Abstract The objective of this paper is to evaluate, through the 100-year Life Cycle Analysis, Global Warming Potential (GWP) and Global Temperature Increasing Potential (GTP) impact categories. It is proposed scenario of replacement of the energy matrix for the supply of electricity by Solar Photovoltaic, adopting as consumption base the facilities of Supermarkets, as they contribute to environmental impacts for greenhouse gas emissions such as: intensive use of electricity, occupation large areas such as the main building or parking lot sealing the ground, the movement of customers' vehicles with air and noise pollution and the use of plastic bags. Modifying the energy matrix using electricity from renewable sources enables the reduction of greenhouse gas emissions. According to proposed scenarios for the composition of the energy matrix, based on the emission values of the Concessionaire's matrix, the result of the analysis confirms the premise that the use of renewable sources contributes to the reduction of environmental impacts, and that the substitution of Concessionaire's energy matrix for Photovoltaic Solar Energy represents a reduction in terms of kgCO2-eq, over the 100-year horizon, of 85% for GTP and 86% for GWP.

Abstract The objective of this paper is to present a mathematical representation by Regression Analysis that enables the projection of electricity consumption according to the built area and population in Higher Education Institutions (HEI) and to define an Indicator that contemplates the most significant variable in consumption. of electric power. The Null Hypothesis -H0 is that in a HEI the most appropriate indicator is the Kilo Watt Hour per square meter (kWh / m2) as proposed by the Ministry of Planning and Management - MP. The research universe is 2,368 HEI, identified in a report from the Ministry of Education (2015). As Sample and case study, data from the thirteen Campi of the Federal Technological University of Paraná (UTFPR) are used. As a computational tool we use the IBM SPSS Statistics Base Software for Windows version 23 from SPSS Inc .. For the considered Sample and research design, the conclusion is that the null hypothesis is rejected accepting that the most significant indicator is the kilo. Watt Time per user (kWh / user). This conclusion does not exclude the relationship between constructed area and Energy Consumption, but reveals that it is not as significant as the number of individuals in HEI for this sample.