Background: Diesel exhaust exposure may cause acute irritant-induced asthma and potentiate allergen-induced asthma. There are no previous reports of occupational asthma due to diesel exhaust.
Aims: To describe occupational asthma with latency in workers exposed to diesel exhaust in bus garages.
Methods: The Shield database of occupational asthma notifications in the West Midlands, UK, was searched between 1990 and 2006 for workers where diesel exhaust exposure was thought to be the cause of the occupational asthma. Those without other confounding exposures whose occupational asthma was validated by serial peak expiratory flow (PEF) analysis using Oasys software were included.
Results: Fifteen workers were identified with occupational asthma attributed to diesel exhaust. Three had validated new-onset asthma with latency. All worked in bus garages where diesel exhaust exposure was the only likely cause of their occupational asthma. Occupational asthma was confirmed by measures of non-specific reactivity and serial measurements of PEF with Oasys scores of 2.9, 3.73 and 4 (positive score > 2.5).
Conclusions: The known non-specific irritant effects of diesel exhaust suggest that this is an example of low-dose irritant-induced asthma and that exposures to diesel exhaust in at least some bus garages are at a sufficient level to cause this.
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http://dx.doi.org/10.1093/occmed/kqp102 | DOI Listing |
Environ Sci Pollut Res Int
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Department of Agricultural Engineering, Technical and Vocational University, Tehran, Iran.
With the growing need for sustainable transportation solutions, understanding the relationship between driving characteristic parameters, vehicle type, and their impact on emissions and fuel consumption over real driving scenarios is becoming increasingly important. In this paper, four conventional vehicles and one hybrid vehicle with different technologies were compared in four distinct routes in Tehran city. Nineteen real driving cycles were generated using widely employed K-means and PCA algorithms.
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IVL Swedish Environmental Research Institute LTD., PO Box 530 21, SE-400 14 Gothenburg, Sweden.
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Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China.
Applying real-world driving emissions (RDE) data to machine learning, this study investigated vehicular emission characteristics and reduction strategies in Tianjin and Xining, two cities at different altitudes. Significant differences in CO₂ and particulate number (PN) emissions were observed, primarily due to altitude-induced changes in air pressure, affecting air resistance and combustion efficiency. Driving conditions and emission standards were identified as key factors influencing emissions, with road grade and air pressure playing crucial roles at high altitudes.
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