Indoor Air Quality Diagnosis Program for School Multi-Purpose Activity and Office Spaces

Yeo-Kyung Lee, Young Il Kim () and Ga-Hyeon Kim
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Yeo-Kyung Lee: Department of Architectural Engineering, Graduate School, Seoul National University of Science and Technology, Seoul 01811, Korea
Young Il Kim: School of Architecture, Seoul National University of Science and Technology, Seoul 01811, Korea
Ga-Hyeon Kim: Architectural Engineering Program, School of Architecture, Seoul National University of Science and Technology, Seoul 01811, Korea

Energies, 2022, vol. 15, issue 21, 1-23

Abstract: This study presents a simple indoor air quality diagnosis program for school office spaces, which are occupied for long durations by teachers, and indoor sports facilities, whose utilization has been on the rise in response to high concentrations of pollutants in outdoor air. The proposed program was made with Visual Basic for Applications (VBA) and Microsoft Excel. This program requires inputs which can be easily determined or measured even by nonexperts and can check the current status of indoor air quality such as CO 2 and PM 2.5 concentrations and predict the effect if changes are made. In addition, it is possible to diagnose indoor air quality before and after class and compare it with the initial plan so that if it exceeds the indoor air quality maintenance standard range, it can be improved by using a ventilation system and an air purifier. The development of the program was divided into four stages. First, prior research on the influencing factors was investigated. Second, influencing factors affecting the changes in PM 2.5 and CO 2 concentrations were selected by category to accommodate the various factors, and those selected as input were presented. Third, mass and concentration conservation equations were utilized to derive PM 2.5 and CO 2 concentration prediction equations according to activity and passage of time, and a VBA code was used for constructing the program. For verification of the developed program, the calculation results were compared with the measured data. The mean absolute percentage error (MAPE) was 19.47% for PM 2.5 concentration. In order to improve accuracy, Simulation 2, in which the wind speed and indoor/outdoor air pressure difference are corrected, is presented. The MAPE of PM 2.5 concentration by the corrected Simulation 2 was lowered 5.15%.

Keywords: carbon dioxide; PM 2.5; indoor air quality; diagnosis program; multipurpose activity; office; energy recovery ventilation; Visual Basic Application (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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