Synergies for sustainability
Renewable energy, urban planning, and green industry in carbon emission reduction
Datos Bibliográficos
| ID | 7397346 |
|---|---|
| Autores | Sivajothi Ramalingam (0000-0003-3945-0925), Waqed H Hassan (0000-0002-2351-2151), Murali (0000-0002-1631-8078), M Ijaz Khan (0000-0003-2036-0372), Dalia H Elkamchouchi (0000-0002-9533-3179), Nainaru Tarakaramu (0000-0001-6049-424X), K V Mahendra Prashanth (0000-0002-7335-5377) |
| Año | 2025 |
| Volumen | 10 |
| Páginas | 101222-101222 |
| Fecha de publicación | 2025-08-29 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Sustainable Futures (JOURNAL) |
| Identificadores de la revista | ISSN: 2666-1888 |
| Editorial | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.sftr.2025.101222 |
| OpenAlex | W4413845236 |
| Idioma | EN |
| Citas recibidas | 4 |
| Referencias citadas | 27 |
This study addresses global carbon emission reduction by integrating renewable energy, urban sustainability, and green industry practices. It highlights the necessity of a holistic approach to tackling carbon footprints, emphasizing renewable alternatives like wind and solar energy alongside sustainable urban planning strategies, such as green roofs, solar energy, and electric vehicle use. Industrial transitions focusing on carbon capture and storage (CCS) and circular economies are essential for reducing emissions. The research underscores the interconnectedness of these strategies, advocating for cross-sectoral collaboration to drive sustainable development. Through data-driven analysis, the study advocates for aligning economic growth with environmental sustainability, promoting a low-carbon economy. The study also examines the significance of integrating renewable energy, urban planning, and industrial transformations to establish a comprehensive emission reduction system. Practical recommendations are provided for policymakers, urging the implementation of comprehensive, integrated strategies that balance ecological responsibility with economic growth. Additionally, the study utilizes predictive modeling, using Long Short-Term Memory (LSTM) neural networks to forecast CO2 emissions trends, ensuring a robust tool for future decision-making. This research aims to provide actionable insights for reducing global carbon footprints, contributing to sustainable urban development, the adoption of renewable energy and green industry practices
Business · Carbon fibers · Economics · Environmental economics · Natural resource economics · Reduction (mathematics · Renewable energy · Sustainability · Urban Sustainability · Computer Science · Engineering · Urban Transport and Accessibility
Empowering low-carbon energy transition with new-quality productive forces in China
How does urban agglomeration network structure influence carbon reduction synergy performance? A dual perspective on characteristics and mechanisms
Strategic interactions in urban carbon reduction
How does urban ecological quality truly evolve? A causal inquiry into its state and drivers in key zones using a novel entropy-based index (Aersei)
Urban adaptation can roll back warming of emerging megapolitan regions
Mitigating and adapting to climate change
Trade-off between vegetation CO2 sequestration and fossil fuel-related CO2 emissions
Low-carbon development quality of cities in China
Participatory land-use approach for integrating climate change adaptation and mitigation into basin-scale local planning
The Impact of Environmental Regulations on Pollution and Carbon Reduction in the Yellow River Basin, China
Climate co-benefits of air quality and clean energy policy in India
Can low-carbon urban development be pro-poor? The case of Kolkata, India
Low Carbon, Low Risk, Low Density
Public participation and policy evaluation in China's smog governance
| Obras citantes distintas | 4 |
|---|---|
| Citas por año | 4 |
| Intervalo de citas | 2025 - 2026 (2) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 4 |