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Economic Analysis: Theory and Practice
 

Studying the intensity of the energy footprint of Chinese provinces based on the Net Primary Productivity model

Vol. 23, Iss. 11, NOVEMBER 2024

Received: 5 September 2024

Received in revised form: 21 September 2024

Accepted: 10 October 2024

Available online: 29 November 2024

Subject Heading: INTEGRATED ECONOMIC-SOCIO-ECOLOGICAL ANALYSIS

JEL Classification: Q56, Q57, Q58

Pages: 2175-2186

https://doi.org/10.24891/ea.23.11.2175

Zhang SHULIN Lomonosov Moscow State University, Moscow, Russian Federation
2534415499@qq.com

https://orcid.org/0000-0001-6897-6219

Subject. The article explores the impact of energy consumption on China's environment as an important factor for China to achieve environmentally friendly and efficient development.
Objectives. The purpose is to measure the environmental footprint of energy consumption in each province of China and analyze regional differences to develop differentiated policies.
Methods. The study draws on the method of measuring the ecological footprint, economic, mathematical and general scientific research methods.
Results. I selected panel data on energy consumption in 30 provinces of China from 2005 to 2020. To calculate the intensity of the energy footprint, I used a model of net primary productivity. Then I divided thirty provinces into four main regions, and used the coefficient of variation and the Gini coefficient to analyze differences in the energy footprint intensity of each province in the region.
Conclusions. The intensity of energy consumption in each province of China varies greatly. Economically developed eastern provinces use energy much more efficiently than western ones. The northeast region of China has the smallest internal differences in the intensity of energy consumption between provinces. Compared to the eastern and northeastern provinces, the differences in energy efficiency between the provinces of the central and western regions are greater.

Keywords: net primary productivity, energy footprint intensity, Gini coefficient, regional differences, China

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