TOWARDS A CARBON-NEUTRAL FUTURE: THE IMPACT OF INTEGRATED APPLICATIONS OF SMART SYSTEMS ON CARBON FOOTPRINT

Abstract

Today, global warming and climate change were primarily driven by greenhouse gas emissions, which have become some of the most significant threats to environmental sustainability and all life forms. Reducing the carbon footprint is one of the key strategies for diminishing this threat, and smart systems play a crucial and central pivot role in this process. This review article examines the influence and potential of smart systems in achieving a carbon-neutral future. It first investigates the contributions of innovative technologies in areas such as smart devices, energy management systems, transportation solutions, and water and wastewater management to environmental sustainability. The study provides a detailed discussion on how IoT-based energy management, smart building systems, the integration of renewable energy, and smart grids enhance energy efficiency and reduce greenhouse gas emissions. Furthermore, it features how electric and autonomous vehicles, intelligent traffic management, public transportation, and micro-mobility optimization boost sustainable urban mobility. In addition, the role of smart water management and circular economy approaches in limiting waste generation and reducing greenhouse gas emissions, especially carbon dioxide is evaluated. However, several key challenges delay the extensive adoption of smart systems. This study discusses the policies, stimulus mechanisms, and research and development efforts needed to overcome these barriers. Finally, it offers recommendations on the future of smart systems and potential areas for further development.

Keywords

• Carbon footprint
• smart systems
• energy efficiency
• smart transportation
• smart devices
• sustainability
• carbon neutral

KARBON NÖTR GELECEĞE DOĞRU: AKILLI SİSTEMLERİN ENTEGRE UYGULAMALARIYLA KARBON AYAK İZİ ÜZERİNDEKİ ETKİSİ

Abstract

Günümüzde sera gazları kaynaklı olan küresel ısınma ve iklim değişikliği, çevresel sürdürülebilirlik ve canlı yaşamı açısından en büyük tehditlerden biri haline geldi. Karbon ayak izinin azaltılması, bu tehdidi en aza indirmek için başlıca stratejilerden birisi olup, akıllı sistemler bu süreçte oldukça önemlidir ve anahtar bir rol oynamaktadır. Bu derleme makalesi, akıllı sistemlerin karbon nötr bir geleceğe ulaşmadaki etkisini ve potansiyelini incelemektedir. Öncelikle, akıllı cihazlar, enerji yönetim sistemleri, ulaşım çözümleri ile su ve atıksu yönetimi gibi alanlardaki yenilikçi teknolojilerin çevresel sürdürülebilirliğe katkıları incelenmiştir. Çalışmada, IoT tabanlı enerji yönetimi, akıllı bina sistemleri, yenilenebilir enerjinin entegre edilmesi ve akıllı şebekeler gibi teknolojilerin enerji verimliliğini artırarak sera gazı salınımlarını nasıl düşürdüğü detaylı bir şekilde aktarılmakta ve örneklerle anlatılmaktadır. Ayrıca, elektrikli ve otonom araçlar, akıllı trafik yönetimi ve toplu taşıma ile beraber mikro mobilite optimizasyonunun şehirlerde sürdürülebilir bir hareketliliği teşvik ettiği vurgulanmaktadır. Bunun yanı sıra, akıllı su yönetimi ve döngüsel ekonomi yaklaşımlarının atık miktarını ve karbon dioksit başta olmak üzere sera gazı salınımını azaltmadaki rolü değerlendirilmiştir. Ancak, akıllı sistemlerin yaygınlaşmasını engelleyen bazı temel zorluklar bulunmaktadır. Çalışmada, bu engellerin aşılması için gerekli olan politikalar, teşvik mekanizmaları ve araştırma-geliştirme faaliyetleri tartışılmıştır. Son olarak, akıllı sistemlerin geleceği ve gelişim alanları üzerine öneriler sunulmuştur.

Keywords

• Karbon ayak izi
• akıllı sistemler
• enerji verimliliği
• akıllı ulaşım
• akıllı cihazlar
• akıllı enerji yönetimi
• sürdürülebilirlik
• karbon nötr

References

1. 1. Skytt, T., S.N. Nielsen, and B.-G. Jonsson, Global warming potential and absolute global temperature change potential from carbon dioxide and methane fluxes as indicators of regional sustainability – A case study of Jämtland, Sweden. Ecological Indicators, 2020. 110: p. 105831.
2. 2. Çelekli, A. and Ö.E. Zariç, From Emissions to Environmental Impact: Understanding the Carbon Footprint. International Journal of Environment and Geoinformatics, 2023. 10(4): p. 146-156.
3. 3. Alofaysan, H., The Effect of Environmental Smart Technology and Renewable Energy on Carbon Footprint: A Sustainability Perspective from the MENA Region. Energies, 2024. 17(11): p. 2624.
4. 4. Sofuoğlu, E. and D. Kirikkaleli, Towards achieving net zero emission targets and sustainable development goals, can long-term material footprint strategies be a useful tool? Environmental Science and Pollution Research, 2023. 30(10): p. 26636-26649.
5. 5. Akrofi, M.M., M. Okitasari, and R. Kandpal, Recent trends on the linkages between energy, SDGs and the Paris Agreement: a review of policy-based studies. Discover Sustainability, 2022. 3(1): p. 32.
6. 6. Chen, L., et al., Strategies to achieve a carbon neutral society: a review. Environmental Chemistry Letters, 2022. 20(4): p. 2277-2310.
7. 7. Zhao, X., et al., Challenges toward carbon neutrality in China: Strategies and countermeasures. Resources, Conservation and Recycling, 2022. 176: p. 105959.
8. 8. Zhang, H., Pathways to carbon neutrality in major exporting countries: the threshold effect of digital transition. Environmental Science and Pollution Research, 2023. 30(3): p. 7522-7542.

9. 9. Erdogan, S., U.K. Pata, and S.A. Solarin, Towards carbon-neutral world: The effect of renewable energy investments and technologies in G7 countries. Renewable and Sustainable Energy Reviews, 2023. 186: p. 113683.
10. 10. Elkhorchani, H. and K. Grayaa, Novel home energy management system using wireless communication technologies for carbon emission reduction within a smart grid. Journal of Cleaner Production, 2016. 135: p. 950-962.
11. 11. Mahapatra, C., A.K. Moharana, and V.C.M. Leung, Energy Management in Smart Cities Based on Internet of Things: Peak Demand Reduction and Energy Savings. Sensors, 2017. 17(12): p. 2812.
12. 12. Li, J., et al., Methods and applications for Artificial Intelligence, Big Data, Internet of Things, and Blockchain in smart energy management. Energy and AI, 2023. 11: p. 100208.
13. 13. Alaybeyoğlu, E. and C. Turhan, TAŞRA BÖLGELERDE KULLANILAN SİSTEMLERİN KABLOSUZ TEKNOLOJİLER YARDIMIYLA DENETİMİ. Akıllı Sistemler Dergisi, 2023. 2(1): p. 68-73.
14. 14. Bayindir, R., et al., Smart grid technologies and applications. Renewable and Sustainable Energy Reviews, 2016. 66: p. 499-516.
15. 15. Coronado Mondragon, A.E., E.S. Coronado, and C.E. Coronado Mondragon, Defining a convergence network platform framework for smart grid and intelligent transport systems. Energy, 2015. 89: p. 402-409.
16. 16. Diahovchenko, I., et al., Progress and Challenges in Smart Grids: Distributed Generation, Smart Metering, Energy Storage and Smart Loads. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 2020. 44(4): p. 1319-1333.
17. 17. Bagdadee, A.H., L. Zhang, and M. Saddam Hossain Remus. A Brief Review of the IoT-Based Energy Management System in the Smart Industry. in Artificial Intelligence and Evolutionary Computations in Engineering Systems. 2020. Singapore: Springer Singapore.
18. 18. Massar, M., et al., Impacts of Autonomous Vehicles on Greenhouse Gas Emissions—Positive or Negative? International Journal of Environmental Research and Public Health, 2021. 18(11): p. 5567.
19. 19. Patella, S.M., et al., Carbon Footprint of autonomous vehicles at the urban mobility system level: A traffic simulation-based approach. Transportation Research Part D: Transport and Environment, 2019. 74: p. 189-200.
20. 20. Chen, W., et al., Artificial Intelligence in Logistics Optimization with Sustainable Criteria: A Review. Sustainability, 2024. 16(21): p. 9145.
21. 21. Mishra, P. and G. Singh, Energy Management Systems in Sustainable Smart Cities Based on the Internet of Energy: A Technical Review. Energies, 2023. 16(19): p. 6903.
22. 22. Dincer, I. and C. Acar, Smart energy systems for a sustainable future. Applied Energy, 2017. 194: p. 225-235.
23. 23. Salman, M.Y. and H. Hasar, Review on environmental aspects in smart city concept: Water, waste, air pollution and transportation smart applications using IoT techniques. Sustainable Cities and Society, 2023. 94: p. 104567.
24. 24. Goundar, S., A. Purwar, and A. Singh, Applications of artificial intelligence, big data and internet of things in sustainable development. 2022: CRC Press.
25. 25. Nguyen, K.H. and M. Kakinaka, Renewable energy consumption, carbon emissions, and development stages: Some evidence from panel cointegration analysis. Renewable Energy, 2019. 132: p. 1049-1057.
26. 26. Shah, S.F.A., et al., The Role of Machine Learning and the Internet of Things in Smart Buildings for Energy Efficiency. Applied Sciences, 2022. 12(15): p. 7882.
27. 27. Shah, A.S., et al., A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments. Information, 2019. 10(3): p. 108.
28. 28. Baharudin, N., et al., Smart lighting system control strategies for commercial buildings: A review. International Journal of Advanced Technology and Engineering Exploration, 2021. 8(74): p. 45.
29. 29. Sinoplu, M. and E.B. Ceyhan, Akıllı Binalarda Yapay Zekâ Destekli Enerji Yönetimi: Bir İnceleme. Uluslararası Batı Karadeniz Mühendislik ve Fen Bilimleri Dergisi, 2023. 5(1): p. 39-63.
30. 30. Asopa, P., et al. Reducing Carbon Footprint for Sustainable development of Smart Cities using IoT. in 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV). 2021.
31. 31. Homod, R.Z., Analysis and optimization of HVAC control systems based on energy and performance considerations for smart buildings. Renewable Energy, 2018. 126: p. 49-64.
32. 32. Vijayan, D.S., et al., Automation systems in smart buildings: a review. Journal of Ambient Intelligence and Humanized Computing, 2020.
33. 33. Sikder, A.K., et al. IoT-enabled smart lighting systems for smart cities. in 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC). 2018.
34. 34. Metallidou, C.K., K.E. Psannis, and E.A. Egyptiadou, Energy Efficiency in Smart Buildings: IoT Approaches. IEEE Access, 2020. 8: p. 63679-63699.
35. 35. Youssef, H., et al., Optimizing energy consumption patterns of smart home using a developed elite evolutionary strategy artificial ecosystem optimization algorithm. Energy, 2023. 278: p. 127793.
36. 36. Stavropoulos, P., et al., A Framework for CO2 Emission Reduction in Manufacturing Industries: A Steel Industry Case. Designs, 2022. 6(2): p. 22.
37. 37. Rathor, S.K. and D. Saxena, Energy management system for smart grid: An overview and key issues. International Journal of Energy Research, 2020. 44(6): p. 4067-4109.
38. 38. Marinakis, V., Big Data for Energy Management and Energy-Efficient Buildings. Energies, 2020. 13(7): p. 1555.
39. 39. Das, A.K. and A. Sharma, Chapter 1 - Climate change and the energy sector, in Advancement in Oxygenated Fuels for Sustainable Development, N. Kumar, et al., Editors. 2023, Elsevier. p. 1-6.
40. 40. Shan, S., et al., Role of green technology innovation and renewable energy in carbon neutrality: A sustainable investigation from Turkey. Journal of Environmental Management, 2021. 294: p. 113004.
41. 41. Hoang, A.T., V.V. Pham, and X.P. Nguyen, Integrating renewable sources into energy system for smart city as a sagacious strategy towards clean and sustainable process. Journal of Cleaner Production, 2021. 305: p. 127161.
42. 42. Aslan, E., N. Beşli, and A. Gümüşçü, İnşaat Güneş Enerjisi Santrallerinin Akıllı Şebekelere Entegrasyonu. Turkish Journal of Scientific Reviews, 2017. 10(2): p. 10-13.
43. 43. Bahçeci, S. and F. Daldaban, Dağıtım Şebekelerinde Güneş Panelleri ve Enerji Depolama Sistemi Uygulaması. El-Cezeri, 2017. 4(3): p. 308-313.
44. 44. Kaygusuz, A. and A. Acar, Güç Sistemlerinde Farklı Enerji Depolama Seviyelerinde Sistem Kararlılığının İncelenmesi. Computer Science, 2023. Vol:8(Issue:1): p. 1-15.
45. 45. Mostafa, N., H.S.M. Ramadan, and O. Elfarouk, Renewable energy management in smart grids by using big data analytics and machine learning. Machine Learning with Applications, 2022. 9: p. 100363.
46. 46. Wong, Y.S., et al. Stationary and mobile battery energy storage systems for smart grids. in 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT). 2011.
47. 47. Diamantoulakis, P.D., V.M. Kapinas, and G.K. Karagiannidis, Big Data Analytics for Dynamic Energy Management in Smart Grids. Big Data Research, 2015. 2(3): p. 94-101.
48. 48. Qian, F., et al., Artificial intelligence for smart energy systems in process industries. Applied Energy, 2022. 324: p. 119684.
49. 49. Oprea, S.-V., et al., Insights into demand-side management with big data analytics in electricity consumers’ behaviour. Computers & Electrical Engineering, 2021. 89: p. 106902.
50. 50. Mariano-Hernández, D., et al., A review of strategies for building energy management system: Model predictive control, demand side management, optimization, and fault detect & diagnosis. Journal of Building Engineering, 2021. 33: p. 101692.
51. 51. Imran, A., et al., Heuristic-Based Programable Controller for Efficient Energy Management Under Renewable Energy Sources and Energy Storage System in Smart Grid. IEEE Access, 2020. 8: p. 139587-139608.
52. 52. Attia, M., et al. Towards an efficient energy management to reduce CO2 emissions and billing cost in smart buildings. in 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC). 2018.
53. 53. Sun, Y.-F., Y.-J. Zhang, and B. Su, How does global transport sector improve the emissions reduction performance? A demand-side analysis. Applied Energy, 2022. 311: p. 118648.
54. 54. Khalili, S., et al., Global Transportation Demand Development with Impacts on the Energy Demand and Greenhouse Gas Emissions in a Climate-Constrained World. Energies, 2019. 12(20): p. 3870.
55. 55. Bamwesigye, D. and P. Hlavackova, Analysis of Sustainable Transport for Smart Cities. Sustainability, 2019. 11(7): p. 2140.
56. 56. Liu, C. and L. Ke, Cloud assisted Internet of things intelligent transportation system and the traffic control system in the smart city. Journal of Control and Decision, 2023. 10(2): p. 174-187.
57. 57. Xia, X., et al., Life cycle carbon footprint of electric vehicles in different countries: A review. Separation and Purification Technology, 2022. 301: p. 122063.
58. 58. Mohammed, A., et al., Strategies and sustainability in fast charging station deployment for electric vehicles. Scientific Reports, 2024. 14(1): p. 283.
59. 59. Chen, B., et al., The Effects of Autonomous Vehicles on Traffic Efficiency and Energy Consumption. Systems, 2023. 11(7): p. 347.
60. 60. Onat, N.C., et al., Rebound effects undermine carbon footprint reduction potential of autonomous electric vehicles. Nature Communications, 2023. 14(1): p. 6258.
61. 61. Pataki, D.E., et al., An integrated approach to improving fossil fuel emissions scenarios with urban ecosystem studies. Ecological Complexity, 2009. 6(1): p. 1-14.
62. 62. Nallaperuma, D., et al., Online Incremental Machine Learning Platform for Big Data-Driven Smart Traffic Management. IEEE Transactions on Intelligent Transportation Systems, 2019. 20(12): p. 4679-4690.
63. 63. Sharif, A., et al. Internet of things — smart traffic management system for smart cities using big data analytics. in 2017 14th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). 2017.
64. 64. Khang, A. and K. Singh, Internet of Things (IoT) Smart Sensing Traffic Lights for Revolutionizing Urban Traffic Management, in Driving Green Transportation System Through Artificial Intelligence and Automation : Approaches, Technologies and Applications, A. Khang, Editor. 2025, Springer Nature Switzerland: Cham. p. 105-118.
65. 65. Nasir, M.K., et al., Reduction of Fuel Consumption and Exhaust Pollutant Using Intelligent Transport Systems. The Scientific World Journal, 2014. 2014(1): p. 836375.
66. 66. Ercan, T., N.C. Onat, and O. Tatari, Investigating carbon footprint reduction potential of public transportation in United States: A system dynamics approach. Journal of Cleaner Production, 2016. 133: p. 1260-1276.
67. 67. Ushakov, D., et al., The Internet of Things impact on smart public transportation. Transportation Research Procedia, 2022. 63: p. 2392-2400.
68. 68. Zhang, Y., et al., A comparative analysis of the potential of carbon emission reductions from shared micro-mobility. Sustainable Energy Technologies and Assessments, 2024. 72: p. 104088.
69. 69. Gupta, A.D., et al., Smart Water Technology for Efficient Water Resource Management: A Review. Energies, 2020. 13(23): p. 6268.
70. 70. Delikanli, N.E., et al., Removal of crystal violet dye with an innovative biosorbent (equisetum ramosissimum desf.). 2024, 2024. 23(3): p. 12.
71. 71. Delikanlı, N.E., Bartın İlinde İçme/Kullanma Suları Üzerine Ön Çalışma. Doğal Afetler ve Çevre Dergisi, 2025. 11(1): p. 1-13.
72. 72. Singh, M. and S. Ahmed, IoT based smart water management systems: A systematic review. Materials Today: Proceedings, 2021. 46: p. 5211-5218.
73. 73. Krishnan, S.R., et al., Smart Water Resource Management Using Artificial Intelligence—A Review. Sustainability, 2022. 14(20): p. 13384.
74. 74. Fardan, S. and A. Al-Sartawi, Roll of Artificial Intelligence in Smart Metering System for Water Distribution, in Artificial Intelligence, Internet of Things, and Society 5.0, A. Hannoon and A. Mahmood, Editors. 2023, Springer Nature Switzerland: Cham. p. 291-298.
75. 75. Slaný, V., et al., An Integrated IoT Architecture for Smart Metering Using Next Generation Sensor for Water Management Based on LoRaWAN Technology: A Pilot Study. Sensors, 2020. 20(17): p. 4712.
76. 76. Kamienski, C., et al., Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture. Sensors, 2019. 19(2): p. 276.
77. 77. Ahmed, M.M., E. Hassanien, and A.E. Hassanien, IoT-based intelligent waste management system. Neural Computing and Applications, 2023. 35(32): p. 23551-23579.
78. 78. Mookkaiah, S.S., et al., Design and development of smart Internet of Things–based solid waste management system using computer vision. Environmental Science and Pollution Research, 2022. 29(43): p. 64871-64885.
79. 79. Fang, B., et al., Artificial intelligence for waste management in smart cities: a review. Environmental Chemistry Letters, 2023. 21(4): p. 1959-1989.
80. 80. Moraga, G., et al., Circular economy indicators: What do they measure? Resources, Conservation and Recycling, 2019. 146: p. 452-461.
81. 81. Ragossnig, A.M. and D.R. Schneider, Circular economy, recycling and end-of-waste. Waste Management & Research, 2019. 37(2): p. 109-111.
82. 82. Sürmeli, R.Ö., et al., Phosphate recovery from digestate using magnesium-modified fungal biochar. Clean Technologies and Environmental Policy, 2024.
83. 83. Senadheera, U.E., et al., Beyond Composting Basics: A Sustainable Development Goals—Oriented Strategic Guidance to IoT Integration for Composting in Modern Urban Ecosystems. Sustainability, 2024. 16(23): p. 10332.
84. 84. Bayrakdar, A., et al., Biogas production from chicken manure: Co-digestion with spent poppy straw. International Biodeterioration & Biodegradation, 2017. 119: p. 205-210.
85. 85. Afotey, B. and G.T. Sarpong, Estimation of biogas production potential and greenhouse gas emissions reduction for sustainable energy management using intelligent computing technique. Measurement: Sensors, 2023. 25: p. 100650.
86. 86. Ferro-Escobar, R., H. Vacca-González, and H. Gómez-Castillo, Smart and Sustainable Cities in Collaboration with IoT: The Singapore Success Case, in Machine Learning for Smart Environments/Cities: An IoT Approach, G. Marques, A. González-Briones, and J.M. Molina López, Editors. 2022, Springer International Publishing: Cham. p. 213-243.
87. 87. Nikolaeva, A., Smart Cities and (Smart) Cycling: Exploring the Synergies in Copenhagen and Amsterdam. Journal of Urban Technology, 2024. 31(1): p. 29-49.
88. 88. Mathiesen, B.V., et al., Copenhagen Energy Vision: A sustainable vision for bringing a Capital to 100% renewable energy. 2015.
89. 89. Aslan, M.M., Akıllı Kent Uygulamalarının Kentlerde Yaşanan Trafik Sorununun ve Ulaşıma Bağlı Olarak Ortaya Çıkan Çevre Kirliliğinin Azaltılmasına Etkisi: Akıllı Ulaşım Uygulamaları. JOEEP: Journal of Emerging Economies and Policy, 2024. 9(2): p. 388-399.
90. 90. Yazkan, B. Impact of Adaptive Traffic Management System on Carbon Emissions: Istanbul Case. in A Pathway to Safe, Smart, and Resilient Road and Mobility Networks. 2024. Cham: Springer Nature Switzerland.
91. 91. Bıyık, C., Smart Cities in Turkey: Approaches, Advances and Applications with Greater Consideration for Future Urban Transport Development. Energies, 2019. 12(12): p. 2308.
92. 92. Uslu, H. and H. Erkekoğlu, ENDÜSTRİ 4.0 TEKNOLOJİK DÖNÜŞÜM SÜRECİNDE SEÇİLMİŞ ÜLKELER VE TÜRKİYE’NİN DURUMU: AMPİRİK BİR ANALİZ. Verimlilik Dergisi, 2021(4): p. 51-65.
93. 93. Turner, S.W. and S. Uludag, Toward Smart Cities via the Smart Grid and Intelligent Transportation Systems. Smart Grid, 2017: p. 117-166.
94. 94. Ma, S., et al., Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries. Applied Energy, 2022. 326: p. 119986.
95. 95. Zhang, Y., et al., A big data driven analytical framework for energy-intensive manufacturing industries. Journal of Cleaner Production, 2018. 197: p. 57-72.
96. 96. Oguntola, O., K. Boakye, and S. Simske, Towards Leveraging Artificial Intelligence for Sustainable Cement Manufacturing: A Systematic Review of AI Applications in Electrical Energy Consumption Optimization. Sustainability, 2024. 16(11): p. 4798.
97. 97. Bocken, N.M.P. and J.M. Allwood, Strategies to reduce the carbon footprint of consumer goods by influencing stakeholders. Journal of Cleaner Production, 2012. 35: p. 118-129.
98. 98. Guo, Q., Y. Wang, and X. Dong, Effects of smart city construction on energy saving and CO2 emission reduction: Evidence from China. Applied Energy, 2022. 313: p. 118879.
99. 99. Borysiak, O., et al., Smart Transition to Climate Management of the Green Energy Transmission Chain. Sustainability, 2022. 14(18): p. 11449.
100. 100. Fetting, C., The European green deal. ESDN Report, December, 2020. 2(9): p. 53.
101. 101. Sinan, B., TÜRKİYE’DE YEKDEM İLE DÖVİZ KURU, ELEKTRİK TÜKETİMİ ARASINDAKİ İLİŞKİ (2012.1-2020.2). Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 2021. 6(2): p. 191-207.
102. 102. Aydoğdu, Ç., Yenilenebilir Enerji Sektöründe ve Enerji Verimliliğinde Kamusal Destekler ve Türkiye’de Yansımaları. Akademik İzdüşüm Dergisi, 2021. 6(1): p. 52-74.
103. 103. Orun, A.F. and B. Demirgil, TÜRKİYE’DE YENİLENEBİLİR ENERJİ YATIRIMLARINA YÖNELİK TEŞVİKLER VE YENİLENEBİLİR ENERJİNİN EKONOMİK ETKİLERİ. Uluslararası İktisadi ve İdari Akademik Araştırmalar Dergisi, 2021. 1(2): p. 90-112.
104. 104. Özcan, M., B. Ergün, and E. Ocaklı, Türkiye’de Kullanılan Yenilenebilir Enerji Sertifika Sistemlerinin Değerlendirilmesi. EMO Bilimsel Dergi, 2021. 11(21): p. 29-41.