城市群经济-能源-碳排放系统协同状态提升的条件组态与驱动路径——基于NCA与动态fsQCA的京津冀证据

摘要

城市群经济-能源-碳排放系统协同状态的提升路径具有显著因果复杂性，传统回归框架下的单因素净效应难以刻画多重条件并发的驱动逻辑。以京津冀城市群13个城市2010—2024年面板为样本，以耦合协调度作为协同状态的代理测度，集成必要条件分析与动态模糊集定性比较分析方法，从规模、结构、效率三维框架遴选经济规模、产业结构、能源结构、能源效率、清洁技术与碳效率6项前因条件，识别高协同与非高协同状态的条件组态及其跨期演化。研究发现：单一条件不构成协同状态提升的严格必要条件，但经济规模、产业结构、能源结构与清洁技术呈大效应量必要性特征，各条件瓶颈水平随协同目标提高呈阶梯式陡增；高协同状态存在多维复合驱动与规模-技术补偿驱动两条等效路径，非高协同状态由要素缺失联合与效率失衡联合两条路径锁定，两类结果的生成逻辑呈显著因果非对称性；组态跨期一致性稳健，条件作用强度呈持续增强、持续衰减与倒U型三类演化模式。研究结论为城市群差异化低碳协同治理提供了组态证据。

Abstract

The enhancement of the synergistic state of the economy-energy-carbon emission (EEC) system in urban agglomerations exhibits significant causal complexity, and the net effects of single factors under traditional regression frameworks fail to capture the driving logic of multiple concurrent conditions. Taking panel data of 13 cities in the Beijing-Tianjin-Hebei urban agglomeration from 2010 to 2024 as the research sample, this study employs the coupling coordination degree as a proxy measure of the synergistic state, integrates Necessary Condition Analysis (NCA) with dynamic fuzzy-set Qualitative Comparative Analysis (fsQCA), and selects six antecedent conditions, namely economic scale, industrial structure, energy structure, energy efficiency, clean technology and carbon efficiency, from the scale-structure-efficiency framework to identify the conditional configurations leading to high and non-high synergistic states as well as their temporal evolution. The results show that: no single condition constitutes a strictly necessary condition for synergistic state enhancement, but economic scale, industrial structure, energy structure and clean technology exhibit necessity characteristics with large effect sizes, and the bottleneck levels of all conditions rise in a stepwise manner as the synergy target increases; two equivalent paths exist for high synergistic states, namely multi-dimensional composite driving and scale-technology compensating driving, whereas non-high synergistic states are locked in by two paths featuring the joint absence of endowments and the imbalance of efficiency, revealing significant causal asymmetry between the two types of outcomes; the configurations are temporally robust, and the action intensity of conditions evolves in three patterns, namely continuous strengthening, continuous decay and inverted-U fluctuation. The findings provide configurational evidence for differentiated low-carbon synergistic governance of urban agglomerations.