Regression Model of PM2.5 Concentration in a Single-Family House

Monika Załuska and Katarzyna Gładyszewska-Fiedoruk
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Monika Załuska: Department of HVAC Engineering, Faculty of Civil and Environmental Engineering, Białystok University of Technology, Wiejska 45E Street, 15-351 Białystok, Poland
Katarzyna Gładyszewska-Fiedoruk: Department of HVAC Engineering, Faculty of Civil and Environmental Engineering, Białystok University of Technology, Wiejska 45E Street, 15-351 Białystok, Poland

Sustainability, 2020, vol. 12, issue 15, 1-15

Abstract: 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.

Keywords: particulate matter; PM10; PM2.5; air pollutants; air quality; indoor environment; linear regression; contaminant modeling (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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