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dc.contributor.authorNazario Ticse, Russell
dc.contributor.authorRamos Saravia, José
dc.contributor.authorWong Kcom, Jorge
dc.contributor.authorQuintana Caceda, María
dc.date.accessioned2024-11-13T23:28:15Z
dc.date.available2024-11-13T23:28:15Z
dc.date.issued2023
dc.identifier.urihttps://hdl.handle.net/20.500.13067/3482
dc.description.abstractIn Peru, as in many countries, road transport is dominated by vehicles with gasoline or diesel internal combustion engines, which represents a challenge for decarbonization in the world. In industrialized countries there is an interest in electric vehicles, with the aim of achieving their objectives in emission reduction, to improve air quality and reduce greenhouse gas emissions. That is why the trend is to electrify the vehicle fleet, thereby reducing fossil fuel imports, thus progressively eliminating energy dependence. Lima has a serious pollution problem that is due to the transportation sector, both due to the emission of gasses, as well as noise, traffic and a poor transportation system. For this reason, it is important to evaluate the environmental impact produced by electric vehicles at different penetration rates in the private sector transport fleet. In this work, an econometric model is used and the use of neural networks, the dependent variable is the CO2 emissions in Peru. Different scenarios have been created, each with different penetration rates. As a result, in the reduction of CO2 emissions, for light vehicles (cars), by 2030 in all scenarios, a reduction in emissions of 0.48% has been demonstrated for the global rate, 2.82% for an AAP scenario, 5.73% for a NGV scenario and a reduction of 20.99% for the very optimistic EV30@30 scenario. With the result, it is observed that the massification of EVs will be essential to reduce GHG emissions.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherLACCEIes_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/es_PE
dc.sourceAUTONOMAes_PE
dc.subjectEV penetration ratees_PE
dc.subjectEnvironmental impactes_PE
dc.subjectElectric vehicleses_PE
dc.subjectNeural networks ANNes_PE
dc.subjectCO2 emissionses_PE
dc.titleInfluence of the introduction of electric vehicles on CO2 emissions in Perues_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.journal22nd LACCEI International Multi-Conference for Engineering, Education, and Technologyes_PE
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.07.00es_PE
dc.relation.urlhttps://doi.org/10.18687/LACCEI2024.1.1.1626es_PE
dc.source.beginpage1es_PE
dc.source.endpage10es_PE


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