Data Elements and the Dual Control of Carbon Emissions: A Perspective Based on Industry Differences

Achieving simultaneous control over total carbon emissions and intensity is essential for China’s dual carbon goals. Using panel data from 1235 listed manufacturing firms (2015–2022), we construct a composite index to measure dual carbon control and investigate how data elements influence corporate carbon performance from an industry heterogeneity perspective. The main findings are as follows. (1) Data elements significantly enhance dual carbon control, with effects concentrated in high-pollution sectors, particularly metallurgy and mineral products, while remaining insignificant in low-pollution industries. (2) Mechanisms differ across industry types: capacity utilization drives improvements in high-pollution industries, whereas green technology innovation matters in low-pollution sectors such as agro-processing and textiles. (3) ESG disclosure and green credit subsidies amplify these effects, though with varying efficacy. Policymakers should adopt differentiated strategies including removing structural barriers to green innovation in high-pollution industries and activating capacity utilization through monitoring standards and technology markets in low-pollution sectors. A tailored policy framework is essential to realize the full potential of data elements in advancing China’s dual carbon goals.

Authors

Institutions

Publication Details

Journal
Systems
Published
2026-03-15
DOI
https://doi.org/10.3390/systems14030305
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Data Elements and the Dual Control of Carbon Emissions: A Perspective Based on Industry Differences

Na Liu, Ying Su
Systems
Energy, Environment, Economic Growth
article

Data Elements and the Dual Control of Carbon Emissions: A Perspective Based on Industry Differences

Na Liu, Ying Su
article en

Abstract

Achieving simultaneous control over total carbon emissions and intensity is essential for China’s dual carbon goals. Using panel data from 1235 listed manufacturing firms (2015–2022), we construct a composite index to measure dual carbon control and investigate how data elements influence corporate carbon performance from an industry heterogeneity perspective. The main findings are as follows. (1) Data elements significantly enhance dual carbon control, with effects concentrated in high-pollution sectors, particularly metallurgy and mineral products, while remaining insignificant in low-pollution industries. (2) Mechanisms differ across industry types: capacity utilization drives improvements in high-pollution industries, whereas green technology innovation matters in low-pollution sectors such as agro-processing and textiles. (3) ESG disclosure and green credit subsidies amplify these effects, though with varying efficacy. Policymakers should adopt differentiated strategies including removing structural barriers to green innovation in high-pollution industries and activating capacity utilization through monitoring standards and technology markets in low-pollution sectors. A tailored policy framework is essential to realize the full potential of data elements in advancing China’s dual carbon goals.

SystemsVol. 14(3)
Qingdao University of Technology (CN)
Natural Science Foundation of Shandong Province
Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Energy, Environment, Economic Growth
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.