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Article: Identifying factors influencing demolition waste generation in Hong Kong
Title | Identifying factors influencing demolition waste generation in Hong Kong |
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Authors | |
Keywords | Construction and demolition (C&D) waste management Demolition waste Demolition waste generation (DWG) Big data Hong Kong |
Issue Date | 2017 |
Publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jclepro |
Citation | Journal of Cleaner Production, 2017, v. 141, p. 799-811 How to Cite? |
Abstract | Among all construction activities, demolition normally generates the largest proportion of construction and demolition (C&D) waste, to which requires more importance being attached for effective manage- ment. Previous studies have attempted to understand demolition waste generation (DWG) but the un- derstanding remains relatively insufficient, largely due to the erratic and poor quality data available. This research aims to identify factors impacting DWG by making use of a big dataset which has recently become available as a result of C&D waste management practices in Hong Kong. Using big data analytics, it is confirmed that DWG, demolition cost, and duration of conducting the demolition work are dependent on each other. It is also found that geographical location, building usage, and the public- private nature of a building project also have a significant impact on DWG in the Hong Kong context. Based on the correlations between DWG and these identified factors, stakeholders may introduce proper managerial or policy interventions to effectively minimize DWG. For example, public policy-makers may formulate more tailor-made regulations to attach more importance to the locations, usages and public- private nature, which have more potentials for demolition waste minimization. |
Persistent Identifier | http://hdl.handle.net/10722/234788 |
ISSN | 2023 Impact Factor: 9.7 2023 SCImago Journal Rankings: 2.058 |
ISI Accession Number ID | |
Grants |
DC Field | Value | Language |
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dc.contributor.author | Chen, X | - |
dc.contributor.author | Lu, W | - |
dc.date.accessioned | 2016-10-14T13:49:16Z | - |
dc.date.available | 2016-10-14T13:49:16Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Journal of Cleaner Production, 2017, v. 141, p. 799-811 | - |
dc.identifier.issn | 0959-6526 | - |
dc.identifier.uri | http://hdl.handle.net/10722/234788 | - |
dc.description.abstract | Among all construction activities, demolition normally generates the largest proportion of construction and demolition (C&D) waste, to which requires more importance being attached for effective manage- ment. Previous studies have attempted to understand demolition waste generation (DWG) but the un- derstanding remains relatively insufficient, largely due to the erratic and poor quality data available. This research aims to identify factors impacting DWG by making use of a big dataset which has recently become available as a result of C&D waste management practices in Hong Kong. Using big data analytics, it is confirmed that DWG, demolition cost, and duration of conducting the demolition work are dependent on each other. It is also found that geographical location, building usage, and the public- private nature of a building project also have a significant impact on DWG in the Hong Kong context. Based on the correlations between DWG and these identified factors, stakeholders may introduce proper managerial or policy interventions to effectively minimize DWG. For example, public policy-makers may formulate more tailor-made regulations to attach more importance to the locations, usages and public- private nature, which have more potentials for demolition waste minimization. | - |
dc.language | eng | - |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/jclepro | - |
dc.relation.ispartof | Journal of Cleaner Production | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Construction and demolition (C&D) waste management | - |
dc.subject | Demolition waste | - |
dc.subject | Demolition waste generation (DWG) | - |
dc.subject | Big data | - |
dc.subject | Hong Kong | - |
dc.title | Identifying factors influencing demolition waste generation in Hong Kong | - |
dc.type | Article | - |
dc.identifier.email | Chen, X: chenx90@hku.hk | - |
dc.identifier.email | Lu, W: wilsonlu@hku.hk | - |
dc.identifier.authority | Lu, W=rp01362 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1016/j.jclepro.2016.09.164 | - |
dc.identifier.scopus | eid_2-s2.0-84994528941 | - |
dc.identifier.hkuros | 269729 | - |
dc.identifier.volume | 141 | - |
dc.identifier.spage | 799 | - |
dc.identifier.epage | 811 | - |
dc.identifier.isi | WOS:000389090300072 | - |
dc.publisher.place | Netherlands | - |
dc.relation.project | Application of Hong Kong construction waste management experience in mainland China: an empirical exploration | - |
dc.identifier.issnl | 0959-6526 | - |