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The heavy reliance on information and communication technology (ICT) has prompted the importance of cyber security more than ever in history. Although there are various studies that explored the importance of cybersecurity solutions, the impact of production and usage of these solutions on the natural environment and their economic impact has been rarely researched. The objective of this research is to investigate the environmental and economic impact of cybersecurity solutions. An extensive Life Cycle Assessment (LCA) has been performed on three cybersecurity solutions to assess and compare their environmental impact. Based on global warming potential, the embodied carbon footprint was determined. Carbon footprint and operational costs were used to calculate Life Cycle Cost (LCC) analysis and these data were then used to compare the eco-efficiency of the three cybersecurity solutions. This research compares three cybersecurity solutions: Next Generation DataGuard (NGD), Current State of Art Solution (CSAS), and a Generic Cybersecurity Solution (GCS), to identify an economically viable and environmentally friendly cybersecurity solution. The result of the analysis indicated that NGD was approximately 58% and 88% more energy-efficient than CSAS and GCS, respectively. Also, the LCC of NGD was approximately 6%- 12% lower than CSAS and 22%- 40% lower than GCS in selected provinces in Canada. The eco-efficiency of CSAS was approximately 60% less than NGD. Next Generation DataGuard is found to be a successful solution in this research among the three solutions. This study will be useful to researchers, cybersecurity industries, and policymakers to develop informed decisions on cybersecurity solutions. [Display omitted] • The life cycle environmental and economic performance of three cybersecurity solutions were compared. • Next Generation DataGuard (NGD) was approximately 58% and 88% more energy-efficient than current state of art solution and generic cybersecurity solution, respectively. • The NGD displayed superior environmental and economic performance for all Canadian cities. [ABSTRACT FROM AUTHOR]

Ongoing climate action programs are prompting more stringent energy performance standards for buildings. Consequently, energy retrofitting of existing buildings has become a common climate action initiative around the world. Building owners are keen to assess the technical and financial feasibility of energy retrofitting in pre-project planning stages. Life cycle cost analysis (LCCA) involves assessment of the economic cost of an asset or a service. LCCA, which is a data-intensive process, is heavily affected by data uncertainties; however, traditional deterministic LCCA models are oblivious to data uncertainty and this can have a significant effect on the final decision. As a solution, this paper proposes a novel LCCA approach for building energy retrofits. The proposed approach calculates life cycle cost (LCC) by adopting fuzzy set theory. In order to illustrate the proposed methodology, a case study was conducted for a public building operated in the Okanagan region of British Columbia, Canada. Two energy retrofit alternatives − a major retrofit and a deep retrofit − were compared using the proposed fuzzy set theory-based approach and the traditional deterministic LCCA approach. Even though the deterministic result had a strong membership to the fuzzy membership function of the LCC, the range of possible LCC is wide. Use of the fuzzy-based approach would enable the forecasting of possible future LCC as a result of changes in macro-economic factors. This information would allow building managers to plan for adverse future scenarios. [ABSTRACT FROM AUTHOR]