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Reports

3 result(s) found

Visualized analysis of global green buildings: Development, barriers and future directions

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English
Authors:
Qianwen Li, Ruyin Long, Hong Chen, Feiyu Chen, Jiaqi Wang

Green building is an important measure to deal with energy and environment problems in the construction sector of the world. In this study, knowledge mapping analysis is used, and 3,060 articles are selected for further study (1900–2019). Based on CiteSpace (5.3.R4 SE 64-bit), the knowledge base, hot topics and research trends of green-building-related research are presented. The key highlights of the overall analysis results are: (1) Research on green buildings has received more extensive attention in the 21st century.

Scoping review to understand the potential for public health impacts of transitioning to lower carbon emission technologies and policies

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English
Authors:
Rachel Tham, Geoff Morgan, Shyamali Dharmage, Guy Marks, Christine Cowie

Background: The transformation of the global energy sector from fossil-based fuels to low/non-carbon fuels will reduce environmental pollutant load, which in turn will benefit human health. However, with upscaling of emerging renewable technologies and energy sources, it is important to identify the potential for unintended health impacts, and to understand where the knowledge gaps lie with respect to health. We aimed to identify these gaps by conducting a scoping review. Methods: We conducted a systematic search of Medline, Web of Science, PubMed and EMBASE.

Drivers for green building: A review of empirical studies

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English
Authors:
Amos Darko,
Chenzhuo Zhang,
Albert P.C. Chan

This paper presents a comprehensive literature review of what drives the adoption of green building (GB) practices among construction stakeholders. The review is based on literature that have been published in peer-reviewed journals. Through a systematic review of the literature, authors are able to identify generic drivers for stakeholders to pursue GB. A total of 64 drivers were identified from reviewing 42 selected empirical studies. The paper presents a classification framework for the GB drivers.

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