Human personal air pollution clouds in a naturally ventilated office during the COVID-19 pandemic

Personal cloud, termed as the difference in air pollutant concentrations between breathing zone and room sites, represents the bias in approximating personal inhalation exposure that is linked to accuracy of health risk assessment. This study performed a two-week field experiment in a naturally ventilated office during the COVID-19 pandemic to assess occupants’ exposure to common air pollutants and to determine factors contributing to the personal cloud effect. During occupied periods, indoor average concentrations of endotoxin (0.09 EU/m3), TVOC (231 μg/m3), CO2 (630 ppm), and PM10 (14 μg/m3) were below the recommended limits, except for formaldehyde (58 μg/m3). Personal exposure concentrations, however, were significantly different from, and mostly higher than, concentrations measured at room stationary sampling sites. Although three participants shared the same office, their personal air pollution clouds were mutually distinct. The mean personal cloud magnitude ranged within 0–0.05 EU/m3, 35–192 μg/m3, 32–120 ppm, and 4–9 μg/m3 for endotoxin, TVOC, CO2, and PM10, respectively, and was independent from room concentrations. The use of hand sanitizer was strongly associated with an elevated personal cloud of endotoxin and alcohol-based VOCs. Reduced occupancy density in the office resulted in more pronounced personal CO2 clouds. The representativeness of room stationary sampling for capturing dynamic personal exposures was as low as 28% and 5% for CO2 and PM10, respectively. The findings of our study highlight the necessity of considering the personal cloud effect when assessing personal exposure in offices

On distinguishing the natural and human-induced sources of airborne pathogenic viable bioaerosols: characteristic assessment using advanced molecular analysis

Ambient air consists of bioaerosols that constitute many microbes from biosphere due to natural and anthropogenic activities. Size-dependent ambient measurements of bioaerosols at two seminatural and three anthropogenic coastal sites in southern tropical India were taken during the summer 2017. All the five sites considered in this study considerably contributed to the bioaerosol burden with larger contribution from the dumping yard site followed by the marshland site, wastewater treatment plant, composting site, and Indian Institute of Technology Madras. The colony-forming units concentration for all the sites ranged from 17 to 2750 m−3 for bacteria and 42–2673 m−3 for fungi. Firmicutes and Actinomycetes were the dominant phyla observed in 698 bacterial OTUs obtained, and Ascomycota and Zygomycota were the dominant phyla observed in 159 fungal OTUs obtained in the study. Further, the study revealed the presence of pathogenic and ice-nucleating bacteria and fungi in the bioaerosols that can largely affect the well-being of the human population and vegetation in this region. Moreover, the statistical analysis revealed high bacterial abundance and diversity at the grit chamber of wastewater treatment plant and high fungal abundance and diversity at the dumping yard. Further, principal coordinate analysis of the sites studied inferred that the marshland, wastewater treatment plant, and the dumping yard sites shared similar microbial community composition indicating the existence of similar source materials and activities at the sites. Further, this study evidently brings out the fact that urban locations may play an important role in anthropogenic contribution of both pathogenic and ice-nucleating microorganisms. © 2020, Springer Nature Switzerland AG

Comparison of two methods for bioaerosol sampling and characterization in a low-biomass chamber environment

Bioaerosols are emitted from various sources into the indoor environment and can positively and negatively impact human health. Humans are the major source of bioaerosol emissions indoors, specifically for bacteria. However, efficient sampling to guarantee successful downstream analyses can be challenging due to the relatively low bioaerosol concentrations in many indoor spaces and variable susceptibility of bioaerosols to sampling stress. Establishing standard procedures for collecting bacteria in low biomass indoor environments can help advance the field. We compared the performance of two approaches (sampling with a personal environmental monitor (PEM) and a two-stage dry cyclone sampler) to capture the bacterial emission from human participants in a controlled chamber environment. The comparison was based on quantifying the DNA yield and characterizing the bacterial community diversity by metabarcoding of the 16S rRNA gene. We found notable differences in the performance of the samplers. The cyclone sampler collected significantly more DNA and 16S rRNA gene copies including Gram-negative bacteria than the PEM sampler (p < 0.001). The bacterial barcode sequencing revealed a significant difference in the diversity of bacteria captured by the two samplers (p < 0.05), with a higher diversity of Gram-negative bacteria captured by PEM than the cyclone sampler. Overall, this study showed that both sampling approaches efficiently sampled in low biomass indoor environments, however with substantial differences in captured DNA concentrations, bacterial concentrations, and bacterial diversity. Our results indicate that bioaerosol sampler choice is highly research question dependent, and this study provides data support to make informed choices

Heating and lighting: understanding overlooked energy-consumption activities in the Indian residential sector

Understanding the climate impact of residential emissions starts with determining the fuel consumption of various household activities. While cooking emissions have been widely studied, non-cooking energy-consumption activities in the residential sector such as heating and lighting, have been overlooked owing to the unavailability of data at national levels. The present study uses data from the Carbonaceous Aerosol Emissions, Source Apportionment and Climate Impacts (COALESCE) project, which consists of residential surveys over 6000 households across 49 districts of India, to understand the energy consumed by non-cooking residential activities. Regression models are developed to estimate information in non-surveyed districts using demographic, housing, and meteorological data as predictors. Energy demand is further quantified and distributed nationally at a 4 × 4 km resolution. Results show that the annual energy consumption from non-cooking activities is 1106 [201] PJ, which is equal to one-fourth of the cooking energy demand. Freely available biomass is widely used to heat water on traditional stoves, even in the warmer regions of western and southern India across all seasons. Space heating (51%) and water heating (42%) dominate non-cooking energy consumption. In comparison, nighttime heating for security personnel (5%), partly-residential personal heating by guards, dominant in urban centers and kerosene lighting (2%) utilize minimal energy. Biomass fuels account for over 90% of the non-cooking consumption, while charcoal and kerosene make up the rest. Half of the energy consumption occurs during winter months (DJF), while 10% of the consumption occurs during monsoon, when kerosene lighting is the highest. Firewood is the most heavily used fuel source in western India, charcoal in the northern hilly regions, agricultural residues and dung cake in the Indo-Gangetic plains, and kerosene in eastern India. The study shows that ∼20% of residential energy consumption is on account of biomass-based heating and kerosene lighting activities