PapersFlow Research Brief
Energy and Environmental Sustainability
Research Guide
What is Energy and Environmental Sustainability?
Energy and Environmental Sustainability is the analysis of innovative strategies for energy investments emphasizing renewable energy, sustainable development, and green supply chain management using fuzzy decision-making models and hybrid modeling to evaluate global indicators, financial development, and innovation strategies in the energy industry.
This field includes 2,573 works focused on renewable energy investment strategies and environmental sustainability. Research employs fuzzy multi-criteria decision-making (MCDM) models for prioritizing renewable energy alternatives, as shown in real-case applications. Hybrid modeling approaches assess economic indicators and bioenergy supply in developed economies.
Topic Hierarchy
Research Sub-Topics
Fuzzy Multi-Criteria Decision Making for Renewable Energy
Researchers apply fuzzy TOPSIS, MCDM, and divergence measures to prioritize renewable sources like solar and wind based on sustainability criteria. Case studies from Turkey and arid regions demonstrate hybrid model efficacy.
Green Hydrogen Production Potential
This area assesses high-potential countries for green hydrogen via solar and wind resources, including techno-economic modeling and scalability reviews. Focus is on global supply chains and investment strategies.
Solar Site Selection Optimization
Studies employ fuzzy logic, weighted linear combination, and GIS for optimal solar farm siting in arid regions like Iran. Research integrates environmental, economic, and technical indicators.
Anaerobic Biotechnology for Bioenergy
Investigators develop biotechnological processes for biogas and biofuel production from organic waste, emphasizing reactor design and microbial kinetics. Links to sustainable development and green supply chains are explored.
Carbon Emission Strategies in Solar Transportation
This sub-topic uses inventive problem-solving maps and TRIZ for low-carbon solar-powered transport investments. Analysis covers financial development and innovation in energy transition projects.
Why It Matters
Renewable energy selection using fuzzy MCDM models supports investment decisions in countries like Turkey, where Murat Çolak and İhsan Kaya (2017) prioritized alternatives through an integrated fuzzy MCDM model, demonstrating practical application for national energy planning. Solar site selection in arid regions benefits from fuzzy logic and weighted linear combination methods, with Mahmood Zoghi et al. (2015) optimizing sites in Isfahan, Iran, to enhance renewable energy deployment. Green hydrogen production prospects are evaluated for high-potential countries by Владимир Панченко et al. (2022), identifying strategies to reduce carbon emissions from fossil fuels. Bioenergy supply forecasting uses QROF-DEMATEL and random forest models, as Miraj Ahmed Bhuiyan et al. (2021) linked economic indicators to supply in developed economies, aiding sustainable investment efficiency.
Reading Guide
Where to Start
"Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: A real case application for Turkey" by Murat Çolak and İhsan Kaya (2017) because it provides a practical, real-world application of fuzzy MCDM accessible for understanding core prioritization methods.
Key Papers Explained
Murat Çolak and İhsan Kaya (2017) established fuzzy MCDM for renewable prioritization in Turkey, which Gang Kou et al. (2022) extended to inventive problem-solving for carbon emission strategies in solar transportation investments. Mahmood Zoghi et al. (2015) complemented this with fuzzy logic for solar site selection in Iran, while Pratibha Rani et al. (2020) advanced fuzzy TOPSIS for energy source selection, building on multi-criteria foundations from Abdolreza Yazdani–Chamzini et al. (2013). Miraj Ahmed Bhuiyan et al. (2021) linked these to economic forecasting for bioenergy supply.
Paper Timeline
Most-cited paper highlighted in red. Papers ordered chronologically.
Advanced Directions
Current research emphasizes hybrid modeling for financial development and innovation in green supply chains, extending fuzzy MCDM from top papers like Çolak and Kaya (2017). Frontiers involve integrating global indicators with QROF-DEMATEL as in Bhuiyan et al. (2021) for bioenergy. No recent preprints available, so focus remains on optimizing MCDM for transportation emissions per Kou et al. (2022).
Papers at a Glance
Latest Developments
Recent developments in energy and environmental sustainability research as of February 2026 include a focus on reducing fossil fuel demand, with global demand expected to grow less than 1% in 2026 (S&P Global). Significant progress is also being made in renewable energy deployment, with solar and wind energy expanding at an unprecedented pace worldwide, and renewable energy surpassing coal as the leading source of electricity in 2025 (Yale School of the Environment). Additionally, major conferences like ICEER 2026 and ISEC 2026 are focusing on innovative solutions for energy and environmental challenges (ICEER, ISEC). Advances in technologies such as corrosion-free flow batteries and sustainable electrolytes are also being actively researched (Nature Energy, Nature Reviews).
Sources
Frequently Asked Questions
What methods are used for renewable energy prioritization?
Integrated fuzzy MCDM models prioritize renewable energy alternatives, as applied in Turkey by Murat Çolak and İhsan Kaya (2017). These models evaluate multiple criteria for optimal selection in real-case scenarios. Fuzzy TOPSIS with new divergence measures extends this for renewable energy source selection.
How is solar site selection optimized?
Fuzzy logic models combined with weighted linear combination methods optimize solar site selection in arid regions. Mahmood Zoghi et al. (2015) applied this in Isfahan, Iran, for effective renewable energy planning. The approach accounts for environmental and geographic factors.
What role do fuzzy models play in energy decisions?
Fuzzy decision-making models evaluate investment strategies and global indicators in renewable energy. Abdolreza Yazdani–Chamzini et al. (2013) used multi-criteria decision making to select optimal renewables considering environmental and resource limits. Pratibha Rani et al. (2020) advanced fuzzy TOPSIS for source selection.
How does bioenergy relate to economic indicators?
QROF-DEMATEL and random forest models identify economic indicators for bioenergy supply forecasting. Miraj Ahmed Bhuiyan et al. (2021) analyzed these in developed economies to improve investment efficiency. Bioenergy reduces fossil fuel dependence while supporting environmental sustainability.
What are prospects for green hydrogen production?
Countries with high potential for green hydrogen production are reviewed by Владимир Панченко et al. (2022). The study assesses production prospects to advance renewable energy strategies. This supports low-carbon alternatives in the energy sector.
What is anaerobic biotechnology for bioenergy?
Anaerobic biotechnology produces bioenergy through processes outlined in the 2008 work with 312 citations. It addresses renewable energy needs amid limited resources and emissions issues. The approach is key for sustainable bioenergy generation.
Open Research Questions
- ? How can inventive problem-solving maps further reduce carbon emissions in solar energy-based transportation projects beyond current strategies in Gang Kou et al. (2022)?
- ? What improvements to fuzzy TOPSIS divergence measures would enhance accuracy in selecting renewable energy sources under Pratibha Rani et al. (2020)?
- ? Which economic indicators most reliably predict bioenergy supply expansions using advanced QROF-DEMATEL models as in Miraj Ahmed Bhuiyan et al. (2021)?
- ? How might hybrid fuzzy models integrate global indicators for green supply chain management in renewable investments?
- ? What site-specific factors limit fuzzy logic optimization for solar energy in semi-arid regions beyond Isfahan cases?
Recent Trends
The field maintains 2,573 works with no specified 5-year growth rate.
Fuzzy MCDM applications persist, as in 2022 papers by Владимир Панченко et al. on green hydrogen and Gang Kou et al. on solar transportation emissions, each with high citations (317 and 249).
Economic modeling for bioenergy by Miraj Ahmed Bhuiyan et al. with 150 citations highlights ongoing focus on investment efficiency amid no recent preprints or news.
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