A multivariate regression model to predict the GHG emission in urban logistics

Abstract

The greenhouse gas (GHG) emission in urban logistics is an important driver for determining future energy needs. An empirical model is developed for the greenhouse gas emissions based on multivariate linear regression to identify the main drivers of greenhouse gas emission. It has been found that the Vehicle-kilometers by Mode (VKM) and Number of Transportation Vehicle (NTV) are the most important variables that affect the gas emission. The results show that the multivariate linear regression model can be used to adequately model with coefficient of determination (R2) and adjusted R2 values of 85.1% and 83.2%, respectively. Keywords Multivariate regression, Urban logistic, Greenhouse Gas Emissions