Abstract
A high-quality grain distribution system is the key to guarantee the balance of grain supply and demand, and the reduction of greenhouse gas emissions in grain transportation is the concern of the government and enterprises. In order to clarify the influence of different low-carbon policies and loading modes on the optimization of grain multimodal transport paths, this paper constructs a low-carbon grain multimodal transport path optimization model with the objective of minimizing transportation, cargo loss, time and carbon emission costs. Taking Jiamusi City, the main grain producing area in China, as an example, a heuristic genetic algorithm is used to solve the model to explore the impacts of carbon tax policy (CTP), carbon emission trading scheme (ETS) policy and carbon offset policy (COP) on the transportation schemes of grain in three loading modes, namely, "bagged, bulk and containerized". We analyze the effects of carbon price fluctuations on decision-making under low carbon quota, medium carbon quota and high carbon quota scenarios, and study the effects of different cost preference values on transportation decision-making under the ETS policy. Under the ETS policy, the optimal transportation path of each loading mode has the lowest total cost, and the total cost is reduced by 1% compared with that of carbon tax and carbon offset policy. Among them, the containerized rail-water intermodal transportation scheme has obvious cost and environmental advantages, with the total cost decreasing by 42% and 33% compared to bag and bulk, and the carbon emission decreasing by 27% compared to both. With the overall relaxation of the time window, the transportation scheme is transformed from road-rail intermodal transportation to rail-water intermodal transportation. In addition, when the carbon price is RMB 2/kgCO[Formula: see text] and above, it can promote the transportation transition to low-carbon rail-water intermodal transportation, and the high carbon quota under the ETS policy can motivate enterprises to realize cost reduction and efficiency. The findings of the study can provide reference for grain transportation enterprises to formulate multimodal transportation solutions and provide theoretical support for the government to formulate low-carbon policies.