Data Analysis on Outdoor-Indoor Air Quality Variation: Buildings' Producing Dynamic Filter Effects

Recently, air quality issues have attracted muchmore 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 PM2.5, the indoor PM2.5, 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 PM2.5 per hour is studied, and the interrelationship between the indoor and the outdoorPM(2.5) is explored in time domain. Some interesting physical laws are discovered by using the collected data. First, the indoor PM2.5 per hour follows Gaussian distribution in most cases. Second, the indoor PM2.5 has a positive correlation with the corresponding outdoor one. Third, a linear regression modelwith high accuracy on analyzing the indoor PM2.5 is presented, which indicates that the indoor PM2.5 consists of two parts-one comes from the outdoor PM2.5 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 thememory effects of the building for both long time and short time scales. Particularly, for the long timememory effect, the indoor PM2.5 average memory duration (AMD) is about 2 h, and the indoor PM2.5 AMD to the outdoor PM2.5 is about 7 h, while for the short time memory effect, the indoor PM2.5 AMD is also about 2 h but that to the outdoor PM2.5 is about 5 h. Additionally, the continuance of outdoor PM2.5 has much greater effect on the indoor one than its concentration.