The global impact of water and soil contamination has become a serious issue that affects the world and all living beings. In this sense, multiple treatment alternatives have been developed at different scales to improve quality. Among them, biochar has become a suitable alternative for environmental remediation due to its high efficiency and low cost, and the raw material used for its production comes from residual biomass. A biochar is a carbonaceous material with interesting physicochemical properties (e.g., high surface area, porosity, and functional surface groups), which can be prepared by different synthesis methods using agricultural wastes (branches of banana rachis, cocoa shells, cane bagasse, among others) as feedstock. This state-of-the-art review is based on a general description of biochar for environmental remediation. Biochar’s production, synthesis, and multiple uses have also been analyzed. In addition, this work shows some alternatives used to improve the biochar properties and thus its efficiency for several applications, like removing heavy metals, oil, dyes, and other toxic pollutants. Physical and chemical modifications, precursors, dopants, and promoting agents (e.g., Fe and N species) have been discussed. Finally, the primary uses of biochar and the corresponding mechanism to improve water and soil quality (via adsorption, heterogeneous photocatalysis, and advanced oxidation processes) have been described, both at laboratory and medium and large scales. Considering all the advantages, synthesis methods, and applications, biochar is a promising alternative with a high potential to mitigate environmental problems by improving water and soil quality, reducing greenhouse gas emissions, and promoting the circular economy through residual biomass, generating value-added products for several uses.

While research articles on students’ perceptions of large language models such as ChatGPT in language learning have proliferated since ChatGPT’s release, few studies have focused on these perceptions among English as a foreign language (EFL) university students in South America or their application to academic writing in a second language (L2) for STEM classes. ChatGPT can generate human-like text that worries teachers and researchers. Academic cheating, especially in the language classroom, is not new; however, the concept of AI-giarism is novel. This study evaluated how 56 undergraduate university students in Ecuador viewed GenAI use in academic writing in English as a foreign language. The research findings indicate that students worried more about hindering the development of their own writing skills than the risk of being caught and facing academic penalties. Students believed that ChatGPT-written works are easily detectable, and institutions should incorporate plagiarism detectors. Submitting chatbot-generated text in the classroom was perceived as academic dishonesty, and fewer participants believed that submitting an assignment machine-translated from Spanish to English was dishonest. The results of this study will inform academic staff and educational institutions about how Ecuadorian university students perceive the overall influence of GenAI on academic integrity within the scope of academic writing, including reasons why students might rely on AI tools for dishonest purposes and how they view the detection of AI-based works. Ideally, policies, procedures, and instruction should prioritize using AI as an emerging educational tool and not as a shortcut to bypass intellectual effort. Pedagogical practices should minimize factors that have been shown to lead to the unethical use of AI, which, for our survey, was academic pressure and lack of confidence. By and large, these factors can be mitigated with approaches that prioritize the process of learning rather than the production of a product.

The use of amine-based solvents for carbon dioxide (CO₂) capture has shown significant promise; however, operational challenges such as high energy requirements, solvent degradation, and equipment corrosion highlight the need for enhanced solutions. This review focuses on identifying amine-based solvents and additives that can improve CO₂ capture efficiency while minimizing costs and avoiding substantial modifications to existing industrial facilities. Specifically, the study emphasizes the development of a comprehensive database of additives to optimize CO₂ capture processes. A detailed analysis of recent advancements in amine-based solvents was conducted, with a focus on (i) process optimization strategies, (ii) sector-specific CO₂ emission profiles, and (iii) equipment issues associated with conventional chemical solvents. The study evaluates these solvents’ kinetic and thermodynamic properties and their potential to address critical operational challenges, including reducing corrosion, solvent viscosity, and evaporation rates. The findings highlight the pivotal role of amino group-containing compounds, particularly alkanolamines, in enhancing CO₂ capture performance. The structural versatility of these compounds, characterized by the presence of hydroxyl groups, facilitates aqueous dissolution while offering kinetic and thermodynamic benefits. This review underscores the importance of continued innovation in solvent chemistry and the integration of amine-based solvents with emerging technologies to overcome current limitations and advance the implementation of efficient and sustainable CO₂ capture technologies.