Digital intelligence and synergy of pollution reduction and carbon reduction: “Dividend” or “gap”?
At the intersection of the “dual carbon” goal and the era of digital intelligence (DI), exploring the synergy between pollution and carbon reduction (SPCR) within the context of DI is important for promoting a comprehensive green transformation of economic and social development. This study, based on urban panel data from 281 prefecture-level cities in Mainland China from 2010 to 2020, developed a DI indicator system for these cities and employed a double machine learning algorithm for the first time to investigate the intrinsic mechanisms and incentivizing effects of DI on SPCR. The results showed that: ① DI significantly promotes SPCR. ② Mechanism tests demonstrated that DI can indirectly enhance SPCR by optimizing resource allocation and reinforcing government interventions. ③ Further analysis showed that the impact of DI on SPCR was more substantial in regions with lower levels of economic and environmental competition. Moreover, the SPCR driven by DI exhibited heterogeneity, characterized by stronger effects in “resource-based cities > non-resource-based cities” and “non-capital economic zones > capital economic zones”. The conclusions of this study hold significant implications for fully harnessing the synergy between digitization and intelligence to empower SPCR. In addition, the findings are valuable for the government’s integrated promotion of the “dual carbon” goal and the “digital China” strategy.
Authors
- Xianfeng Han
- Jian Xiao (ORCID: https://orcid.org/0000-0003-4272-6865)
- Longtao Chen
- Jiajia Li (ORCID: https://orcid.org/0000-0002-8609-900X)
- Tonglei Zhang
Institutions
- Kunming University of Science and Technology (CN)
- Xinjiang University of Finance and Economics (CN)
Publication Details
- Journal
- Chinese Journal of Population Resources and Environment
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1016/j.cjpre.2024.11.003
- Citations
- 2
- Primary Topic
- Energy, Environment, Economic Growth
- Type
- article
- Field-Weighted Citation Impact
- 2.26
Funders
- National Natural Science Foundation of China