Indoor air quality plays a key role in assessing people's quality of life, as a large proportion of people spend up to 22 hours a day indoors and people are exposed to indoor air almost all day long [1]. People in developed countries spend much more time indoors. Recently, employers are paying more and more attention to ensuring the well - being of employees, as it affects the quality and productivity of their work [2, 3]. Ensuring an appropriate working environment on the part of employers ensures both sustainable social and economic links. Well-being can be affected by various parameters of the indoor environment, in addition to the microclimate, they can be - lighting, noise level, various odors. However, one of the primary indicators of comfort or discomfort in an indoor environment is thermal comfort or discomfort [4]. Gas stations were chosen as place for measurements because they are considered dangerous for several reasons: gas station territory is potentially hazardous with a high environmental risk and explosion hazard. Working shifts and nights is also considered undesirable for human health as it disrupts the biological rhythms in the human body [5]. In such circumstances, the indoor microclimate and air parameters play a very important role, as spending long hours in inappropriate microclimatic conditions is likely to lead to various long - term health problems for the workers.

Corporate sustainability reporting has become a central component of corporate governance under the European Sustainability Reporting Standards (ESRS); yet organizations continue to face challenges in integrating sustainability data into decision-making processes. This study addresses this gap by developing a system dynamics (SD) model for analyzing corporate sustainability performance based on ESG indicators. The proposed framework integrates environmental, social, and governance variables into a unified dynamic structure, capturing feedback loops, time delays, and interdependencies among sustainability dimensions. The model is empirically tested using a ten-year dataset from a fuel retail company, enabling both historical validation and scenario-based analysis. The results demonstrate that the model successfully reproduces observed trends in resource efficiency, safety performance, and social indicators while highlighting trade-offs associated with business growth, particularly in energy consumption and CO₂ emissions. Sensitivity analysis demonstrates that the sustainability index remains stable under uncertainty in normalized ESG indicator values. Scenario simulations indicate that several sustainability targets for 2030 are achievable under current development trajectories; however, maintaining progress requires continuous investment and organizational commitment. The study contributes to sustainability research by integrating ESRS-based indicators into a dynamic modeling framework and provides a practical decision-support tool for corporate sustainability management, enabling more informed planning, performance evaluation, and strategic alignment with long-term sustainability goals.