Characterization of Bioaerosols and Particulate Matter (PM) in Residential Settings of Asthmatic Patients of Lahore, Pakistan

Syed Shahid  Imran Bukhari; Zulfiqar Ali

doi:10.18502/ijaai.v20i2.6048

Syed Shahid Imran Bukhari Department of Zoology, Environmental Health and Wildlife Lab, University of the Punjab, Lahore, Pakistan
Zulfiqar Ali Department of Zoology, Environmental Health and Wildlife Lab, University of the Punjab, Lahore, Pakistan

DOI: https://doi.org/10.18502/ijaai.v20i2.6048

Keywords: Asthma; Bacteria; Fungi; Particulate matter

Abstract

Airborne bioaerosols and particulate matter (PM) have been associated with asthma occurrence. Due to the adverse indoor environment and the absence of any baseline data for asthmatic patients of Pakistan, this study was aimed to establish a correlation between microflora and PM of residential microenvironments of asthmatic patients. This pilot study was conducted in different residential settings of asthmatic patients registered in the Jinnah hospital, Lahore. The characterization of PM (PM01, PM2.5, PM10) and bioaerosols were carried out in the houses of fifty patients that were categorized into four groups; A-large (418.06 m2 ), B-medium (211 m2 ), C-medium (104 m2 ), and D-small (62.71 m2 ) houses. The PM concentrations were monitored; using the DustTrack8533 aerosol monitor and the bioaerosols were characterized up to the Genus; using the culture-based method and biochemical testing. The bioaerosols were sampled; using the expose plate method and were analyzed using morphological features and biochemical tests. Eleven types of fungi and seven bacterial types were found in the air samples. The tendency of asthma occurrence is linked with higher Alternaria spp and Aspergillus spp. The mean indoor readings of PM01, PM2.5, PM10 were highest in D-category (331.75, 342.5, and 502.33 respectively). Moreover, the highest bacterial 9618 CFU/m3 ) and fungal levels (3092 CFU/m3 ) were also seen in D-category. According to two-way ANOVA, bacterial concentration was significantly different among the four groups while fungi concentration was non-significant (p<0.05). Pearson correlation showed a significant positive correlation among bioaerosol counts, relative humidity, and temperature. Moreover, a positive significant correlation was also observed among PM, bioaerosols, and temperature (p<0.01). The multiple regression analysis confirms temperature as a significant predictor of bioaerosols and bacterial and fungal concentrations were observed to be a significant predictor for PM. Hence monitoring the PM levels could help in maintaining the indoor microenvironment for sensitive asthmatic patients.