id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
aijes-6710	Hasanov, Ramil; Safarov, Jamil; Safarli, Arzu	ANALYZING AND FORECASTING CO2 EMISSIONS IN THE ALUMINUM SECTOR USING ARIMA MODEL	2024	10	.pdf	application/pdf	3821	218	34	Prediction of CO2 emissions in https://alfed.org.uk/wp-content/uploads/2023/10/CRU-SummaryReport-for-IAI.pdf https://www.carbonchain.com/blog/understand-your-aluminum-emissions https://doi.org/10.1007/97 https://doi.org/10.1016/j.jclepro.2014.03.062 http://doi.org/10.46754/jssm.2023.10.012 https://international-aluminium.org/statistics/greenhouse-gas-emissions-aluminium-sector/ https://international-aluminium.org/statistics/greenhouse-gas-emissions-aluminium-sector/ https://www.iea.org/energy-system/industry/aluminium https://doi.org/10.1002/for.2677 ANALYZING AND FORECASTING CO2 EMISSIONS IN THE ALUMINUM SECTOR USING ARIMA MODEL 64 Iran using grey and ARIMA models. Despite being consumed in lower quantities compared to steel or cement, aluminum emerges as the most carbon-intensive material per tonne among https://orcid.org/0000-0003-4267-7039 mailto:r.hasanov@uteca.edu.az https://orcid.org/0009-0004-0392-3860 mailto:jamil.safarov@Azeraluminium.com https://orcid.org/0000-0003-2670-0665 mailto:arzu.safarli@aztu.edu.az ANALYZING AND FORECASTING CO2 EMISSIONS IN THE ALUMINUM SECTOR USING ARIMA MODEL 56 the top three highest-emitting materials (Berker, 2022).	cache/aijes-6710.pdf	txt/aijes-6710.txt