E3S Web Conf.
Volume 80, 20192018 International Conference on Renewable Energy and Environment Engineering (REEE 2018)
|Number of page(s)||7|
|Section||Environmental Monitoring and Assessment|
|Published online||15 January 2019|
Study of indoor PM2.5 distribution characteristics and optimal location for its monitoring in an office
Joint International Research Laboratory of Green Buildings and Built Environments (Ministry of Education), Chongqing University, Chongqing 400045, China
2 National Centre for International Research of Low-carbon and Green Buildings (Ministry of Science and Technology), Chongqing University, Chongqing 400045, China
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.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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