Conference Agenda

Currently, one of the water quality assessment techniques that is being considered worldwide is the use of bioindicators, due to their easy application and low cost, benefiting human beings and the ecosystem. The objective of this research was to perform a bibliometric analysis of the use of macroinvertebrates as bioindicators of freshwater quality. For the study, research related to the topic (between January 2010 and August 2021) was selected from the Scopus and Web of Science databases, using a search string comprised of keywords. Excel software was used to record and prepare tables and figures, and VOSviewer was used for data and bibliometric network analysis. The results of the search yielded 567 investigations in the Scopus database and 716 for the Web of Science (WoS) database, identifying that the most studied class of macroinvertebrates as a bioindicator of freshwater quality is the Insecta class. The journal with the highest scientific production on the topic studied was “ecological indicator”, both for the Scopus and WoS databases, and the country with the highest number of publications was the United States. The largest number of publications on macroinvertebrates was found in the thematic area “Environmental science”, and the most used keyword was “macroinvertebrates”. Finally, it is concluded that the orders Ephemeroptera, Plecoptera and Trichoptera of the class Insecta are the most used and with the best results as bioindicators of freshwater quality.

The aim of this project is to develop a modular system for the collection and disposal of solid waste in the Tambo River, based on a comprehensive redesign of the collection machine. This system will utilize a waterwheel powered by the river's current to generate the required energy, eliminating the reliance on solar panels. The proposal includes floating barriers to capture debris and automatic mechanisms to transport it via a conveyor belt. The redesign seeks to optimize operational efficiency and extend the equipment's lifespan, contributing to the conservation of the fluvial ecosystem and aligning with the Sustainable Development Goal of "Clean Water and Sanitation".

The adoption of electric vehicles has become a well-established initiative, driven by their sustainability and significant environmental advantages compared to combustion vehicles. However, it has been observed that the batteries of these vehicles encounter temperature-related challenges during their charge and discharge cycles. This study investigates the influence of cell spacing on airflow distribution and temperature within the module through computational simulations. Two configurations with separations of S_x = 20 mm and S_x = 23 mm are analyzed to evaluate their impact on thermal dissipation. The results indicate that when the cell spacing is smaller, the airflow exhibits a more enveloping pattern around the cells, promoting a more uniform thermal dissipation. However, in this configuration, the maximum temperature reaches approximately 328 K. Conversely, when the spacing increases to S_x = 23 mm, the airflow moves more rapidly through the module without fully surrounding the cells, creating higher temperature regions on the right side of the module and reaching a maximum temperature of 325 K. It is concluded that a smaller spacing improves thermal uniformity, while a larger spacing reduces the peak temperature but generates more pronounced thermal gradients. The correlation between airflow distribution and temperature underscores the importance of optimizing cell arrangement to enhance cooling efficiency.

This work presents the results of an operational analysis of a dual-fuel Otto cycle internal combustion engine using different gaseous fuels. Various variables are considered, such as the physical and chemical properties of fuel mixtures, including Hydrogen (H2), CNG, and LPG, along with the use of exhaust gas recirculation (EGR). As a case study, simulations will be conducted in SimScale software for the engine of a Toyota Yaris 5p VVT-i. Subsequently, the carbon footprint of each fuel mixture will be calculated. The results for the different fuel mixtures show that the combination of LPG and hydrogen produces the highest power output but also results in a higher carbon footprint. On the other hand, the mixture of CNG and hydrogen exhibits a lower carbon footprint. The simulations provided valuable insights into the fuel flow and in-cylinder behavior of the engine.