• Energy Research
• 11. Sustainability close
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The workshop ‘Creating Desirable Sustainable Practices; the Challenge of the Bucket Wash’ offers the opportunity to engage in the emerging realm of ‘practice-oriented design’, and to explore the tension between sustainability and desirability. Practice-oriented design builds design and research approaches on practice theory (from sociology) which takes practices – such as bathing or cooking – as its main unit of analysis. It offers a framework for understanding what goes on in people’s daily activities- routines, habits, et cetera. This is not only interesting for taking a different look at user experiences, but also for tackling issues of sustainability. To make this abstract topic tangible, a case is introduced using existing research on bathing. The ‘bucket wash’ concept boldly represents a way of bathing that is clearly less resource intensive than the currently dominant practice of showering and poses challenges for desirability.

Abstract The success of smart city projects is intrinsically related to the existence of large volumes of data that could be processed to achieve their objectives. For this purpose, the plethora of data stored by public administrations becomes an incredibly rich source of insight and information due to its volume and diversity. However, it was only with the Open Government Movement when governments have been concerned with the need to open their data to citizens and businesses. Thus, with the emergence of open data portals, these myriad of data enables the development of new business models. The achievement of the benefits sought by making this data available triggers new challenges to cope with the diversity of sources involved. The business potential could be jeopardized by the scarcity of relevant data in the different blocks and domains that makes a city and by the lack of a common approach to data publication, in terms of format, content, etc. This paper introduces a holistic approach that relies on the Smart City Ontology as the cornerstone to standardise and structure data. This approach, which is proposed to be an analytical tool to assess the potential of data in a given smart city, analyses three main aspects: availability of data, the criteria that data should fulfil to be considered eligible and the model used to structure and organise data. The approach has been applied to the case of Brussels Capital Region, which first results are presented and discussed in this paper. The main conclusion that has been obtained is that, besides its commitment with open data and smart cities, Brussels is not mature enough to fully exploit the real intelligence that smart cities could provide. This maturity would be achieved in the following years with the implementation of the new Brussels’ Smart City Strategy.

Abstract Carbon Capture and Storage at industrial processes (industrial CCS) is expected to play an important role in reducing industrial CO2 emissions in the short term. Industrial CCS involves capturing CO2 from industrial processes, such as steel and cement making, and storing the CO2 underground. This study examined the public opinion of industrial CCS through an informed opinion survey in the Netherlands (N = 987) and the United Kingdom (UK; N = 974). On average, respondents were neutral to slightly positive about the implementation of industrial CCS in their country. UK respondents were slightly more positive (M = 4.66 on a 7-point scale) than Dutch respondents (M = 4.38). Awareness and perceived knowledge levels were somewhat higher in the Netherlands than in the UK. In both countries, perceived outcomes of industrial CCS (e.g. for climate change; safety; employment) were strongly associated with industrial CCS opinion, when compared to socio-demographics, proximity to industry (actual and perceived), and psychological variables. Differences between countries in outcome perceptions occur. For example, the safety of CO2 transport is a larger concern in the Netherlands than in the UK, while cost-control is a larger concern in the UK than in the Netherlands. These findings suggest that the national context for CCS implementation matters. Our research suggests that public engagement strategies will benefit from focusing on the economic and climate impacts of industrial CCS, as well as from building trust in industry and addressing perceived safety concerns surrounding different aspects of industrial CCS.

Abstract Narrowing the performance deficit between design intent and the real-time environmental and energy performance of buildings is a complex and involved task, impacting on all building stakeholders. Buildings are designed, built and operated with increasingly complex technologies. Throughout their life-cycle, they produce vast quantities of data. However, many commercial buildings do not perform as originally intended. This paper presents a semantic web based approach to the performance gap problem, describing how heterogeneous building data sources can be transformed into semantically enriched information. A performance assessment ontology and performance framework (software tool) are introduced, which use this heterogeneous data as a service for a structured performance analysis. The demonstrator illustrates how heterogeneous data can be published semantically and then interpreted using a life-cycle performance framework approach.

Abstract For computational fluid dynamics (CFD) simulations of large urban areas the air flow near surfaces is normally modelled using Wall Functions (WFs). This study aims at improving the accuracy of WFs, in terms of heat transfer predictions. Turbulent boundary layers at heated building surfaces in a street canyon were analysed with low-Reynolds number modelling (LRNM). Buoyancy was accounted for, due to its importance in street canyons e.g. by solar radiation. Two extreme types of normalized temperature profiles could be identified in the thermal boundary layer dependent on the Richardson (Ri) number. One extreme at low Ri number could be attributed to forced convective flow, which is adequately described by existing standard wall functions (SWFs), and the second extreme at Ri>1 to mixed convective flows, where WFs adapted for non-equilibrium flows (NEWFs) are appropriate. Based on these two extremes, an adaptive temperature wall function (AWF) was derived that varies between the two existing WFs dependent on the local Ri. This AWF can account for the co-occurrence of forced and mixed convective flow regimes at a single surface. CFD simulations of street canyon configurations with SWF showed errors in the wall heat fluxes up to 60%, compared to the LRNM results, and up to 30% for NEWFs. With the proposed AWF, these errors were reduced to less than 10% for the majority of the cases studied over the whole range of Ri numbers. We conclude that the proposed AWF allows for more accurate convective heat transfer analysis in urban CFD studies.

Renewable energy has been considered as the solution to the hydra-headed problems of energy security, energy access and climate change, especially in Africa. In addition, renewable energy sources, such as the sun, wind, wave and waste abound in Africa are in need of investment. In order to provide both policy and investment guide, this study investigates the drivers of renewable energy demand in oil-producing African countries. Three panel data models – a random effect model, a fixed effects model and a dynamic panel data model – are used to estimate renewable energy demand with a comprehensive set of determinants. The estimation results indicate that the main drivers of renewable energy in oil-producing African countries are real income per capita, energy resource depletion per capita, carbon emissions per capita and energy prices. The study recommends that policies should encourage the consumption of commercial sources of renewable energy to attract the needed investments.

Whole-economy scenarios for limiting global warming to 1.5C suggest that direct carbon emissions in the buildings sector should decrease to almost zero by 2050, but leave unanswered the question how this could be achieved by real-world policies. We take a modelling-based approach for simulating which policy measures could induce an almost-complete decarbonisation of residential heating, the by far largest source of direct emissions in residential buildings. Under which assumptions is it possible, and how long would it take? Policy effectiveness highly depends on behavioural decision- making by households, especially in a context of deep decarbonisation and rapid transformation. We therefore use the non-equilibrium bottom-up model FTT:Heat to simulate policies for a transition towards low-carbon heating in a context of inertia and bounded rationality, focusing on the uptake of heating technologies. Results indicate that the near-zero decarbonisation is achievable by 2050, but requires substantial policy efforts. Policy mixes are projected to be more effective and robust for driving the market of efficient low-carbon technologies, compared to the reliance on a carbon tax as the only policy instrument. In combination with subsidies for renewables, near-complete decarbonisation could be achieved with a residential carbon tax of 50-200Euro/tCO2. The policy-induced technology transition would increase average heating costs faced by households initially, but could also lead to cost reductions in most world regions in the medium term. Model projections illustrate the uncertainty that is attached to household behaviour for prematurely replacing heating systems.