Stochastic analysis of embodied carbon dioxide emissions considering variability of construction sites

Dongyoun Lee, Goune Kang, Chulu Nam, Hun Hee Cho, Kyung In Kang

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Article number4215
JournalSustainability (Switzerland)
Volume11
Issue number15
DOIs
Publication statusPublished - 2019 Aug 1

Keywords

  • CO emissions
  • Construction phase
  • Monte Carlo simulation
  • Stochastic analysis

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law

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