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

Park, Soo Bhin; Park, Ju‐Hyeong; Jo, Young Min; Song, Doosam; Heo, Sujeong; Lee, Tae Jeong; Park, Sowoo; Koo, Junemo

doi:10.1016/j.buildenv.2021.108465

Cited by 4 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the case of PM 10 , the accuracy was significantly low because the factor caused by the resuspension of particles in the classroom was not considered. Park et al predicted indoor PM based on the operation of an air purifier in an office 12 . The indoor PM prediction model considers the air change rate, penetration, occupants, resuspension by human activity, particle deposition rate, and particle removal rate of an air purifier.…”

Section: Introductionmentioning

confidence: 99%

“…Park et al predicted indoor PM based on the operation of an air purifier in an office. 12 The indoor PM prediction model considers the air change rate, penetration, occupants, resuspension by human activity, particle deposition rate, and particle removal rate of an air purifier. Each factor was acquired through experiments according to the particle size and verified by applying it to a mass balance model.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Prediction of indoor PM _2.5 concentrations and reduction strategies for cooking events through various IAQ management methods in an apartment of South Korea

et al. 2022

View full text Add to dashboard Cite

Indoor PM2.5 in apartments must be effectively managed to minimize adverse impacts on human health. Cooking is the one of the main PM2.5 sources in apartments, and indoor air quality (IAQ) management methods (natural ventilation, mechanical ventilations, range hoods, and air purifiers) are typically used to reduce PM2.5 generated during cooking. For effective control of indoor PM2.5, prediction of PM2.5 reduction for various IAQ management methods is necessary. This study carefully predicted indoor PM2.5 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 PM2.5 generated by cooking was also derived by comparing the experimental PM2.5 changes with the predicted values for PM2.5 natural decay. Through this method, effective PM2.5 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 PM2.5 control methods for various seasons and outdoor conditions.

show abstract

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Prediction of indoor PM _2.5 concentrations and reduction strategies for cooking events through various IAQ management methods in an apartment of South Korea

et al. 2022

View full text Add to dashboard Cite

show abstract

Ventilation strategy for simultaneous management of indoor particulate matter and airborne transmission risks – A case study for urban schools in South Korea

Koo

Lee

et al. 2023

Building and Environment

View full text Add to dashboard Cite

Hybrid models of machine-learning and mechanistic models for indoor particulate matter concentration prediction

Kim,

Son,

Koo

2024

Journal of Building Engineering

View full text Add to dashboard Cite

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

Cited by 4 publications

References 11 publications

Prediction of indoor PM _2.5 concentrations and reduction strategies for cooking events through various IAQ management methods in an apartment of South Korea

Prediction of indoor PM _2.5 concentrations and reduction strategies for cooking events through various IAQ management methods in an apartment of South Korea

Ventilation strategy for simultaneous management of indoor particulate matter and airborne transmission risks – A case study for urban schools in South Korea

Hybrid models of machine-learning and mechanistic models for indoor particulate matter concentration prediction

Contact Info

Product

Resources

About

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

Cited by 4 publications

References 11 publications

Prediction of indoor PM 2.5 concentrations and reduction strategies for cooking events through various IAQ management methods in an apartment of South Korea

Prediction of indoor PM 2.5 concentrations and reduction strategies for cooking events through various IAQ management methods in an apartment of South Korea

Ventilation strategy for simultaneous management of indoor particulate matter and airborne transmission risks – A case study for urban schools in South Korea

Hybrid models of machine-learning and mechanistic models for indoor particulate matter concentration prediction

Contact Info

Product

Resources

About

Prediction of indoor PM _2.5 concentrations and reduction strategies for cooking events through various IAQ management methods in an apartment of South Korea

Prediction of indoor PM _2.5 concentrations and reduction strategies for cooking events through various IAQ management methods in an apartment of South Korea