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A platform for research: civil engineering, architecture and urbanism
Estimating and minimizing embodied carbon of prefabricated high-rise residential buildings considering parameter, scenario and model uncertainties
https://orcid.org/0000-0002-2720-3073
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.
Highlights A five-level framework facilitates carbon calculation and meaningful comparison. A DQI-based MCS uncertainty analysis helps to avoid misinterpretation of results. Decisions on material selection affect buildings' embodied carbon significantly. Reliability of carbon estimation results is highly correlated with analytical uncertainty models. Prefabricated high-rise buildings' embodied carbon in HK can be reduced by up to 31.6%.
Estimating and minimizing embodied carbon of prefabricated high-rise residential buildings considering parameter, scenario and model uncertainties
https://orcid.org/0000-0002-2720-3073
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.
Highlights A five-level framework facilitates carbon calculation and meaningful comparison. A DQI-based MCS uncertainty analysis helps to avoid misinterpretation of results. Decisions on material selection affect buildings' embodied carbon significantly. Reliability of carbon estimation results is highly correlated with analytical uncertainty models. Prefabricated high-rise buildings' embodied carbon in HK can be reduced by up to 31.6%.
Estimating and minimizing embodied carbon of prefabricated high-rise residential buildings considering parameter, scenario and model uncertainties
https://orcid.org/0000-0002-2720-3073
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.
Highlights A five-level framework facilitates carbon calculation and meaningful comparison. A DQI-based MCS uncertainty analysis helps to avoid misinterpretation of results. Decisions on material selection affect buildings' embodied carbon significantly. Reliability of carbon estimation results is highly correlated with analytical uncertainty models. Prefabricated high-rise buildings' embodied carbon in HK can be reduced by up to 31.6%.
Estimating and minimizing embodied carbon of prefabricated high-rise residential buildings considering parameter, scenario and model uncertainties
Building and Environment ; 180
2020-05-05
Article (Journal)
Electronic Resource
English
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