Side road measurements of fine particle (FP) concentrations were performed in two narrow and deep street canyons in the historic center of Naples using point sampling technology (PS). The FP concentration in the range of 20–103 nm was measured using a condensation particle number counter (CPC) with a 1 Hz frequency. Video recording was used to detect passing vehicles classified into three categories: motorcycles, cars, and light-duty vehicles. The two monitored streets were adjacent, with similar geometrics and orientation but different high- and low-traffic levels. FP concentration time series data were processed to identify concentration peaks generated by the exhausts of passing vehicles. A sensitivity analysis study was carried out to determine how data processing parameters could affect high-emitting vehicle (high emitter) identification. Once the optimum parameters were defined, the contribution of high emitters exhaust emissions to local air quality was assessed. The results showed that PS technology offered viable opportunities for application in narrow street canyons where deploying more common crossroad and top-down monitoring can be troublesome. However, some issues remain to be solved to accurately identify high emitterss in high-traffic cases. PS technology can be useful for developing effective air quality management policies in historical centres.
Development of point sampling technology for identifying high-emitting vehicles in narrow and deep street canyons / Murena, F.; Toscano, D.. - In: ATMOSPHERIC POLLUTION RESEARCH. - ISSN 1309-1042. - 14:10(2023), p. 101876. [10.1016/j.apr.2023.101876]
Development of point sampling technology for identifying high-emitting vehicles in narrow and deep street canyons
Murena F.;Toscano D.
2023
Abstract
Side road measurements of fine particle (FP) concentrations were performed in two narrow and deep street canyons in the historic center of Naples using point sampling technology (PS). The FP concentration in the range of 20–103 nm was measured using a condensation particle number counter (CPC) with a 1 Hz frequency. Video recording was used to detect passing vehicles classified into three categories: motorcycles, cars, and light-duty vehicles. The two monitored streets were adjacent, with similar geometrics and orientation but different high- and low-traffic levels. FP concentration time series data were processed to identify concentration peaks generated by the exhausts of passing vehicles. A sensitivity analysis study was carried out to determine how data processing parameters could affect high-emitting vehicle (high emitter) identification. Once the optimum parameters were defined, the contribution of high emitters exhaust emissions to local air quality was assessed. The results showed that PS technology offered viable opportunities for application in narrow street canyons where deploying more common crossroad and top-down monitoring can be troublesome. However, some issues remain to be solved to accurately identify high emitterss in high-traffic cases. PS technology can be useful for developing effective air quality management policies in historical centres.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.