Combining Off-the-Job Productivity Regression Model with EPA’s NONROAD Model in Estimating CO2 Emissions from Bulldozer - Apif M. Hajji; Aisyah Larasati; Michael P. Lewis (Institute of Research and Community Outreach - Petra Christian University, 2017)
Heavy duty diesel (HDD) construction equipment which includes bulldozer is important in infrastructure development. This equipment consumes large amount of diesel fuel and emits high level of carbon dioxide (CO2). The total emissions are dependent upon the fuel use, and the fuel use is dependent upon the productivity of the equipment. This paper proposes a methodology and tool for estimating CO2 emissions from bulldozer based on the productivity rate. The methodology is formulated by using the result of multiple linear regressions (MLR) of CAT’s data for obtaining the productivity model and combined with the EPA’s NONROAD model. The emission factors from NONROAD model were used to quantify the CO2 emissions. To display the function of the model, a case study and sensitivity analysis for a bulldozer’s activity is also presented. MLR results indicate that the productivity model generated from CAT’s data can be used as the basis for quantifying the total CO2 emissions for an earthwork activity.