Uncertanty Analysis of Project Emissions

Abstract

Many nations are implementing or plan to implement a carbon pricing program in response to global warming and climate change issues. A significant amount of greenhouse gas (GHG) emissions can be attributed to projects, mainly construction works. Therefore, projects' environmental impact should be estimated before the project commencement and be monitored during its implementation phase. In this paper, we propose a probabilistic model to quantify the uncertainty of project GHG emissions using Bayesian networks (BNs) and simulation techniques. The model provides a quantitative risk analysis mechanism to estimate the total emissions of the project as well as an update of the final emissions using information on the completed activates.