Analysis and modeling of fresh air systems usage behavior in residential buildings in Beijing during heating season

Abstract

Fresh air systems (FAS) represent an excellent solution for improving indoor air quality. Because FAS has a significant impact on buildings’ energy consumption, it is vital to investigate FAS usage behavior. At present, there is a research gap with respect to individualized FAS usage behavior and prediction models for residential buildings. From November 15th, 2018 to March 15th, 2019, this paper conducted a field measurement and modeling study of FAS usage behavior in thirteen Beijing households. During heating season, the FAS is used intermittently, with an average daily opening duration of 17.5 hours. Based on the “average daily opening duration”, two FAS usage behaviors were identified: economical households and conventional households. The average daily indoor particles matter 2.5 (PM2.5) concentration was observed to be lower in FAS-using households (16.19 μg/m3, 12.30 μg/m3) than in non-FAS-using households (46.1 μg/m3). Outdoor PM2.5 concentration is a motivating factor for FAS opening. The paper used binary logistic regression to predict the FAS status of both economical and conventional households (two classified models), as well as for all tested households (unclassified model). These results suggest that classified models (84.1%, 83.5%) have greater accuracy than the unclassified model (75.9%), opening the possibility of using the average daily opening duration to classify and examine FAS usage behavior. The study provides accurate field data for evaluating FAS usage behavior, as well as a reference for further simulating the energy consumption of FAS-using households.