School of Management Engineering, Qingdao University of Technology, Qingdao, 266520, China.
School of Business, Qingdao University, Qingdao, 266071, China.
Environ Sci Pollut Res Int. 2023 Oct;30(47):104148-104168. doi: 10.1007/s11356-023-29762-5. Epub 2023 Sep 12.
Reducing carbon emissions is a critical approach for attaining global environmental sustainability and combating climate change. To investigate how energy, population, industry, and economic structure affect environmental quality. This study collects panel data for 90 Belt and Road (B&R) nations from 1995 to 2021. For the first time, the nonlinear dynamic impacts of renewable energy, newborn birth rate, industrialization, and economic growth on carbon emissions are investigated using a threshold panel model and a panel vector autoregression (PVAR) model. According to the study's findings: (1) models 1-4 demonstrate that all structural factors have substantial threshold impacts on carbon emissions, demonstrating a nonlinear connection. (2) Carbon emissions are negatively impacted by energy structure (renewable energy) and population structure (newborn birth rate). Industrial structure (industrialization) and economic structure (economic growth), on the other hand, have a beneficial influence on carbon emissions. However, when the structural variables grow in size, their threshold effects all increase this contribution. (3) In three groups of nations with varying wealth levels, differences in the influence intensity of structural factors on carbon emissions, particularly renewable energy and economic growth, were detected. The impact of renewable energy on carbon emissions is: middle-income (MI) countries > high-income countries (HI) > low-income countries (LI). The impact of economic growth on carbon emissions is MI countries > LI countries > HI countries. Based on the findings, relevant policy recommendations are provided to the policy makers of the "B&R" countries from the perspectives of structural factors and heterogeneity. It provides certain references for the realization of global environmentally sustainable development strategies and the coordinated development of economic, social and environmental systems.
减少碳排放是实现全球环境可持续性和应对气候变化的关键途径。本研究旨在探讨能源、人口、产业和经济结构如何影响环境质量。为此，我们收集了 1995 年至 2021 年期间 90 个“一带一路”国家的面板数据，并首次利用门槛面板模型和面板向量自回归（PVAR）模型研究了可再生能源、新生出生率、工业化和经济增长对碳排放的非线性动态影响。研究结果表明：（1）模型 1-4 表明，所有结构因素对碳排放都有实质性的门槛影响，表明存在非线性关系。（2）能源结构（可再生能源）和人口结构（新生出生率）对碳排放产生负面影响，而产业结构（工业化）和经济结构（经济增长）则对碳排放产生积极影响。然而，当结构变量增长时，它们的门槛效应都增加了这种贡献。（3）在三组不同财富水平的国家中，发现结构因素对碳排放的影响强度存在差异，特别是可再生能源和经济增长。可再生能源对碳排放的影响是：中等收入（MI）国家>高收入（HI）国家>低收入（LI）国家。经济增长对碳排放的影响是：MI 国家>LI 国家>HI 国家。基于这些发现，从结构因素和异质性的角度，为“一带一路”国家的决策者提供了相关政策建议。本研究为实现全球环境可持续发展战略和经济、社会和环境系统的协调发展提供了一定的参考。
