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Although risks are present in any organisation and the importance of their study is obvious, the authors find that risk analysis is an area still in its infancy, as reflected in the small number of existing publications on this topic. Human resources tend to understand risk in an elementary way. The ability of human resources to perceive risk is the ability and competence to identify a potential threat that does not always appear.

Aim: The aim of the this chapter was to provide additional knowledge on human resource competencies, in order to avoid the emergence and spread of risks at the organisational and cyber level.

Methodology: The authors used the quantitative–comparative analysis, by presenting all the details regarding the competencies of the human resource in order to manage the risks at organisational and cybernetic level.

Findings: The findings of this chapter show that the compulsory competencies of the human resource influence both the general competencies and the special competencies: information technology and communications, security ethics and economic ones. These, in turn, can improve or diminish cyber security competencies by almost 50%.

Originality of the Study: This study is highlighted by results obtained from the analysis of the capacity of human resources, to integrate theoretical knowledge and practical competencies on the perception of cyber risk. Of particular importance for this research are the analysis of data and the interpretation of results on human resources competencies. In this sense, throughout the chapter are assessed the skills of human resources, necessary for the management of cyber risks at the organisational level. In terms of future research implications, it could be important research to identify a method of assessing the competencies acquired by human resources applied from the perspective of cyber risk.

Global warming is a process that takes place 11,500 years after the end of the last Ice Age. The main identified reason is the increased emissions of greenhouse gases (GHGs). Since the nineteenth century, GHG evolution has recorded a quantum leap from the previous linear development. Human is the main factor behind this evolution, through industrialization and the exponential increase of population. Based on these, the chapter’s primary goal was to highlight an original method of predicting the future evolution of GHG emissions in the domains of Energy (including Transportation), Industry Processes and Product Use, Agriculture, and Waste Management. The novelty of the research consisted of testing several variants of functions (power, exponential, inverse trigonometric) to identify, from a group of variants. This optimal function would generate those predictions, which are closest to the real values. The causes that create GHG emissions in each of the four domains were the foundation for the analysis. This chapter focuses on two main subjects: first, the identification of a smooth function to predict the evolution of GHG emissions, and second, the function’s use to estimate the projections of GHG emissions in the coming years for the four domains: Energy (including Transportation), Industry Processes and Product Use, Agriculture, and Waste Management. An observation was that the weights of these four domains remain relatively the same despite the reductions in the total GHG emissions.