18 October 2016 Real-time vehicle emissions monitoring using a compact LiDAR system and conventional instruments: first results of an experimental campaign in a suburban area in southern Italy
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Abstract
Urban air pollution causes deleterious effects on human health and the environment. To meet stringent standards imposed by the European Commission, advanced measurement methods are required. Remote sensing techniques, such as light detection and ranging (LiDAR), can be a valuable option for evaluating particulate matter (PM), emitted by vehicles in urban traffic, with high sensitivity and in shorter time intervals. Since air quality problems persist not only in large urban areas, a measuring campaign was specifically performed in a suburban area of Crotone, Italy, using both a compact LiDAR system and conventional instruments for real-time vehicle emissions monitoring along a congested road. First results reported in this paper show a strong dependence between variations of LiDAR backscattering signals and traffic-related air pollution levels. Moreover, time-resolved LiDAR data averaged in limited regions, directly above conventional monitoring stations at the border of an intersection, were found to be linearly correlated to the PM concentration levels with a correlation coefficient between 0.75 and 0.84.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Stefano Parracino, Stefano Parracino, Maria Richetta, Maria Richetta, Michela Gelfusa, Michela Gelfusa, Andrea Malizia, Andrea Malizia, Carlo Bellecci, Carlo Bellecci, Leonardo De Leo, Leonardo De Leo, Carlo Perrimezzi, Carlo Perrimezzi, Alessandro Fin, Alessandro Fin, Marco Forin, Marco Forin, Francesca Giappicucci, Francesca Giappicucci, Massimo Grion, Massimo Grion, Giuseppe Marchese, Giuseppe Marchese, Pasquale Gaudio, Pasquale Gaudio, } "Real-time vehicle emissions monitoring using a compact LiDAR system and conventional instruments: first results of an experimental campaign in a suburban area in southern Italy," Optical Engineering 55(10), 103107 (18 October 2016). https://doi.org/10.1117/1.OE.55.10.103107 . Submission:
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