000117371 001__ 117371
000117371 005__ 20231006143307.0
000117371 0247_ $$2doi$$a10.3390/su132313424
000117371 0248_ $$2sideral$$a127015
000117371 037__ $$aART-2021-127015
000117371 041__ $$aeng
000117371 100__ $$0(orcid)0000-0001-6765-4218$$aFernández E.
000117371 245__ $$aA new approach for static NOx measurement in PTI
000117371 260__ $$c2021
000117371 5060_ $$aAccess copy available to the general public$$fUnrestricted
000117371 5203_ $$aNOx emissions in vehicles are currently only controlled through the homologation process. There is a lack of knowledge to assess and control real NOx emissions of vehicles reliably. Even if vehicles in EU-27 are subject to Periodical Technical Inspection (PTI), NOx are not among the pollutants currently being controlled. For PTIs, tests need to be simple, quick, inexpensive, representative, and accurate. Ideally, tests need to be carried out under static conditions, without the need for a power bench or complex equipment. In this paper, a new approach for measuring NOx in PTI is proposed. The method has been developed and validated at a PTI Spanish station to ensure feasibility and repeatability. This method is based on the relationship between the “% engine load” value and exhaust NOx concentration at idle engine speed. Starting from the state of minimum possible power demand in a vehicle (idling and without any consumption), a load state with an average 98% increase in engine power demand is generated by connecting elements of the vehicle’s equipment. The relationship between power demand (through the “% engine load” value) and NOx concentration is then analyzed. The quality and representativity of this relationship have been checked with a p-value lower than 0.01. The method has been compared with a different NOx measurement technique, based on the simulation on a test bench and the ASM 2050 cycle, showing better performance in terms of repeatability and representativeness. The “% engine load” dispersion with the new approach is 7%, which ensures the reliability and repeatability of the method. The results show that the proposed method could be a valuable tool in PTI to detect high NOx emitting vehicles and to obtain information from the diesel vehicles fleet. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
000117371 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000117371 590__ $$a3.889$$b2021
000117371 592__ $$a0.664$$b2021
000117371 594__ $$a5.0$$b2021
000117371 591__ $$aENVIRONMENTAL STUDIES$$b57 / 128 = 0.445$$c2021$$dQ2$$eT2
000117371 593__ $$aEnergy Engineering and Power Technology$$c2021$$dQ1
000117371 591__ $$aENVIRONMENTAL SCIENCES$$b133 / 279 = 0.477$$c2021$$dQ2$$eT2
000117371 593__ $$aRenewable Energy, Sustainability and the Environment$$c2021$$dQ1
000117371 591__ $$aGREEN & SUSTAINABLE SCIENCE & TECHNOLOGY$$b35 / 47 = 0.745$$c2021$$dQ3$$eT3
000117371 593__ $$aManagement, Monitoring, Policy and Law$$c2021$$dQ1
000117371 591__ $$aGREEN & SUSTAINABLE SCIENCE & TECHNOLOGY$$b7 / 9 = 0.778$$c2021$$dQ4$$eT3
000117371 593__ $$aGeography, Planning and Development$$c2021$$dQ1
000117371 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000117371 700__ $$0(orcid)0000-0003-3330-1793$$aValero A.$$uUniversidad de Zaragoza
000117371 700__ $$0(orcid)0000-0003-4440-830X$$aAlba J.J.$$uUniversidad de Zaragoza
000117371 700__ $$0(orcid)0000-0002-6148-1253$$aOrtego A.$$uUniversidad de Zaragoza
000117371 7102_ $$15004$$2530$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Ingen.e Infraestr.Transp.
000117371 7102_ $$15004$$2590$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Máquinas y Motores Térmi.
000117371 773__ $$g13, 23 (2021), 13424 [34 pp]$$pSustainability (Basel)$$tSustainability (Switzerland)$$x2071-1050
000117371 8564_ $$s2543925$$uhttps://zaguan.unizar.es/record/117371/files/texto_completo.pdf$$yVersión publicada
000117371 8564_ $$s2762139$$uhttps://zaguan.unizar.es/record/117371/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000117371 909CO $$ooai:zaguan.unizar.es:117371$$particulos$$pdriver
000117371 951__ $$a2023-10-06-14:08:53
000117371 980__ $$aARTICLE