Two possible methods of examining environmental load at macro and micro levels

The concept of carbon footprint and the application of the calculation methods thereof have become part of the discourse on sustainable economy. Measuring CO2 emissions at macrolevels has become more important in the field of environment and economy in the 21st century. Determining the local environmental impact of microeconomic actors has also come to the fore. This study uses the timeseries data analysis method at two levels. At the macro level, the disparity of distribution of GDP produced and the associated CO2 emissions by continent are analysed, and the study seeks to answer the question whether there is an increasing or decreasing trend in inequality. In the case of microeconomic actors, the study focuses on the built environment: buildings account for 40% of global energy consumption and 1/3 of greenhouse gas emission, so this proportion represents a key responsibility for decision-makers of built environments. For micro-level analysis, the experiences related to determining the annual carbon load of a central unit of a higher education institution are summarized. The data collection and time series analysis show the direct CO2 emissions of the institution and the emissions of the energy inputs used for operation. In addition to presenting time series data, the study seeks to answer the question whether growing and widespread post-COVID-19 online solutions can have a long-term impact on the composition of the environmental load of the examined higher education service centre.

Application of the Generalized Thurstone Method for Evaluations of Sports Tournaments' Results

Due to the non-played matches on the grounds of COVID-19 pandemics, the usual evaluation of the results of tournaments is biased. Matches won by default may cause unrealistic results. In this paper, an expedient method, the generalization of Thurstone method for more than two options, is applied. It is able to evaluate the results of the played matches without requiring equal matches' numbers. This method takes the strength of the opposer into consideration as well. We apply the method for evaluating Handball Champions' League's results. We illustrate that it efficiently predicts the results in the future.