基于WOA-ELM的上海市交通碳排放测算及情景分析

Measurement and Scenario Analysis of Shanghai’s Transport Carbon Emissions Based on WOA-ELM

本研究旨在评估上海市交通部门碳排放能否在2030年前实现碳达峰目标。首先,本研究通过STIRPAT模型筛选出9项指标作为上海市交通碳排放影响因素,随后基于WOA-ELM算法构建了碳排放预测模型,并以1995~2019年上海市交通碳排放相关数据为基础数据,使用MATLAB软件搭建模型,对上海市2020~2040年的交通碳排放量进行预测。通过与岭回归、传统ELM模型的预测结果对比,本研究提出的碳排放预测模型具有较高的准确性,同时设置各特征值变化率组合,提出5种情景,运用情景分析法对上海市2040年前的交通碳排放量做出预测,最终得出结论:上海交通需要平衡经济与交通发展、在能源结构方面持续创新、指定完善的减排政策。

This study aims to assess whether Shanghai’s transportation sector can achieve peak carbon emis-sions before 2030. Firstly, the research identifies nine indicators as influencing factors for Shang-hai’s transportation carbon emissions using the STIRPAT model. Subsequently, a carbon emissions prediction model based on the WOA-ELM algorithm is constructed, utilizing data related to Shang-hai’s transportation carbon emissions from 1995 to 2019. The MATLAB software is used to build the model and predict transportation carbon emissions in Shanghai from 2020 to 2040. By comparing the prediction results with ridge regression and traditional ELM models, the carbon emissions pre-diction model proposed in this study demonstrates high accuracy. Various combinations of eigen-value change rates are set, and five scenarios are proposed. Scenario analysis is employed to fore-cast transportation carbon emissions in Shanghai up to 2040. The final conclusion drawn is that Shanghai’s transportation sector needs to balance economic and transportation development, con-tinue to innovate in terms of energy structure, and implement sound emission reduction policies.