Breaking the carbon bind: How digitalization and energy transformation reshape carbon dependency based on wavelet and machine learning approaches

IF 4.7 2区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Yang Yu , Xin Jian , DooHwan Won , Atif Jahanger
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Abstract

As global efforts to combat climate change intensify, digitalization has emerged as a crucial driver in reducing carbon dependency, with energy transformation also playing a significant role. Within this purview, this paper delves into the interplay among digitalization, energy transformation, and carbon dependency, utilizing Chinese country-level data spanning from 2005 to 2021. Recognizing potential variations in emission reduction policies over time, we employ the wavelet spectrum, wavelet local multiple correlation, wavelet coherence and machine learning methods for a comprehensive exploration. The outcomes of the wavelet spectrum analysis offer a visual depiction of the variable dynamics over time, furnishing substantial underpinning for discerning their intricate behaviors. Simultaneously, the findings from the wavelet local multiple correlation and wavelet coherence analyzes underscore disparities in the impacts of digitalization and energy transformation on carbon dependency across different temporal intervals and frequencies. Specifically, digitalization intensifies carbon dependency in the short to medium term (below 8 band), while both digitalization and energy transformation significantly reduce carbon dependency in the long term (above 16 band), demonstrating a dynamic correlation among these variables. Furthermore, the results derived from the machine learning tests demonstrate that the influence of digitalization and energy transformation on carbon dependency reveal time-varying effects, digitalization exacerbates carbon dependency within the threshold range of −0.5 to 0.8, whereas energy transformation effectively reduces carbon dependency beyond the threshold of 0.3. This research investigates the complex interrelations among digitalization, energy transformation, and carbon dependency, providing essential experiences and lessons that are applicable to green and sustainable development efforts worldwide.
打破碳约束:基于小波和机器学习方法的数字化和能源转型如何重塑碳依赖
随着全球应对气候变化努力的加强,数字化已成为减少碳依赖的关键驱动力,能源转型也发挥着重要作用。在此范围内,本文利用2005年至2021年的中国国家级数据,深入研究了数字化、能源转型和碳依赖之间的相互作用。认识到减排政策随时间的潜在变化,我们采用小波谱、小波局部多重相关、小波相干和机器学习方法进行全面探索。小波谱分析的结果提供了随时间变化的动态的可视化描述,为识别其复杂的行为提供了实质性的基础。同时,小波局部多重相关和小波相干分析的结果强调了数字化和能源转型对碳依赖的影响在不同时间间隔和频率上的差异。具体而言,数字化在中短期(8波段以下)加剧了碳依赖,而数字化和能源转型在长期(16波段以上)都显著降低了碳依赖,显示了这些变量之间的动态相关性。此外,机器学习测试结果表明,数字化和能源转型对碳依赖的影响呈现时变效应,在- 0.5至0.8的阈值范围内,数字化加剧了碳依赖,而在0.3阈值以上,能源转型有效降低了碳依赖。本研究探讨了数字化、能源转型和碳依赖之间的复杂相互关系,为全球绿色和可持续发展工作提供了重要的经验和教训。
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来源期刊
Environmental Development
Environmental Development Social Sciences-Geography, Planning and Development
CiteScore
8.40
自引率
1.90%
发文量
62
审稿时长
74 days
期刊介绍: Environmental Development provides a future oriented, pro-active, authoritative source of information and learning for researchers, postgraduate students, policymakers, and managers, and bridges the gap between fundamental research and the application in management and policy practices. It stimulates the exchange and coupling of traditional scientific knowledge on the environment, with the experiential knowledge among decision makers and other stakeholders and also connects natural sciences and social and behavioral sciences. Environmental Development includes and promotes scientific work from the non-western world, and also strengthens the collaboration between the developed and developing world. Further it links environmental research to broader issues of economic and social-cultural developments, and is intended to shorten the delays between research and publication, while ensuring thorough peer review. Environmental Development also creates a forum for transnational communication, discussion and global action. Environmental Development is open to a broad range of disciplines and authors. The journal welcomes, in particular, contributions from a younger generation of researchers, and papers expanding the frontiers of environmental sciences, pointing at new directions and innovative answers. All submissions to Environmental Development are reviewed using the general criteria of quality, originality, precision, importance of topic and insights, clarity of exposition, which are in keeping with the journal''s aims and scope.
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