Wastewater from dairy industries, characterized by its high COD content and relative high COD/TKN ratio, requires post-treatment after anaerobic treatment to complete the removal of organic matter and nutrients. Due to its simplicity, robustness and low maintenance costs, sequencing batch reactors (SBR) result in an attractive system, especially in case of small dairy industries in order to comply with the emission standards. The goal of this work was to determine the operational parameters, optimize the performance, and study the stability of the microbial population of a SBR system for the post-treatment of an anaerobic pond effluent. High and stable removal of COD and TKN was achieved in the reactor, which can easily be set up in dairy industries. An active nitrifying population was selected during reactor operation and maintained relatively stable, while the heterotrophic (total and denitrifying) communities were more unstable and susceptible to changes in the operating conditions.

Many dairy industries have been using SBR wastewater treatment plants because they allow optimal working condition to be reached. However, to take advantage of SBR capabilities, strong process automation is needed. The aim of this work is to study the factors that influence SBR performance to improve modelling and control. To better understand the whole process we studied the kinetic modelling, the carbon removal mechanism and the relation between reactor performance, aerobic heterotrophic activity and bacterial population dynamics (by terminal restriction fragment length polymorphisms of 16S rDNA, T-RFLP). The heterotrophic activity values presented high variability during some periods; however, this was not reflected on the reactor performance. As sludge health indicator, the average activity in a period was better than individual values. Although all the carbon removal mechanisms are still unclear for this process, they seemed to be influenced by non-respirometric ways (storage, biosorption, accumulation, etc.). The variability of heterotrophic activity could be correlated with the bacterial population diversity over time. Despite the high variability of the activity, a simple kinetic model (pseudo ASM1) based on apparent constant parameters was developed and calibrated. Such modellisation provided a good tool for control purposes.

The deployment of green hydrogen production is increasingly considered a strategic opportunity for energy-exporting countries. However, beyond technological and environmental aspects, large-scale industrial projects may generate complex and uncertain social and economic impacts at the regional level. This study investigates the potential social implications of introducing a green hydrogen production plant in the Department of Paysandú, Uruguay, using a System Dynamics modeling approach. It proposes an initial system model designed to establish a foundational Modeling and Simulation framework. The model explicitly represents feedback mechanisms linking public finance, education, labor competencies, productivity, and social behavior impact, allowing the exploration of long-term socio-economic trajectories under alternative institutional and policy conditions. It is used as an exploratory decision-support tool to assess conditional pathways, trade-offs, and risks. Results indicate that positive social outcomes, such as human capital accumulation and regional income growth, are possible but not automatic; they depend critically on governance capacity, fiscal sustainability, labor market coordination, and social acceptance, and may be attenuated or delayed under adverse scenarios. While this framework provides a strategic engineering lens on the social dimension, it represents a first step toward a comprehensive decision-making tool. The study analyzes a complex system by integrating energy, production, economic, social, and environmental aspects from strategic engineering lens and contributes to the literature by integrating social dimension and institutional constraints into a Modeling and Simulation framework applied to green hydrogen industrialization, offering insights into policy design under uncertainty in emerging energy-export contexts.

This article presents the results of a project with a South American oil refinery that explored the production of sustainable aviation fuel (SAF) from local biomass resources. Two process flowsheets for the production of hydrocarbons in the aviation fuel range from oil-based crops (canola, Brassica carinata, sunflower, and soybean) and tallow via hydrotreating and later hydrocracking and isomerization are developed. In addition, an optimization-based methodology for estimating a detailed composition of hydrocarbons after the hydrotreating reaction from incomplete experimental data is presented. The properties of the obtained fuels are estimated and compared to the ASTM D7566 standard for renewable aviation fuel. An environmental assessment using the EPA-GREENSCOPE methodology for 26 indicators is performed for the final design. Overall, this design provides a jet fuel cut with attractive ASTM D7566 properties for all the considered feedstocks, higher yields for soybean oil and tallow, and sustainability scores exceeding 80% for all feeds and indices except those related to the production of smog when soybean oil is considered as the feed.