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Article: Estimating and minimizing embodied carbon of prefabricated high-rise residential buildings considering parameter, scenario and model uncertainties
Title | Estimating and minimizing embodied carbon of prefabricated high-rise residential buildings considering parameter, scenario and model uncertainties |
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Authors | |
Keywords | Embodied carbon emission Prefabricated high-rise building Uncertainty analysis Scenario analysis Carbon reduction |
Issue Date | 2020 |
Publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/buildenv |
Citation | Building and Environment, 2020, v. 180, article no. 106951 How to Cite? |
Abstract | Carbon emissions associated with high-rise buildings are expected to grow with the increasing population in high-density cities. As an environmentally friendly construction method, prefabrication should lead to reduced buildings' emissions. However, few studies have considered the uncertainty caused by errors in input parameters, scenario assumptions and choices of analytical uncertainty models when examining the embodied carbon of prefabricated high-rise buildings, leading to the misinterpretation of results. To address this, a five-level framework is developed for assessing the deterministic embodied carbon of prefabricated buildings using the process-based method. A Data Quality Index based Monte Carlo Simulation is applied for the uncertainty analysis using SimaPro 9.0 software. A typical prefabricated high-rise residential building in Hong Kong is examined. Seven scenarios are developed by varying system boundaries, materials used, partition wall thickness, waste rate, prefabrication rate, transportation distance, and analytical uncertainty model's transformation coefficients, to examine the influences of the scenario and model uncertainty. Results indicate that the embodied carbon of the case averages 561 kg CO2/m2. When considering both deterministic results and parameter uncertainty, the key processes are identified as being the production of concrete, steel and timber, as well as transportation activities. The results reveal that 31.6% of the embodied carbon can be possibly reduced by combining the pre-defined scenarios. The selection of transformation coefficients in analytical uncertainty model significantly affects the variances of the results and should be carefully examined. This paper can better facilitate the uncertainty measurement of prefabricated buildings' embodied carbon assessment for improving the reliability of results. |
Persistent Identifier | http://hdl.handle.net/10722/294854 |
ISSN | 2023 Impact Factor: 7.1 2023 SCImago Journal Rankings: 1.647 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Teng, Y | - |
dc.contributor.author | Pan, W | - |
dc.date.accessioned | 2020-12-21T11:49:30Z | - |
dc.date.available | 2020-12-21T11:49:30Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Building and Environment, 2020, v. 180, article no. 106951 | - |
dc.identifier.issn | 0360-1323 | - |
dc.identifier.uri | http://hdl.handle.net/10722/294854 | - |
dc.description.abstract | Carbon emissions associated with high-rise buildings are expected to grow with the increasing population in high-density cities. As an environmentally friendly construction method, prefabrication should lead to reduced buildings' emissions. However, few studies have considered the uncertainty caused by errors in input parameters, scenario assumptions and choices of analytical uncertainty models when examining the embodied carbon of prefabricated high-rise buildings, leading to the misinterpretation of results. To address this, a five-level framework is developed for assessing the deterministic embodied carbon of prefabricated buildings using the process-based method. A Data Quality Index based Monte Carlo Simulation is applied for the uncertainty analysis using SimaPro 9.0 software. A typical prefabricated high-rise residential building in Hong Kong is examined. Seven scenarios are developed by varying system boundaries, materials used, partition wall thickness, waste rate, prefabrication rate, transportation distance, and analytical uncertainty model's transformation coefficients, to examine the influences of the scenario and model uncertainty. Results indicate that the embodied carbon of the case averages 561 kg CO2/m2. When considering both deterministic results and parameter uncertainty, the key processes are identified as being the production of concrete, steel and timber, as well as transportation activities. The results reveal that 31.6% of the embodied carbon can be possibly reduced by combining the pre-defined scenarios. The selection of transformation coefficients in analytical uncertainty model significantly affects the variances of the results and should be carefully examined. This paper can better facilitate the uncertainty measurement of prefabricated buildings' embodied carbon assessment for improving the reliability of results. | - |
dc.language | eng | - |
dc.publisher | Pergamon. The Journal's web site is located at http://www.elsevier.com/locate/buildenv | - |
dc.relation.ispartof | Building and Environment | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Embodied carbon emission | - |
dc.subject | Prefabricated high-rise building | - |
dc.subject | Uncertainty analysis | - |
dc.subject | Scenario analysis | - |
dc.subject | Carbon reduction | - |
dc.title | Estimating and minimizing embodied carbon of prefabricated high-rise residential buildings considering parameter, scenario and model uncertainties | - |
dc.type | Article | - |
dc.identifier.email | Pan, W: wpan@hku.hk | - |
dc.identifier.authority | Pan, W=rp01621 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1016/j.buildenv.2020.106951 | - |
dc.identifier.scopus | eid_2-s2.0-85085729699 | - |
dc.identifier.hkuros | 320646 | - |
dc.identifier.volume | 180 | - |
dc.identifier.spage | article no. 106951 | - |
dc.identifier.epage | article no. 106951 | - |
dc.identifier.isi | WOS:000562688900005 | - |
dc.publisher.place | United Kingdom | - |