Carbon Emission Prediction Method for Inland Ports Based on an Improved ASIF Model

Addressing the complexities and low accuracy of prediction associated with medium-to-long-term forecasting of port carbon emissions, this study proposes a carbon emission prediction (CEP) model for inland container ports based on an improved activity-modal structure-energy intensity-emission factor (ASIF) method. The objective is to quantify the impact of primary factors on long-term port carbon emissions, thereby providing a basis for targeted carbon neutrality strategies. By considering port container throughput, equipment structure, energy consumption intensity, and emission factors as influential factors of port carbon emissions, and accounting for the "multi-process, multi-equipment" characteristics within the container transportation chain, an improved ASIF model is established, which enables CEP from macro to micro levels. A scenario prediction indicator system is developed based on the explanatory variables of the ASIF model. Taking a container port on the Yangtze River as an example, predictions are made for its throughput, equipment composition, and transportation structure under the business-as-usual (BAU) scenario and the low-carbon (LC) scenario. Subsequently, carbon emissions from ship navigation, ship berthing, quay cranes, internal container trucks, yard cranes, and external container trucks are calculated. Lastly, to analyze the emission reduction potential under different low-carbon development strategies, a single-factor experimental approach is employed. The results indicate that: ①compared to existing prediction models, the deviations of carbon emission by the improved ASIF are within 10%. ②Under BAU and LC scenarios for the case port, with the continuous growth of container throughput, carbon emissions have not yet peaked by the year 2060 in the BAU scenario, whereas they are projected to the peak around the year 2055 in the LC scenario. ③Ship emission control, energy efficiency improvement, energy structure optimization, and collection and distribution system optimization are all effective low-carbon development strategies, albeit with decreasing effectiveness. ④Between the year 2020 to 2060, these strategies could achieve cumulative carbon reductions of approximately 190 000, 170 000, 144 000, and 11 000 t, respectively.