Carbon Footprint of Utility Consumption and Cleaning Tasks in Buildings

Abstract

In recent years, numerous studies have focused on quantifying the environmental impact of building construction. This is, to a certain extent, because of the intense activity over the last decade, in which the construction sector has generated 40% of the global CO2 emissions currently in the atmosphere (Bastianoni et al., 2007). Currently, however, because of the recent decrease in the construction of new buildings, most of the sector’s activity is dedicated to maintenance and rehabilitation work of existing buildings. Furthermore, the intense pace of new construction failed to include any reflection on the cost and environmental impact that the maintenance of those new buildings would involve in future years. In this study, a methodology, which had initially focused on utility consumption and cleaning tasks, is proposed for the estimation of the costs and environmental impact of buildings during their use-and-maintenance phase. Since the concept of CO2 emissions and their consequences regarding human health has already been settled in today’s society, the carbon footprint (CF) stands as an ideal indicator for the efficient communication of results from environmental impact assessments to the general public. To prove the validity of the model, it is applied to a case study of a university Hall of Residence located in Seville (Spain). First, the utility consumption and cleaning tasks to be performed are studied to obtain the estimated cost. Secondly, the resources consumed during this phase are quantified in terms of energy, water, fuel, construction materials, labor, and machinery. Finally, these resource consumptions are translated into environmental impact through specific formulae of the calculation model. The developed methodology is applicable to any type of building, and it is only necessary to estimate, or obtain actual data, regarding the utility consumption, count the number of rooms of each type present in the building under study, and to establish the frequency of the cleaning tasks. The utility consumption represents 97% of the total CF of this phase, whereas the remaining 3% is caused by cleaning tasks. Manpower leads to 14% of the CF of cleaning tasks, and the manufacture of materials (cleaning tools and products) covers 79% of this impact. Thirty-five different scenarios have been studied out to prove the sensitivity of the model, whereas BLUE map scenario has been applied to estimate the evolution of the CF during the entire service life of the building.