Nonlinear impacts of industrial intelligence on synergistic reduction of pollution and carbon emissions: The role of technological factors

Bangzhu Zhu, Gang Chen and Ping Wang

Energy Economics, 2025, vol. 149, issue C

Abstract: The integration of digital and intelligent technologies into industrial processes positions industrial intelligence as a potential driver of improved environmental performance. However, its role in the synergistic reduction of pollution and carbon emissions (PCSR) under varying technological conditions remains underexplored. This study compiles data on industrial intelligence, greenhouse gas emissions, and pollutant emissions across China, and quantifies both the level of industrial intelligence and the degree of PCSR. By incorporating technological factors into the transition function, we employ panel smooth transition regression (PSTR) and instrumental variable PSTR models to examine the nonlinear effects of industrial intelligence on PCSR. Results show that industrial intelligence significantly improves PCSR, but its marginal effect declines after technological thresholds are exceeded. Moreover, the effect of industrial intelligence on PCSR differs significantly across technological threshold levels. Specifically, key thresholds are identified for R&D investment (14.940), digital economy development (0.284), and innovation output (2.761). Mechanism analysis reveals that green technological innovation, total factor productivity improvements, and industrial structure upgrading are key channels through which industrial intelligence promotes PCSR. Significant regional heterogeneity is also observed. The positive impact of industrial intelligence on PCSR is substantially greater in coastal regions than in inland areas. In regions with stricter environmental regulations, policy pressure further amplifies this effect. In regions with a higher share of clean energy consumption, industrial intelligence yields the most pronounced emission reduction benefits. Our findings provide effective pathways and policy recommendations for achieving synergistic emissions reduction.

Keywords: Industrial intelligence; Synergistic reduction of pollution and carbon emissions; Nonlinear impact; Technological factors (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140988325006243
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:149:y:2025:i:c:s0140988325006243

DOI: 10.1016/j.eneco.2025.108797

Access Statistics for this article

Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().