Buildings must provide an environment that is pleasant, productive, and healthy for users. At the same time, buildings must be sustainable and resistant in the current environment and be ready for the predicted climate changes, as these are the foundation of the transition to a zero-carbon society. The purpose of the dissertation is to propose, in the theoretical part, new methods for a holistic evaluation of the indoor environment’s quality in three considered domains with proposed quality indices: IEQTOT in the physical domain, which is associated with healthy living; O-IEQTOT in the domain of perceived quality, which is associated with a pleasant stay; and S-IEQTOT in the domain of productivity. The indices include both conventional areas of assessment, as well as new and newly evaluated composite indicators. The methodological determination of the indices is based on the discretization of the experimental results from a simulated indoor environment. The novelty of the research is discretization, based on the standard deviation of personal assessments of perceived quality and the performance of mental work. Through a statistical analysis, we have proven that there is no statistically significant mutual influence between the IEQ domains; therefore, the domain quality indices can be determined based on the Euclidean distance. In the dissertation, the weights of the areas in the O-IEQTOT and S-IEQTOT indices are proposed, which were determined exclusively based on the standard deviation of the experimental results. By parallel monitoring of the psychological response, using a wearable mEEG device, we determined the correlation between the subjects' personal characteristics and the IEQ quality indices, and then proposed the most appropriate biomarkers. In the applied part of the research, IEQ assessment models were introduced into the selected BIM/BEM tool in the form of an exchangeable calculation module, connected to dynamic simulations of the energy flows in the building, which enables a higher level of BIM/BEM modelling than is established today. Dynamic modelling also includes new computational algorithms for the management of natural resources and natural processes, with which we have demonstrated a strong synergistic connection between low-carbon buildings and the IEQ domains for different climates. In the last part of the dissertation, the research is supplemented with predictive models of selected indicators of the energy efficiency of buildings and IEQ, which we believe will lead to the full implementation of dynamic modelling in the analysis of IEQ in cases of specific characteristics for the external urban environment.
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