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Air, Volume 2, Issue 2 (June 2024) – 5 articles

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16 pages, 910 KiB  
Article
Quantifying the Environmental Impact of Private and Commercial Pilot License Training in Canada
by Syed A. Q. Rizvi, Suzanne Kearns and Shi Cao
Air 2024, 2(2), 162-177; https://doi.org/10.3390/air2020010 - 10 May 2024
Viewed by 261
Abstract
As the global aviation sector expands to accommodate increasing air travel demand, the subsequent rise in flights exacerbates carbon dioxide (CO2) emissions, challenging the sector’s environmental sustainability. Targeting net-zero emissions by 2050, international aviation agencies are stressing the imperative of reducing [...] Read more.
As the global aviation sector expands to accommodate increasing air travel demand, the subsequent rise in flights exacerbates carbon dioxide (CO2) emissions, challenging the sector’s environmental sustainability. Targeting net-zero emissions by 2050, international aviation agencies are stressing the imperative of reducing emissions directly at their source. While the literature provides abundant estimates of aviation emissions from airline flights, there has been a lack of work aimed at quantifying CO2 emissions specific to the general aviation sector. This study investigates CO2 emissions attributed to the pilot training sub-sector within Canada’s general aviation sector. It specifically examines the initial phase of pilot training, known as ab initio training, extending through to the attainment of a commercial pilot license. Utilizing a mathematical framework alongside assumptions, combined with data on license issuances over a 23-year period, it estimated that each hour of flight training emits about 70.4 kg of CO2, varying between 44.9 kg and 94.9 kg per hour. Annual CO2 emissions from Canada’s ab initio pilot training are estimated at approximately 30,000 tons, with a possible range of 19,000 to 40,000 tons. The study also explores mitigation opportunities, such as flight simulation training devices and electric aircraft. Though focusing on Canada’s ab initio pilot training, the findings have international relevance. Full article
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20 pages, 4549 KiB  
Article
Montana Statewide Google Earth Engine-Based Wildfire Hazardous Particulate (PM2.5) Concentration Estimation
by Aspen Morgan, Jeremy Crowley and Raja M. Nagisetty
Air 2024, 2(2), 142-161; https://doi.org/10.3390/air2020009 - 2 May 2024
Viewed by 599
Abstract
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 [...] Read more.
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
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20 pages, 3950 KiB  
Article
Source Apportionment of Air Quality Parameters and Noise Levels in the Industrial Zones of Blantyre City
by Constance Chifuniro Utsale, Chikumbusko Chiziwa Kaonga, Fabiano Gibson Daud Thulu, Ishmael Bobby Mphangwe Kosamu, Fred Thomson, Upile Chitete-Mawenda and Hiroshi Sakugawa
Air 2024, 2(2), 122-141; https://doi.org/10.3390/air2020008 - 1 May 2024
Viewed by 607
Abstract
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 [...] Read more.
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 PM2.5 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
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13 pages, 4030 KiB  
Article
Assessing Worker and Pedestrian Exposure to Pollutant Emissions from Sidewalk Cleaning: A Comparative Analysis of Blowing and Jet Washing Techniques
by Hélène Niculita-Hirzel, Maria Serena Merli and Kyle Baikie
Air 2024, 2(2), 109-121; https://doi.org/10.3390/air2020007 - 28 Apr 2024
Viewed by 313
Abstract
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 [...] Read more.
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
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23 pages, 7084 KiB  
Article
Correlation Methodologies between Land Use and Greenhouse Gas emissions: The Case of Pavia Province (Italy)
by Roberto De Lotto, Riccardo Bellati and Marilisa Moretti
Air 2024, 2(2), 86-108; https://doi.org/10.3390/air2020006 - 27 Apr 2024
Viewed by 585
Abstract
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, [...] Read more.
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
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