Renewable Energy, Год журнала: 2025, Номер unknown, С. 122859 - 122859
Опубликована: Март 1, 2025
Язык: Английский
Renewable Energy, Год журнала: 2025, Номер unknown, С. 122859 - 122859
Опубликована: Март 1, 2025
Язык: Английский
Environmental Science and Pollution Research, Год журнала: 2023, Номер 31(4), С. 6040 - 6053
Опубликована: Дек. 26, 2023
Язык: Английский
Процитировано
28Journal of Cleaner Production, Год журнала: 2023, Номер 436, С. 140479 - 140479
Опубликована: Дек. 30, 2023
Язык: Английский
Процитировано
28Fuel, Год журнала: 2024, Номер 370, С. 131806 - 131806
Опубликована: Май 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.
Язык: Английский
Процитировано
13Energy Economics, Год журнала: 2024, Номер 136, С. 107721 - 107721
Опубликована: Июнь 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.
Язык: Английский
Процитировано
12Renewable Energy, Год журнала: 2024, Номер 232, С. 121025 - 121025
Опубликована: Июль 26, 2024
Язык: Английский
Процитировано
10Utilities Policy, Год журнала: 2024, Номер 88, С. 101757 - 101757
Опубликована: Апрель 22, 2024
Язык: Английский
Процитировано
9Journal of Environmental Management, Год журнала: 2024, Номер 365, С. 121549 - 121549
Опубликована: Июль 1, 2024
Язык: Английский
Процитировано
9Journal of Cleaner Production, Год журнала: 2023, Номер 428, С. 139282 - 139282
Опубликована: Окт. 12, 2023
Язык: Английский
Процитировано
21Process Safety and Environmental Protection, Год журнала: 2024, Номер 190, С. 276 - 287
Опубликована: Июль 30, 2024
Язык: Английский
Процитировано
7Energy & Environment, Год журнала: 2024, Номер unknown
Опубликована: Июль 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.
Язык: Английский
Процитировано
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