Around three billion people, largely in low and middle income countries, rely on biomass fuels for their household energy needs. The combustion of these fuels generates a range of hazardous indoor air pollutants and is an important cause of morbidity and mortality in developing countries. Worldwide, it is responsible for four million deaths. A reduction in indoor smoke can have a significant impact on lives and can help achieve many of the Millennium Developments Goals.
Abstract Bioaerosol emissions during toilet flushing are an often‐overlooked source of potential health risks in shared public facilities. This study systematically investigated the emission characteristics of Staphylococcus aureus and Escherichia coli bioaerosols in washrooms with squat and bidet toilets under varying flushing conditions and ventilation scenarios. Using Monte Carlo simulation–based quantitative microbial risk assessment and sensitivity analysis, the study estimated the disease burden and identified key factors influencing risk. The results showed that squat toilets generated 1.7–2.6 times higher concentrations of S. aureus bioaerosols and 1.2–1.4 times higher concentrations of E. coli bioaerosols compared to bidet toilets. After the first flush, bioaerosol concentrations were 1.3–1.8 times ( S. aureus ) and 1.2–1.4 times ( E. coli ) lower than those observed after the second flush. The second flush released a higher proportion of fine bioaerosol particles (<4.7 µm), increasing inhalation risks. The disease health risk burden was consistently one order of magnitude lower after the first flush than the second one. Ventilation with a turned‐on exhaust fan further reduced the risk by one order of magnitude. Sensitivity analysis identified exposure concentration as the most influential parameter, contributing up to 50% of the overall risk. This study highlights the importance of optimizing toilet design and ventilation systems to mitigate bioaerosol emissions and associated health risks. It provides actionable insights for improving public washroom hygiene and minimizing bioaerosol exposure.
Air pollution is a major concern in Pakistan. Levels of particulate matter (PM2.5) in educational built environments, have not yet been studied comprehensively in Pakistan. This study was conducted to assess relationships between indoor and outdoor particulate matter in classrooms of the University of the Punjab, Lahore, using a DUSTTRAK Aerosol Monitor
(TSI Model 8520). Sampling for PM2.5 concentrations was carried out simultaneously outdoors and indoors in different classrooms on the campus. According to the level of occupancy three classrooms were selected i.e. Classroom I: low occupancy, Classroom II: medium occupancy and Classroom III: high occupancy. Simultaneous outdoor measurements
were carried out at rooftop of each classroom. A tracer method was used to measure the air change per hour in each classroom. The 24 hour average concentrations of PM2.5 in Classrooms I, II and III were observed to be 282 μg/m³, 75 μg/m³ and 673 μg/m³ whereas 24 hour average outdoor levels were 324 μg/m³, 121 μg/m³ and 998μg/m³ respectively. Results showed a significant impact of ambient air and occupancy level on PM2.5 levels inside classrooms and all observed values exceeded the WHO limits.
The Taunsa Barrage controls water flow in the River Indus for irrigation and flood control purposes. The river ecology is sensitive to climate change due to the high portion of its flow derived glacial melt. To assess the socio-economic status of the rural communities living within the Taunsa Barrage Wildlife sanctuary, a questionnaire was developed based on the perception of local communities about their resilience capacity and climate change. Temperature and rainfall data over the period 1951 – 2010 were analysed and used as an indicator of climate change. 85 of the respondents (n =100) reported that there had been an increase extreme climatic events over the past 60 years. These communities have proved to be resilient (94% n = 100) to it by changing occupations and lifestyles. However at the same time they have increased the pressure on natural resource use and this is causing a serious problem in the management of the protected area.
To understand the dynamics of particulate matter inside train coaches and public cars, an investigation was carried out during 2004-2006. For air-conditioned rail coaches, during peak journey times, the mean concentrations of PM10, PM2.5 and PM1 were 44 microg m(-3), 14 microg m(-3) and 12 microg m(-3), respectively. The levels fell by more than half (21 microg m(-3), 6 microg m(-3), and 4 microg m(-3)) for the same size fractions, on the same route, during the off-peak journeys. On the other hand, in non-air-conditioned coaches, the PM10 concentrations of up to 95 microg m(-3) were observed during both peak and off-peak journeys. However the concentrations of PM2.5 and PM1 were 30 microg m(-3) and 12 microg m(-3) in peak journeys in comparison to 14 microg m(-3) and 6 microg m(-3) during off-peak journeys. Over a period of four months the concentrations of PM10, PM2.5 and PM1 in car journeys were generally similar during both morning and evening journeys with average values of 21 microg m(-3) for PM10, 9 microg m(-3) for PM2.5 and 6 microg m(-3) for PM1. However during October the average concentration of PM10 was 31 microg m(-3). An analysis of nearby fixed monitoring sites for both PM10 and PM2.5 revealed an episode of high particulate pollution over southern England during one week of October. There was no statistically significant difference between particulate matter levels for morning and evening car journeys. A statistically significant correlation was found between morning and evening PM10 (0.45), PM2.5 (0.39) and PM1 (0.46). In train journeys, a statistically significant difference was observed for peak and off-peak levels of PM10, PM2.5 and PM1 in air-conditioned coaches. On the other hand, in non air-conditioned coaches a significant difference was documented only for PM2.5 and PM1.
Bioaerosol emissions from waste management operations and facilities are a potential hazard for human and environmental health.This study was aimed to assess the concentration as well as identification of bacteria and fungi, their seasonal variation and association with meteorological measurements at solid waste management (SWM) sites.A total of 16 air samples were collected between October 2017 to March 2018 in wet and dry seasons by using Portable Dust Sampler.Samples were analyzed both by culture and molecular methods.The total culturable bacterial and fungal population ranged from 4.7 × 10 4 to 7.4 × 10 5 CFU/m 3 and 0.2 × 10 2 to 2.8 × 10 3 CFU/m 3 respectively in wet season and from 7.5 × 10 4 to 6.8 × 10 5 CFU/m 3 and 0.1 × 10 2 to 1.6 × 10 3 CFU/m 3 in dry season.Isolated bacterial and fungal strains were processed for molecular identification by using 16S and 18S rRNA.The sequenced bacterial and fungal species were Bacillus (B.cereus, B. subtilis, B.
Rapid population growth and urbanization process have led to increasing demand for wastewater treatment capacity resulting in a non-negligible increase of wastewater treatment plants (WWTPs) in several cities around the world. Bioaerosol emissions from WWTPs may pose adverse health risks to the sewage workers and nearby residents, which raises increasing public health concerns. However, there are still significant knowledge gaps on the interplay between process-based bioaerosol characteristics and exposures and the quantification of health risk which limit our ability to design effective risk assessment and management strategies. This review provides a critical overview of the existing knowledge of bioaerosol emissions from WWTPs including their nature, magnitude and size distribution, and highlights the shortcoming associated with existing sampling and analysis methods. The recent advancements made for rapid detection of bioaerosols are then discussed, especially the emerging real time detection methods to highlight the directions for future research needs to advance the knowledge on bioaerosol emissions from WWTPs.
'/%3e%3cpath fill='%23fff' d='m8.751-17.959 10.11 11.373L3.997-9.844l13.94-6.1-7.692 13.129z'/%3e%3c/svg%3e)
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)