Forecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithms

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dc.authoridHoang, Anh Tuan/0000-0002-1767-8040
dc.authoridSaini, Gaurav/0000-0001-9593-5180
dc.authoridBakır, Hüseyin/0000-0001-5473-5158
dc.authoridyıldız, gökhan/0000-0001-6039-9226
dc.authoridSoudagar, Manzoore Elahi M./0000-0002-0935-2040
dc.authoridAfzal, Asif/0000-0003-2961-6186
dc.authoridHoang, Anh Tuan/0000-0002-3433-7029
dc.authorwosidHoang, Anh Tuan/C-4780-2019
dc.authorwosidGürel, Ali Etem/HKF-0948-2023
dc.authorwosidSaini, Gaurav/AAA-2803-2021
dc.authorwosidyıldız, gökhan/GSO-2803-2022
dc.authorwosidBakır, Hüseyin/HMO-5183-2023
dc.authorwosidyıldız, gökhan/AAA-5700-2021
dc.authorwosidSoudagar, Manzoore Elahi M./R-4943-2019
dc.contributor.authorBakır, Hüseyin
dc.contributor.authorAğbulut, Ümit
dc.contributor.authorGürel, Ali Etem
dc.contributor.authorYıldız, Gökhan
dc.contributor.authorGüvenç, Uğur
dc.contributor.authorSoudagar, Manzoore Elahi M.
dc.contributor.authorHoang, Anh Tuan
dc.date.accessioned2023-07-26T11:50:44Z
dc.date.available2023-07-26T11:50:44Z
dc.date.issued2022
dc.departmentDÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümüen_US
dc.departmentDÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractThe accelerating increment of greenhouse gas (GHG) concentration in the atmosphere already reached an alarming level, and nowadays its adverse impacts on the living organisms, environment, and ecological balance of nature have been well-understood. India is one of the top countries that contribute the most to global GHG emissions. Therefore, it is of great significance to forecast the future GHG trends of the country in advance and accordingly take measures against the parameters that cause these emissions, considerably. In this direction, the present research has centered on forecasting the greenhouse gas trajectory of India with various metaheuristic algorithms. In this framework, marine predators algorithm (MPA), lightning search algorithm (LSA), equilibrium optimizer (EO), symbiotic organisms search (SOS), and backtracking search algorithm (BSA) are used for modeling the future GHG emission trajectory of India. Accordingly, the significant economic and energy indicators of India such as renewable energy generation, electricity generation from coal, electricity generation from gas, electricity generation from oil, gross domestic product, and population between 1990 and 2018 are collected to make a nexus with GHG emissions. As GHG emissions, CO2, CH4, F-gases, N2O, as well as total GHG emissions are separately forecasted by the year 2050. To make a better comparison, each GHG emission data in the last year five years is used for the testing phase of the algorithms, and then statistically discussed in terms of R2, MBE, rRMSE, and MAPE benchmarks. In the results, it is found that the R2 value changes between 0.8822 and 0.9923 for CO2, 0.2855-0.9945 for CH4, 0.9-0.9904 for F-gases, 0.4655-0.9964 for N2O, and 0.9016-0.9943 for total GHG emission, and the results in terms of rRMSE are very satisfying for all algorithms. In the study, it is forecasted that the two greenhouse gas emissions with the highest increase rate in 2050 will be between 2.5 and 2.87 times for CO2 emissions and between 2.8 and 3.5 times for F-gases, compared to today's data. According to the results of the present paper, the total GHG emission for India is forecasted to be 2.1-2.4 times higher in the year 2050 as compared to today. Given all forecasting results together, it is seen that the MPA algorithm generally gives the best results according to the statistical metric results, while the LSA algorithm generally gives the worst results. Consequently, the present paper strongly reports that the decision-makers and policy-makersen_US
dc.identifier.doi10.1016/j.jclepro.2022.131946
dc.identifier.issn0959-6526
dc.identifier.issn1879-1786
dc.identifier.scopus2-s2.0-85130526477en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.jclepro.2022.131946
dc.identifier.urihttps://hdl.handle.net/20.500.12684/12416
dc.identifier.volume360en_US
dc.identifier.wosWOS:000810119300005en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorAğbulut, Ümit
dc.institutionauthorGürel, Ali Etem
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofJournal of Cleaner Productionen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz$2023V1Guncelleme$en_US
dc.subjectIndian Ghg Emissions; Energy; Environment; Carbon Footprint; Metaheuristic Algorithmsen_US
dc.subjectBacktracking Search Algorithm; Symbiotic Organisms Search; Air-Pollution; Power-Flow; Optimization; Systems; Demanden_US
dc.titleForecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithmsen_US
dc.typeArticleen_US

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