Urban air pollution

Air quality is a pressing concern in the modern industrialised era. As urban populations continue to grow, there is an increased demand for infrastructure, housing, and transportation. This often results in the expansion of cities, construction activities, and increased energy consumption, all of which contribute to air pollution through emissions from construction equipment, energy production, and increased traffic. Apart from the six criteria pollutants, there is another significant category of airborne contaminants that are often overlooked but have a profound impact on the health of living beings: bioaerosols. The current COVID-19 pandemic serves as a stark example of the havoc that these bioaerosols can wreak.

Air quality in Pakistan is already severely compromised, with major cities consistently ranking among the worst in terms of air quality in 2022. This situation, coupled with the annual smog episodes, particularly in the Central Punjab region, poses dire consequences for humans. Furthermore, the effects on livestock cannot be ignored, as inhalation is an involuntary process for all living beings. Recent research has established a relationship between poor air quality and respiratory diseases, leading to increased mortality rates in populations.

While human exposure to air pollution is closely monitored and studied, there are limited studies on air quality on livestock farms. Agriculture, especially livestock farming, is the largest sector of Pakistan’s economy. While ongoing efforts aim to improve this sector, there is an urgent need to understand the environmental factors that affect the well-being of animals. Air quality in animal husbandry facilities impacts the health of both animals and workers due to inhalable particles and harmful compounds present in these farms.

The current study was conducted to assess the air quality of ten livestock farms in the districts of Kasur and Lahore, with the aim of identifying factors contributing to a healthier environment for these valuable animals. The farms were selected and categorised based on their history of respiratory disease outbreaks. Particulate matter (PM10 and PM2.5), bioaerosols, CO2 levels, temperature, and relative humidity were measured at each farm during both the summer and winter seasons. Particulate matter was monitored using a real-time, cost-effective particulate counter, the Gradko DC-1700, which simultaneously counts PM2.5 and PM10. Additionally, a volumetric sampler fitted with filter paper was used to measure trace metals and total suspended particle matter (TSPM), as well as the elemental composition of suspended dust. Carbon dioxide, temperature, and relative humidity were measured using real-time sensors. While a wide range of microorganisms is associated with infectious respiratory diseases, bacteria are of paramount importance. Therefore, bacterial colony-forming units were also documented. The results revealed elevated levels of fine particulate matter in the selected farms, with higher concentrations in farms with a history of disease outbreaks. Seasonal influences were also evident.

In the second experiment, we aimed to investigate the common microflora present in the respiratory tracts of livestock animals on farms with a history of bovine respiratory disease (BRD). Nasal swab samples were collected from 40 suspected cattle and 10 healthy animals (control) from 10 livestock farms. DNA was extracted using the direct DNA extraction method. Among bacteria, the most prevalent respiratory pathogens, including Mycobacterium bovis, Staphylococcus aureus, Pasteurella multocida, Mannheimia hemolytica, Histophilus somni, and Mycoplasma capricolum, were successfully identified through Sanger sequencing. Given the economic and production implications of this disease, this study aimed to identify the major prevalent respiratory disease-causing bacteria through molecular methods, which are considerably faster than conventional culturing methods.

In the third experiment, we successfully developed a multiplex PCR assay for the simultaneous and rapid identification of three selected species isolated in the previous experiment. Overall, this study provides a rapid, reliable, and straightforward tool for the simultaneous detection of multiple respiratory bacterial pathogens. This technology holds significant implications for the agricultural industry, as it can aid in preventing and controlling the spread of these pathogens, ultimately leading to improved livestock health.