1
UG student, ai & ds panimalar engineering college, chennai,india
(171110066@aue.ae)
2
UG student, ai & ds panimalar engineering college, chennai,india
(171110025@aue.ae)
3
UG student, ai & ds panimalar engineering college, chennai,india
(181120029@aue.ae)
Abstract :
The aim of this proof of concept is to develop a framework to trace the carbon footprints emitted by fossil fuels during power generation. The framework will utilize a life cycle assessment approach to identify the amount of greenhouse gas emissions associated with each stage of the power generation process, from raw material (fuel) extraction to power delivery. The proof of concept will focus on the use of coal and natural gas, which are the most widely used fossil fuels in power generation.The data collected from sources is used to create model which can help us to estimate the amount of carbon footprint generated from different types of power plants like coal-fired power plants and natural gas-fired power plants.The results of this proof of concept are analyzed to identify areas where we can reduce the greenhouse gas emission and also to develop and deploy strategies to transition to cleaner sustainable energy sources.Overall, this concept will provide a valuable tool for energy policymakers and stakeholders to make informed decisions about reducing carbon footprints from fossil fuel power generation
Keywords :
Carbon Footprints; Coal; Natural gas; Power Generation; Greenhouse Gas Emissions; Energy Sources.
References :
[1] Basma K. Eldrandaly. "ActivBench: Leveraging Human Activity Inference from Smartphone Sensors for Human Computer Interactions." Journal of Cognitive Human-Computer Interaction, Vol. 5, No. 2, 2023 ,PP. 45-62.
[2] Balan Sundarakani, Robert de Souza, Mark Goh, Stephan M. Wagner, Sushmera Manikandan, Modeling carbon footprints across the supply chain,International Journal of Production Economics,Volume 128, Issue 1,2010,Pages 43-50,ISSN 0925-5273,
[3] Benjamin K. Sovacool, Marilyn A. Brown, Twelve metropolitan carbon footprints: A preliminary comparative global assessment,Energy Policy,Volume 38, Issue 9,2010,Pages 4856-4869,ISSN 0301-4215,
[4] Malini Srinivasan,Jishnu Dineshan ,Gondi Surender Dhanunjay,Shamala Ramappa. "Measuring the Coverage of Assembly elections and Covid 19 during the pandemic in India." Journal of Cognitive Human-Computer Interaction, Vol. 6, No. 1, 2023 ,PP. 18-31.
[5] S. Manigandaa,V. D. Ambeth Kumar,G. Ragunath,R. Venkatesan,N. Senthil Kumar, De-Noising and Segmentation of Medical Images using Neutrophilic Sets, Journal of Fusion: Practice and Applications, Vol. 11 , No. 2 , (2023) : 111-123 (Doi : https://doi.org/10.54216/FPA.110208)
[6] Shan, Shaonan & Li, Yulong & Zhang, Zicheng & Zhu, Wei & Zhang, Tingting. (2023). Identification of Key Carbon Emission Industries and Emission Reduction Control Based on Complex Network of Embodied Carbon Emission Transfers: The Case of Hei-Ji-Liao, China. International Journal of Environmental Research and Public Health. 20. 10.3390/ijerph20032603.
[7] Wang, Qiang & Li, Rongrong & Su, Min & Wang, Shasha. (2022). Extreme events and carbon emissions: What we could learn from decomposition of national- and sector-carbon emission. Energy Strategy Reviews. 44. 100978. 10.1016/j.esr.2022.100978.
[8] P. Kavitha,R. Subha Shini,R. Priya. "An Implementation Of Statistical Feature Algorithms For The Detection Of Brain Tumor." Journal of Cognitive Human-Computer Interaction, Vol. 1, No. 2, 2021 ,PP. 57 - 62.
[9] Sonia Jenifer Rayen. "Survey On Smart Cane For Visually Impaired Using IOT." Journal of Cognitive Human-Computer Interaction, Vol. 1, No. 2, 2021 ,PP. 81 - 85.
[10] Has, Michael. (2021). Methodology to assess Green House Gas Emissions and emission-related Risks for Companies.
[11] Ibemere, Uche & Mmata, Bella & Onyekonwu, M.O.. (2015). Effective Monitoring of GreenHouse Gas Emission - A Laboratory Approach. 10.2118/178390-MS.
[12] Vol, Aabfj & Bhagwat, & Gujar, & Rout, & Natholia, & Sanjay, & Nulkar, Gurudas & Malik, & Bhagwat, & Pawar, & Carbon,. (2023). Carbon Emissions in the Pune Metropolitan Region (PMR) due to Logistics Industries. Australasian Accounting, Business and Finance Journal. 17. 10.14453/aabfj.v17i1.10.
[13] R. Venkatesan,Gokul Santhosh Y.,Sathya Preiya V.,V.D.Ashok Kumar. "Smart Wheelchair-An Effective Transport for Handicapped and Aged Citizens." Journal of Cognitive Human-Computer Interaction, Vol. 4, No. 2, 2022 ,PP. 08-19.
[14] Pream Anand S.,Manamalli D.,Vasanthi D.,Mythily M.,Naveen N. E.. "Optimization of Performance Attributes Using RTDA Controller for Dual CSTR." Journal of Cognitive Human-Computer Interaction, Vol. 5, No. 1, 2023 ,PP. 08-19.
[15] Delanoë, Paul & Tchuente, Dieudonne & Colin, Guillaume. (2023). Method and evaluations of the effective gain of artificial intelligence models for reducing CO2 emissions. Journal of environmental management. 331. 117261. 10.1016/j.jenvman.2023.117261.
[16] Sharma, Neha & De, Prithwis. (2022). Climate Change and AI in the Financial, Energy, Domestic, and Transport Sectors. 10.1007/978-981-19-5244-9_1.
[17] Dvorak, Tomas & Shah, Amish & Rineer, J.M. & Dvorak, C. & Zeidan, Omar & Meeks, S.. (2022). Carbon Footprint of Clinical Photon Therapy: Initial Estimates. International Journal of Radiation Oncology*Biology*Physics. 114. e337. 10.1016/j.ijrobp.2022.07.1426.
[18] Shah, Savan & Barnard, Heidi & George, Kuriakose. (2023). The use of AI-technology to determine the carbon footprint of spinal surgery: experiences of a tertiary center (Preprint). 10.2196/preprints.46775.
[19] Shi, Xiaoyang & Xiao, Hang & Weifeng, Liu & Lackner, Klaus & Buterin, Vitalik & Stocker, Thomas. (2023). Confronting the Carbon-Footprint Challenge of Blockchain. Environmental Science & Technology. 10.1021/acs.est.2c05165.
[20] Thani Almuhairi, Ahmad Almarri, Khalid Hokal . An Artificial Intelligence -based Intrusion Detection System American University in the Emirates, Dubai, UAE. (JCIM) Vol. 7, No. 2, PP. 95-111, 2021.
[21] S. Hemamalini,V. D. Ambeth Kumar,R. Venkatesan,S. Malathi, Relevance Mapping based CNN model with OSR-FCA Technique for Multi-label DR Classification, Journal of Fusion: Practice and Applications, Vol. 11 , No. 2 , (2023) : 90-110 (Doi : https://doi.org/10.54216/FPA.110207)
[22] Malini Srinivasan,Jishnu Dineshan ,Gondi Surender Dhanunjay,Shamala Ramappa. "Measuring the Coverage of Assembly elections and Covid 19 during the pandemic in India." Journal of Cognitive Human-Computer Interaction, Vol. 6, No. 1, 2023 ,PP. 18-31.
| Style | # |
|---|---|
| MLA | Mohammad Nawaz Sheriff, Mota Harshavardhan Reddy, Mohamed Tharik. "Survey Paper About Carbon Footprint." Journal of Cognitive Human-Computer Interaction, Vol. 6, No. 1, 2023 ,PP. 39-44 (Doi : https://doi.org/10.54216/JCHCI.060104) |
| APA | Mohammad Nawaz Sheriff, Mota Harshavardhan Reddy, Mohamed Tharik. (2023). Survey Paper About Carbon Footprint. Journal of Journal of Cognitive Human-Computer Interaction, 6 ( 1 ), 39-44 (Doi : https://doi.org/10.54216/JCHCI.060104) |
| Chicago | Mohammad Nawaz Sheriff, Mota Harshavardhan Reddy, Mohamed Tharik. "Survey Paper About Carbon Footprint." Journal of Journal of Cognitive Human-Computer Interaction, 6 no. 1 (2023): 39-44 (Doi : https://doi.org/10.54216/JCHCI.060104) |
| Harvard | Mohammad Nawaz Sheriff, Mota Harshavardhan Reddy, Mohamed Tharik. (2023). Survey Paper About Carbon Footprint. Journal of Journal of Cognitive Human-Computer Interaction, 6 ( 1 ), 39-44 (Doi : https://doi.org/10.54216/JCHCI.060104) |
| Vancouver | Mohammad Nawaz Sheriff, Mota Harshavardhan Reddy, Mohamed Tharik. Survey Paper About Carbon Footprint. Journal of Journal of Cognitive Human-Computer Interaction, (2023); 6 ( 1 ): 39-44 (Doi : https://doi.org/10.54216/JCHCI.060104) |
| IEEE | Mohammad Nawaz Sheriff, Mota Harshavardhan Reddy, Mohamed Tharik, Survey Paper About Carbon Footprint, Journal of Journal of Cognitive Human-Computer Interaction, Vol. 6 , No. 1 , (2023) : 39-44 (Doi : https://doi.org/10.54216/JCHCI.060104) |