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Peer-reviewedCC BY 4.0Frontiers in Public Health

Synergistic impacts of low-carbon city pilot policy and information consumption pilot policy on carbon lock-in

  • Yan Peng1
  • Rongguang Zhang2
  1. 1School of Digital Economy, Sichuan University Jinjiang College
  2. 2College of Management Science, Chengdu University of Technology
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Abstract

Introduction: Carbon lock-in poses a significant barrier to the low-carbon transition, necessitating synergistic policy interventions.

Methods: Using a dual machine learning (DML) model, this study estimates carbon lock-in data for 262 Chinese cities and examines how the dual policy (the low-carbon city pilot and information consumption pilot policy) affects carbon lock-in.

Results: The dual policy significantly suppresses carbon lock-in, with a markedly stronger effect than implementing either policy in isolation. The analysis indicates that the dual policy works through industrial structure upgrading, government environmental support, climate technology innovation, and public climate concern. Additionally, the heterogeneity test reveals that the suppressive effect is more pronounced in non-resource-based cities, large cities, and those with high market vitality and strong financial regulation.

Discussion: Consequently, this study provides evidence for promoting the synergistic implementation of the low-carbon city pilot and the information consumption pilot policy, thereby breaking carbon lock-in.

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Cite

BibTeXRIS
BibTeX
@article{peng2026synergistic,
  title = {{Synergistic impacts of low-carbon city pilot policy and information consumption pilot policy on carbon lock-in}},
  author = {Yan Peng and Rongguang Zhang},
  journal = {Frontiers in Public Health},
  year = {2026},
  month = oct,
  doi = {10.3389/fpubh.2026.1929422},
  url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1929422/full},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Synergistic impacts of low-carbon city pilot policy and information consumption pilot policy on carbon lock-in
AU  - Yan Peng
AU  - Rongguang Zhang
PY  - 2026
DA  - 2026/10/09
JO  - Frontiers in Public Health
DO  - 10.3389/fpubh.2026.1929422
UR  - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1929422/full
AB  - Introduction: Carbon lock-in poses a significant barrier to the low-carbon transition, necessitating synergistic policy interventions.  Methods: Using a dual machine learning (DML) model, this study estimates carbon lock-in data for 262 Chinese cities and examines how the dual policy (the low-carbon city pilot and information consumption pilot policy) affects carbon lock-in.  Results: The dual policy significantly suppresses carbon lock-in, with a markedly stronger effect than implementing either policy in isolation. The analysis indicates that the dual policy works through industrial structure upgrading, government environmental support, climate technology innovation, and public climate concern. Additionally, the heterogeneity test reveals that the suppressive effect is more pronounced in non-resource-based cities, large cities, and those with high market vitality and strong financial regulation.  Discussion: Consequently, this study provides evidence for promoting the synergistic implementation of the low-carbon city pilot and the information consumption pilot policy, thereby breaking carbon lock-in.
SN  - 2296-2565
ER  -