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Impact of building systems usage on indoor particulate matter $(PM_{2.5})$ concentration in residential buildings
Pandey, Pratik Raj
Pandey, Pratik Raj
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2021-07
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Indoor air quality (IAQ) is essential because people spend up to 90% of their time indoors. There are various sources of indoor air pollutants, including combustion, building materials, and outdoor air pollution. Particulate Matter $(PM_{2.5})$: fine aerosol particles with diameters less than 2.5 microns (μm) near the surface have received considerable attention because of their adverse effects on regional air quality and human health. Exposure to $PM_{2.5}$ can cause upper respiratory problems such as asthma and heart diseases. Therefore, many previous studies conducted studies related to the residential building indoor PM2.5 concentrations and tried to find ways to remove them. This study defines the effectiveness of HVAC units, windows, and range hoods on $PM_{2.5}$ concentration in real situations. The decay rate, which can explain the system's effectiveness, was calculated to identify these systems' impact. This study conducted the field data collection in homes to collect the indoor environmental data and analyzed this data to define the system effectiveness in the actual environment.
The result shows that opening the window is the most effective way to remove the particles indoors; 1) in the first ten minutes, the $PM_{2.5}$ concentration is reduced by 73%, and 2) $PM_{2.5}$ decay rate of 1.26 h-1 is fastest as compared to other systems (the decay rate of HVAC system usage was 0.61 h-1). Range hood alone, on the other hand, did not have a significant impact because the homeowners use the range hood for a brief period. The uniqueness of this study is that developing new simulation approaches which can intake the building system usage time to estimate $PM_{2.5}$ concentrations. This study looked at the combined impact of various systems together. This study separated the decay rate while the system was used or not and created the unitless number for $PM_{2.5}$ removal effectiveness for the simulation purpose. Using this unitless number, we can accurately estimate the $PM_{2.5}$ concentrations by using the duration of the system usage time and the peak concentration. This preliminary model can predict the $PM_{2.5}$ concentrations with 70% of accuracy. To increase the accuracy of the model, future studies need other variables.
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Thesis (M.S.)-- Wichita State University, College of Engineering, Dept. of Mechanical Engineering
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Wichita State University
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© Copyright 2021 by Pratik Raj Pandey
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