Suppr超能文献

重新审视二氧化碳排放的决定因素:扩展的STIRPAT模型下高等教育的作用。

Revisiting the determinants of CO2 emissions: The role of higher education under the extended STIRPAT model.

作者信息

Li Qiang

机构信息

School of Humanities and Social Sciences, North China Electric Power University, Beijing, China.

出版信息

PLoS One. 2025 Mar 18;20(3):e0319930. doi: 10.1371/journal.pone.0319930. eCollection 2025.

Abstract

This study directly aligns with Sustainable Development Goals (SDGs), i.e., SDG-13 and SDG-4. Carbon emissions (CO2e) are primarily addressed under SDG-13: Climate Action, which aims to combat climate change and its impacts. CO2e reduction efforts contribute to achieving this goal by mitigating greenhouse gas emissions. SDG 4: Quality Education aims to ensure inclusive and equitable quality education for all. It emphasizes explicitly lifelong learning opportunities and targets higher education (HE) access to improve skills for sustainable development. Therefore, the current study aims to examine the determinants of CO2e in China and the role of HE under the extended STIRPAT model. This study utilizes the Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) methods using the time series data from 1985 to 2023. The finding shows that total population, GDP, and industry positively affect CO2e, while technological innovation and higher education negatively affect CO2e in China.

摘要

本研究与可持续发展目标(SDGs)直接相关,即SDG-13和SDG-4。碳排放(CO2e)主要在SDG-13:气候行动中得到解决,该目标旨在应对气候变化及其影响。减少CO2e的努力通过减少温室气体排放有助于实现这一目标。SDG 4:优质教育旨在确保为所有人提供包容和公平的优质教育。它明确强调终身学习机会,并以高等教育(HE)入学率为目标,以提高可持续发展技能。因此,本研究旨在考察扩展的STIRPAT模型下中国CO2e的决定因素以及高等教育的作用。本研究使用1985年至2023年的时间序列数据,采用完全修正普通最小二乘法(FMOLS)和动态普通最小二乘法(DOLS)。研究结果表明,中国的总人口、国内生产总值和工业对CO2e有正向影响,而技术创新和高等教育对CO2e有负向影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8341/11919276/d467e603065c/pone.0319930.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验