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The aim of this research was to obtain bioplastic films based on potato starch, graphene and aloe vera to study the effect of varying the content of these components on the thermal and permeability properties of the bioplastic. The water vapor barrier property is being of great interest in the study of bioplastic materials since materials with low permeability to water vapor are needed in the packaging industry to ensure the conservation of packaged products and are an alternative to conventional plastics. According to the results, two thermal decomposition zones were found, the first in the range of 100 to 280°C and the second around 300°C. A minimum value of permeability and permeability of 5,35 kg/h.kPa.m2 and 0,001839 kg/h.kPa.m, respectively, was also found at a graphene concentration of 0,005%w/w; aloe concentration of 24% w/w; and starch concentration of 10% w/w.

Population and industrial growth in Mexico’s Bajío region demand greater electricity consumption. The production of electricity from fuel oil has severe implications on climate change and people’s health due to SO2 emissions. This study describes the simulation of eight different scenarios for SO2 pollutant dispersion. It takes into account distance, geoenvironmental parameters, wind, terrain roughness, and Pasquill–Gifford–Turner atmospheric stability and categories of dispersion based on technical information about SO2 concentration from stacks and from one of the atmospheric monitoring stations in Salamanca city. Its transverse character, its usefulness for modeling, and epidemiological, meteorological, and fluid dynamics studies, as suggested by the models approved by the Environmental Protection Agency (EPA), show a maximum average concentration of 399 µg/m3, at an average distance of 1800 m. The best result comparison in the scenarios was scenery 8. Maximum nocturnal dispersion was shown at a wind speed of 8.4 m/s, and an SO2 concentration of 280 µg/m3 for stack 4, an atypical situation due to the geography of the city. From the validation process, a relative error of 14.7 % was obtained, which indicates the reliability of the applied Gaussian model. Regarding the mathematical solution of the model, this represents a reliable and low-cost tool that can help improve air quality management, the location or relocation of atmospheric monitoring stations, and migration from the use of fossil fuels to environmentally friendly fuels.