Building sustainability assessment methods

Over last 15 years it has been increasingly important to understand the sustainability performance of buildings across a broad range of considerations. This has stimulated the development of a number of sustainability assessment tools intended to measure objectively a project's impact in sustainability terms and so encourage designers and planners to improve a building's performance. This paper examines the nature and contribution, as well as the limitations, of current sustainability rating assessment tools in evaluating building sustainability in different countries. Two yardsticks are used to review the current tools: first, how well they relate to the goal of sustainable development, and second, how adequately they adhere to the principles of objective assessment. Scope for further development of sustainability assessment tools is identified – in particular, the need for tools to assess more adequately how buildings provide well-being, and to expand how assessment systems capture qualitative information. The paper proposes that methodology and procedures of assessment methods should feature the broad participation of user groups drawn from the public. This paper was first published in the Proceedings of the Institution of Civil Engineers - Engineering Sustainability and is reproduced with their permission http://www.icevirtuallibrary.com/content/journals Permission is granted by ICE Publishing to print one copy for personal use. Any other use of these PDF files is subject to reprint fees.</p

Achieving quality through statistical prediction for building services systems

The application of prediction theories has been widely practised for many years in many industries such as manufacturing, defence and aerospace. Although these theories are not new, their application has not been widely used within the building services industry. Collectively, the building services industry should take a deeper look at these approaches in comparison with the traditional deterministic approaches currently being practised. By extending the application into this industry, this paper seeks to provide the industry with an overview of how simplified stochastic modelling coupled with availability and reliability predictions using historical data compiled from various sources could enhance the quality of building services systems