Unveiling the Dynamic Interplay of Industrial Carbon Emissions: Insights from Quantile Time–Frequency Analysis

Reducing carbon emissions in the industrial sector is a critical component of achieving green and sustainable development. We employ quantile vector autoregressive methods to analyze the dynamic interactions of industrial carbon emissions across various countries. Initially, we observe that, under normal conditions, developed countries led by the EU exhibit a significant total spillover effect. Secondly, during extreme quantile conditions, the spillover effects of EU-led developed countries shift from positive to negative, whereas in the UK, the opposite trend is observed. This highlights the importance of considering carbon transfer’s role in emission reduction during extreme quantile scenarios. Thirdly, we find that China’s industrial carbon emissions spillover effects remain relatively stable at all times. Lastly, total spillover effects are highly volatile during extreme market conditions, such as the COVID-19 pandemic. These findings will help clarify each country’s emission reduction responsibilities within the international industrial system and facilitate a more equitable allocation of emission reduction tasks.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2025-09-25
DOI
https://doi.org/10.3390/su17198626
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unveiling the Dynamic Interplay of Industrial Carbon Emissions: Insights from Quantile Time–Frequency Analysis

D. Liu, Wei Jiang, Xiaoliang Guo, Xuantao Wang et al.
Sustainability
Environmental Impact and Sustainability
article

Unveiling the Dynamic Interplay of Industrial Carbon Emissions: Insights from Quantile Time–Frequency Analysis

D. Liu, Wei Jiang, Xiaoliang Guo, Xuantao Wang, Xin Li
article en

Abstract

Reducing carbon emissions in the industrial sector is a critical component of achieving green and sustainable development. We employ quantile vector autoregressive methods to analyze the dynamic interactions of industrial carbon emissions across various countries. Initially, we observe that, under normal conditions, developed countries led by the EU exhibit a significant total spillover effect. Secondly, during extreme quantile conditions, the spillover effects of EU-led developed countries shift from positive to negative, whereas in the UK, the opposite trend is observed. This highlights the importance of considering carbon transfer’s role in emission reduction during extreme quantile scenarios. Thirdly, we find that China’s industrial carbon emissions spillover effects remain relatively stable at all times. Lastly, total spillover effects are highly volatile during extreme market conditions, such as the COVID-19 pandemic. These findings will help clarify each country’s emission reduction responsibilities within the international industrial system and facilitate a more equitable allocation of emission reduction tasks.

SustainabilityVol. 17(19)
Qingdao University (CN), Guangdong University of Finance (CN)
Openalex Percentile: Top 76%
Environmental Impact and Sustainability
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.

Unveiling the Dynamic Interplay of Industrial Carbon Emissions: Insights from Quantile Time–Frequency Analysis — D. Liu, Wei Jiang, et al. · Sustainability (2025) | TGRS Research Map | TGRS