In Northern China, heavy trucks are common on highways. Vehicles traveling on longitudinal sections of expressways produce higher carbon emissions. Current carbon emission models include the vehicular operating conditions, but do not reveal the influence of highway alignment conditions, such as the longitudinal gradient and slope length, on emissions. To address this problem, this study attempts to relate the design parameters of longitudinal roadway segments with carbon emissions, as derived from diesel fuel consumption data, using an iterative nonlinear multiple regression method. Diesel fuel consumption data were collected through field tests along two typical overloaded expressways in China’s coal-producing regions. The associated carbon emission data were calculated using the method defined by the Intergovernmental Panel on Climate Change. Using this data, a carbon emission prediction model was developed that related carbon emissions with roadway segment gradients, segment slope length, and initial vehicle speed. The proposed model was verified using the field test data. A relative error of 4.9% between predicted and observed data suggested high accuracy and applicability for the proposed prediction model.
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