ABSTRACT
In response to the COVID-19 pandemic in early 2020, Sri Lanka underwent a nationwide lockdown that limited motor vehicle movement, industrial operations, and human activities. This study analyzes the impact of COVID-19 lockdown on carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM10, PM2.5) concentrations in two urban cities (Colombo and Kandy) in Sri Lanka, by comparison of data from the lockdown period (March to May 2020) with its analogous period of 2019 and 2021. The results showed that the percentage change of daytime PM10, PM2.5, CO, and NO2 concentration during the lockdown in Colombo (Kandy) is –42.3% (–39.5%), –46% (–54.2%), –14.7% (–8.8%) and –82.2% (–80.9%), respectively. In both cities, the response of NO2 to the lockdown was the most sensitive. In contrast, daytime O3 concentration in Colombo (Kandy) has increased by 6.7% (27.2%), suggesting that the increase in O3 concentration was mainly due to a reduction in NOx emissions leading to lower O3 titration by NO. In addition, daytime SO2 concentration in Colombo has increased by 22.9%, while daytime SO2 concentration in Kandy has decreased by –40%. During the lockdown period, human activities were significantly reduced, causing significant reductions in industrial operations and transportation activities, further reducing emissions and improving air quality in two cities. The results of this study offer potential for local authorities to better understand the emission sources, assess the effectiveness of current air pollution control strategies, and form a basis for formulating better environmental policies to improve air quality and human health. © The Author(s).
ABSTRACT
Training for industrial operations is an important task in different aspects related to safety, technical and operational topics, that are developed in university specialties. These issues are a priority process of learning and training for the use of machine tool workshop equipment. Likewise, the application of the industrial innovation paradigms of the different topics of Industry 4.0 are a necessity for technical and training development in engineering students, with augmented reality being one of the most important concepts of said industrial trend. This study shows the process of the development and validation study of a digital model of a conventional C&J CQ6125V lathe, based on augmented reality, with the aim of contributing to the educational process in the machine tool workshop at the Mexican University UPAEP. Given the need for Hybrid learning activities, caused by the SARS-COV-2 pandemic, where students considered models of Face-to-Face and Online activities, it was used in machine tool workshop courses as an alternative training and a learning instrument of laboratory teams. This application based on software for mobile devices was developed taking into account training considerations for the recognition of the essential elements of the lathe and the safety characteristics in its use, through the identification of its moving parts, using an interface easy to use for students involved in the machine tool shop. Once access to the augmented reality application was facilitated to interested parties, a survey was conducted on a non-probabilistic sample of engineering students to diagnose the essential operational functions of the application. The results stand out that the augmented reality exercise has an average higher than a value of four in Likert's scale for the number of components shown, the identification of the components from color codes and the animation of the lathe mechanisms. As well as the availability for installation and management of the application. The improvement findings of the students in the engineering areas show the need to improve the graphics to represent the real components of the lathe and the training parameters of the machine tool described. © 2022 IMCIC 2022 - 13th International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings. All rights reserved.