ABSTRACT: The sustainability of socio-economic and industrial systems is a key concern, particularly within the framework of the 2030 agenda. A holistic understanding of the functioning and relationships of these systems is essential if we want to implement practical actions to achieve sustainability. This study uses econometric techniques, such as the distributed lag autoregressive model, to explore the interactions between industrial and environmental factors and the unemployment rate. The variables analyzed include working hours, wage costs, and tropospheric ozone concentration, over two periods: 2008-2020 (reduced period) and 2008-2024 (extended period). Between both periods, substantial differences have been found in the variables significantly influencing the unemployment rate. The significance of working hours and ozone (O3) concentration, determinants of the unemployment rate in the reduced period, are replaced by wage costs, determining the unemployment rate in the extended period. The results show that an initial increase in worked hours reduces unemployment, while wage increases and high levels of O3 tend to increase the unemployment rate. Granger causality analysis suggests bidirectional relationships between unemployment, wage costs, and O3 concentration, highlighting the connection between the different aspects and feedback collateral effects. The study underscores the need for balanced socioeconomic policies that promote both economic growth and environmental sustainability and the promotion of fostering of technological innovations. The importance of policies that mitigate the adverse effects of wage increases on employment is underlined, and that favor a more sustainable development model capable of decoupling economic well-being from intensive resource consumption. Keywords: Sustainability, Socioeconomic systems, ARDL techniques, Granger causality, unemployment, O3 concentration, working hours, hourly wage.