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As a raw material for clean energy supply for the new generation, the soybean is conducive to the realization of global energy transition and sustainable development in the context of "carbon neutrality". However, global warming has been affecting soybean yields in recent years. How to clarify the correlation between meteorological factors and soybean yields, so as to ensure the security of soybean growth and development and the stability of renewable energy development, is a key concern of the government and academia. Based on the data of temperature, precipitation, sunshine duration and active accumulated temperature during the soybean growing season in Hulunbuir, Inner Mongolia Autonomous Region from 1951 to 2019, and soybean yield data of the city from 1985 to 2019, this paper adopted statistical methods such as the Trend Analysis Method, the Rescaled Range Analysis Method and so on to analyze the trends of yield changes, characteristics of abrupt changes and periodic patterns of climate factors and soybean yields in Hulunbuir. A Pearson Correlation Analysis and a Grey Relation Analysis were used to explore the correlation between climatic factors and soybean yields, followed by a comprehensive impact model of the combined effect of temperature and precipitation on soybean yields established by the Method of Integral Regression. The results showed that temperature and active accumulated temperature are the dominant factors affecting soybean yields in Hulunbuir, while the decrease in precipitation is unfavorable to the improvement of soybean yields. Meanwhile, temperature and precipitation have different effects on the growth and development of the soybean at different stages. The conclusion of this paper is of great practical significance for Hulunbuir to promote the sustainable development of clean energy. [ABSTRACT FROM AUTHOR]

Amid global imperatives to combat climate change and achieve sustainable economic development, the convergence of digital transformation and the transition to clean energy has emerged as a critical focal point for oil-exporting nations. This study comprehensively investigates the interplay of digital technology, clean energy transition, climate change, and economic growth among selected oil-exporting nations. Drawing upon a diverse set of economic and geographical contexts, this study uses panel data analysis of data from the World Bank's Economic Indicators and the United Nations Development Program for the period from 2006 to 2020. The results show that digital technology reduces climate change by improving environmental quality, but internet and mobile access have insignificant and negative effects on environmental quality, respectively. Meanwhile, all technology variables negatively impact green energy and economic growth, while the Happy Planet Index and financial development positively impact the green energy transition. This study is important for regulators, producers, and consumers, as it provides a better understanding of the crucial role of digital transformation in sustainable development within oil-export countries. This study's findings can be used to develop policy recommendations for a low-carbon economy, the promotion of digital transformation through green energy, and the management of climate change. [ABSTRACT FROM AUTHOR]