Corrigendum to "Integration of datasets to provide insights about households' natural gas expenditure as trigger to building stock decarbonisation" [Heliyon 9(4) (April 2023) e14922]

[This corrects the article DOI: 10.1016/j.heliyon.2023.e14922.].

Integration of datasets to provide insights about households’ natural gas expenditure as trigger to building stock decarbonisation

Deep-renovations measures are identified as possible solutions to support European Union's natural gas phase-out and fuel independency. However, it has been difficult to increase renovation rates (about 1% per year), and previous studies have recognized socio-economic barriers as one of the reasons for that. Then, integrated (techno-socio-economic) datasets are vital to support building policy measures that circumvent the negative consequences of high gas prices. This paper's main objective is to develop and to test a methodology that merges two data sources: the European Union Statistics on Income and Living Conditions and the Household Budget Survey in order to create an integrated techno-socio-economic dataset. The following research questions are answered: What is the replicable methodology for merging both datasets in order to create an accurate statistical model? What can we learn about household savings and natural gas expenditures of household types characterised by ownership status and dwelling type? The modelling results show that the developed logistic regression model presented an accuracy of 77% using 2015 data from Spain. The explorative statistical analysis showed that the owner-occupied single-family houses predominate in the highest natural gas expenditure quintiles, while the rented single-family houses in the lowest quintiles, indicating that ownership status may have a stronger influence on the natural gas expenditure than building type. The mean annual household savings are negative, an evidence of households' budget restrictions to finance deep renovation activities. As a conclusion, the generated techno-socio-economic synthetic dataset provides useful information about the relation between household budget restrictions, natural gas expenditure and potential investment on deep renovation. Based on the generated dataset, it is also concluded that higher natural gas prices alone are not sufficient to stimulate deep renovations. For boosting renovation activities, the design of financing and incentive schemes should be end-user targeted considering the households' heterogeneity. Then, the definition of households' profiles should include ownership status and other socio-economic parameters not only dwelling type. This work prepares the ground for setting techno-socio-economic databases that can be used to design more accurate incentives and financing schemes to accelerate European building stock decarbonisation and fossil fuel independency.