Reverse osmosis is the leading technology for desalination of brackish water and seawater, important for solving the growing problems of fresh water supply. Thermal technologies such as multi-effect distillation and multi-stage flash distillation still comprise an important portion of the world’s desalination capacity. They consume substantial amounts of energy, generally obtained from fossil fuels, due to their low efficiency. Hybridization is a strategy that seeks to reduce the weaknesses and enhance the advantages of each element that makes it up. This paper introduces a review of the most recent publications on hybridizations between reverse osmosis and thermal desalination technologies, as well as their integration with renewable energies as a requirement to decarbonize desalination processes. Different configurations provide improvements in key elements of the system to reduce energy consumption, brine production, and contamination, while improving product quality and production rate. A combination of renewable sources and use of energy and water storage systems allow for improving the reliability of hybrid systems.

Thermal desalination is yet a reliable technology in the treatment of brackish water and seawater; however, its demanding high energy requirements have lagged it compared to other non-thermal technologies such as reverse osmosis. This review provides an outline of the development and trends of the three most commercially used thermal or phase change technologies worldwide: Multi Effect Distillation (MED), Multi Stage Flash (MSF), and Vapor Compression Distillation (VCD). First, state of water stress suffered by regions with little fresh water availability and existing desalination technologies that could become an alternative solution are shown. The most recent studies published for each commercial thermal technology are presented, focusing on optimizing the desalination process, improving efficiencies, and reducing energy demands. Then, an overview of the use of renewable energy and its potential for integration into both commercial and non-commercial desalination systems is shown. Finally, research trends and their orientation towards hybridization of technologies and use of renewable energies as a relevant alternative to the current problems of brackish water desalination are discussed. This reflective and updated review will help researchers to have a detailed state of the art of the subject and to have a starting point for their research, since current advances and trends on thermal desalination are shown.

The objective of this article is to review how Artificial Intelligence (AI) tools have helped the process of formulating agricultural public policies in the world. For this, a search process was carried out in the main scientific repositories finding different publications. The findings have shown that, first, the most commonly used AI tools are agent-based models, cellular automata, and genetic algorithms. Secondly, they have been utilized to determine land and water use, and agricultural production. In the end, the large usefulness that AI tools have in the process of formulating agricultural public policies is concluded.

One of the environmental challenges that is currently negatively affecting the ecosystem is the continuous discharge of untreated industrial waste into both water sources and soils. For this reason, one of the objectives of this qualitative study of exploratory-descriptive scope was the review of scientific articles in different databases—Scopus, Web of Science, and Science Direct—published from 2010 to 2021 on the use of fruit peels as a sustainable waste in the removal of heavy metals present in industrial wastewater. For the selection of articles, the authors used the PRISMA guide as a basis, with which 210 publications were found and 93 were compiled. Considering the reported work, a content analysis was carried out using NVivo 12 Plus and VOSviewer 1.6.17 software. The results show that the fruits mentioned in these publications are lemon, banana, mango, tree tomato, pineapple, passion fruit, orange, coconut, avocado, apple, lulo, and tangerine. However, no studies were found with lulo and tree tomato peels. On the other hand, the heavy metals removed with the selected fruit peels were Pb⁺², Cr⁺³, Cr⁺⁶, Ni⁺², Cd⁺², As⁺⁵, Cu⁺², and Zn⁺².

The purpose of this article consists of analyzing publications discussing the use of agent-based artificial intelligence models in sustainable agriculture research. The analysis involved bibliometric indicators and the Rstudio software with Bibliometrix library. The methodology is descriptive with a quantitative approach. Scientific databases SCOPUS and Web of Science were consulted and the PRISMA methodology was used during the selection process. This led to finding 86 publications that met the inclusion criteria. Amongst the results, United States was listed as the country with the highest production of scientific material, although France had a higher impact. Additionally, the bibliographical resources that help promote scientific development are open source. It was concluded that the agent-based model has been adopted to simulate different scenarios, which help decision-makers to formulate public policies in favor of sustainable agriculture. This optimizes the use of natural resources and reduces negative consequences for the environment, while also delivering value for the stakeholders of the agricultural system.

A circular economy (CE) promotes the reuse, reincorporation and valuation of waste and by-products under the framework of sustainable development through models and indicators that evaluate scenarios of second use and reduction in non-incorporated outputs to reduce negative externalities and pressures on the dimensions of development. A CE model applied to the transformation process of RFF in agro-industries is developed, which consists in the identification of the residue coefficients of EFB (22.48% ± 0.8), fiber (15.58% ± 0.49), husk (6.03% ± 0.66) and ash (0.55% ± 1.67). Subsequently, the valuation trends of potential second use were verified through a systematic review, which allowed the construction of the scenario of avoided costs of USD 678,721.5, a product of the total use of the outputs under bioenergy and nutrient source approaches. Finally, the RRSFM indicator was constructed, which can reach the level of 72% and a degree of improvement of 26% by 2026. In parallel, the HCRRS indicator revealed a reduction of 57.1%, 59.6% and 82.8% in emissions of t CO_2-eq product in the comparison of scenarios for the use of residues and by-products of palm oil from agro-industries in the Casanare Department.