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An Environmental Impact Causal Model for improving the environmental performance of construction processes

Fuertes, A. ORCID: https://orcid.org/0000-0002-6224-1489, Casals, M., Gangolells, M., Forcada, N., Macarulla, M. and Roca, X. (2013) An Environmental Impact Causal Model for improving the environmental performance of construction processes. Journal of Cleaner Production, 52. pp. 425-437. ISSN 0959-6526

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To link to this item DOI: 10.1016/j.jclepro.2013.02.005

Abstract/Summary

Despite the increasing efforts made by the construction sector to reduce the environmental impact of their processes, construction sites are still a major source of pollution and adverse impacts on the environment. This paper aims to improve the understanding of construction-related environmental impacts by identifying on-site causal factors and associated immediate circumstances during construction processes for residential building projects. Based on the literature and focus group findings, we have developed a construction-related Environmental Impact Causal Model consisting of a process-oriented causal network of thirty-nine environmental impacts, forty-five causal factors and over two hundred causal relationships. It is intended to contribute to a reduction in construction-related environmental impacts on building sites by supporting contractors and other decision-makers in the early identification of factors that are likely to lead to impacts or to exacerbate their consequences, as well as the later environmental performance evaluation and control. The causal model is validated by investigating over a hundred environmental incidents. Finally, possible methods to improve construction-related environmental performance are suggested.

Item Type:Article
Refereed:Yes
Divisions:No Reading authors. Back catalogue items
Science > School of the Built Environment > Construction Management and Engineering
Science > School of the Built Environment > Energy and Environmental Engineering group
Science > School of the Built Environment > Organisation, People and Technology group
ID Code:105803
Publisher:Elsevier

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