城市数智化发展的降碳效应

王凤娟，张明斗

（东北财经大学 经济学院，辽宁 大连 116025）

摘要：在大数据时代背景下，深入探究城市数智化发展的降碳效应，对于实现“双碳”目标、助推经济高质量发展有重要意义。本文以中国256个地级及以上城市为研究样本，实证分析2014—2023年城市数智化发展的降碳效应与作用机制。研究发现：城市数智化发展能够降低碳排放强度，此结论在经过缓解内生性问题、剔除特殊年份以及替换核心解释变量的测度方法等一系列检验后依然成立。异质性分析发现，城市数智化发展的降碳效应因城市地理区位、城市规模以及城市行政等级的不同而存在异质性。具体而言，数智化发展降低了中西部地区城市、小城市以及外围城市的碳排放强度更为明显。机制分析发现，城市数智化发展能够通过增加政府环保投资以及推动企业绿色技术创新两条途径降低碳排放强度。进一步研究发现，城市数智化发展对碳减排具有显著的正向空间溢出效应。本文的研究结论为进一步明确城市数智化发展的环境治理效应及拓展碳减排的治理路径提供了实证参考。

基金项目：国家社会科学基金重点项目“青年就业新动向、新问题及其政策机制研究”（24AJY021）

关键词：城市数智化发展；碳排放强度；政府环保投资；企业绿色技术创新；绿色低碳发展

作者简介：王凤娟，东北财经大学经济学院博士研究生；张明斗，东北财经大学经济学院教授。

引用格式：王凤娟，张明斗. 城市数智化发展的降碳效应［J］. 首都经济贸易大学学报，2026，28（5）：45-57.

Carbon Reduction Effect of Urban Digital-Intelligent Development

WANG Fengjuan, ZHANG Mingdou

（Dongbei University of Finance and Economics, Dalian 116025）

Abstract: During the critical period of China's pursuit of Chinese modernization, green and low-carbon development has become a strategic pathway for coordinating high-quality economic development with high-level ecological and environmental protection. At present, China's industrial and energy structures still exhibit considerable rigidity, and the pressure to reduce carbon emissions remains substantial. As a key vehicle of the new round of technological revolution, digitalization and intelligentization have opened up new avenues for carbon emission governance. Compared with total carbon emissions, carbon emission intensity more objectively reflects the true level of urban low-carbon development. Against this backdrop, a systematic examination of the carbon-reduction effects of urban digital-intelligent development is of great significance for unlocking the environmental dividends of digitalization and promoting urban green transformation.

Using a sample of 256 Chinese cities at the prefecture level and above, this study empirically analyzes the carbon- reduction effects and mechanisms of urban digital-intelligent development from 2014 to 2023. The results show that urban digital-intelligent development significantly reduces carbon emission intensity. Mechanism analysis indicates that such development lowers carbon emission intensity through two channels: increasing government environmental investment and promoting corporate green technology innovation. Heterogeneity analysis reveals that the carbon- reduction effect is more pronounced in cities in the central and western regions, small cities, and peripheral cities. Further analysis demonstrates that urban digital-intelligent development exerts a significant positive spatial spillover effect on carbon reduction.

This study offers the following policy implications. First, urban digital-intelligent development should be advanced in a coordinated manner to consolidate the foundation for carbon governance. Second, differentiated governance strategies should be implemented to tap the carbon-reduction potential of digital-intelligent development in a targeted manner. Third, green governance foundations should be strengthened through multiple channels to stimulate the vitality of diverse governance actors. Fourth, inter-city coordination should be enhanced to achieve regional environmental co-governance and common progress.

This study provides three key contributions. First, it integrates urban digital-intelligent development and carbon emission intensity into a unified analytical framework, systematically examining the impact and spatial spillover effects of digital-intelligent development on carbon emission intensity, thereby enriching research on the environmental governance effects of urban digital-intelligent development. Second, from the dual dimensions of the government environmental investment effect and the corporate green technology innovation effect, it identifies the internal mechanisms through which urban digital-intelligent development affects carbon emission intensity, providing empirical evidence for further clarifying the channels of influence. Third, it investigates the heterogeneous effects from the perspectives of geographical location, city size, and administrative hierarchy, offering a theoretical basis for precisely formulating differentiated environmental governance strategies and optimizing urban digital-intelligent development pathways across regions.

Keywords: urban digital-intelligent development; carbon emission intensity; government environmental protection investment; enterprise green technology innovation; green and low-carbon development

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