实现全球碳中和是不可阻挡的历史大势，而能源绿色低碳转型是必由之路，在此过程中保障能源安全是能源政策关注的优先事项。我国提出积极稳妥推进碳达峰碳中和，在此要求下，研究低碳转型背景下的能源安全风险、保障措施及其潜在影响对我国具有重要的现实意义和决策参考价值。本研究基于多属性决策分析和全球变化分析模型（GCAM），对中国历史和未来低碳转型背景下的能源安全变化趋势以及加强能源安全政策的潜在影响进行分析。本研究首先构建了评估中国能源安全状况的评价指标体系，利用中国2000~2021年的历史数据对能源安全变化趋势及其驱动力进行回顾性分析。接下来基于GCAM对中国未来不同低碳转型情景进行模拟，评估了未来能源安全的变化趋势，进而识别了低碳转型背景下能源安全面临的潜在风险。最后，本研究探讨了低碳转型背景下加强能源安全政策综合情景在能源安全、气候、环境、能源投资支出等政策目标之间的协同和权衡关系。研究结果表明，中国历史能源安全指数呈现波动上升趋势，能源安全指数从2000年的34.1上升到2021年的61.3，变化的驱动力在不同时间阶段存在差异。在不同典型低碳转型情景下，中国2025~2060年的能源安全指数长期来看将继续上升，但相对激进的减排情景下能源安全指数在不同时间阶段显示出波动。GCAM模拟结果显示，不同低碳转型情景下，中国未来的能源安全在化石能源供应和贸易、电力供应、非化石能源消费占比等方面存在风险，表明气候目标和能源安全目标之间可能存在权衡。针对潜在风险设计的加强能源安全综合情景具备可行性，相比于无加强能源安全措施的情景，综合情景将进一步提升能源安全指数表现，实现温室气体的进一步减排，但可能面临其他政策目标的权衡。综合情景到2060年的累计水资源消耗量增加0.1%~1.1%，累计能源投资支出增加6.5%~14.2%，相当于同期累计GDP的0.2%~0.4%。此外，综合情景对其他空气污染物累计排放量的影响取决于措施力度，力度较弱的情景空气污染物累计排放量可能上升，而力度较强的情景空气污染物累计排放量有望下降。
The realization of global carbon neutrality is an unstoppable trend, and the green and low-carbon energy transition is an inevitable path, in which guaranteeing energy security is a priority of energy policy. China proposes to actively and steadily promote carbon peaking and carbon neutrality. In response to such requirements, the analysis of energy security risks, safeguard measures and potential impacts in the context of low-carbon transition is of great practical significance and reference value for decision-making to China.This study analyzed the changing trends of China’s energy security in the context of its historical and future low-carbon transition as well as the potential impacts of strengthening energy security policies based on the Multiple Attribute Decision Analysis method and Global Change Analysis Model (GCAM). This study first constructed an evaluation index system for assessing China’s energy security, and retrospectively analyzed China‘s energy security dynamics and driving forces using historical data from 2000 to 2021. Next, this study simulated different low-carbon transition scenarios based on the GCAM, assessed the trend of China’s future energy security, and subsequently identified the potential risks facing energy security in the context of low-carbon transition. Finally, this study explored the synergies and trade-offs between the policy objectives of energy security, climate, environment, and energy investment expenditure in the context of low-carbon transition under the integrated scenarios with strengthening measures for the energy security.The results are as followed. China’s historical energy security index shows a fluctuating upward trend, with the energy security index increasing from 34.1 in 2000 to 61.3 in 2021, and the drivers of change varying across time. Under different low-carbon transition scenarios, China’s energy security index from 2025 to 2060 will continue to rise in the long term, but the energy security index under the relatively aggressive emission reduction scenarios shows fluctuations at different time stages. The GCAM simulation results show that, under different low-carbon transition scenarios, China’s future energy security faces risks in terms of the fossil fuel supply and trade, electricity supply, and share of non-fossil energy consumption, suggesting that there may be a trade-off between climate and energy security goals. The feasibility is demonstrated to enhance energy security to address potential risks under the low-carbon transition scenarios. Compared to scenarios without measures to enhance energy security, scenarios with strengthening measures will further improve the performance of the energy security index and achieve further GHG reductions, but may face trade-offs with other policy objectives. These scenarios could further increase cumulative water consumption by 0.1% to 1.1% by 2060 and cumulative energy investment expenditures by 6.5% to 14.2% by 2060, equivalent to 0.2% to 0.4% of cumulative GDP over the same period. In addition, the impact of the scenarios with strengthening measures on cumulative emissions of other air pollutants depends on the intensity of the measures, with cumulative emissions of air pollutants likely to increase in the weaker scenarios and expected to decrease in the stronger scenarios.
