Abstract
An increasing number of studies apply life-cycle assessment methodology to assess the impact of a new building or to prioritize between different building refurbishment strategies. Among the different hypotheses to consider during the application of this methodology, the selection of the impact indicator is critical, as this choice will completely change the interpretation of the results. This article proposes applying four indicators that allow analysing the results of a refurbishment project of a residential building with the life-cycle approach: non-renewable primary energy use reduction (NRPER), net energy ratio (NER), internal rate of return (IRR), and life-cycle payback (LC-PB). The combination of environmental and economic indicators when evaluating the results has allowed to prioritize among the different strategies defined for this case study. Furthermore, an extensive sensitivity assessment reflects the high uncertainty of some of the parameters and their high influence on the final results. To this end, new hypotheses related to the following parameters have been considered: reference service life of the building, estimated service life of material, operational energy use, conversion factor, energy price, and inflation rate. The results show that the NRPE use reduction value could vary up to −44%. The variation of the other indicators is also very relevant, reaching variation rates such as 100% in the NER, 450% in the IRR, and 300% in the LC-PB. Finally, the results allow to define the type of input or hypothesis that influences each indicator the most, which is relevant when calibrating the prioritization process for the refurbishment strategy.
Highlights
Numerous studies and reports show that life-cycle assessment (LCA) methodology is currently the best framework available to assess the potential environmental impacts of any activity [1,2,3,4,5]
The second option is based on a weighting system, where a percentage value is applied to each indicator, obtaining a final score that reflects the overall behaviour of each refurbishment strategy [27,77]
The 0% axis shall draw the line of the results obtained by means of the original inputs defined for the tbceTheavhesaeiesclvuFaFavsasitliageutugreuuadisdarttryee.tueido9da9.nnyssdhihas,oonwmfwdrosa,smihfhnroooltywmwhlaittntthhhkepeaeoNtNdipnRRtotoPP,iEntEthhRtR,eevtvdhianaielrlfueulieucneteflccniouoncuuefellnldudocevefvnauaocrernfyycuo±e±fnr33tct0h0ae%%rirnet,aetrryiepneaaoatcycrnhahoimtinnhngegetthaeapremrmsop.aapTrxxoohiispmmeeofduusimrempsdtavvcrpaaraarirmtiriiaaacettmaitioeloenrpnstaeoosrrffahs−−mas44lhle44at%%belelr
Summary
Numerous studies and reports show that life-cycle assessment (LCA) methodology is currently the best framework available to assess the potential environmental impacts of any activity [1,2,3,4,5] Proofs of this are numerous review studies that focus on analysing, grouping, and comparing other previous works focused on evaluating the environmental and/or economic impact of the construction industry under the perspective of life cycle [6,7,8,9,10,11,12,13,14,15,16,17,18]. Another critical area of the construction sector is energy refurbishment, which is becoming increasingly relevant mainly in countries where the level of new construction compared with the number of buildings with refurbished energy is very low
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