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dc.creatorStamenković, Lidija J.
dc.creatorAntanasijević, Davor
dc.creatorRistić, Mirjana
dc.creatorPerić-Grujić, Aleksandra
dc.creatorPocajt, Viktor
dc.date.accessioned2021-03-10T13:03:47Z
dc.date.available2021-03-10T13:03:47Z
dc.date.issued2016
dc.identifier.issn0944-1344
dc.identifier.urihttp://TechnoRep.tmf.bg.ac.rs/handle/123456789/3279
dc.description.abstractThis paper describes the development of an artificial neural network (ANN) model based on economical and sustainability indicators for the prediction of annual non-methane volatile organic compounds (NMVOCs) emissions in China for the period 2005-2011 and its comparison with inventory emission factor models. The NMVOCs emissions in China were estimated using ANN model which was created using available data for nine European countries, which NMVOC emission per capita approximately correspond to the Chinese emissions, for the period 2004-2012. The forward input selection strategy was used to compare the significance of particular inputs for the prediction of NMVOC emissions in the nine selected EU countries and China. The final ANN model was trained using only five input variables, and it has demonstrated similar accuracy in predicting NMVOC emissions for the selected EU countries that were used for the development of the model and then for China for which the input dataset was previously unknown to the ANN model. The obtained mean absolute percentage error (MAPE) values were 8 % for EU countries and 5 % for China. Also, the temporal trend of NMVOC emissions predicted in this study is generally consistent with the trend obtained using inventory emission models. The proposed ANN approach can represent a viable alternative for the prediction of NMVOC emissions at the national level, in particular for developing countries which are usually lacking emission data.en
dc.publisherSpringer Heidelberg, Heidelberg
dc.relationinfo:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/172007/RS//
dc.rightsrestrictedAccess
dc.sourceEnvironmental Science and Pollution Research
dc.subjectANNen
dc.subjectChinaen
dc.subjectEmissionsen
dc.subjectNMVOCen
dc.subjectModelingen
dc.titleEstimation of NMVOC emissions using artificial neural networks and economical and sustainability indicators as inputsen
dc.typearticle
dc.rights.licenseARR
dc.citation.epage10762
dc.citation.issue11
dc.citation.other23(11): 10753-10762
dc.citation.rankM22
dc.citation.spage10753
dc.citation.volume23
dc.identifier.doi10.1007/s11356-016-6279-z
dc.identifier.pmid26888640
dc.identifier.scopus2-s2.0-84958767328
dc.identifier.wos000377021500040
dc.type.versionpublishedVersion


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