Biomonitoring of traffic originated PAHs in the air

This article sets out the results of air quality biomonitoring along a transect bordering on the A32 Turin–Bardonecchia motorway (Italy). The results were obtained using aeroponic sampling units, an innovation insofar as the plants acting as monitor live and grow in these units above ground, assuring that atmospheric pollutants are absorbed only through the leaves. The accumulation of 15 polynuclear aromatic hydrocarbons (PAHs) on the leaves of Brassica oleracea var. Acephala, used as biosampler, was determined on samples taken in the months of February, July and October 2002, in each case after two months' exposure. The results highlight: (i) the influence of the seasons on the accumulation of pollutants, (ii) that phenanthrene, fluoranthene, pyrene and chrysene generally account for more than 80% of total PAHs, (iii) that the data may be considered representative of both volatile and non-volatile compounds. Comparison with other sampling methods are supplied and discussed.     

Phases of scaling and cross-correlation behavior in traffic

While many microscopic models of traffic flow describe transitions between different traffic phases, such transitions are difficult to quantify in measured traffic data. Here we study long-term traffic recordings consisting of ≈2900$\approx 2900$ days of flow, density, and velocity time series with minute resolution from a Spanish motorway. We calculate fluctuations, cross-correlations, and long-term persistence properties of these quantities in the flow–density diagram. This leads to a data-driven definition of (local) traffic states based on the dynamical properties of the data, which differ from those given in standard guidelines. We find that detrending techniques must be used for persistence analysis because of non-stationary daily and weekly traffic flow patterns. We compare our results for the measured data with analysis results for a microscopic traffic model, finding good agreement in most quantities. However, the simulations cannot easily reproduce the congested traffic states observed in the data. We show how fluctuations and cross-correlations in traffic data may be used for prediction, i.e., as indications of increasing or decreasing velocities.     

Motorway noise modelling based on perpendicular propagation analysis of traffic noise

A model for motorway traffic noise has been obtained from measurements along the the Bangkok-Chonburi motorway. The model’s parameters include traffic volume and combination, the average spot speed of each type of vehicle and the physical conditions of the motorway in terms of right-of-way width, number of lanes, lane width, shoulder width, and median width for both of the main carriageways and frontage roads. The noise level that is generated by each type of vehicle has been analyzed according to the propagation in the direction perpendicular to the center line of motorway’s carriageway. The total traffic noise is then analyzed from traffic volume of all vehicle types on both sides of carriageways and frontage roads. The basic noise levels used in the motorway traffic noise model are modified according to the effective ground effect along the propagation path. The final result of this study is that a motorway traffic noise model based on the perpendicular propagation analysis technique performs well in a statistical goodness-of-fit test against the field data, and therefore, can be used effectively in traffic noise prediction for related or similar motorway projects.