The purpose of this study is to model air pollution with the PM2.5 suspended particulate in a single-family house located in Bialystok. A linear regression model was developed that describes the relationship between the concentration of PM2.5 (response variable) in a building and external factors: concentrations of PM10 and PM2.5 particulates, air temperature and relative humidity (independent variables). Statistical and substantive verification of the model indicates that the concentration of PM10 in outdoor air is the variable most strongly affecting the concentration of harmful PM2.5 in indoor air. The model therefore allows estimating the concentration of PM2.5 in the building on the basis of data on the concentration of PM10 outside the tested object, which can be useful for assessing indoor air quality without using a measuring tool inside the building. Excel and GRETL were used to develop the model.
The level of environmental quality is the result of many factors, and the most important of these is human activity. A responsible approach to the environment is looking for methods to eliminate pollution from the environment. Waste incineration is a way to rationally manage and process waste, minimize emissions of air pollutants and ecologically produce heat and electricity. The purpose of this article is to build and analyze a regression model describing the relationship of pollutant emissions to air from waste incineration plants depending on various factors.
This article examines the correlation between the amount of pollutants emitted from medical waste incinerator plant and the number of COVID-19 infections, based on the example of Podlaskie Voivodeship in Poland. This paper deals with the issues of medical waste management during the COVID-19 pandemic. Thermal processing is characterised as a method of medical waste utilisation. The technological sequence of the medical waste incineration installation and the integrated exhaust gas cleaning system are discussed. The results of studies on the emission of pollutants into the atmosphere during combustion are compared with the number of COVID-19 cases in the same voivodeship to investigate how the coronavirus pandemic affects the amount of medical waste generated, thus the amount of pollutants emitted into the atmosphere. The Pearson's linear correlation coefficient and the Student's t-test are used to verify the results. The analysis results show a statistically significant, moderate positive correlation between the amount of covid waste and the number of COVID-19 cases (0.5140). In turn, there is also a statistically significant moderate correlation between the number of COVID-19 cases and emissions of SO2 (r = 0.6256, p = 0.010), NO x (0.5019, p = 0.048), and HCl (0.5130, p = 0.042). This correlation finding highlights additional costs to the environment and public health as the number of COVID-19 cases increase, which can be taken into account for pandemic planning by governments in the future.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.