A soybean supply chain model to analyze the greenhouse gas emissions of the transport sector

VERRENGIA, MILAGROS; VECCHIETTI, ALDO

Computer Aided Chemical Engineering

Elsevier B.V.

Año: 2022 vol. 51 p. 1327 - 1332

1570-7946

This article presents a mathematical model of the soybean´s supply chain for Argentina where the different stakeholders and the material flows among them are represented. The transport used in this sector are trucks, trains, and river ships. The objective is to analyze the emissions of greenhouse gases (GHG) generated by the transportation in this sector using electric trucks as an alternative to biodiesel ones. The model generated is a mixed multi-period / multi-objective linear integer model, destined at minimizing operating and GHG emissions cost. The accuracy of the model is compared against two statistical studies made by the Transport Agency of Argentina in 2014 and 2017 regarding the soybean transportation. The results show a good fit with those reports. Two scenarios are compared, in the first one only biodiesel trucks are used for transportation, while in the second one trains, barges and electric trucks are included. Results show the tradeoff between investment costs and reduction of emissions where it is possible to achieve a 60% GHG decrease, which is far to compensate for the investment cost.