Sustaining environment through municipal solid waste: evidence from European Union economies

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 31(4), P. 6040 - 6053

Published: Dec. 26, 2023

Language: Английский

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High-income developing countries as pollution havens: Can financial development and environmental regulations make a difference?

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 436, P. 140479 - 140479

Published: Dec. 30, 2023

Language: Английский

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Artificial neural networks-based performance and emission characteristics prediction of compression ignition engines powered by blends of biodiesel derived from waste cooking oil

Fuel, Journal Year: 2024, Volume and Issue: 370, P. 131806 - 131806

Published: May 11, 2024

Compression ignition engines are essential for power generation, yet the use of fossil fuels like petrol and diesel results in emission harmful toxins into atmosphere, leading to ecological disruption exacerbating environmental issues. To address these challenges, there is a growing interest alternative fuels, with vegetable oil-based biodiesels emerging as promising option due their renewable nature comparable performance characteristics that diesel. The main aim this study develop artificial neural network (ANN) models predicting biodiesel characteristics, aiming reduce reliance on resource-intensive physical testing through accurate property-based predictions. optimum model topologies prediction parameters, i.e., brake specific fuel consumption, energy thermal efficiency, exhaust gas temperature, were 6–5-1, 6–3-1, respectively. mean square error, root absolute deviation percentage error efficiency 0.0397, 0.1993, 0.1234, 0.5599, sensitivity analysis showed developed consumption highly sensitive torque; similarly, power, temperature consumption. aid broader adoption (i.e. derived from waste cooking oil) viable fuel, mitigating greenhouse emissions promoting sustainable practices greener future.

Language: Английский

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Environmental policy stringency and ecological footprint linkage: Mitigation measures of renewable energy and innovation

Energy Economics, Journal Year: 2024, Volume and Issue: 136, P. 107721 - 107721

Published: June 18, 2024

We scrutinize the environmental policies' efficacy in reducing ecological footprint by interweaving two other vibrant parameters of degradation mitigation, i.e., renewable energy sources and innovation. To this end, we apply a Cross-Sectional Autoregressive Distributed Lags (CS-ARDL) approach to analyze panel time-series data (1990–2018) context OECD countries. Our analysis shows that policy significantly reduces through innovation channels. findings also support idea policy's effectiveness is conditional on countries' bio-capacity surplus/deficit level industrialization. The overall hold up well presence cross-sectional dependence, short-run heterogeneity, long-run homogeneity under respective sample. underscore need for more stringent policies, supported technological advancements clean initiatives, mitigate impact human economic activities natural resources.

Language: Английский

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Green energy dynamics: Analyzing the environmental impacts of renewable, hydro, and nuclear energy consumption in Pakistan.

Renewable Energy, Journal Year: 2024, Volume and Issue: 232, P. 121025 - 121025

Published: July 26, 2024

Language: Английский

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The effect of geopolitical risk and green technology on load capacity factors in BRICS

Utilities Policy, Journal Year: 2024, Volume and Issue: 88, P. 101757 - 101757

Published: April 22, 2024

Language: Английский

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Assessing the environmental impacts of clean energy investment in Pakistan using a dynamic autoregressive distributed lag model

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 365, P. 121549 - 121549

Published: July 1, 2024

Language: Английский

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Load capacity factor and carbon emissions: Assessing environmental quality among MINT nations through technology, debt, and green energy

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 428, P. 139282 - 139282

Published: Oct. 12, 2023

Language: Английский

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The Impact of Energy (Electricity) Losses on Load Capacity Factor: A Dynamic ARDL-Based Evidence from Pakistan

Process Safety and Environmental Protection, Journal Year: 2024, Volume and Issue: 190, P. 276 - 287

Published: July 30, 2024

Language: Английский

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Growth-environment nexus in Canada: Revisiting EKC via demand and supply dynamics

Energy & Environment, Journal Year: 2024, Volume and Issue: unknown

Published: July 21, 2024

Previous research on the growth-environment nexus has predominantly focused demand-side indicators, disregarding supply-side dynamic and environmental Kuznets curve (EKC) hypothesis. This study examines role of economic growth quality in Canada, considering various macroeconomic factors such as energy consumption, technology innovation, foreign direct investment, institutional quality. Using time series data for period 1990 to 2022, this employs autoregressive distributive lag (DARDL) co-integration model assess co-integrating relationship among variables conduct counterfactual shock analysis. The results demonstrate that significantly affects dynamics, leading increased carbon emissions ecological footprint, while concurrently reducing factor, namely load capacity both short long run. Notably, these findings include confirmation EKC hypothesis it relates safety, measured through consumption within Canadian context. In addition, analysis DARDL approach effects (±) 1% 5% shocks from independent dependent variables. For robustness, kernel regularized least squares machine learning algorithm validates obtained estimation technique. study's suggest implementing stringent policies enhance parameters carefully balancing support growth. It is crucial ensure not achieved at expense degradation Canada.

Language: Английский

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