Ecological footprint analysis as a tool for advancing sustainable development goals (SDGs): Evidence from China

• This paper examines Ecological Footprint use for SDGs in China, focusing on sustainability. • The study employs time series data for the period 1995 to 2023, and employed Vector Error Correction Model and Autoregressive Distributed Lag Cointegration analysis. • Based on the analysis of China’s ecological footprint the study explores the link between growth, resources, and the environment. The growing environmental pressures linked to resource consumption and economic expansion in China necessitate a more integrated approach to sustainable development. This study explores the critical role of Ecological Footprint Analysis in aligning China’s development trajectory with Sustainable Development Goals (SDGs) by investigating the dynamic relationships between renewable energy consumption (REC), CO 2 emissions, ecological footprint growth (EFG), governance effectiveness (GE), urbanization (UP), population growth (PG), and GDP per capita (GDPPC). Using time series data from 1995 to 2023, the study applies a Vector Error Correction Model (VECM), Autoregressive Distributed Lag (ARDL) analysis, and Fully Modified Ordinary Least Squares (FMOLS) to capture both long-term equilibrium and short-run dynamics. The findings reveal that ecological footprint growth significantly drives renewable energy adoption as environmental stress increases; governance effectiveness positively influences renewable energy use but with limited strength in mitigating emissions; GDP per capita initially raises CO 2 emissions, validating the Environmental Kuznets Curve hypothesis; and urbanization, while contributing to short-term emissions, gradually promotes renewable energy transitions through infrastructure modernization. Policy implications underscore the urgent need for China to integrate circular economy practices, green urban planning, and stronger governance frameworks to effectively decouple economic growth from ecological degradation and achieve long-term sustainability goals.

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Publication Details

Journal
Ecological Indicators
Published
2025-06-02
DOI
https://doi.org/10.1016/j.ecolind.2025.113653
Citations
8
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
6.39

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article

Ecological footprint analysis as a tool for advancing sustainable development goals (SDGs): Evidence from China

Ning Cao, Jing Zhang, David Lee, Jie Wu et al.
8 citations
Ecological Indicators
Environmental Impact and Sustainability
6.39
article

Ecological footprint analysis as a tool for advancing sustainable development goals (SDGs): Evidence from China

Ning Cao, Jing Zhang, David Lee, Jie Wu, Jawad Khan, Haozhe Yu
article en
8 citations

Abstract

• This paper examines Ecological Footprint use for SDGs in China, focusing on sustainability. • The study employs time series data for the period 1995 to 2023, and employed Vector Error Correction Model and Autoregressive Distributed Lag Cointegration analysis. • Based on the analysis of China’s ecological footprint the study explores the link between growth, resources, and the environment. The growing environmental pressures linked to resource consumption and economic expansion in China necessitate a more integrated approach to sustainable development. This study explores the critical role of Ecological Footprint Analysis in aligning China’s development trajectory with Sustainable Development Goals (SDGs) by investigating the dynamic relationships between renewable energy consumption (REC), CO 2 emissions, ecological footprint growth (EFG), governance effectiveness (GE), urbanization (UP), population growth (PG), and GDP per capita (GDPPC). Using time series data from 1995 to 2023, the study applies a Vector Error Correction Model (VECM), Autoregressive Distributed Lag (ARDL) analysis, and Fully Modified Ordinary Least Squares (FMOLS) to capture both long-term equilibrium and short-run dynamics. The findings reveal that ecological footprint growth significantly drives renewable energy adoption as environmental stress increases; governance effectiveness positively influences renewable energy use but with limited strength in mitigating emissions; GDP per capita initially raises CO 2 emissions, validating the Environmental Kuznets Curve hypothesis; and urbanization, while contributing to short-term emissions, gradually promotes renewable energy transitions through infrastructure modernization. Policy implications underscore the urgent need for China to integrate circular economy practices, green urban planning, and stronger governance frameworks to effectively decouple economic growth from ecological degradation and achieve long-term sustainability goals.

Ecological IndicatorsVol. 176
Nanjing University of Finance and Economics (CN), Shaanxi University of Technology (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, Shaanxi Provincial Science and Technology Department
Openalex Percentile: Top 3%
Environmental Impact and Sustainability
6.39
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