000150578 001__ 150578
000150578 005__ 20251017144652.0
000150578 0247_ $$2doi$$a10.3390/app15020514
000150578 0248_ $$2sideral$$a142660
000150578 037__ $$aART-2025-142660
000150578 041__ $$aeng
000150578 100__ $$0(orcid)0000-0001-9455-0414$$aBeltrán-Velamazán, Carlos$$uUniversidad de Zaragoza
000150578 245__ $$aPredicting Energy and Emissions in Residential Building Stocks: National UBEM with Energy Performance Certificates and Artificial Intelligence
000150578 260__ $$c2025
000150578 5060_ $$aAccess copy available to the general public$$fUnrestricted
000150578 5203_ $$aTo effectively decarbonize Europe’s building stock, it is crucial to monitor the progress of energy consumption and the associated emissions. This study addresses the challenge by developing a national-scale urban building energy model (nUBEM) using artificial intelligence to predict non-renewable primary energy consumption and associated GHG emissions for residential buildings. Applied to the case study of Spain, the nUBEM leverages open data from energy performance certificates (EPCs), cadastral records, INSPIRE cadastre data, digital terrain models (DTM), and national statistics, all aligned with European directives, ensuring adaptability across EU member states with similar open data frameworks. Using the XGBoost machine learning algorithm, the model analyzes the physical and geometrical characteristics of residential buildings in Spain. Our findings indicate that the XGBoost algorithm outperforms other techniques estimating building-level energy consumption and emissions. The nUBEM offers granular information on energy performance building-by-building related to their physical and geometrical characteristics. The results achieved surpass those of previous studies, demonstrating the model’s accuracy and potential impact. The nUBEM is a powerful tool for analyzing residential building stock and supporting data-driven decarbonization strategies. By providing reliable progress indicators for renovation policies, the methodology enhances compliance with EU directives and offers a scalable framework for monitoring decarbonization progress across Europe.
000150578 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T37-23R$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-104871RB-C21
000150578 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000150578 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000150578 700__ $$0(orcid)0000-0002-0492-3625$$aMonzón-Chavarrías, Marta$$uUniversidad de Zaragoza
000150578 700__ $$0(orcid)0000-0003-1458-7685$$aLópez-Mesa, Belinda$$uUniversidad de Zaragoza
000150578 7102_ $$15015$$2110$$aUniversidad de Zaragoza$$bDpto. Arquitectura$$cÁrea Construc. Arquitectónicas
000150578 773__ $$g15, 2 (2025), 514 [27 pp.]$$pAppl. sci.$$tApplied Sciences (Switzerland)$$x2076-3417
000150578 8564_ $$s8696879$$uhttps://zaguan.unizar.es/record/150578/files/texto_completo.pdf$$yVersión publicada
000150578 8564_ $$s2614072$$uhttps://zaguan.unizar.es/record/150578/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000150578 909CO $$ooai:zaguan.unizar.es:150578$$particulos$$pdriver
000150578 951__ $$a2025-10-17-14:36:44
000150578 980__ $$aARTICLE