|M.Sc Student||Drahler Dana|
|Subject||Spatiotemporal Distribution of Air Pollution in an Indoor|
|Department||Department of Civil and Environmental Engineering||Supervisor||Professor Barak Fishbain|
|Full Thesis text|
Particulate air pollution has known negative impacts on human health. The main measurement methods are divided into methods that measure mass concentration and those that measure Particulate Number Concentration (PNC). In the last few years, low-cost optical particle counters are very commonly used for studies aimed at estimating particle concentrations. Some evidences suggest that these low-cost sensors are not as reliable as the traditional measuring instruments, however, more recent publications implied that they can be used as a network, reporting PNC comparatively to each other.
Indoor air pollution may present different spatial variabilities. The main known sources for particulate air pollution in the indoor environment are smoking, cooking, heating, the outdoor environment and peoples' movements. Most of these sources are frequent activities in public environments such as pub.
Previous studies that attempted to estimate air pollution exposure in hospitalities and other indoor environments, performed short time measurements, usually at a single location and with poor temporal resolution. In this research indoor air quality, in terms of PNC, was measured. These measurements were conducted simultaneously in several locations in a pub, for a considerable period of time. The measurements were done by a set of low-cost PNC sensors.
The aim of this study is to investigate the spatiotemporal patterns of PNC in a highly polluted indoor environment, as well as the ability of the low-cost sensor to capture these patterns.
High agreement between 10 identical sensors and sensitivity to local sources of pollution were reveled in this study. These findings suggest these sensors can be used for spatiotemporal investigation of indoor environment.
In order to create dense pollution maps from the sparse measurements, two spatial interpolation methods were performed - the Inverse Distance Weights (IDW) and linear combination Radial Basis Functions (RBF). The IDW performances evaluated as better than the RBF in this specific study.
This study suggests that the influence of the smoking zone on the non-smoking area is substantial, hence, more research on this topic has to be done as well as reexamination of the policy on smoking-zones in public places.