The Green Engine of Growth: Assessing the Influence of Renewable Energy Consumption and Environmental Policy on China’s Economic Sustainability

Sustainability, Journal Year: 2024, Volume and Issue: 16(8), P. 3120 - 3120

Published: April 9, 2024

Utilizing Fourier autoregressive distributed lag and Toda–Yamamoto causality methodologies, this research assesses the effects that renewable energy consumption environmental policy had on economic sustainability of China from 1991 to 2022. Our findings highlight positive impacts use stringent policies China’s growth, while also pinpointing supportive roles played by foreign direct investment, trade openness, financial sector evolution in fostering a sustainable environment. Conversely, reliance fossil fuels emerges as significant barrier sustainability. Causality tests confirm essential advancing This study underscores critical need for integrating strategies within development framework, advocating holistic approach balances growth with conservation. imperative sustainability-centered strategy advancement.

Language: Английский

---

Towards Optimal Image Processing-based Internet of Things Monitoring Approaches for Sustainable Cities

International Journal of Advanced Computer Science and Applications, Journal Year: 2024, Volume and Issue: 15(5)

Published: Jan. 1, 2024

Population growth and urbanization demand innovative strategies for sustainable city management. This paper focuses on the integration of Internet Things (IoT) image processing technologies environmental monitoring in urban development. The IoT forms an integral part Information Communication Technology (ICT) infrastructure smart cities. It offers a new model design, due to ability offer environmentally alternatives. Furthermore, is method employed computer vision that provides reliable approaches extracting significant data from images. convergence these has capacity enhance effectiveness durability our surroundings. discusses current state-of-the-art both processing, highlighting their individual applications, architectures, challenges. explores aforementioned harmonized system promote synergies complementarities. Several case studies demonstrate successful adoption approach contexts, focusing monitoring, energy management, transportation, social well-being. combination with raises concerns regarding privacy, standardization, scalability. study provided direction future research suggested more participant multiple-strategy could be beneficial address some existing limitations move toward context. should therefore viewed as compass or roadmap areas processing-based towards todays environments.

Language: Английский

---

Green Energy, Economic Growth, and Innovation for Sustainable Development in OECD Countries

Sustainability, Journal Year: 2024, Volume and Issue: 16(22), P. 10113 - 10113

Published: Nov. 20, 2024

This study explores the interrelationship between green energy adoption, economic growth, and innovation in promoting sustainable development within OECD countries. Using a random forest regression model, research analyzes secondary data from 2013 to 2022 identify most significant contributors development. The model was selected for its ability handle non-linear relationships feature importance ranking, providing comprehensive understanding of variables’ impacts. analysis reveals that adoption has strongest influence on human index (HDI), with an score 0.43, followed by gross domestic product (GDP) global (GII). These findings underscore pivotal role amplified growth technological innovation, advancing While focuses countries, insights offer valuable implications sustainability initiatives. evidence supports argument prioritizing energy, supported innovative drivers, is crucial achieving broader goals. provides methodological contribution demonstrating effectiveness machine learning models analyzing complex offers empirical informs policy future context.

Language: Английский

---

The Impact of Weather Variability on Renewable Energy Consumption: Insights from Explainable Machine Learning Models

Sustainability, Journal Year: 2024, Volume and Issue: 17(1), P. 87 - 87

Published: Dec. 26, 2024

The pursuit of carbon neutrality is reshaping global energy systems, making the transition to renewable critical for mitigating climate change. However, unstable weather conditions continue challenge consumption stability and grid reliability. This study investigates effectiveness various machine learning (ML) models at predicting differences employs SHapley Additive Explanations (SHAP) interpretability tool quantify influence key variables, using five years data (2017–2022) 196,776 observations collected across Europe. dataset consists hourly records, variables such as Global Horizontal Irradiance (GHI), sunlight duration, day length, cloud cover, humidity are identified predictors. results demonstrate that Random Forest (RF) model achieves highest accuracy (R2 = 0.92, RMSE 360.17, MAE 208.84), outperforming other in differences. Through SHAP analysis, this demonstrates profound GHI, which exhibits a correlation coefficient 0.88 with variance. Incorporating advanced preprocessing predictor selection techniques remains RF but reduces by approximately 25% XGBoost model, underlining importance selecting appropriate input variables. Hyperparameter tuning further enhances performance, particularly less robust algorithms prone overfitting. reveals complex seasonal regional effects on demands. These findings underscore ML addressing challenges systems provide valuable insights policymakers practitioners optimize management strategies, integrate sources, achieve sustainable development objectives.

Language: Английский

---

Releasing the Power of Nature

Practice, progress, and proficiency in sustainability, Journal Year: 2024, Volume and Issue: unknown, P. 108 - 124

Published: June 28, 2024

The growing urgency to combat climate change and the finite nature of traditional fossil fuel reserves have prompted a worldwide call for transition sustainable energy alternatives. Green energy, derived from renewable sources such as solar, wind, hydro, geothermal, emerges an essential solution address environmental concerns while fostering economic development. This comprehensive review critically examines current landscape green technologies, exploring their potential impact, inherent challenges, crucial role they play in shaping future. discusses issues intermittency, storage, infrastructure requirements, proposing innovative solutions policy considerations overcome these hurdles. synthesizes state addressing potential, overall impact on

Language: Английский

---