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 limited emphasis on understanding how construction processes can be best managed to reduce GHG emissions. Unexpected disruptive events tend to adversely impact 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 reduced by appropriate management of disruptive events. First, an empirical analysis of construction data from a specific highway construction project is used to illustrate the impact of unexpected schedule delays in increasing project GHG emissions. Next, a simulation based methodology is described to assess the effectiveness of alternative project management strategies in reducing GHG emissions. The contribution of this paper is that it explicitly considers projects 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.

Financial decision making about found oil and gas in Ghana : real options vs. traditional methods

This research is a study of the use of capital budgeting methods for investment decisions. It uses both the traditional methods and the newly introduced approach called the real options analysis to make a decision. The research elucidates how capital budgeting can be done when analysts encounter projects with high uncertainty and are capital intensive, for example oil and gas production. It then uses the oil and gas find in Ghana as a case study to support its argument. For a clear understanding a thorough literature review was done, which highlights the advantages and disadvantages of both methods. The revenue that the project will generate and the costs of production were obtained from the predictions by analysts from GNPC and compared to others experts’ opinion. It then applied both the traditional and real option valuation on the oil and gas find in Ghana to determine the project’s feasibility. Although, there are some short falls in real option analysis that are presented in this research, it is still helpful in valuing projects that are capital intensive with high volatility due to the strategic flexibility management possess in their decision making. It also suggests that traditional methods of evaluation should still be maintained and be used to value projects that have no options or those with options yet the options do not have significant impact on the project. The research points out the economic ripples the production of oil and gas will have on Ghana’s economy should the project be undertaken. These ripples include economic growth, massive job creation and reduction of the balance of trade deficit for the country. The long run effect is an eventually improvement of life of the citizens. It is also belief that the production of gas specifically can be used to generate electricity in Ghana which would enable the country to have a more stable and reliable power source necessary to attract more foreign direct investment.

EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.