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

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.