With the appearance of the word “haze” in China, PM2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) that can enter occupants' lungs has become a public topic of discussion. Today, the indoor PM2.5 or fine particulate concentration has become one of important factors affecting indoor air quality (IAQ). How to properly monitor indoor PM2.5 is an urgent issue to be discussed and solved. At present, sampling is adopted to know PM2.5 concentration in a room, and Chinese related standard required the sampling time for indoor PM2.5 is at least 8 hours. However, the sampling method takes too much time, and the HVAC system cannot react in real time such as increasing the fresh air volume with increase of indoor PM2.5 concentration. So, there is a great need to find an optimal location for continuous PM2.5 monitoring. Before finding the monitoring point, the spatial and temporal distribution characteristics of indoor PM2.5 concentration are needed to be known. Computational fluid dynamics (CFD) can be used to simulate airflow and dispersion of PM2.5 in rooms with different scales, functions and ventilations. This paper will contribute to find the optimal location which could preferably describe indoor PM2.5 concentration in an office combined with experimental research and CFD simulation. In short, the aim of the paper is to reveal the spatial-temporal characteristics of indoor PM2.5 concentration distribution and optimize the layout of PM2.5 monitoring points for air conditioning systems to better control indoor contaminate PM2.5 concentration.
Experimental Study on the Factors Affecting Indoor PM2.5 Concentration
