This paper discusses the impact of the COVID-19 pandemic on air pollution. Many urban inhabitants were confined to their homes during the lockdown. This had an impact air pollution, due to a reduction the number of vehicles being operated in cities. People also limited the number of visits to shopping centers; additionally, sports venues were closed and cultural events cancelled. The COVID-19 pandemic therefore had a positive impact on air pollution. Several studies from around the world confirm this. The research presented here is based on hourly measurements of PM₁₀ and NO₂ concentrations measured in background ambient air at a specific intersection located in Uherske Hradiste, Czech Republic. The aim of the paper is to confirm or exclude the hypothesis that the measured concentrations of PM₁₀ and NO₂ pollutants were lower during 2020 than in 2019, when states of emergency related to the COVID-19 pandemic were declared. The data were aggregated into monthly subsets and statistically analyzed. The data was graphically visualized and evaluated by means of exploratory data analysis. To compare the pollution levels in individual months, a parametric statistical analysis (two-sample t-test) was used. A statistically significant reduction was observed in the measured concentrations in 2020 compared to 2019 during periods when states of emergency were declared.

Power outages present a significant threat to all of humanity. However, elements of critical infrastructure are most affected by this event. Among other things, healthcare facilities can be considered critical infrastructure. They are the backbone for saving lives. However, even these medical facilities can be endangered. The primary aim of this paper is to design an algorithm to assess healthcare facilities to solve power outages. Several inputs are considered for the evaluation of healthcare facilities. Based on these inputs, we could gain several outputs, such as object priority, preparedness of the healthcare facility, missing aggregate capacity and fuel stocks. Calculations to obtain this information are available in this article. This algorithm follows up the methodology for the categorisation and prioritisation of objects necessary for the resumption of electricity supply after a blackout. We conclude that only 15% of the surveyed healthcare facilities are prepared for a power outage.

The current turbulent times have never been so demanding to adapt to ever-changing conditions. Small and medium enterprises (SMEs) form the cornerstone of the economy. Moreover, they are the driving force of economic processes in all countries. Therefore, this paper aims to empirically map and identify the causes of the crisis and statistically verify how these crises affect the personnel measures taken and human resource management (HRM) in SMEs. The chi-square test and Cramer’s coefficient were used to verify the statistical dependences of research questions and hypotheses. A statistically significant impact of external economic influences on enterprises’ activities was empirically confirmed (59%). It was proved that nowadays, the most important external factor influencing the activities of enterprises in the market is the COVID-19 pandemic. The study also focused on the personnel measures taken during the crisis. It was confirmed that small businesses apply alternative personnel measures, namely reducing variable wage components before radical redundancies. AcknowledgmentThis study was supported by the project DKRVO Tomas Bata University in Zlín – Risk management in logistics – RVO/FLKŘ/2021/03, Faculty of Logistics and Crisis Management, and project GAAA – Project risk management in the conditions of SMEs in the Czech Republic – GA/16/2019.