Data Analysis on Outdoor–Indoor Air Quality Variation: Buildings’ Producing Dynamic Filter Effects

Recently, air quality issues have attracted much more attention. This paper aims to find an effective way to analyse the buildings’ effects on the air quality variation between indoor and outdoor. To do so, we treat the building as a dynamic filter system by regarding the outdoor PM $_{2.5}$ , the indoor PM $_{2.5}$ , and the building as the input, the output, and a response system, respectively. To analyze the filtering effect produced by buildings, the statistical distribution of the indoor PM $_{2.5}$ per hour is studied, and the interrelationship between the indoor and the outdoor PM $_{2.5}$ is explored in time domain. Some interesting physical laws are discovered by using the collected data. First, the indoor PM $_{2.5}$ per hour follows Gaussian distribution in most cases. Second, the indoor PM $_{2.5}$ has a positive correlation with the corresponding outdoor one. Third, a linear regression model with high accuracy on analyzing the indoor PM $_{2.5}$ is presented, which indicates that the indoor PM $_{2.5}$ consists of two parts—one comes from the outdoor PM $_{2.5}$ penetrating into the building and the other comes from the indoor environment. Fourth, by applying different system identification methods, it is found that the B–J model is the best one in characterizing the memory effects of the building for both long time and short time scales. Particularly, for the long time memory effect, the indoor PM $_{2.5}$ average memory duration (AMD) is about 2 h, and the indoor PM $_{2.5}$ AMD to the outdoor PM $_{2.5}$ is about 7 h, while for the short time memory effect, the indoor PM $_{2.5}$ AMD is also about 2 h but that to the outdoor PM $_{2.5}$ is about 5 h. Additionally, the continuance of outdoor PM $_{2.5}$ has much greater effect on the indoor one than its concentration.