Assessment of types of bacterial bio-aerosols and concentrations in the indoor air of gyms

Zavieh, Fatemeh Shahi; Mohammadi, Mohammad Javad; Vosoughi, Mehdi; Abazari, Malek; Raesee, Elham; Fazlzadeh, Mehdi; Geravandi, Sahar; Behzad, Aylar

doi:10.1007/s10653-020-00774-1

Cited by 12 publications

(10 citation statements)

References 26 publications

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“…Previous research by Zavieh et. al., used the NIOSH method 0800-0999 to evaluate the bacterial bio-aerosols in the indoor air concentration of gyms (Zavieh et al, 2021). In this mtehod, a Hi-flow active air-sampling pump is used to trap the air from the room through a flexible hose (minimum flow rate of 28.3 L/min).…”

Section: Methodsmentioning

confidence: 99%

Indoor Air Factors Affecting the Growth of Microorganism in an Indonesian Gas Company’s Dormitory

Nasri

Athari

Hastiti

et al. 2022

IJOSH

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Introduction: Mold may affect the Indoor Air Quality (IAQ) in workplace dormitories. This study aims to investigate indoor air factors that affect molds growth in a dormitory of an LNG Company in Indonesia. Several indoor air determinant factors, including relative humidity, general temperature, wet temperature, dry temperature, air velocity, illumination, particulate matter, and carbon dioxide concentration were assessed against the growth of microorganism colonies. Methods: This study was a cross-sectional study using a 2 (two)-stage Andersen sampler based on NIOSH 0800 Bioaerosol Sampling Method for Indoor Air Quality for viable bioaerosol sampling. Bioaerosol samples were collected from 50 indoor, corridor, and outdoor sampling points. The total colony count for bioaerosols (TCC) was then determined (CFU/m3). Ten indoor air quality parameters, i.e., relative humidity, general temperature, wet temperature, dry temperature, air velocity, illumination, particulate matter, and carbon dioxide concentration, were measured. Results: The average mold colony concentration in the dormitory rooms was higher (703.1 CFU/m3) than the maximum standard issued by the Ministry of Health of the Republic of Indonesia (< 700 CFU/m3) while the relative humidity was very high (84.4% RH on average), with a direct relation between the humidity and the mold colony concentration. A significant correlation was also identified between mold colony concentration, wet temperature, and CO2 concentration. Conclusion: Significant correlations between bioaerosols, relative humidity, wet temperature, and indoor CO2 concentration indicate insufficient ventilation and poor indoor air quality in the dormitory.

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Section: Methodsmentioning

confidence: 99%

Indoor Air Factors Affecting the Growth of Microorganism in an Indonesian Gas Company’s Dormitory

Nasri

Athari

Hastiti

et al. 2022

IJOSH

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“…Existen otros estudios que han informado una correlación significativamente positiva entre las variables ambientales de T y HR con el recuento de bacterias y hongos 16 . Esta similitud y divergencia entre nuestros resultados y los informados en la literatura científica podría deberse a que tanto la T como la HR que permiten el desarrollo los microorganismos varía entre las especies halladas en los distintos estudios 17 . Por ejemplo, las condiciones óptimas de HR para el crecimiento fúngico es > 75% 18 , condición que en este estudio se presentó en un solo día, en las salas D, E y F (Tabla 3), lo que pudo haber contribuido a que la mayoría de los recuentos de hongos obtenidos fueron bajos.…”

Section: Talaromyces Columbinusunclassified

Calidad microbiológica del aire en un Centro Comunitario de Salud Familiar de Talcahuano, Región del Biobío, Chile

Parra-Donoso

Valdebenito-Rolack

Cid-Maldonado

et al. 2021

Rev. chil. infectol.

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“…DNA metabarcoding using trnL and nrITS2 have also shown highly improved taxonomic resolution for pollen from aerobiological samples [ 18 , 19 ], even though not at a (near-)real-time temporal resolution. Still, there is a huge gap in the application of automation techniques regarding other bioaerosols, i.e., fungi [ 20 ] or bacteria [ 21 ], as well as development of such methods in indoor environments, as has been traditionally elaborated [ 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

Detecting Airborne Pollen Using an Automatic, Real-Time Monitoring System: Evidence from Two Sites

Plaza

Kolek

Leier-Wirtz

et al. 2022

IJERPH

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Airborne pollen monitoring has been an arduous task, making ecological applications and allergy management virtually disconnected from everyday practice. Over the last decade, intensive research has been conducted worldwide to automate this task and to obtain real-time measurements. The aim of this study was to evaluate such an automated biomonitoring system vs. the conventional ‘gold-standard’ Hirst-type technique, attempting to assess which may more accurately provide the genuine exposure to airborne pollen. Airborne pollen was monitored in Augsburg since 2015 with two different methods, a novel automatic Bio-Aerosol Analyser, and with the conventional 7-day recording Hirst-type volumetric trap, in two different sites. The reliability, performance, accuracy, and comparability of the BAA500 Pollen Monitor (PoMo) vs. the conventional device were investigated, by use of approximately 2.5 million particles sampled during the study period. The observations made by the automated PoMo showed an average accuracy of approximately 85%. However, it also exhibited reliability problems, with information gaps within the main pollen season of between 17 to 19 days. The PoMo automated algorithm had identification issues, mainly confusing the taxa of Populus, Salix and Tilia. Hirst-type measurements consistently exhibited lower pollen abundances (median of annual pollen integral: 2080), however, seasonal traits were more comparable, with the PoMo pollen season starting slightly later (median: 3 days), peaking later (median: 5 days) but also ending later (median: 14 days). Daily pollen concentrations reported by Hirst-type traps vs. PoMo were significantly, but not closely, correlated (r = 0.53–0.55), even after manual classification. Automatic pollen monitoring has already shown signs of efficiency and accuracy, despite its young age; here it is suggested that automatic pollen monitoring systems may be more effective in capturing a larger proportion of the airborne pollen diversity. Even though reliability issues still exist, we expect that this new generation of automated bioaerosol monitoring will eventually change the aerobiological era, as known for almost 70 years now.

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Assessment of types of bacterial bio-aerosols and concentrations in the indoor air of gyms

Cited by 12 publications

References 26 publications

Indoor Air Factors Affecting the Growth of Microorganism in an Indonesian Gas Company’s Dormitory

Indoor Air Factors Affecting the Growth of Microorganism in an Indonesian Gas Company’s Dormitory

Calidad microbiológica del aire en un Centro Comunitario de Salud Familiar de Talcahuano, Región del Biobío, Chile

Detecting Airborne Pollen Using an Automatic, Real-Time Monitoring System: Evidence from Two Sites

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