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Education about climate change faces an evolution of the knowledge, and universities should respond with innovative learning processes. As facilitators can adapt to these changes, they will be able to improve learning experiences for students. In this work, learning experiences about climate change were evaluated in undergraduate students without engineering background, as function of the size of the group, duration of the course, gamification activities and technology and virtual tools experiences. The implementation of these activities in the intensive 5-week course focused on climate change education has revealed valuable insights into student motivation, attitude, knowledge acquisition, and engagement. Notably, students' trust in information sources about climate change exhibited variations, with global organizations garnering higher confidence compared to local and personal sources. In a 15-week course exposed to virtual tools (e.g. escape room), the diagnostic test highlighted a 53% understanding level, particularly challenging in numeric aspects. However, the escape room significantly improved results in the final exam, demonstrating a 93% correctness rate, emphasizing the effectiveness of the activities in reinforcing key climate change concepts. On the other hand, the emergence of climate change-themed escape room as an engagement tool demonstrated its potential in enhancing knowledge acquisition and cooperative learning. In addition, Escape room offered an immersive environment that encourages active participation, enabling students to grasp complex climate concepts and solutions more effectively. The study underscores that climate education should go beyond facts, emphasizing universities' crucial role in nurturing the "climate change generation" with the knowledge and motivation for meaningful contributions to climate action and policy formulation. [ABSTRACT FROM AUTHOR]

The use of lignocellulosic wastes reduces dependence on fossil fuel resources, contributes to sustainable waste management, and reinforces the circular economy model of continual use of resources. Typically, the second generation of bioethanol production involves several steps to transform lignocellulosic material into bioethanol. The more complicated step of the overall process is to define a tailor-made to each lignocellulosic material available with a wide variety of complex structures of the lignin, hemicellulose, and cellulose. However, the thermochemicals are the most frequently reported pretreatments, and they have the bottleneck of producing an additional waste stream with a high charge of pollution owing to chemical products implicated. This problem harms on the zero waste policy that we must include in our technological process to be considered sustainable and ecological processes. Consolidated bioprocessing (CBP) is a viable alternative to produce bioethanol from lignocellulosic materials, using a single microorganism, in one-step, and no chemical products are implied. Three agro-industrial wastes with lignocellulosic characteristics were evaluated as a substrate for bioethanol production with a Mexican native white-rot fungus Trametes hirsuta CS5 in a one-step process. Qualitative and quantitative analyses of lignocellulolytic enzymes produced by native fungus were carried out. Instead, Trametes hirsuta is a lignin degrader white-rot fungus; it was capable to produce until 500 U/L of cellulase titers and a maximum xylanase activity of 45 U/mL when it was cultivated in orange peel substrate. Substantial ethanol yields were achieved using lignocellulosic materials like brewer's spent grain (BSG), orange peel (OP), and wheat bran (WB) as a carbon source in fermentation with no chemicals, which represents a zero waste environment-friendly ethanol production system. Ethanol yield on wheat bran was the highest of all evaluated substrates, reaching value of 34.9% at 7 days, being T. hirsuta able to degrade other hexoses and pentoses present in the structural polymers of cellulose and hemicellulose. [ABSTRACT FROM AUTHOR]

Inadequate management practices for solid waste and wastewater are some of the main causes of eutrophication globally, especially in regions where intensive livestock, agricultural, and industrial activities are coupled with inexistent or ineffective waste and wastewater treatment infrastructure. In this study, a methodological approach is presented to spatially assess the trophic state of large territories based on public water quality databases. The trophic state index (TSI) includes total nitrogen, total phosphorus, chlorophyll A, chemical oxygen demand, and Secchi disk depth values as water quality indicators. A geographical information system (GIS) was used to manage the spatiotemporal attributes of the water quality data, in addition to spatially displaying the results of TSI calculations. As a case study, this methodological approach was applied to determine the critical regions for mitigating eutrophication in the state of Jalisco, Mexico. Although a decreasing trend was observed for the TSI values over time for most subbasins (2012–2019), a tendency for extreme hypereutrophication was observed in some regions, such as the Guadalajara metropolitan area and the Altos region, which are of high economic relevance at the state level. A correlation analysis was performed between the TSI parameters and rainfall measurements for all subbasins under analysis, which suggested a tendency for nutrient wash-off during the rainy seasons for most subbasins; however, further research is needed to quantify the real impacts of rainfall by including other variables such as elevation and slope. The relationships between the water quality indicators and land cover were also explored. The GIS methodology proposed in this study can be used to spatially assess the trophic state of large regions over time, taking advantage of available water quality databases. This will enable the efficient development and implementation of public policies to assess and mitigate the eutrophication of water sources, as well as the efficient allocation of resources for critical regions. Further studies should focus on applying integrated approaches combining on-site monitoring data, remote sensing data, and machine learning algorithms to spatially evaluate the trophic state of territories. [ABSTRACT FROM AUTHOR]