Combining Off-the-Job Productivity Regression Model with EPA’s NONROAD Model in Estimating CO2 Emissions from Bulldozer
Keywords:Bulldozer, CO2 emissions, EPA’s NONROAD model, productivity rate.
AbstractHeavy 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.
1. EPA, Measuring Construction Industry Environ mental Performance, Washington D.C.: EPA’s Sector Strategies Program, 2007. [CrossRef]
EPA, Cleaner Diesels: Low Cost Ways to Reduce Emissions from Construction Equipment, Washing-ton D.C.: EPA’s Sector Strategies Program, 2007. [CrossRef]
Lewis, P. and Hajji, A., Estimating the Economic, Energy, and Environmental Impact of Construction Equipment, The 2012 Construction Research Congress, Purdue University, West Lafayette, IN, 2012. [CrossRef]
Akinsola, A.O., An Intelligent Model of Variations Contingency on Construction Projects, PhD Dissertation, University of Wolverhampton, Wolverhampton, 1997. [CrossRef]
Akintoye, A. and Skitmore, M., Models of UK Private Sectors Quarterly Construction Demand, Construction Management and Economics, 12, 1994, pp. 3-13. [CrossRef]
Edwards, D.J., Holt, G.D., and Harris, F.C., A Comparative Analysis between the Multilayer Perceptron 'Neural Network' and Multiple Regression Analysis for Predicting Construction Plant Maintenance Cost, Journal of Quality in Maintenance Engineering, 6(1), 2000, pp. 45-60. [CrossRef]
David, J.E. and Gary, D.H., ESTIVATE: A Model for Calculating Excavator Productivity and Outputs Cost, Engineering, Construction, and Architectural Management, 7(1), 1993, pp. 52-62. [CrossRef]
Dunlop, P. and Smith, S., Estimating Key Characteristics of the Concrete Delivery and Placement Process using Linear Regression Analysis, Civil Engineering and Environmental System, 20(4), 2003, pp. 273-290. [CrossRef]
Han, S. and Halpin, D.W., The Use of Simulation for Productivity Estimation based on Multiple Regression Analysis, The 37th Conference on Winter Simulation, Orlando, Florida, 2005. [CrossRef]
Ok, S.C. and Sinha, S.K., Construction Equipment Productivity Estimation using Artificial Neural Network Model, Construction Management and Economics, 24(10), 2006, pp. 1029-1044. [CrossRef]
Smith, S.D., Earthmoving Productivity Estimation Using Linear Regression Techniques, Journal of Construction Engineering and Management, 125(3), 1999, pp. 133-141. [CrossRef]
CARB, User’s Guide for OFFROAD2007, California Air Resources Board: Mobile Source Emissions Inventory Program, Sacramento, CA, 2007. [CrossRef]
CARB, EMFAC2002, California Air Resources Board: Planning and Technical Support Division, Sacramento, CA, 2003. [CrossRef]
Li, H.X. and Lei, Z., Implementation of Discrete Event Simulation (DES) in Estimating and Analyzing CO2 Emission During Earthwork of Building Construction Engineering, The 17th International Conference on Industrial Engineering and Engineering Management (IEEM), Xiamen, China, 2010. [CrossRef]
Peurifoy, R.L. and Oberlender, G.D., Estimating Construction Cost, 5th Ed., McGraw Hill, New York, 2005. [CrossRef]
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