Abstract
The current method of estimating CO2 emissions during the construction phase does not consider the variability that can occur in actual work. Therefore, this study aims at probabilistic CO2 estimation dealing with the statistical characteristics in activity data of building construction work, focused on concrete pouring work and based on field data. The probabilistically estimated CO2 emissions have some differences from CO2 emissions measured by current deterministic methods. The results revealed that the minimum difference was 11.4%, and the maximum difference was 132.7%. This study also used Monte Carlo simulations to derive information on a probability model of CO2 emissions. Results of the analysis revealed that there is a risk of underestimating emissions because the amount of emissions was estimated at a level that exceeds the 95% confidence interval of the simulation results. In addition, the probability that CO2 emissions using the measured activities data were less than the estimated CO2 emissions using the bill of quantity was 73.2% in the probability distribution model.
Highlights
The building sector consumes about 40% of the world’s annual energy production, which accounts for approximately a quarter of the world’s annual CO2 emissions [1]
This study used actual activity data gathered during the construction phase and performed Monte Carlo simulation to determine the probabilistic interval of CO2 emissions, focusing on concrete pouring work
Other studies analyzed the variability of emission coefficients by evaluating the most-consumed building materials based on accumulated greenhouse gas emissions, as well as the energy emissions coefficient, in order to assess the level of uncertainty and variability when estimating the emissions of the apartment housing construction stage [10,11]
Summary
The building sector consumes about 40% of the world’s annual energy production, which accounts for approximately a quarter of the world’s annual CO2 emissions [1]. Previous studies have mentioned that it is important to deal with the embodied carbon emissions generated in the production, construction, maintenance, and disposal of building materials [4]. Among these phases, the construction phase accounts for approximately 10–30% of the entire building life cycle, even if it represents a short period. This study aims at probabilistic CO2 estimation dealing with the statistical characteristic in activity data of building construction work, based on field data and considering variability. This study used actual activity data gathered during the construction phase and performed Monte Carlo simulation to determine the probabilistic interval of CO2 emissions, focusing on concrete pouring work. We executed the simulation test 10,000 times at a 95% confidence interval
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