The monitoring of human exposures to diesel exhaust continues to be a vexing problem for specialists seeking information on the potential health effects of this ubiquitous combustion product. Exposure biomarkers have yielded a potential solution to this problem by providing a direct measure of an individual's contact with key components in the exhaust stream. Spurred by the advent of new, highly sensitive, analytical methods capable of detecting substances at very low levels, there have been numerous attempts at identifying a stable and specific biomarker. Despite these new techniques, there is currently no foolproof method for unambiguously separating diesel exhaust exposures from those arising from other combustion sources. Diesel exhaust is a highly complex mixture of solid, liquid, and gaseous components whose exact composition can be affected by many variables, including engine technology, fuel composition, operating conditions, and photochemical aging. These factors together with those related to exposure methodology, epidemiological necessity, and regulatory reform can have a decided impact on the success or failure of future research aimed at identifying a suitable biomarker of exposure. The objective of this review is to examine existing information on exposure biomarkers for diesel exhaust and to identify those factors and trends that have had an impact on the successful identification of metrics for both occupational and community settings. The information will provide interested parties with a template for more thoroughly understanding those factors affecting diesel exhaust emissions and for identifying those substances and research approaches holding the greatest promise for future success.
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http://dx.doi.org/10.1080/10643389.2013.790748 | DOI Listing |
Environ Sci Pollut Res Int
January 2025
Research Centre for Energy, Environment and Technology (CIEMAT), Avda. Complutense, 40, 28040, Madrid, Spain.
As tailpipe emissions have decreased, there is a growing focus on the relative contribution of non-exhaust sources of vehicle emissions. Addressing these emissions is key to better evaluating and reducing vehicles' impact on air quality and public health. Tailoring solutions for different non-exhaust sources, including brake emissions, is essential for achieving sustainable mobility.
View Article and Find Full Text PDFInorg Chem
January 2025
State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Jiangsu Key Laboratory of Vehicle Emissions Control, Center of Modern Analysis, Key Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
The emission of NH has been reported to pose a serious threat to both human health and the environment. To efficiently eliminate NH, catalysts for the selective catalytic oxidation of NH (NH-SCO) have been intensively studied. FeO-based catalysts were found to exhibit superior NH oxidation activity; however, the low N selectivity made it less attractive in practical applications.
View Article and Find Full Text PDFPLoS One
January 2025
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.
View Article and Find Full Text PDFUrban Inform
January 2025
IVL Swedish Environmental Research Institute LTD., PO Box 530 21, SE-400 14 Gothenburg, Sweden.
In response to the demand for advanced tools in environmental monitoring and policy formulation, this work leverages modern software and big data technologies to enhance novel road transport emissions research. This is achieved by making data and analysis tools more widely available and customisable so users can tailor outputs to their requirements. Through the novel combination of vehicle emissions remote sensing and cloud computing methodologies, these developments aim to reduce the barriers to understanding real-driving emissions (RDE) across urban environments.
View Article and Find Full Text PDFEnviron Pollut
January 2025
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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