Development and validation of a dynamic mass-balance prediction model for indoor particle concentrations in an office room

Development of air purifier operation guidelines using grey box models for the concentrations of particulate matter in elementary school classrooms

Considering the hazardous effects of particulate matter (PM) exposure on students and teachers and the high PM concentration issue in South Korea, air purifiers have recently been installed in most classrooms to improve air quality. However, some on-site challenges, such as operational costs and noise, have been issues with the continuous operation of air purifiers. Therefore, a guideline is needed to dynamically predict the indoor PM concentration based on the changes in outdoor PM concentration and activate the air purifiers only when necessary. This study develops a grey-box model that uses measured data and physical differential equations to perform the given objective and verifies its accuracy using ASTM D5157. Modeling and analysis results have obtained information that can form the basis for developing guidelines to address PM issues in schools: The air purifier should be operated during periods where the predicted values exceed the limit in closed windows and the air purifier is not operating. It was also confirmed that the need for the operation of the air purifier varies between schools and classrooms under the same outdoor PM concentration. Indoor PM concentration increased significantly after students' simultaneous mass movement, necessitating air purifiers' operation before and after the events. The prefilter of the heater also aided in the removal of coarse PM. Additionally, the limitations and future development directions of the model were discussed.

Prediction of indoor PM2.5 concentrations and reduction strategies for cooking events through various IAQ management methods in an apartment of South Korea

Indoor PM_2.5 in apartments must be effectively managed to minimize adverse impacts on human health. Cooking is the one of the main PM_2.5 sources in apartments, and indoor air quality (IAQ) management methods (natural ventilation, mechanical ventilations, range hoods, and air purifiers) are typically used to reduce PM_2.5 generated during cooking. For effective control of indoor PM_2.5 , prediction of PM_2.5 reduction for various IAQ management methods is necessary. This study carefully predicted indoor PM_2.5 concentrations in an apartment when IAQ management methods were applied separately and/or in combination during cooking. The infiltration and exfiltration were verified by comparing the experimental results of CO₂ concentration with those predicted with or without mechanical ventilation. The deposition rate for PM_2.5 generated by cooking was also derived by comparing the experimental PM_2.5 changes with the predicted values for PM_2.5 natural decay. Through this method, effective PM_2.5 control ways during cooking in apartments can be proposed, such as natural ventilation with a range hood for 30 min and then the operation of an air purifier for 30 min. Additionally, if this prediction is combined with energy consumption, it will be possible to propose the most energy-efficient indoor PM_2.5 control methods for various seasons and outdoor conditions.