Environmental regulation and industrial energy efficiency: new evidence from partially linear functional-coefficient models DOI

Xiaoyan Shen,

Sui Ji, Tao Ge

и другие.

Environment Development and Sustainability, Год журнала: 2024, Номер unknown

Опубликована: Дек. 19, 2024

Язык: Английский

Do energy and geopolitical risks influence environmental quality? A quantile-based load capacity factor assessment for fragile countries DOI Creative Commons
Uğur Korkut Pata, Mustafa Tevfik Kartal, Shahriyar Mukhtarov

и другие.

Energy Strategy Reviews, Год журнала: 2024, Номер 53, С. 101430 - 101430

Опубликована: Май 1, 2024

Most countries have tried to decline fossil fuels dependency by supporting clean energy transition. In light of this, this study investigates the impact security risk (ESR) and geopolitical (GPR) on load capacity factor (LCF) in four fragile (Brazil-BRA; India-IND; South Africa-ZAF, Türkiye-TUR). The applies quantile approaches for period between 1985/m2 2018/m12, which represents largest amount accessible data. results show that (i) at higher quantiles, ESR declines LCF IND ZAF, while it has an increasing BRA a mixed TUR; (ii) GPR increases BRA, TUR lower middle decreases ecological quality quantiles all countries; (iii) causal effect across various quantiles; (iv) are strong predictors LCF, but their predictive power varies becomes significantly weaker with lags. With these fresh outcomes, underlines significant influence ensuring sustainability countries. overall findings emphasize risks uncertainties degrade policymakers should turn sources case increase risks.

Язык: Английский

Процитировано

11

Decarbonization efforts under the energy and climate policy uncertainties: a comparison between the USA and China DOI
Uğur Korkut Pata

Clean Technologies and Environmental Policy, Год журнала: 2024, Номер unknown

Опубликована: Авг. 20, 2024

Язык: Английский

Процитировано

10

Assessing the environmental impacts of clean energy investment in Pakistan using a dynamic autoregressive distributed lag model DOI
Sami Ullah, Boqiang Lin

Journal of Environmental Management, Год журнала: 2024, Номер 365, С. 121549 - 121549

Опубликована: Июль 1, 2024

Язык: Английский

Процитировано

9

Comparative carbon footprint of electric and hydrogen vehicles: Insights from Morocco, Africa, and global energy transitions DOI
Hamza Khaldi, Hamid Mounir

Energy Sustainable Development/Energy for sustainable development, Год журнала: 2025, Номер 85, С. 101685 - 101685

Опубликована: Март 11, 2025

Язык: Английский

Процитировано

0

Environmental legislative shaping or green competitive advantages? The role of FDI among environmental regulations DOI
Gonzalo Hernández Soto, Daniel Balsalobre‐Lorente, Xavier Martínez-Cobas

и другие.

Energy Economics, Год журнала: 2025, Номер unknown, С. 108445 - 108445

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

The long-term impact of carbon emission trading and renewable energy support policy on China’s power sector under the context of electricity marketed reform: an analysis based on system dynamics DOI

王书越 WANG Shuyue,

Yue Wang

Environment Development and Sustainability, Год журнала: 2025, Номер unknown

Опубликована: Апрель 19, 2025

Язык: Английский

Процитировано

0

Impact of extreme high temperatures on pollution emissions of enterprise: Evidence from China DOI

Jie Zhang,

Fanglin Chen

Journal of Environmental Management, Год журнала: 2024, Номер 365, С. 121493 - 121493

Опубликована: Июнь 18, 2024

Язык: Английский

Процитировано

3

A machine learning algorithm to explore the drivers of carbon emissions in Chinese cities DOI Creative Commons
Wenmei Yu, Lina Xia, Qiang Cao

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Окт. 9, 2024

As the world's largest energy consumer and carbon emitter, task of emission reduction is imminent. In order to realize dual-carbon goal at an early date, it necessary study key factors affecting China's emissions their non-linear relationships. This paper compares performance six machine learning algorithms that traditional econometric models in predicting China from 2011 2020 using panel data 254 cities China. Specifically, analyzes comparative importance domestic economic, external policy uncertainty as well nonparametric relationship between these based on Extra-trees model. Results show consumption (ENC) remains root cause increased among economic factors, although government intervention (GOV) digital finance (DIG) can significantly reduce it. Next, foreign direct investment (FDI) (EPU) are important influencing emissions, partial dependence plots (PDPs) confirm pollution haven hypothesis also reveal role EPU reducing emissions. The heterogeneity analyzed under different city sizes, found ENC a common driving factor but there some differences. Finally, appropriate recommendations proposed by us help move rapidly towards green sustainable development path.

Язык: Английский

Процитировано

3

Which works better? Comparing the multiple effects of heterogeneous environmental regulations on urban green economic transformation in China DOI
Yanming Sun, Chuanyu Zhou

Journal of Environmental Management, Год журнала: 2024, Номер 368, С. 122124 - 122124

Опубликована: Авг. 11, 2024

Язык: Английский

Процитировано

2

The health impacts of renewable energy consumption in sub-Saharan Africa: A machine learning perspective DOI Creative Commons
Mwoya Byaro, Anicet Rwezaula

Energy Strategy Reviews, Год журнала: 2024, Номер 57, С. 101621 - 101621

Опубликована: Дек. 27, 2024

Язык: Английский

Процитировано

2