scholarly journals LEVELS OF SELECTED INDOOR AIR POLLUTANTS IN THREE HA NOI OFFICES

2018 ◽  
Vol 56 (2C) ◽  
pp. 148-156 ◽  
Author(s):  
Ly Bich Thuy
Keyword(s):  
Indoor Air ◽  
High Frequency ◽  
Air Pollutants ◽  
Sampling Site ◽  
High Time Resolution ◽  
Air Conditioners ◽  
Dry Seasons ◽  
Indoor Air Pollutants ◽  
Respirable Particulate ◽  
Wet And Dry Seasons

A study on the levels of indoor air pollutants in Ha Noi was conducted. Three offices in Ha Noi were selected for this purpose. Selected indoor air pollutants including SO2, NO2 and respirable particulate matter (PM10) were monitored in the wet and dry seasons of 2015. Air conditioners were turned on for the whole time, while air purifiers were turned on for haft of the time in each sampling site. An hourly measurement of outdoor levels was also conducted before indoor measurement. Levels of outdoor PM10 varied in the range of 13.4-106.0 µg/m3. The level of indoor PM10 varied in the range of 3.5-25.1 µg/m3. The average levels of indoor PM10 were lower than that of outdoor one in all cases. High time resolution data showed that indoor PM10 levels temporarily increased sharply by activities (walking and room sweeping) and high frequency of opening the doors. Concentrations of outdoor/indoor SO2 varied in the range of             < 0.4-34.5 /< 0.4-47.1 ppb. Concentrations of outdoor/indoor NO2 varied in the range of              4.3-33.4/3.3-27.8 ppb.

scholarly journals Exposure and Health Impacts Related to Outdoor and Indoor Air Pollutants

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 105
Author(s):  
Haider A. Khwaja
Keyword(s):  
Indoor Air ◽  
Air Pollutants ◽  
Health Impacts ◽  
Special Issue ◽  
Indoor Air Pollutants ◽  
Selection Of

The five papers included in this Special Issue represent a diverse selection of contributions [...]

Risk assessment of exposure to indoor air pollutants

1990 ◽  
Vol 11 (4) ◽  
pp. 295-302 ◽  
Author(s):  
J. J. McAughey ◽  
J. N. Pritchard ◽  
A. Black
Keyword(s):  
Risk Assessment ◽  
Indoor Air ◽  
Air Pollutants ◽  
Indoor Air Pollutants

How low-cost air pollution sensors could make homes smarter?

2021 ◽  
Author(s):  
Hamid Omidvarborna ◽  
Prashant Kumar
Keyword(s):  
Air Pollution ◽  
Indoor Air ◽  
Air Pollutants ◽  
Indoor Air Pollution ◽  
Prediction Models ◽  
Disease Risk ◽  
Low Cost ◽  
Mortality And Morbidity ◽  
Spatio Temporal ◽  
Indoor Air Pollutants

&lt;p&gt;The majority of people spend most of their time indoors, where they are exposed to indoor air pollutants. Indoor air pollution is ranked among the top ten largest global burden of a disease risk factor as well as the top five environmental public health risks, which could result in mortality and morbidity worldwide. The spent time in indoor environments has been recently elevated due to coronavirus disease 2019 (COVID-19) outbreak when the public are advised to stay in their place for longer hours per day to protect lives. This opens an opportunity to low-cost air pollution sensors in the real-time Spatio-temporal mapping of IAQ and monitors their concentration/exposure levels indoors. However, the optimum selection of low-cost sensors (LCSs) for certain indoor application is challenging due to diversity in the air pollution sensing device technologies. Making affordable sensing units composed of individual sensors capable of measuring indoor environmental parameters and pollutant concentration for indoor applications requires a diverse scientific and engineering knowledge, which is not yet established. The study aims to gather all these methodologies and technologies in one place, where it allows transforming typical homes into smart homes by specifically focusing on IAQ. This approach addresses the following questions: 1) which and what sensors are suitable for indoor networked application by considering their specifications and limitation, 2) where to deploy sensors to better capture Spatio-temporal mapping of indoor air pollutants, while the operation is optimum, 3) how to treat the collected data from the sensor network and make them ready for the subsequent analysis and 4) how to feed data to prediction models, and which models are best suited for indoors.&lt;/p&gt;

Human exposure to indoor air pollutants in sleep microenvironments: A literature review

2017 ◽  
Vol 125 ◽  
pp. 528-555 ◽  
Author(s):  
Brandon E. Boor ◽  
Michal P. Spilak ◽  
Jelle Laverge ◽  
Atila Novoselac ◽  
Ying Xu
Keyword(s):  
Literature Review ◽  
Indoor Air ◽  
Air Pollutants ◽  
Human Exposure ◽  
Indoor Air Pollutants

Asthma‐related outcomes associated with indoor air pollutants among schoolchildren from four informal settlements in two municipalities in the Western Cape Province of South Africa

Indoor Air ◽  
2018 ◽  
Vol 29 (1) ◽  
pp. 89-100 ◽  
Author(s):  
Toyib Olaniyan ◽  
Mohamed Aqiel Dalvie ◽  
Martin Röösli ◽  
Rajen Naidoo ◽  
Nino Künzli ◽  
...  
Keyword(s):  
South Africa ◽  
Indoor Air ◽  
Air Pollutants ◽  
Informal Settlements ◽  
Western Cape ◽  
Western Cape Province ◽  
Indoor Air Pollutants
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