 Abstract: Nowadays, it is known that water is a critical issue for human life. For this reason, research in this category is a complex subject. The case chosen for this work is in the district of Tambobamba, Cotabambas province, in the region of Apurimac. This is where Las Bambas mine is operating and the area of influence includes the Challhuahuacho and Ferrobamba rivers. Based on six monitoring points, carried out between February 2017 and March 2019 by ANA, it was possible to know if these rivers would have a low or high degree of contamination. Therefore, the methodology used in this work was the Grey Clustering Method. This method includes vital water parameters established by Peruvian D.S. N° 004-2017-MINAM. The results of these studies show that the Ferrobamba River has a high water quality while the Challhuahuacho River has a poor water quality, which could be associated with spills in the area.

The purpose of this study is to simultaneously analyze the different risk factors (lighting, noise, and ergonomics), obtain an overall assessment of the risk of these factors and classify them in scales of levels of: Very poor, poor, good and very good, from three libraries of the National University of Engineering. In order to classify them, the grey clustering method was used, which establishes two types of data: Standard data and sampling data, the first one refers to the minimum standards required to be met by a library according to each criterion (lighting, noise, ergonomics). The second one refers to the real data obtained in the field. Both data are evaluated in the indicated methodology and the clustering vector is constructed, which will allow to classify the libraries in the scales of established levels. According to the results obtained, it was determined that the lowest noise levels were obtained in the library of the Faculty of Environmental Engineering; nevertheless, these levels are not within the minimum standards of noise for libraries; in addition, it was determined that the lowest values obtained in illumination of each library correspond to the library of the Faculty of Environmental Engineering, since it is in levels of illumination significantly below what is required according to the minimum standards. On the other hand, adequate lighting levels were obtained in the library of the Faculty of Sciences, and it was determined that the best ergonomic comfort was obtained in the Central Library. According to the overall assessment of each of the libraries under study, according to the scale of levels established, it is concluded that the library of the Faculty of Environmental Engineering is at a poor level with respect to the other libraries (good level).

The district of Comas in Lima, Peru, is considered one of the districts with the highest number of critical points due to the accumulation of solid waste, causing the proliferation of vectors and the generation of bad smells, producing in this way a negative environmental and social impact on the population and on the landscape characteristics of the environment. The objective of this investigation is to evaluate the risk produced by the critical points of solid waste identified in Tupac Amaru Avenue, in the district of Comas, using the Grey Clustering method. This method allows to consider the uncertainty in the analysis being an adequate methodology for the evaluation of the risk of critical points since it is an issue of high level of uncertainty due to the limited information. The criteria for the evaluation of the risk of the critical points are according to the methodology of the Risk Evaluation Guide of the Ministry of the Environment. Five critical points of solid waste identified in the corresponding Tupac Amaru Avenue in all Zone 1 of the district of Comas were evaluated during 3 days. The results revealed that the three of the monitoring points present moderate risk and two slight risk. This study could be a useful tool for decision making by local and regional authorities to prioritize critical points for eradication and prevention

Air pollution is a problem in large cities, which increases with population growth and industrialization. This work assessed air quality in four Mexican cities related to mining activities near monitoring points. The method used for this study was the Grey Clustering method, which is based on the theory of grey systems. This method uses information with a high degree of uncertainty, air quality analysis being an issue that uses data with a high degree of uncertainty. The results revealed that all four cities have good air quality based on Metropolitan Air Quality Index (IMECA) standards, even when mining activities take place near these cities. The results of this work could help the relevant authorities to implement further studies on the impact of polluting emissions from mining activities on the environment

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