Awosusi Abraham Ayobamiji, Kutlay Kaan, Altuntaş Mehmet, Khodjiev Bakhtiyor, Agyekum Ephraim Bonah, Shouran Mokhtar, Elgbaily Mohamed, Kamel Salah
Department of Economics, Faculty of Economics and Administrative Science, Near East University, North Cyprus, Mersin 99040, Turkey.
Vocational School of Health Service, European University of Lefke, Northern Cyprus, Mersin 99770, Turkey.
Int J Environ Res Public Health. 2022 Mar 10;19(6):3288. doi: 10.3390/ijerph19063288.
Technological innovations have been a matter of contention, and their environmental consequences remain unresolved. Moreover, studies have extensively evaluated environmental challenges using metrics such as nitrogen oxide emissions, sulfur dioxide, carbon emissions, and ecological footprint. The environment has the supply and demand aspect, which is not a component of any of these indicators. By measuring biocapacity and ecological footprint, the load capacity factor follows a certain ecological threshold, allowing for a thorough study on environmental deterioration. With the reduction in load capacity factor, the environmental deterioration increases. In the context of the environment, the interaction between technological innovation and load capacity covers the demand and supply side of the environment. In light of this, employing the dataset ranging from 1980 to 2017 for the case of South Africa, the bound cointegration test in conjunction with the critical value of Kripfganz and Schneider showed cointegration in the model. The study also employed the ARDL, whose outcome revealed that nonrenewable energy usage and economic growth contribute to environmental deterioration, whereas technological innovation and globalization improve the quality of the environment. This study validated the hypothesis of the environmental Kuznets curve for South Africa, as the short-term coefficient value was lower than the long-term elasticity. Furthermore, using the frequency-domain causality test revealed that globalization and economic growth predict load capacity in the long term, and nonrenewable energy predicts load capacity factors in the long and medium term. In addition, technological innovation predicts load capacity factors in the short and long term. Based on the findings, we propose that policymakers should focus their efforts on increasing funding for the research and development of green technologies.
技术创新一直是一个有争议的问题，其环境后果仍未得到解决。此外，研究已经广泛使用氮氧化物排放、二氧化硫、碳排放和生态足迹等指标来评估环境挑战。环境具有供需方面，而这并非这些指标中的任何一个的组成部分。通过测量生物承载力和生态足迹，负载能力因子遵循一定的生态阈值，从而能够对环境恶化进行全面研究。随着负载能力因子的降低，环境恶化加剧。在环境背景下，技术创新与负载能力之间的相互作用涵盖了环境的供需双方。有鉴于此，以南非为例，利用1980年至2017年的数据集，结合克里普夫甘茨和施奈德的临界值进行的边界协整检验表明该模型存在协整关系。该研究还采用了自回归分布滞后模型（ARDL），其结果显示不可再生能源的使用和经济增长会导致环境恶化，而技术创新和全球化则会改善环境质量。本研究验证了南非环境库兹涅茨曲线的假设，因为短期系数值低于长期弹性。此外，使用频域因果关系检验表明，全球化和经济增长在长期预测负载能力，不可再生能源在中长期预测负载能力因子。此外，技术创新在短期和长期预测负载能力因子。基于这些发现，我们建议政策制定者应集中精力增加对绿色技术研发的资金投入。
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