Investigating the effect of construction management strategies on project greenhouse gas emissions using interactive simulation
The challenges posed by global climate change are motivating the investigation of strategies that can reduce the life cycle greenhouse gas (GHG) emissions of products and processes. While new construction materials and technologies have received significant attention, there has been a limited emphasis on understanding how construction processes can be best managed to control GHG emissions. Unexpected disruptive events tend to adversely affect construction costs and delay project completion. They also tend to increase project GHG emissions. The objective of this paper is to investigate ways in which project GHG emissions can be controlled by appropriately managing disruptive events. First, an empirical analysis of a specific highway construction project is used to illustrate the impact of unexpected schedule delays in increasing project GHG emissions. Next, a simulation based method is introduced to assess the effectiveness of alternative project management strategies in controlling GHG emissions. It demonstrates that appropriately selected strategies can reduce project GHG emissions without increasing the contractor's financial burden or causing project schedule delays. The contribution of this paper is that it explicitly considers project emissions, in addition to cost and project duration, in developing project management strategies. Practical application of the method discussed in this paper will help construction firms reduce their project emissions through strategic project management, and without significant investment in new technology. In effect, this paper lays the foundation for best practices in construction management that will optimize project cost and duration, while minimizing GHG emissions. © 2013 Elsevier Ltd. All rights reserved.
Journal of Cleaner Production
Investigating the effect of construction management strategies on project greenhouse gas emissions using interactive simulation.
Journal of Cleaner Production,
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