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Hydropower renewable energy is known to be pro-environment: flexible and affordable. Above all, it is compatible with other energy frames and also with the policies that otherwise prove to be inimical towards its future. Where environmental stability is concerned it needs an assiduous study coupled with research by the policymakers to get around knowing the different perspectives of hydropower renewable energy. The study has taken nine different and diverse perspectives of hydropower renewable energy into account to stop the process of environmental degradation. EKC framework has been put to use in a case study of South and East Asia economies. Time period has been selected from 1975 to 2020 to measure the long-term impact. GMM model has been used for the panel estimation besides getting future dynamics. The results which have come about confirmed EKC in the selected countries. Non-renewable energy (coal and gas) had an adverse impact on environmental stability. However, switching towards hydropower renewable energy can mitigate these environmental losses. Empirical findings have proved that more use of clean energy production can bring about a considerable amount of environmental stability. Insofar as East Asia economies are considered they have reached the second stage of EKC with a turning point of $13844 (per capita income). This paper, therefore, suggests that the future depends upon renewable hydropower energies in South and East Asia economies. That being said, there appears to be a dire need to undertake the role of various socioeconomic and geographic factors that influence hydropower renewable energies to check the long-term effect. [Display omitted] [ABSTRACT FROM AUTHOR]

Carbon emission efficiency, which is mainly affected by economic output, energy efficiency and energy structure, is the effect of carbon emissions generated in economic activities. Improving carbon emission efficiency and narrowing regional differences are very important for green development in Belt and Road Initiative regions with developing countries as the main body. The existing literature mostly uses the Theil index to study the temporal differences in carbon emission efficiency, but spatial differences and the reasons for the differences have rarely been examined. This paper measures the differences of carbon emission efficiency using the Theil index and examines the reasons based on the Logarithmic Mean Divisia index (LMDI) method in five groups of 60 Belt and Road Initiative countries. The results show that the Theil index of carbon emission efficiency in these countries is 0.196, with an intra-group difference of 0.165 and an inter-group difference of 0.031. Between most of the groups, energy efficiency is the dominant factor affecting carbon emission efficiency differences, especially between East Asia and Central and Eastern Europe, South Asia and East Asia. Between most of the countries with the highest and lowest carbon emission efficiency in the same group, such as Singapore and Vietnam in East Asia, energy efficiency is still the primary factor affecting the differences. Only some differences between a few groups, countries and sectors have been caused mainly by energy structures. Therefore, improving energy efficiency is the first way for those countries with low carbon emission efficiency to catch up other countries with high carbon emission efficiency, followed by improving the energy structure. [ABSTRACT FROM AUTHOR]

Abstract: The rapid growth of energy consumption in conjunction with economic development during past decades in East Asia, especially China, caused severe air pollution problems at local and regional scales. Understanding of the meteorological conditions for air pollution is essential to the understanding of the formation mechanism of air pollutants and the development of effective emission control strategies to reduce air pollution. In this paper, the Fifth Generation National Center for Atmospheric Research (NCAR)/Pennsylvania State University (PSU) Mesoscale Model (MM5) modeling system is applied to simulate meteorological fields during selected six 1-month periods in 2007/2008 over a triple-nested modeling domain covering East Asia, the eastern China, and Shandong Province at horizontal grid resolutions of 36-, 12-, and 4-km, respectively. MM5 generally reproduces well the observations in the eastern China but performs worse in the western China and northeastern China. Largest biases occur in 2-m temperatures (T2) and wind speed and wind direction at 10-m in haze months (i.e., winter) and daily mean precipitation (Precip) in non-haze months (i.e., summer), due to limitations of the model in simulating snow cover and convective precipitation. Meteorological predictions agree more closely with observations at urban sites than those at the coastal and mountain sites where the model performance deteriorates because of complex terrains, influences of urban heat island effect and land/sea breezes, and higher elevations. Model results at 12-km in Shandong Province show an overall better performance than those at 4- or 36-km while the results at 4-km show worst performance due to inaccurate land use and the model’s incapability in simulating meteorological processes at a fine scale. [Copyright &y& Elsevier]