Air, Volume 2, Issue 2 (June 2024) – 4 articles

Wildfires pose a direct threat to the property, life, and well-being of the population of Montana, USA, and indirectly to their health through hazardous smoke and gases emitted into the atmosphere. Studies have shown that elevated levels of particulate matter cause impacts to human health ranging from early death, to neurological and immune diseases, to cancer. Although there is currently a network of ground-based air quality sensors (n = 20) in Montana, the geographically sparse network has large gaps and lacks the ability to make accurate predictions for air quality in many areas of the state. Using the random forest method, a predictive model was developed in the Google Earth Engine (GEE) environment to estimate PM2.5 concentrations using satellite-based aerosol optical depth (AOD), dewpoint temperature (DPT), relative humidity (RH), wind speed (WIND), wind direction (WDIR), pressure (PRES), and planetary-boundary-layer height (PBLH). The validity of the prediction model was evaluated using 10-fold cross validation with a R² value of 0.572 and RMSE of 9.98 µg/m³. The corresponding R² and RMSE values for ‘held-out data’ were 0.487 and 10.53 µg/m³. Using the validated prediction model, daily PM2.5 concentration maps (1 km-resolution) were estimated from 2012 to 2023 for the state of Montana. These concentration maps are accessible via an application developed using GEE. The product provides valuable insights into spatiotemporal trends of PM2.5 concentrations, which will be useful for communities to take appropriate mitigation strategies and minimize hazardous PM2.5 exposure. Full article

The increase in industrial activities has raised concerns regarding air quality in urban areas within Malawi. To assess the source apportionment of air quality parameters (AQPs) and noise levels, concentrations of AQPs (CO, TSP, PM _2.5, PM₁₀) and noise levels were monitored at 15 sites in Makata, Limbe, Maselema, Chirimba, and Maone during dry and wet seasons, respectively. Active mobile multi-gas monitors and a Dylos DC1100 PRO Laser Particle Counter (2018 model) were used to monitor AQPs, while Integrated Sound Level Meters were used to measure noise levels. Monitoring and analysis were guided by the World Health Organization (WHO) and Malawi Standards (MS). A Positive Matrix Factorization (PMF) model was used to determine source apportionment of AQPs, and matrix trajectories analysed air mass movement. In the wet season, the average concentration values of CO, TSP, PM₁₀, and PM_2.5 were 0.49 ± 0.65 mg/m³, 85.03 ± 62.18 µg/m³, 14.65 ± 8.13 µg/m³, and 11.52 ± 7.19 µg/m³, respectively. Dry season average concentration values increased to 1.31 ± 0.81 mg/m³, 99.86± 30.06 µg/m³, 24.35 ± 9.53 µg/m³, and 18.28 ± 7.14 µg/m³. Noise levels remained below public MS and WHO standards (85 dB). Positive correlations between AQPs and noise levels were observed, strengthening from weak in the dry season to moderately strong in the wet season. PMF analysis identified key factors influencing AQPs accumulation, emphasizing the need for periodic sampling to monitor seasonal pollution trends, considering potential impacts on public health and environmental sustainability. Further studies should look at factors affecting the dynamics of PMF in Blantyre City. Full article

Sidewalk cleaning operations are essential to maintaining a clean and safe urban environment. Despite their vital role, these activities, particularly the blowing of road dust, can lead to the resuspension of road dust and associated pollutants, which poses risks to human health and the environment. While the role of blowers on particulate matter resuspension has been investigated, there is limited information on emitted bioaerosols. This study aimed to compare the occupational exposure of operators and passersby during sidewalk cleaning using two manual methods—blowing and jet washing—in two distinct urban environments. The study focused on metal road traffic tracers (copper (Cu), zinc (Zn), manganese (Mn), cadmium (Cd), and lead (Pb)) and cultivable/non-cultivable microorganisms. We showed that blowing resuspends inhalable particles containing metals (Cu, Zn, and Mn, but not Cd or Pb) and bioaerosols (fungi and Gram-negative bacteria) throughout the year. This represents an important source of exposure for the blower operators and poses a potential long-term respiratory health risk for them. Operators working in cabs are shielded from such exposure, but passersby, especially vulnerable populations, may be at risk. While jet washing reduces operator exposure to Gram-negative bacteria in comparison to blowing, it does not mitigate fungal exposure, particularly in vegetated sites. These findings underscore the necessity for the implementation of effective protective measures and the development of alternative cleaning methods to mitigate exposure risks. Full article

The authors present an analysis of the correlation between demographic and territorial indicators and greenhouse gas (GHG) emissions, emphasizing the spatial aspect using statistical methods. Particular attention is given to the application of correlation techniques, considering the spatial correlation between the involved variables, such as demographic, territorial, and environmental indicators. The demographic data include factors such as population, demographic distribution, and population density; territorial indicators include land use, particularly settlements, and road soil occupancy. The aims of this study are as follows: (1) to identify the direct relationships between these variables and emissions; (2) to evaluate the spatial dependence between geographical entities; and (3) to contribute to generating a deeper understanding of the phenomena under examination. Using spatial autocorrelation analysis, our study aims to provide a comprehensive framework of the territorial dynamics that influence the quantity of emissions. This approach can contribute to formulating more targeted environmental policies, considering the spatial nuances that characterize the relationships between demographics, territory, and GHGs. The outcome of this research is the identification of a direct formula to obtain greenhouse gas emissions from data about land use starting from the case study of Pavia Province in Italy. In the paper, the authors highlight different methodologies to compare land use and GHG emissions to select the most feasible correlation formula. The proposed procedure has been tested and can be used to promote awareness of the spatial dimension in the analysis of complex interactions between anthropogenic factors and environmental impacts. Full article