Traffic Fluxes Research Articles

Quantifying vehicle restriction related PM2.5 reduction using field observations in an isolated urban basin

Vehicle (related particulate matter) emissions, including primary vehicle (related particulate matter) emissions, secondary nitrate, and road dust, have become an important source of fine particulate matter (PM2.5) in many cities across the world. The relationship between vehicle emissions and PM2.5 during vehicle restrictions has not yet been revealed using field observational data. To address this issue, a three-month field campaign on physical and chemical characteristics of PM2.5 at hourly resolution was conducted in Lanzhou, an urban basin with a semi-arid climate. The Lanzhou municipal government implemented more strict vehicle restriction measure during the latter part of field campaign period. The concentration of nitrogen oxides (NO x ) and PM2.5 decreased by 15.6% and 10.6%, respectively during the strict vehicle restriction period. The daily traffic fluxes decreased by 11.8% due to the vehicle restriction measure. The vehicle emission reduction led to a decrease of 2.43 μg·m−3 in PM2.5, including the decrease of primary vehicle emissions, secondary nitrate, and road dust. The contribution of vehicle emissions to PM2.5 decreased by 9.0% based on the results derived from a positive matrix factorization model. The sources other than vehicle emissions increased by 0.2 μg·m−3. Combining all evidence from the observations, the reduction of vehicle emissions is almost equal to the observed reduction in PM2.5. A further extrapolation that 9.0% reduction in vehicle emissions led to the observed reduction in PM2.5 (2.32 μg·m−3). This study clearly quantifies the vehicle restriction related PM2.5 reduction using field observations. The results provide scientific support for the implementation of effective vehicle emission reduction measures.

Bidirectional Vehicle-to-Vehicle Communication System Based on VLC: Outdoor Tests and Performance Analysis

Intelligent Transportation Systems (ITS) aim at integration of innovative technologies in next-generation vehicles in order to increase the safety and efficiency standards of vehicular traffic fluxes. Although many sensors are currently available in modern cars, mutual data exchange between vehicles in real-time will be crucial in future smart vehicles, but this domain, and in particular bidirectional Vehicle-to-Vehicle (V2V) through Visible Light Communications (VLC), remain relatively unexplored yet. In this paper we present a system for bidirectional data transmission between vehicles through VLC. Specifically, we implement for the first time a bidirectional VLC link using real motorcycle headlights (HL) and rear lights (RL), and we provide a characterization of transmission performances under direct sunlight conditions in an outdoor scenario for realistic distances (up to 30 m) and relative positions between two vehicles. The performance of the VLC system has been evaluated in terms of Signal-to-Noise (SNR) maps and Packet Error Rate (PER), measured in various configurations and for different baudrates (28 kBaud / 57 kBaud). Our result show that a bidirectional error-free communication is possible between two consecutive vehicles for distances up to 12 m, whilst successful transmission could be observed up to 21 m. Finally, we compare our bidirectional intensity and PER data in realistic ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">flat</i> ) configuration against the predictions of a physical model which considers non-ideal orientations of the receiver stage through a novel, simple technique that could also be exploited in different VLC implementations. A very good agreement between the experimental data set and the model is found on the whole measurements grid.

Soil tillage and machinery traffic influence soil water availability and air fluxes in sugarcane fields

Intensive soil disturbance by conventional tillage and heavy machinery traffic for planting, cultivation, and harvesting operations are the main causes of soil compaction and degradation of soil physical quality in sugarcane fields. However, the adoption of conservation soil tillage practices, such as no-till and reduced tillage associated with traffic control have been proposed as a key strategy to preserve soil physical quality, enhancing water availability and air fluxes. Nevertheless, the effects of reduced tillage associated with traffic control in sugarcane fields are still not well documented. A study was carried out to quantify soil water availability and air flux indicators in two soils with contrasting textures (named Sandy Loam and Clayey soil) under conventional and reduced tillage practices associated with and without controlled machinery traffic in central-southern Brazil. Soil physical parameters such as bulk density, total porosity, air-filled porosity, air permeability, pore continuity index, and the least limiting water range (LLWR) were measured. In both soils, there was no difference between conventional and reduced tillage in bulk density, air permeability, and LLWR. However, reduced tillage with non-traffic decreased bulk density and increased macroporosity, air-filled porosity, air permeability, pore continuity, and LLWR in Sandy Loam soil. In Clayey soil, the bulk density and LLWR did not change between tillage practices, but air permeability and pore continuity index were larger under reduced tillage with non-traffic. These results highlighted that soil disturbance by conventional tillage does not improve the water availability and air permeability during the crop cycle. However, the traffic control is essential to support the adoption of reduced tillage in sugarcane fields, preserving soil water availability and air fluxes for the subsequent ratoons. Reduced tillage and traffic control are two of the most important pillars for reducing soil compaction and promoting sustainability of sugarcane production in Brazil.

Operational Data-Driven Intelligent Modelling and Visualization System for Real-World, On-Road Vehicle Emissions—A Case Study in Hangzhou City, China

On-road vehicle emissions play a crucial role in affecting air quality and human exposure, particularly in megacities. In the absence of comprehensive traffic monitoring networks with the general lack of intelligent transportation systems (ITSs) and big-data-driven, high-performance-computing (HPC) platforms, it remains challenging to constrain on-road vehicle emissions and capture their hotspots. Here, we established an intelligent modelling and visualization system driven by ITS traffic data for real-world, on-road vehicle emissions. Based on the HPC platform (named “City Brain”) and an agile Web Geographic Information System (WebGISs), this system can map real-time (hourly), hyperfine (10~1000 m) vehicle emissions (e.g., PM2.5, NOx, CO, and HC) and associated traffic states (e.g., vehicle-specific categories and traffic fluxes) over the Xiaoshan District in Hangzhou. Our results show sharp variations in on-road vehicle emissions on small scales, which even fluctuated up to 31.2 times within adjacent road links. Frequent and widespread emission hotspots were also exposed. Over custom spatiotemporal scopes, we virtually investigated and visualized the impacts of traffic control policies on the traffic states and on-road vehicle emissions. Such results have important implications for how traffic control policies should be optimized. Integrating this system with chemical transport models and air quality measurements would bridge the technical gap between air pollutant emissions, concentrations, and human exposure.

Traffic Request Generation through a Variational Auto Encoder Approach

Traffic and transportation forecasting is a key issue in urban planning aimed to provide a greener and more sustainable environment to residents. Their privacy is a second key issue that requires synthetic travel data. A possible solution is offered by generative models. Here, a variational autoencoder architecture has been trained on a floating car dataset in order to grasp the statistical features of the traffic demand in the city of Rome. The architecture is based on multilayer dense neural networks for encoding and decoding parts. A brief analysis of parameter influence is conducted. The generated trajectories are compared with those in the dataset. The resulting reconstructed synthetic data are employed to compute the traffic fluxes and geographic distribution of parked cars. Further work directions are provided.

Hyperfine-resolution mapping of on-road vehicle emissions with comprehensive traffic monitoring and an intelligent transportation system

Abstract. Urban on-road vehicle emissions affect air quality and human health locally and globally. Given uneven sources, they typically exhibit distinct spatial heterogeneity, varying sharply over short distances (10 m–1 km). However, all-around observational constraints on the emission sources are limited in much of the world. Consequently, traditional emission inventories lack the spatial resolution that can characterize the on-road vehicle emission hotspots. Here we establish a bottom-up approach to reveal a unique pattern of urban on-road vehicle emissions at a spatial resolution 1–3 orders of magnitude higher than current emission inventories. We interconnect all-around traffic monitoring (including traffic fluxes, vehicle-specific categories, and speeds) via an intelligent transportation system (ITS) over Xiaoshan District in the Yangtze River Delta (YRD) region. This enables us to calculate single-vehicle-specific emissions over each fine-scale (10 m–1 km) road segment. Thus, the most hyperfine emission dataset of its type is achieved, and on-road emission hotspots appear. The resulting map shows that the hourly average on-road vehicle emissions of CO, NOx, HC, and PM2.5 are 74.01, 40.35, 8.13, and 1.68 kg, respectively. More importantly, widespread and persistent emission hotspots emerged. They are of significantly sharp small-scale variability, up to 8–15 times within individual hotspots, attributable to distinct traffic fluxes, road conditions, and vehicle categories. On this basis, we investigate the effectiveness of routine traffic control strategies on on-road vehicle emission mitigation. Our results have important implications for how the strategies should be designed and optimized. Integrating our traffic-monitoring-based approach with urban air quality measurements, we could address major data gaps between urban air pollutant emissions and concentrations.

Assessment of urban CO2 budget: Anthropogenic and biogenic inputs

Understanding combinations of biogenic and anthropogenic inputs, and dynamics of carbon dioxide (CO2) fluxes in the urban environment is critical to investigate feedback between carbon cycle and climate system. The main objectives of this study are to analyse the role and interactions of anthropogenic and biogenic CO2 emission sources and sinks in the total carbon cycle within city limits, determine processes controlling urban ecosystem-atmosphere gas exchange under varying environmental conditions with a high temporal and spatial resolution.The research addressing this issue was carried out in Wroclaw, the fourth largest city in Poland, throughout the year from July 2017 to August 2018. Chamber measurements of surface-atmosphere CO2 and CO2 net fluxes across various types of land cover (grassland, city park and arable land) provided the basis for assessing biogenic component of the urban C budget. In particular, the approach applied Picarro CRDS (cavity ring-down spectroscopy) technique with model G2201-I. Anthropogenic C fluxes were reported based on local statistical datasets and existing emission inventories, as well as the Low Emission Economy Plan from the Wroclaw urban area.The findings showed that biogenic fluxes, over the course of one year, accounted for about 16.3% (RESP = 0.68 Mton CO2·yr−1) of the total city carbon emissions for Wroclaw, being entirely compensated by local vegetation C uptake (GEE = −0.89 Mt. CO2·yr−1). Compared to fluxes given by the previously reported emission inventory, the net biogenic CO2 sink (NEE) of 0.201 Mt. CO2·yr−1 was substantially greater, which indicates that the biosphere in Wroclaw is a net biogenic C sink. The average annual C budget in Wroclaw, obtained from the investigation of sectoral emission trends including those related to energy, road traffic, industrial processes, and other fluxes (human respiration), reaches about 3.87 kg C·m−2·yr−1.

Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

Switching to electric vehicles can lead to significant reductions of PM2.5 and NO2 across China

Towards the coupling of a chemical transport model with a micro-scale Lagrangian modelling system for evaluation of urban NOx levels in a European hotspot

A multi-scale modelling system was developed to provide hourly NOx concentration fields at a building-resolving scale in the urban area of Modena, a city in the middle of the Po Valley (Italy), one of the most polluted areas in Europe. The WRF-Chem model was applied over three nested domains and employed with the aim of reproducing local background concentrations, taking into account meteorological and chemical transformation at the regional scale with nested resolutions of 15 km, 3 km and 1 km. Conversely, the PMSS modelling system was applied to simulate 3D air pollutant dispersion, due to traffic emissions, with a very high-resolution (4 m) on a 6 km × 6 km domain covering the city of Modena.The methodology employed to account for anthropogenic emissions relies on two different strategies. Traffic emissions were based on a bottom-up approach using emission factors suggested by the European Environmental Agency with traffic fluxes estimated by the PTV VISUM model in the urban area of Modena, combined with direct traffic flow measurements performed between October 28 and November 8, 2016 which was used for the hourly vehicle modulation. Other anthropogenic emissions were taken from the TNO-MACC III inventory at the scales resolved by the WRF-Chem model. Simulations were performed for the same period whereby the traffic measurement campaign was carried out.2 m temperature and 10 m wind speed were captured quite well by the WRF-Chem model with statistical metrics in line with similar case studies related to the Northern Italy. The NOx concentrations reproduced in the Po Valley area by WRF-Chem were on average simulated reasonably well with a general negative bias in almost all the examined rural background monitoring stations. Additionally, the deployment of an emission inventory at the original resolution (7 km) highlighted that increasing resolution from 3 km to 1 km does not generally improve the model performance.Nevertheless, simulated and observed NOx hourly concentrations in the urban area of Modena exhibit a large agreement in particular for urban traffic site where detailed traffic emission estimations proved to be very successful in reproducing the observed NOx trend. At urban background stations, despite a general underestimation of the observed concentrations, the combination of WRF-Chem with PMSS provided daily pattern in line with observations. The analysis of the modelled NOx daily cycle pointed out also that at both traffic and background urban stations the morning NOx peak concentration was on average underestimated. This could be explained with an overestimation of mixing phenomena between 07:30 a.m. and 10:00 a.m. by WRF-Chem which leads to a greater dispersion of NOx along the vertical and thus a morning underestimation.The statistical analysis showed finally that PMSS combined with WRF-Chem at both the resolutions (3 km and 1 km) and at both traffic and background sites fulfilled standard acceptance criteria for urban dispersion model evaluation, confirming that the proposed multi-modelling system can be employed as a tool to support environmental policies, epidemiological studies and urban mobility planning.

Aerosol particles during the Innsbruck Air Quality Study (INNAQS): Fluxes of nucleation to accumulation mode particles in relation to selective urban tracers

Despite the widely accepted implications of particulate matter on urban air quality, the knowledge of directly measured real-world emissions of particles from urban areas is highly uncertain. During the Innsbruck Air Quality Study (INNAQS), size-resolved particle number concentrations and fluxes for particles with diameters between 6 nm and 0.64 μm diameter were measured together with CO2, NOX and selective non-methane volatile organic tracers. With this unique dataset, exchange fluxes of eight different particle size bins were studied in relation to urban gas phase tracers. Particle number fluxes were almost completely dominated by ultrafine particles with diameters <0.1 μm of which 50% were smaller than 50 nm. Correlation analysis reveals that urban particles shared common sources with NOX, benzene, and CO2, which, based on footprint analysis, can mostly be attributed to traffic. Fluxes of particles with diameters between 0.03 μm and 0.1 μm were mostly positive and showed the best correlations with traffic and traffic associated tracer fluxes. Fluxes in the few-nanometer size-range showed more variability, which was caused by bidirectional flux patterns. Fluxes of particles larger than 0.25 μm correlated only poorly with traffic-related emissions. This manuscript demonstrates size-specific variability and bi-directionality in particle exchange and provides size-specific particle emission factors for traffic related tracers from the urban area of Innsbruck.

Total and fraction content of elements in volcanic soil: Natural or anthropogenic derivation

Soil element composition derives from parent material disaggregation during pedogenesis and weathering processes but also by anthropogenic inputs. Elements are present in soils in different chemical forms that affect their availability and mobility. The aim of the study was to evaluate the main derivation, natural or anthropogenic, of elements in the soils of the Vesuvius National Park (a natural environment strongly affected by human impacts). Besides, the effects of age of the lava from which soils derive, different vegetation covers, traffic fluxes along the two roads connecting the Vesuvius crater and altitudes of the sites on the pseudo-total element concentrations and on their contents in different fraction of soil were investigated. To reach the aims, BCR (Bureau Commun de Référence) sequential extraction was performed in order to determine the distribution of elements into: acid-soluble, reducible, oxidizable and residual fractions. The relationship between the main environmental media and distribution of elements was discussed using non-metric multidimensional scaling (NMDS). The findings showed that, with the exception of Cd, Cu, Pb and Zn that would seem to derive also from human activities, the other investigated elements (Al, As, B, Ba, Ca, Cd, Cr, Cu, Fe, K, La, Mg, Mn, Na, Ni, P, Pb, Si, Ti, V, W and Zn) mainly had a natural derivation. Among the investigated elements, only Cd could represent a potential high risk for the studied andosols. The highest element accumulations in the soils at low altitude could be attributable to an integrated effect of plant cover, vicinity of downtowns and traffic flux. The acid-soluble fraction of elements appeared more linked to lava age; the reducible and oxidizable ones to plant cover; the residual one to the chemical composition of the parent material that gave origin to the soils.

Low-cost methodology to estimate vehicle emission factors

Road traffic emission factors (EFs) are important parameters in managing air quality. Estimation typically requires data from advanced (and expensive) monitoring systems which remain unavailable in some regions (e.g. in developing countries). In this context, the use of simpler (lower-cost) systems may be more appropriate, but it is essential to guarantee the robustness of EF estimations. This article describes a methodology designed to estimate vehicle EFs from street canyon measurements of traffic fluxes, wind speed and direction, and pollutant concentration levels by using low-cost devices, all samples at a one-minute interval. We use different moving window filters (time periods) to average the raw measurements. Applying standard multiple linear regressions (MRL) and principal component regressions (PCR), we show that there is an optimal smoothing level that best relates traffic episodes and pollutant concentration measurements. An application for PM10's EFs on four vehicle categories of Havana's fleet shows a preference for PCR over MLR techniques since it reduced the collinearity effects that appear when traffic fluxes are naturally correlated between vehicle categories. The best regression fits (R > 0.5 and standard deviation of estimates < 15%) were obtained by averaging data between 40′ and 60’; within the boundaries of 95% confidence interval motorcycles have an EF = 111.1 ± 2.7 mg km−1 veh−1; modern, light vehicles have an EF = 90.6 ± 11.2 mg km−1 veh−1; old, light vehicles have an EF = 125.4 ± 18.5 mg km−1 veh−1 and heavy vehicles have an EF = 415.1 ± 31.2 mg km−1 veh−1. We showed that upgrading old light vehicles is a promising scenario for reducing PM10 air pollution in Havana by between 10 and 17%.

Stormwater Management: Calculation of Traffic Area Runoff Loads and Traffic Related Emissions

Metals such as antimony, cadmium, chromium, copper, lead, nickel, and zinc can be highly relevant pollutants in stormwater runoff from traffic areas because of their occurrence, toxicity, and non-degradability. Long-term measurements of their concentrations, the corresponding water volumes, the catchment areas, and the traffic volumes can be used to calculate specific emission loads and annual runoff loads that are necessary for mass balances. In the literature, the annual runoff loads are often specified by a distinct catchment area (e.g., g/ha). These loads were summarized and discussed in this paper for all seven metals and three types of traffic areas (highways, parking lots, and roads; 45 sites). For example, the calculated median annual runoff loads of all sites are 355 g/ha for copper, 110 g/ha for lead (only data of the 21st century), and 1960 g/ha for zinc. In addition, historical trends, annual variations, and site-specific factors were evaluated for the runoff loads. For Germany, mass balances of traffic related emissions and annual heavy metal runoff loads from highways and total traffic areas were calculated. The influences on the mass fluxes of the heavy metal emissions and the runoff pollution were discussed. However, a statistical analysis of the annual traffic related metal fluxes, in particular for different traffic area categories and land uses, is currently not possible because of a lack of monitoring data.

Theory and Simulation for Traffic Characteristics on the Highway with a Slowdown Section.

We study the traffic characteristics on a single-lane highway with a slowdown section using the deterministic cellular automaton (CA) model. Based on the theoretical analysis, the relationships among local mean densities, velocities, traffic fluxes, and global densities are derived. The results show that two critical densities exist in the evolutionary process of traffic state, and they are significant demarcation points for traffic phase transition. Furthermore, the changing laws of the two critical densities with different length of limit section are also investigated. It is shown that only one critical density appears if a highway is not slowdown section; nevertheless, with the growing length of slowdown section, one critical density separates into two critical densities; if the entire highway is slowdown section, they finally merge into one. The contrastive analysis proves that the analytical results are consistent with the numerical ones.

Variations in carbon dioxide fluxes within a city landscape: Identifying a vehicular influence

To date, studies examining carbon dioxide (CO2) fluxes in urban areas have been limited compared to those in rural environments. The objectives of our study were to examine the relationship between traffic volume and CO2 fluxes. We demonstrated that CO2 fluxes were strongly linked with surrounding land use, specifically impervious surfaces and traffic volume. A site near downtown Syracuse in New York State (USA) had relatively constant positive fluxes (source: +39 μmol CO2 m−2 s−1) throughout the year as a result of strong vehicular traffic influence from two nearby interstate highways. There was a strong positive relationship between traffic and CO2 fluxes (r2 = 0.93, p < 0.0001) with marked differences between the weekend days versus the workweek days. In contrast, a residential site in Syracuse was dominated by vegetative influences during the leaf-on period due to CO2 uptake by photosynthesis, reaching a maximum negative mean diurnal flux of −11 μmol CO2 m−2 s−1 around midday (sink). The spatial variations of CO2 fluxes identify the critical role played by local traffic volumes in affecting the CO2 dynamics of urban environments. Understanding the dynamic fluxes of CO2 in urban environments has important implications for local, regional and global evaluations of CO2 budgets and inventories, and carbon cycle and climate modeling.

Impact of realistic hourly emissions profiles on air pollutants concentrations modelled with CHIMERE

Abstract Regional chemistry-transport models are used for atmospheric composition studies in several contexts: analysis of past events, scenarios studies, trends or forecast. Modelled concentrations are sensitive to many inputs data like anthropogenic surface emissions of NOx, VOCs and particulate matter. These emissions are provided as annual masses of pollutants for several activity sectors and projected onto a spatial grid. To use these data, modellers must make important assumptions in order to estimate pollutants fluxes for their own model grid and time frequency. Among these hypotheses, the time resolution is crucial and the way to redistribute emissions from annual to hourly fluxes determines the modelled concentrations accuracy. The usual CTMs approaches handle the time distribution with averaged factors. The present study quantifies with the chemistry-transport model CHIMERE the benefit of improving the calculation of traffic emissions fluxes by using hourly NO2 measurements nearby roadside areas as a proxy of road traffic sources. This work shows very different diurnal variation of emissions from country to country and suggests the use of a new hourly emission factor dataset for various countries. The induced changes are quantified for ozone, nitrogen dioxide and particulate matter surface concentrations over the whole Europe during the summer 2007. It is shown that the daily ozone peak remains relatively insensitive to this improvement whereas the pollutants concentrations during nighttime are closer to the measurements with the new profiles.

The model SIRANE for atmospheric urban pollutant dispersion; PART II, validation of the model on a real case study

Abstract We analyse the performance of the model SIRANE by comparing its outputs to field data measured within an urban district. SIRANE is the first urban dispersion model based on the concept of street network, and contains specific parametrical law to explicitly simulate the main transfer mechanisms within the urban canopy. The model validation is performed by means of field data collected during a 15 days measurement campaign in an urban district in Lyon, France. The campaign provided information on traffic fluxes and cars emissions, meteorological conditions, background pollution levels and pollutant concentration in different location within the district. This data set, together with complementary modelling tools needed to estimate the spatial distribution of traffic fluxes, allowed us to estimate the input data required by the model. The data set provide also the information essential to evaluate the accuracy of the model outputs. Comparison between model predictions and field measurements was performed in two ways. By evaluate the reliability of the model in simulating the spatial distribution of the pollutant and of their time variability. The study includes a sensitivity analysis to identify the key input parameters influencing the performance of the model, namely the emissions rates and the wind velocity. The analysis focuses only on the influence of varying input parameters in the modelling chain in the model predictions and complements the analyses provided by wind tunnel studies focussing on the parameterisation implemented in the model. The study also elucidates the critical role of background concentrations that represent a significant contribution to local pollution levels. The overall model performance, measured using the Chang and Hanna (2004) criteria can be considered as ‘good’ except for NO and some of BTX species. The results suggest that improvements of the performances on NO require testing new photochemical models, whereas the improvement on BTX could be achieved by correcting their vehicular emissions factors.

The influence of traffic on road surface temperatures: implications for thermal mapping studies

AbstractUsed to predict icy stretches of road during winter nights, thermal mapping is the measurement and visualisation of road surface temperatures for road ice prediction. From its development in the 1970s, the accuracy of thermal mapping has been subject to numerous systematic and random errors. One source of error is the effect of traffic, which is known to have a considerable influence on road surface temperatures. However, as the effects have never been fully quantified, the full implications for thermal mapping are unknown. In this study, consistent temperature differences of around 1.5°C were found across the different lanes and carriageways of a multi‐laned road. The thermal differences are significant and can be directly attributed to traffic heat fluxes. Copyright © 2005 Royal Meteorological Society

INTEGRATED MODELING OF ROAD TRAFFIC EMISSIONS: APPLICATION TO LISBON AIR QUALITY MANAGEMENT

The application of three distinct modeling tools to deal with Lisbon atmospheric problems is presented. Information and forecasting system for private and public transport (VISUM), Transport Emission Model for Line Sources (TREM) and Variable Dispersion (VADIS) models were used to characterize the traffic fluxes, to quantify the emission amounts, and finally to evaluate the air quality in a specific area of the city characterized by intense traffic respectively. The results show the benefit of integrated use of the modeling tools VISUM and TREM to estimate the atmospheric emissions induced by traffic. On the other hand, the results obtained with VADIS are in acceptable agreement with the measured air quality data.

Analysis Of The Acoustic Climate Along Main Streets In Villa San Giovanni

In this paper an analysis of the noise acoustic climate characterizing the urban area of Villa San Giovanni (Italy) is presented. The investigation has involved the experimental measurement of the main indexes for noise pollution and specifically the A-weighted continuous equivalent sound level L, and the cumulative statistical levels Llo, LS0, LgO. Contemporarily, traffic fluxes data of five vehicle classes have been taken. The survey has been carried out in 14 measurement sites selected to adequately represent the different areas of the municipal territory on the basis of an acoustical zoning proposed by the same authors. Collected data, compared with the threshold limits fixed by the rule in action, point out the inadequacy of the actual road network and suggest the need of urgent and suitable actions of urban planning.