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Indoor Household Air Quality Assessment: The case of the use of low cost sensor
* 1 , 2 , 3
1  Science and Education Development Institute, Akure, Ondo State, Nigeria
2  Department of Horticulture and Landscape Technology, Federal College of Agriculture, Akure, Ondo State, Nigeria
3  Department of Chemistry, University of Education, Science, and Technology, Ikere, Ekiti State, Nigeria
Academic Editor: Dibyendu Sarkar

https://doi.org/10.3390/ASEC2021-11171 (registering DOI)
Abstract:

According to World Health Organisation (WHO) over 4 million people die world-wide in 2012. This was due to one of the indoor contributors - particulate matter (PM) of a diameter 2.5. The use of low-cost PM measurements is assisting individuals to take actions by providing personalized information on indoor concentrations in real time. The low-cost sensor – SentinAir used in this study was designed and developed by group of researchers from ENEA-Italian National Agency for New Technologies, Energy and Environment. Sustainable Development Department, Research Center of Brindisi, Italy. It measures PM (1, 2.5, 10), NO2, SO2, CO2, O3, temperature, and relative humidity. The aim of this study was to deploy the sensor into the indoor (kitchen) of a household with the view of assessing all the parameters over a period of thirty (30) days as a preliminary investigation measurement. The protocol of the sensor was strictly followed. The results (mean) depicted: PM 1 (17.80 µg/m3), PM 2.5 (25.21 µg/m3), PM 10 (27.61 µg/m3), CO2 (435.3 ppm), O3 (24.75 ppb), NO2 (66.52 ppb), SO2 (48.04 ppb), temperature (34.1 oC), and humidity (64 %). When these results were compared with the WHO and National Environmental Standards and Regulations Enforcement Agency (NESREA) it was observed that the PM2.5 and 10 were within the 24 h guideline values of 25 and 50 µg/m3 respectively. Although that of PM 2.5 may be a risk. There were significant influences of temperature and humidity on the pollutants. Food frying and baking generated the largest increase in PM, in the kitchen activity. Because the data is reproducible, it is recommended that this low-cost PM sensor be integrated into an indoor air-quality measurement network to assist individuals in managing their personal exposure.

Keywords: Indoor air; Particulate matter; Sensor network, Low-cost particulate matter sensor

 
 
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