UWCS and development of a self-assessment tool. http://hdl.handle.net/10251/3573

Geo-referenced building stock analysis as a basis for local-level energy and climate mitigation strategies

A geo-referenced building stock model was used to analyse the energy and climate performance of the Knowledge Axis in Trondheim, Norway, by 2050. Strategies for energy upgrades, construction of more energy-efficient new constructions, changes in heating technologies, and their implications in terms of energy savings and greenhouse gas (GHG) emissions associated with energy and materials are assessed through various scenarios. Thematic maps were used to display the development of the total floor area and energy use. Compared to the baseline scenario for the same year, the energy savings range from 2 to 9%, 2–14%, and 2–19% in 2030, 2040, and 2050, respectively. New passive house constructions combined with energy upgrades in renovation projects and the maximum use of heat pumps have the greatest energy-saving potential. Our results displayed a large variation in the total net GHG emissions as a result of the alternative emission factors. The total net GHG emissions are primarily affected by the energy savings (amplified by assuming fossil fuel as the marginal mix), electricity mix (Norwegian or European), and allocation chosen for the incinerated waste to feed the district heating system.publishedVersio

Energy renovation rates in the Netherlands – comparing long and short term prediction methods

The building sector plays a major role in order to meet the energy saving targets set in the EU and the Netherlands (SER, 2013; ürge-Vorsatz et al., 2007). Existing buildings are responsible for 36% of the CO2 emissions in the European Union (EU) (European Commission, 2008 and 2014). Moreover, among the end use sectors – industry, transport, households, services, fishing, agriculture, forestry and non-specified – households represent one of the most energy intensive sectors consuming 24.8% of the total final energy (European Commission, 2016a; EEA 2017). Two major directives are currently in force, on an EU level, to tackle the issue of energy&nbsp;efficiency improvement of buildings – the Energy Efficiency Directive (EED) and the Energy Performance Buildings Directive (EPBD) (European Parliament, 2010, 2012). Improving the efficiency of the building stock is a central pillar for the carbon reduction goals of the member states (MS) and the EU as a whole. Energy renovations in existing dwellings offer unique opportunities for reducing the energy consumption and greenhouse gas (GHG) emissions on a national scale in the Netherlands, but also on a European and global level. Due to the long lifespan of buildings, currently existing buildings will constitute a major part of the Dutch housing stock for several decades (Sandberg et al. 2016a). In the Netherlands, it is expected that the renovation activity will be greater than the construction and demolition activity in the future (Sandberg et al. 2016a). The rate at which energy renovations are realized and the energy performance level achieved after the renovations are crucial factors for an energy-efficient built environment. Energy renovation rates assumed by EU officials and policy makers usually range from 2.5-3% (Stadler et al. 2007; BPIE 2011; European Parliament 2012; Boermans et al. 2012; Dixon et al. 2014). However, at current rates it is claimed that more than 100 years will be needed to renovate the EU building stock (European Commission 2016). Furthermore, the intervention level – how many and what type energy efficiency measures – of the renovations plays an equally significant role to the rate as it can define when the next renovation cycle can occur and the possibility of lock-in effects. The main question addressed in this paper is what the estimated renovation rates for the Dutch housing stock are for different types of renovation, depending on the level of renovation and energy saving measures applied. Answering this question can help evaluate current and previous policies but also shape future ones. The need for renovations depends greatly on the buildings’ age and typology. The characteristics of the building stock are quite different across countries in Europe. In addition, building ownership and the construction sector are naturally fragmented. Research performed so far, has revealed that the majority of building renovations consist of small scale projects and relatively low investments or occur at the natural need of dwellings to be retrofitted (Filippidou et al. 2016; Sandberg et al. 2016; Filippidou et al. 2017). In order to assess and examine the energy renovation measures, how fast or how deep they are being realized, up-to-date monitoring of these activities is required. Moreover, time series monitoring is crucial in order to achieve longitudinal studies that properly report renovation rates. Approaches to monitor the building stock have evolved separately across countries in Europe. Information about the progress of energy performance renovations is necessary to track the progress of policy implementation and its effectiveness. Moreover, advanced quality information and data are needed to help develop roadmaps and future policies resulting in energy efficient buildings. To this day, each country is gathering and analysing data for the development of their building stocks individually and in a different manner. Some collect data through the Energy Performance Certificates (EPCs) databases and others perform housing surveys in representative samples (Filippidou et al. 2017). In some cases, information gained through the investments on energy renovations are used to calculate the progress. To address the data monitoring issues identified, there is a need for new methods on the estimation of renovation rates that can be used for consistent and scalable analyses of building stocks. In this paper, we compare two different methods, long and short term, to simulate and assess the energy renovation rate of the Dutch non-profit housing stock. First we apply the dynamic dwelling stock model which has been developed and validated in NTNU, Norway (Sartori et al. 2016). The input parameters are based on statistical information for the development of the non-profit housing stock. Second, we use yearly records gathered centrally and stored in a time series database by housing associations through the energy labelling of their stocks, called SHAERE (Sociale Huursector Audit en Evaluatie van Resultaten Energiebesparing [English: Social Rented Sector Audit and Evaluation of Energy Saving Results]). Ultimately, we are comparing the renovation rates resulting from the dynamic modelling and the analysis of empirical building energy epidemiology data. As a result, we are able to suggest renovation rates for various types of renovation measures, which should be applied in studies of future development of energy demand in the dwelling stock. This paper is structured as follows. The remaining of section 6.1 sets the background and the second section presents an overview of the data and methods of our research. The third section introduces the results. The fourth section deals with our experiences concerning the dynamic building stock modelling and the longitudinal data analysis using big data. Finally, the fifth section elaborates on policy implications and draws conclusions

Crossing the Antarctica: Exploring the Effects of Appetite-Regulating Hormones and Indicators of Nutrition Status during a 93-Day Solo-Expedition

Future deep space astronauts must maintain adequate nutrition despite highly stressful, isolated, confined and dangerous environments. The present case-study investigated appetite regulating hormones, nutrition status, and physical and emotional stress in a space analog condition: an explorer conducting a 93-day unsupported solo crossing of Antarctica. Using the dried blood spot (DBS) method, the subject drew samples of his blood on a regular basis during the expedition. The DBSs were later analyzed for the appetite regulating hormones leptin and adiponectin. Energy intake and nutritional status were monitored by analysis of albumin and globulin (including their ratio). Interleukin-6 (IL-6) was also analyzed and used as an energy sensor. The results showed a marked reduction in levels of the appetite-reducing hormone, leptin, and the appetite stimulating hormone, adiponectin, during both extreme physical and psychological strain. Nutrition status showed a variation over the expedition, with below-normal levels during extreme psychological strain and levels abutting the lower bounds of the normal range during a phase dominated by extreme physical hardship. The IL-6 levels varied substantially, with levels above the normal range except during the recovery phase. It was concluded that a daily intake of 5058 to 5931 calories seemed to allow recovery of both appetite and nutritional status between extreme physical and psychological hardship during a long Arctic expedition. Furthermore, IL-6 may be a sensor in the muscle-liver, muscle-fat and muscle-brain crosstalk. These results may help guide nutrition planning for future astronaut crews, mountaineers and others involved in highly demanding missions.publishedVersio