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Item type:Publication, Water quality analysis in Mantaro River, Peru, before and after the tailing's accident using the Grey clustering method(Insight Society, 2021-01-01)Problems with environmental accidents are increasing worldwide, which generates great damage to the environment. In fact, in July 2019, a tailing spill occurred that flowed into the Mantaro River, contaminating it with thousands of liters of waste. This had environmental consequences and social ones since there were people for and against mining, which is the principal economic activity in the area. In this way, this study proposes to quantify the damage caused by the tailing spill using the grey clustering method, which is based on grey systems theory. For this purpose, two sampling points were chosen for data collection and evaluation both before and after the accident, which allowed to measure the impact of metal concentrations and other physical-chemical parameters caused by accident. The results obtained from the study revealed increases in the concentration levels of metals such as aluminum, arsenic, among others, in some cases very high that exceeded the maximum permitted limits. Such findings could help local and national government authorities, people living and transiting near the river, and activities related to the use of the water in this river; since the quality of the river water can be lethal if the necessary measures are not taken. In addition, the method used in this study showed to be very practical and efficient during its application. Finally, it is advised that future research investigate each point along the Mantaro River and show the areas where the disaster had the most impact to develop some mitigating techniques. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, How to determinate water quality using an artificial intelligent model based on grey clustering?(Institute of Advanced Engineering and Science, 2022-10-01)Water quality is an important topic for countries like Peru, where the mining sector is one of the main economic activities, so the study of its impact on water quality is also necessary to have a regular control of benefits and dangers. In this way, to achieve this objective, the chosen methodology was grey clustering, which is based on artificial intelligent theory. Specifically, the central point triangular whitening weight function better known as CTWF, which is an approach from grey clustering, was used. The case study was focused on the Mashcon and Chonta rivers, located in the province of Cajamarca, Peru, these rivers are directly affected by an open pit mine. The study was carried out taking into account thirteen monitoring points taken by National Water Authority (ANA). The results showed that all the points considered were classified as not contaminated, A1 category, this using the parameters of the Peruvian government. With these results, the mining company was able to demonstrate that they are taking the water quality into account and that they are making an effort to keep these rivers as healthy as possible. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Algorithm based on grey clustering and Shannon entropy to assess landscape visual quality(IJETAE Publication House, 2022-01-01)Landscape assessment has been limited to methodologies with subjective and qualitative approaches, due to prevailing the concept of landscape as the perception of territory. In this work, the intrinsic visual quality of the landscape was evaluated using an algorithm based on grey clustering and Shannon entropy. The grey clustering method was used to determine the landscape visual quality, and Shannon entropy was applied to calculate wights of criteria used for evaluation. The case study was performed on mining project located in Cajamarca, Peru, where three landscape units were identified and four evaluation criteria were established, before and after the implementation of project. The results revealed that there is a notable effect of the change in landscape visual quality in three evaluated landscapes units. The criteria in order of evaluation were the intrinsic visual quality of the water, relief, vegetation cover, and artificial elements. Consequently, the method showed quantitative and qualitative results that could help the landscape assessment process to make better decisions regarding mining projects. Keywords—Grey clustering, Landscape visual quality, Mining project, Shannon entropy. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Socio-Economic Impact Assessment from a Scholarship Program Founded by Mining Project Using Grey Systems(Seventh Sense Research Group, 2023-01-01)The large-scale mining operations around indigenous and rural populations, despite their tremendous profit for Peru's economy, have usually been accompanied by limited improvement in wealth and standards of living and thus leading currently to a rise in social conflict and violence. A case study was carried out on a scholarship programme founded by the mining company Las Bambas surrounding the community of Fuerabamba. This study was conducted using a method based on grey systems. One main stakeholder group and four evaluation criteria were recognized. The result has reported that the program has a positive social impact on the sponsored students, thus contributing to closing education gaps in the country and promoting diversity. The method showed interesting results and could be applied to future socio-economic evaluations of programs that offer significant opportunities for young people, especially those founded by mining companies.