徐舜天,王灿,朱俊明.支撑深度脱碳的技术研发投资配置与路径优化[J].中国环境管理,2026,18(3):49-59.
XU Shuntian,WANG Can,ZHU Junming.Investment Allocation and Pathway Optimization for Technology R&D Supporting Deep Decarbonization[J].Chinese Journal of Environmental Management,2026,18(3):49-59. |
| 支撑深度脱碳的技术研发投资配置与路径优化 |
| Investment Allocation and Pathway Optimization for Technology R&D Supporting Deep Decarbonization |
| DOI：10.16868/j.cnki.1674-6252.2026.03.049 |
| 中文关键词: “双碳”目标 科技创新 研发投资 路径优化 |
| 英文关键词:carbon peaking and carbon neutrality targets technological innovation R&D investment pathway optimization |
| 基金项目:国家重点研发计划政府间国际创新合作项目“区域绿色低碳转型的环境—经济—社会耦合机制与实现路径研究”（2023YFE0104600）；国家自然科学基金委中美国际合作项目“面向城乡协调发展的区域碳中和路径优化”（T2261129475）。 |
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| 中文摘要: |
| 碳达峰碳中和目标的实现需要持续的低碳技术进步与规模化应用。对研发的投资配置是驱动低碳技术进步的关键，涉及投资强度、时间路径及技术类型的优化决策。本文构建具有内生技术进步的中国能源经济优化模型，根据研发回报不确定性特征区分先进适用技术与前沿突破性技术两类研发方向，并基于多阶段随机动态优化框架分析了面向“双碳”目标的最优研发投资路径。结果表明，研发回报不确定性推高了前沿突破性技术的最优投入强度，为了把握不确定性下的“高风险高回报”机会，应保持较高研发强度以确保长期减排的可行性和成本效益。根据减排时序与人口情景进一步分析宏观趋势性因素的影响，本文发现提前行动、线性、延迟行动三类碳中和路径的研发投资从近中期就开始显现分化趋势，表明研发投资部署规划需整体考虑气候政策的长期取向；低人口情景要求的前沿突破性技术研发投资比中、高情景可高出逾一倍，为社会经济结构变迁的系统影响提供了一个情景例证。基于此，本文建议系统完善针对成熟与新兴技术研发创新活动的支持体系，强化跨领域跨部门的系统协同，建立前瞻性的技术预见与评估机制。 |
| 英文摘要: |
| Achieving CO2 peaking and carbon neutrality targets requires sustained low-carbon technological progress and largescale deployment. Investment allocation in R&D is the key driver of low-carbon technological progress, involving joint decisions over investment intensity, timing, and technology portfolios. This study develops a China energy-economy optimization model with endogenous technological change. It distinguishes between advanced applicable technologies and frontier breakthrough technologies based on the uncertainty characteristics of R&D returns, and analyzes the optimal R&D investment pathways toward carbon peaking and carbon neutrality targets using a multi-stage stochastic dynamic optimization framework. The results show that uncertainty in R&D returns substantially increases the optimal investment intensity for frontier breakthrough technologies. To capture the “high-risk, high-reward” opportunities under uncertainty, maintaining a relatively high level of R&D effort is essential for ensuring the feasibility and cost-effectiveness of longterm emission reductions. Further analysis incorporating mitigation timing and population scenarios reveals that R&D investment trajectories begin to diverge in the near to medium term across early-action, linear, and delayed-action decarbonization pathways, indicating that R&D deployment strategies need to account for the long-term orientation of climate policy. The low-population scenario requires more than twice the R&D investment in frontier breakthrough technologies compared to medium- and high-population scenarios, providing a scenario-based illustration of the systemic influence of socio-economic structural changes. Based on these findings, the paper recommends systematically strengthening the support systems for innovation activities across both mature and emerging technologies, enhancing cross-sectoral and cross-disciplinary coordination, and establishing forward-looking mechanisms for technology foresight and assessment. |
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