scholarly journals 512 PB 286 EFFECTS OF INTERIOR PLANTS ON RELATIVE HUMIDITY AND AIR-BORNE PARTICULATE MATTER IN INDOOR ENVIRONMENTS

HortScience ◽  
1994 ◽  
Vol 29 (5) ◽  
pp. 504g-504
Author(s):  
Virginia I. Lohr ◽  
Georgia K. Goodwin ◽  
Caroline H. Pearson-Mims

Foliage plants were added to different environments, including an office and a computer lab. Relative humidity and air-borne particulate matter were monitored in the presence and absence of the plants. When the relative humidity was low, the addition of plants increased the relative humidity slightly, but significantly, over that when no plants were present. Particulate matter accumulation was not increased in the presence of plants. Some have hypothesized that the growing medium could be a source of increased particulates when plants are used indoors. Some of our experiments used self-watering containers, irrigated from below, resulting in very dusty conditions in the top of the container. If the growing medium could contribute to increases in particulate matter, we should have detected it in this study.

2021 ◽  
Vol 16 (1) ◽  
pp. 158-162
Author(s):  
Rengaraj Ramasamy ◽  
Krishnendu Mukhopadhyay

Equations of ‘ventilation index’ in industrial and medical sectors are already established, but not yet been worked out for domestic household environments. This study intended to establish an empirical formula for ‘ventilation index’ for domestic indoor environments. Measurements of 2.5 micron size particulate matter (PM2.5) with biomass, air velocity, room index, temperature and relative humidity were used for developing the empirical formula. A total of 54 households from rural Andhra Pradesh and Karnataka states of India were selected. Average air velocity ranges in selected kitchens were categorised into three parts for developing ventilation indices in household kitchen environments. Observations in kitchen environments were found to be very interesting and promising. The formula captured inverse relation between PM2.5 and air velocities, consistently.


Author(s):  
Laurentiu Predescu ◽  
Daniel Dunea

Optical monitors have proven their versatility into the studies of air quality in the workplace and indoor environments. The current study aimed to perform a screening of the indoor environment regarding the presence of various fractions of particulate matter (PM) and the specific thermal microclimate in a classroom occupied with students in March 2019 (before COVID-19 pandemic) and in March 2021 (during pandemic) at Valahia University Campus, Targoviste, Romania. The objectives were to assess the potential exposure of students and academic personnel to PM and to observe the performances of various sensors and monitors (particle counter, PM monitors, and indoor microclimate sensors). PM1 ranged between 29 and 41 μg m−3 and PM10 ranged between 30 and 42 μg m−3. It was observed that the particles belonged mostly to fine and submicrometric fractions in acceptable thermal environments according to the PPD and PMV indices. The particle counter recorded preponderantly 0.3, 0.5, and 1.0 micron categories. The average acute dose rate was estimated as 6.58 × 10−4 mg/kg-day (CV = 14.3%) for the 20–40 years range. Wearing masks may influence the indoor microclimate and PM levels but additional experiments should be performed at a finer scale.


Author(s):  
Iman Goldasteh ◽  
Goodarz Ahmadi ◽  
Andrea Ferro

Particle resuspension is an important source of particulate matter in indoor environments that significantly affects the indoor air quality and could potentially have adverse effect on human health. Earlier efforts to investigate indoor particle resuspension hypothesized that high speed airflow generated at the floor level during the gate cycle is the main cause of particle resuspension. The resuspended particles are then assumed to be dispersed by the airflow in the room, which is impacted by both the ventilation and the occupant movement, leading to increased PM concentration. In this study, a three dimensional model of a room was developed using FLUENT™ CFD package. A RANS approach with the RNG k-ε turbulence model was used for simulating the airflow field in the room for different ventilation conditions. The trajectories of resuspended particulate matter were computed with a Lagrangian method by solving the equations of particle motion. The effect of turbulent dispersion was included with the use of the eddy lifetime model. The resuspension of particles due to gait cycle was estimated and included in the computational model. The dispersion and transport of particles resuspended from flooring as well as particle re-deposition on flooring and walls were simulated. Particle concentrations in the room generated by the resuspension process were evaluated and the results were compared with experimental chamber study data as well as simplified model predictions, and good agreement was found.


2020 ◽  
Vol 8 (2) ◽  
pp. 61-67
Author(s):  
Nurul Bahiyah Abd Wahid ◽  
Intan Idura Mohamad Isa ◽  
Ahmad Khairuddin Hassan ◽  
Muhammad Izzat Iman Razali ◽  
Ahmad Haziq Hasrizal ◽  
...  

This study aims to determine the particulate matter (PM2.5) mass concentrations and the comfort parameters (total bacterial counts (TBC), total fungal counts (TFC), relative humidity and temperature) in a university building. The samplings were carried out in three different indoor areas, including lecture hall, laboratory and lecturer office. PM2.5 samples were collected over a period of 8 h sampling using a low volume sampler (LVS). The anemometer Model Kestrel 0855YEL was used to measure relative humidity and temperature parameters. The sampling of airborne microorganisms was conducted by using microbial sampler at 350 L air sampled volume. The results showed that the highest average of PM2.5 was at lecture hall (88.54 ± 26.21 µgm-3) followed by lecturer office (69.79 ± 19.06 µgm-3) and laboratory (47.92 ± 24.88 µgm-3). The mean of TBC and TFC readings recorded as follow; 32.71 ± 5.91 cfu m-3 and 76.71 ± 21.5 cfu m-3 for laboratory, 112.1 ± 29.06 cfu m-3 and 124.67 ± 23.35 cfu m-3 for lecturer office, 121.74 ± 19.33 cfu m-3 and 115.33 ± 8.08 cfu m-3 for lecture hall. The average of all comfort parameter was within the prescribed standard by Industry Code of Practice on Indoor Air Quality 2010 for all sampling sites. Therefore, all occupants of the building can work in a conducive and comfortable environment. This study is in line with the objectives of National Policy on the Environment (DASN), which focusing on achieving a clean, safe, healthy and productive environment for present and future generations.


2021 ◽  
Author(s):  
Vito A Ilacqua ◽  
Nicole Scharko ◽  
Jordan Zambrana ◽  
Daniel Malashock

We surveyed literature on measurements of indoor particulate matter in all size fractions, in residential environments free of solid fuel combustion. Data from worldwide studies from 1990-2019 were assembled into the most comprehensive collection to date. Out of 2,752 publications retrieved, 538 articles from 433 research projects met inclusion criteria and reported unique data, from which more than 2,000 unique sets of indoor PM measurements were collected. Distributions of mean concentrations were compiled, weighted by study size. Long-term trends, the impact of non-smoking, air cleaners, and the influence of outdoor PM were also evaluated. Similar patterns of indoor PM distributions for North America and Europe could reflect similarities in the indoor environments of these regions. Greater observed variability for all regions of Asia may reflect greater heterogeneity in indoor conditions, but also low numbers of studies for some regions. Indoor PM concentrations of all size fractions were mostly stable over the survey period, with the exception of observed declines in PM2.5 in European and North American studies, and in PM10 in North America. While outdoor concentrations were correlated with indoor concentrations across studies, indoor concentrations had higher variability, illustrating a limitation of using outdoor measurements to approximate indoor PM exposures.


2015 ◽  
Vol 15 (2) ◽  
pp. 399-409 ◽  
Author(s):  
Marco Casati ◽  
Grazia Rovelli ◽  
Luca D’Angelo ◽  
Maria Grazia Perrone ◽  
Giorgia Sangiorgi ◽  
...  

2016 ◽  
Author(s):  
M. Song ◽  
P. F. Liu ◽  
S. J. Hanna ◽  
R. A. Zaveri ◽  
K. Potter ◽  
...  

Abstract. To improve predictions of air quality, visibility, and climate change, knowledge of the viscosities and diffusion rates within organic particulate matter consisting of secondary organic material (SOM) is required.Most qualitative and quantitative measurements of viscosity and diffusion rates within organic particulate matter have focused on SOM particles generated from biogenic VOCs such as α-pinene and isoprene. In this study, we quantify the relative humidity (RH)-dependent viscosities at 295 ± 1 K of SOM produced by photo-oxidation of toluene, an anthropogenic VOC. The viscosities of toluene-derived SOM were 2 × 10−1 to ∼6 × 106 Pa·s from 30 to 90 % RH, and greater than ~2 × 108 Pa·s (similar to or greater than the viscosity of tar pitch) for RH ≤ 17 %. These viscosities correspond to Stokes-Einstein-equivalent diffusion coefficients for large organic molecules of ~2 × 10−15 cm2·s−1 for 30 % RH, and lower than ~3 × 10−17 cm2·s−1 for RH ≤ 17 %. Based on these estimated diffusion coefficients, the mixing time of large organic molecules within 200 nm toluene-derived SOM particles is 0.1–5 hr for 30 % RH, and higher than ~100 hr for RH ≤ 17 %. These results were used, as a first-order approximation, to estimate if organic particulate matter will be in well-mixed over the world's top 15 most populous megacities. If the organic particulate matter in the megacities is similar to the toluene-derived SOM in this study, in Kolkata, Istanbul, Dhaka, Tokyo, Shanghai, and Mumbai, mixing times in organic particulate matter during extended periods of the year will be very short, and well-mixed particles can be assumed. On the other hand, the mixing times of large organic molecules in organic particulate matter in Delhi, Beijing, Mexico City, Cairo, and Karachi may be long and the particles may not be well-mixed in the afternoon (3:00–5:00 local time) during certain times of the year.


Air Pollution ◽  
2010 ◽  
pp. 277-296
Author(s):  
Rajasekhar Balasubramanian ◽  
See Wei ◽  
Sathrugnan Karthikeyan

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1919 ◽  
Author(s):  
Federico Carotenuto ◽  
Lorenzo Brilli ◽  
Beniamino Gioli ◽  
Giovanni Gualtieri ◽  
Carolina Vagnoli ◽  
...  

The Arctic is an important natural laboratory that is extremely sensitive to climatic changes and its monitoring is, therefore, of great importance. Due to the environmental extremes it is often hard to deploy sensors and observations are limited to a few sparse observation points limiting the spatial and temporal coverage of the Arctic measurement. Given these constraints the possibility of deploying a rugged network of low-cost sensors remains an interesting and convenient option. The present work validates for the first time a low-cost sensor array (AIRQino) for monitoring basic meteorological parameters and atmospheric composition in the Arctic (air temperature, relative humidity, particulate matter, and CO2). AIRQino was deployed for one year in the Svalbard archipelago and its outputs compared with reference sensors. Results show good agreement with the reference meteorological parameters (air temperature (T) and relative humidity (RH)) with correlation coefficients above 0.8 and small absolute errors (≈1 °C for temperature and ≈6% for RH). Particulate matter (PM) low-cost sensors show a good linearity (r2 ≈ 0.8) and small absolute errors for both PM2.5 and PM10 (≈1 µg m−3 for PM2.5 and ≈3 µg m−3 for PM10), while overall accuracy is impacted both by the unknown composition of the local aerosol, and by high humidity conditions likely generating hygroscopic effects. CO2 exhibits a satisfying agreement with r2 around 0.70 and an absolute error of ≈23 mg m−3. Overall these results, coupled with an excellent data coverage and scarce need of maintenance make the AIRQino or similar devices integrations an interesting tool for future extended sensor networks also in the Arctic environment.


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