| 基于STIRPAT-LEAP模型的陕西省增汇减排发展路径及驱动因素 |
| 摘要点击 484 全文点击 21 投稿时间：2025-02-13 修订日期：2025-04-11 |
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| 中文关键词 碳达峰 碳中和 RR-STIRPAT-LEAP-Shaanxi模型 联合情景设置 ReliefF分析 |
| 英文关键词 carbon peak carbon neutralization RR-STIRPAT-LEAP-Shaanxi model joint scenario setting ReliefF analysis |
| DOI 10.13227/j.hjkx.20260212 |
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| 中文摘要 |
| 中国作为全球碳排放大国，其省市区域贡献了全国90%以上的碳排放量. 如何准确预测不同省市区域的碳排放量并制定减排政策，是实现国家“双碳”目标以及经济高质量协同发展的基础. 以位于中国西北地区的陕西省为例，利用2000~2021年相关截面数据，建立自上而下与自下而上集成的RR-STIRPAT-LEAP模型，并通过优化子模型权重提升预测准确性. 在此基础上，预测2022~2060年陕西省碳排放量，结合碳汇吸收量模型设计5种联合情景仿真模拟陕西省“双碳”路径，并使用ReliefF算法分析碳减排重要潜力驱动因素. 结果发现，RR-STIRPAT-LEAP-Shaanxi模型预测精度显著优于单一模型，优化后的模型误差为0.24%. 预测陕西省2030年达峰，排放量（以CO2计）为41 909万t. 在联合情景macro-control-EMT-F下陕西省在2060前实现碳中和，排放量为-2 569万t，表明生态碳汇在实现碳中和过程中发挥重要作用. 对比不同联合情景下的碳排放变化情况发现，能源结构升级和能效提升是陕西省低碳转型的关键驱动力，且实施宏观经济和部门能耗综合调控的策略可以减少更多的碳排放量. ReliefF中表明陕西省碳减排侧重产业部门排序依次为：工业>发电部门>农业>居民部门>运输仓储邮政业>建筑业>其他服务业. 其中，农业不仅是重要的碳排放源，也是重要的碳汇，其减排潜力不可忽视. 在综合分析短期和中长期碳排放路径以及碳减排驱动因素后，通过给出陕西省增汇减排协同发展路径图，可为政府决策者和相关企业制定低碳高质量经济发展规划提供科学依据. |
| 英文摘要 |
| As a major global carbon emitter， China's provinces and municipalities contribute more than 90% of the country's carbon emissions， while the rest is mainly emitted by special administrative regions， trans-regional emission sources， and airspace and sea areas. How to accurately predict the carbon emissions of different provinces and municipalities and formulate emission reduction policies is the basis for realizing the national dual-carbon target and high-quality synergistic economic development. Taking Shaanxi Province， located in Northwest China， as an example， a top-down and bottom-up integrated RR-STIRPAT-LEAP model is developed using relevant cross-section data from 2000 to 2021， and the prediction accuracy is improved by optimizing the weights of sub-models. On this basis， the carbon emissions of Shaanxi Province from 2022 to 2060 are forecasted， and five joint scenarios are designed to simulate the dual-carbon pathway of Shaanxi Province in combination with the carbon sink absorption model. The ReliefF algorithm is used to analyze the important potential drivers of carbon emission reduction. The results found that the prediction accuracy of the RR-STIRPAT-LEAP-Shaanxi model was significantly better than that of a single model， and the optimized model error was 0.24%. It was predicted that Shaanxi Province will reach its peak in 2030， and the emissions （in terms of tons） will be 419.09 million tons （Mt）. Under the joint scenario， macro-control-EMT-F Shaanxi Province will achieve carbon neutrality by 2060， with an emission of -25.69 million tons， indicating that ecological carbon sinks played an important role in achieving carbon neutrality. Comparison of carbon emission changes under different joint scenarios revealed that upgrading the energy structure and improving energy efficiency were the key drivers of Shaanxi Province's low-carbon transition and that the implementation of macroeconomic and sectoral energy consumption control strategies could reduce more carbon emissions. ReliefF showed that Shaanxi Province's carbon emission reduction focused on the following industrial sectors in order： industry > power generation > agriculture > residential sector > transportation， storage， and postal services > construction > other services. Among them， agriculture was not only an important source of carbon emissions but also an important carbon sink， and its potential for emission reduction should not be ignored. After comprehensively analyzing the short and medium to long-term carbon emission pathways and carbon emission reduction drivers， this study provides a pathway map for the synergistic development of Shaanxi Province， which will provide a scientific basis for government policymakers and relevant enterprises to formulate low-carbon and high-quality economic development plans. |
