The UK has set a highly ambitious target to reduce greenhouse gas emissions by 80% by 2050. Around 27% of emissions of carbon dioxide [the main greenhouse gas] is generated by housing in use. Around 30% of the UK housing stock is social landlord and local authority owned. Meanwhile, fuel prices are increasing, and consequently fuel poverty. Turnover in the building stock is much lower than for any other product; buildings have a much longer average life, and most new build is additional not replacement, so the most important impacts on energy use and carbon emissions will come from the existing stock even in 2050. Thus considerable innovation and investment is needed to meet the ambitious carbon reduction targets and to contain rising energy costs, by reducing demand and decarbonising supply.
One of the repeating themes around the provision of the knowledge and skills needed for delivering sustainable communities is the idea of a “common language” for all built environment professionals. This suggestion has been repeated regularly with each new political and professional review within and between different sectors responsible for the delivery of sustainable communities. There have been multiple efforts to address academic limitations, industry fragmentation and promote more interdisciplinary working and sector collaboration. This research explored the role of skills for sustainable communities, particularly within the higher education (HE) sector, and the responses to support the development of a “common language of sustainability” that can be shared between different sectors, professional disciplines and stakeholders. As an interdisciplinary group of academics and practitioners working with the HE sector in the North East of England, we evaluate the progression of sector collaboration to develop a quintuple helix model for HE. We use this as a suitable framework for systematically “mapping” out the mixed sector (academic, public, business, community and environmental organisations) inputs and influences into a representative sample of HE degree modules that are delivered from foundation and undergraduate to postgraduate levels, including examples of part-time and distance-learning modules. We developed a cascade of models which demonstrate increasing levels of collaboration and their potential positive impact on the effectiveness of education on sustainable communities. The methodological assessments of modules were followed by semi-structured group reflective analysis undertaken through a series of online workshops (recorded during the Covid19 lockdown) to set out a collective understanding of the generic skills needed for the delivery of sustainable communities. These generic skills for sustainable communities are presented as a pedagogical progression model of teaching activities and learning outcomes applied to the levels within HE. We propose sustainability education principles and progressions with the hope that they can have an impact on the design or review of current degree modules and programmes. The paper informs future sustainability research to be grounded in holism and systems thinking; better understanding of values, ethics, influencing and political impact; and procedural authenticity.
This paper explores the potential for using remotely sensed data from a combination of commercial and open-sources, to improve the functionality, accuracy of energy-use calculations and visualisation of carbon emissions. We present a study demonstrating the use of LiDAR (Light Detection And Ranging) data and aerial imagery for a mixed-use inner urban area within the North East of England and how this can improve the quality of input data for modelling standardised energy uses and carbon emissions. We explore the scope of possible input data for both (1) building geometry and (2) building physics models from these sources. We explain the significance of improved data accuracy for the assessment of heat-loss parameters, orientation, and shading and renewable energy micro-generation. We also highlight the limitations around the sole use of remotely sensed data and how these concerns can be partially addressed through combinations with (1) open-source property data, such as age, occupancy, tenure and (2) existing stakeholder data sets, including building services and measured performance. We set out some of the technical challenges; addressed through data approximation (considering data quality and metadata protocols) and a combination of automated or manual processing; in the use, adaptation, and transferability of this data. We elucidate how the output can be visualised and be supported by many of industry-standard CAD, GIS, and BIM software applications hence, broadening the scope for realworld applications. We demonstrate the support of commercial interest and potential drawing evidence from primary market research regarding the principal applications, functionality, and output. In summary, we conclude on the benefits in the use of remotely sensed data for improved accuracy in energy use and carbon emission calculations, the need for semantic integration of mixed data sources and the importance of output visualisation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.