This research dives deep into the interplay between environmental technology, taxes, and renewable energy consumption, emphasizing their collective influence on ecological footprints within East Asian context. The scrutiny period extends from 1999 to 2019, encompassing five pivotal nations: Japan, North Korea, South Mongolia, China. At heart of this study lies choice technology as a core variable, driven by its potential be game-changer in sustainable development trajectories. Our findings...

The rapid growth experienced by the Gulf Council countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and United Arab Emirates) has placed significant strain on their ecological footprint due to extensive energy consumption. Consequently, it becomes necessary examine factors contributing high explore potential solutions for its reduction. This study aims analyze key influencing in GCC from 1995 2020. Through an review of existing literature, is evident that economic growth, urbanization,...

Abstract The study investigates the effects of renewable energy, globalization, and agriculture on long‐term economic progress environment. Using a data set Gulf Council Countries (GCC) from 1980 to 2019, used panel fully modified ordinary least squares dynamic techniques. Panel analysis results indicate relevance foreign investment, trade in enhancing growth. Capital globalization are fundamental sources environmental degradation, whereas energy essential variables for mitigating...

The aim of current study is to investigate the significance green and blue economic activities mitigate carbon emission in Saudi Arabia. We use time series data which covers period from 1990 2019. For empirical estimations, we nonlinear ARDL approach confirms that energy indicators are not mature enough achieve neutrality objectives. However, after Vision 2030 empirics, positive shocks turning down level. findings useful for policy recommendations help sustainable environmental goals 2030.

The current study examines the significant determinants of electricity consumption and identifies an appropriate model to forecast price accurately. main contribution is focused on eastern region Saudi Arabia, a relatively hottest geographical area full energy resources but with different patterns. relative irrelevance temperature as predicting factor quite surprising contradicts previous studies. In region, has negative association consumption. While comparing traditional machine learning,...

This paper investigates the impact of life expectancy on carbon emission, in Saudi Arabia. Additionally, we examined role governance to achieve neutrality status. We used novel dynamic ARDL technique for estimations. is one pioneer studies that analyze control emissions. The coefficients expectancy, education, and political stability are significantly negative. On contrary, effectiveness an obstacle achieving neutrality. Empirical findings quite surprising. In terms Vision 2030 estimations,...

The motivation behind this research is to investigate the determinants of ecological footprint in MENA countries and find appropriate solutions. We updated STIRPAT model applied sophisticated panel techniques data from 1996 2020. According findings, economic expansion along with urbanization tourism blame for these countries’ huge environmental footprints. In addition, when it comes degradation remedies, innovation use renewable energy play an important role minimizing externalities. results...

Navigating the intricate dynamics between environmental decentralization and green growth, this research meticulously explores multifaceted relationships among these variables within China's specific socio-economic political context from 2002 to 2022. The study unveils a nuanced picture, revealing significant negative relationship (ED) growth while also highlighting divergent impacts of administrative (EAD) supervisory (ESD). Furthermore, illuminates partial mediating role renewable energy...

The current study attempts to compare the hybrid artificial intelligence models forecast environmental externalities in Saudi Arabia. We have used denoising based construct models. While comparing techniques, CSD-based has outperformed. However, we CSD-ANN and CSD-RNN are for denoising-based models, whereas CSD-ARIMA is traditional All these check their performance terms of level direction prediction PM10. results show that ANN model a higher predictability PM10 levels Arabia due low error...

ABSTRACT The aim of this study is to analyze Saudi Arabia's economic transformation, emphasizing the period from 1990 2022 and considering implementation Vision 2030. Land use, energy consumption, growth are evaluated through use a nonlinear ARDL model. Based on findings, economy has shifted relieving heavily oil revenues diversification sustainability. been positively impacted by sustainable land practices reduction in nonrenewable consumption since 2030, which highlights early successes...

The current study contributes to the existing literature by constructing a digitalization index investigate significance of in controlling environmental footprint. Moreover, dataset is divided into pre-Vision 2030 and post-Vision implementation scrutinize progress Saudi Vision counter challenges. strategic framework reduce Arabia's dependence on oil, diversify its economy, develop public service sectors such as health, education, infrastructure, recreation, tourism. findings have documented...

The prediction performance of traditional forecasting methods is low due to the high level complexity in a series energy prices. present study attempts compare regression, machine learning tools and hybrid models conclude outperforming model. first step propose effective denoising technique for Tadawul index, which has confirmed superiority CSD based denoising. However, we use CSD-ARIMA, CSD-ANN, CSD-RNN as models. As result, outperforms both other terms MSE, MAPE, RMSE Dstat. findings are...

The current study investigates the impact of economic growth, carbon emission, temperature, and environmental technology on public health in GCC countries. Panel data from 1990 to 2020 is used, panel unit root test used check stationarity data. After cointegration analysis, ARDL estimation technique checks long-run short-run association between variables. results have proved that growth enhances exposure PM2.5 mortality but helps increasing life expectancy. Likewise, emission also improves...

Abstract This study innovatively combines healthy life expectancy (LE) with traditional LE measures to shed light on environmental impacts public health. Second, it utilizes the Markov chain Monte Carlo algorithm model data until 2025; this is a new method in health research. investigates impact of indicators and LE, landmark piece research that incorporates latter such analyses. The major harmful outcomes economic growth, carbon emissions, particulate matter 2.5 both expectancies are...

Due to its heavy reliance on fossil fuels and rapid urbanization, China's economic growth is accompanied by environmental problems. Hence, it vital solve the issue promoting green finding factors boost it. The current study presents FinTech as a factor enhancing in China through mediation effect of energy transition. index created comprehensive literature review selecting most critical indicators. It has been established benchmark regression that positively affects China. However, results...