An innovative study of noise and atmospheric pollution emission by urban vehicular traffic

Transcription

1 An innovative study of noise and atmospheric pollution emission by urban vehicular traffic L. M. Caligiuri, A. Reda & A. Sabato Department of Mechanics, Faculty of Engineering, University of Calabria Via P. Bucci Rende (Cs), Italy Abstract Vehicular traffic represents one of the most important sources of noise and environmental pollution in urban centres. The concentration values of main atmospheric pollutants (CO x, NO x, SO x, O 3, HC, PM) strongly depend on atmospheric conditions and traffic flow features (composition, mean speed, utilized fuels, driving conduct, etc). This information about traffic, except engine data, can be obtained from acoustical data, by considering the time behaviour of L eq and a suitable set of statistical noise levels L n (as defined in ISO 1996). In this paper we analyse the results of a noise and atmospheric pollutants concentrations levels measurement campaign carried out in a typical urban centre. The pollutants concentration and climatological data have been compared to the acoustics indicator values measured in the same overall environmental and traffic conditions, in order to put in evidence the influence of the above traffic features on pollutants concentration levels. For a better phenomenological understanding, an innovative noise-like statistical approach has been developed, by introducing opportunely modified statistical levels of concentration. 1 Introduction Vehicular traffic represents the most important source of noise and atmospheric pollution in the urban centres. In high density traffic areas, the main air pollutants are constituted by sulphur dioxide ( SO 2 ), nitrogen oxides ( NO x ), carbon monoxide (CO ), particulate matter ( PM10 and PTS ), Ozone ( O 3 ) and, in some cases, also by organic compounds. Air pollution level is quantified by means of concentration values of the above pollutants, expressed in

2 802 Urban Transport X 3 ppm or µgm, whose space and time behaviour, in urban centres, is related both to the vehicular traffic features (overall vehicular density flow, mean speed, composition, engine types, driving habits, etc) and meteo-climatic conditions (atmospheric pressure, temperature, wind direction and intensity, relative humidity). Noise pollution levels also, when generated by urban traffic, are generally described through the values of L Aeq (the continuous equivalent pressure level, A-weighted, defined in the ISO 1996/1) or leq-based quantity like Lden and L night (as stated in the Directive 2002/49/CE of the European Community). We have seen [1] that the combined analysis of L Aeq and a particular set of statistical levels calculated over appropriate time intervals can help us to identify the main features of mobile noise sources as well as the presence of atypical events able to modify the value of L Aeq. In this paper we'll analyze the results of simultaneous measurements of noise levels, air pollutants concentrations and meteo-climatic parameters performed during a measurement campaign in the urban centre of a middle-size municipality. A set of statistical levels (percentiles) has been calculated, over specific time intervals, from the experimental noise and air pollutants data, also comparing their values with those relative to traffic total flow and composition, during the same measurements time interval. It will be shown that a suitable choose of statistical levels set and relative calculation time intervals, permit us to put in evidence relationship between vehicular traffic features and the time behaviour of noise and air pollutants concentration levels. The indications obtained in such way can be useful employed in order to realize noise and air pollution control and mitigation plans in the urban centres under given meteoclimatic conditions. 2 The use of statistical levels in the analysis of noise and air pollution Given a set { x1,..., xn } of values of variable X, (numerically ordered), we can define the percentile j as the element x k where jn k = 100 The percentile P 50 has a general special meaning because coincides with the value of median of the data distribution and it's resistant to outliers; it will be change slightly if a large perturbation has added to any value. For time-varying quantities the data set { x1,..., xn } represents, at a given point, the values assumed at successive measurement time instants { t1,..., t n }, by the variable X( t ). In this case the value of the P n percentile represents the value overcame by X during a time interval equal to n% of the total time interval of measurement. For air pollutants the quantity X is assumed to be the concentration of the different compounds studied, expressed in appropriate units. In the case of noise pollution

3 Urban Transport X 803 the statistical level L n is defined [2] as the A-weighted sound pressure level obtained by using time constant F that is exceeded for the n% of the time interval considered. In the study of road traffic noise the statistical levels L10 and L 50 have a very special meaning. The value of L 10 is related to the number of constant energetic level events in the vehicular flow and the behaviour of the difference L10 LAeq can be expressed as a function of a quantity that is, at a given distance from the road, directly proportional to the total flow and inversely proportional to the average speed v [3]. The percentile level L 50, because of its statistical meaning, can be related to the absolute traffic flow; for this reason, it represents an independent measure of the average vehicular speed. The comparison between the above L n and LAeq permits a suitable characterization of urban traffic features [1]. 3 Analysis of experimental data In this paragraph we shall analyze experimental noise and air pollutants data by means of the above considerations of statistical levels. The data have been simultaneous collected by using a mobile laboratory equipped with the following instrumentations: o meteo-climatic station for the measure of atmospheric pressure, temperature, relative humidity, wind direction and intensity; o UV fluorescence SO2 analyzer; o NO / NOx chemiluminescent analyzer; o CO infrared analyzer; o chemiluminescent O3 analyzer; o hydrocarbons flame ionization detector analyzer; o integrating sound level pressure analyzer. The signals from the different analyzers are recorded through a multichannel acquisition board and later processed by means of mathematical routines performing the statistical analysis required. A particular mathematical time frequency subtraction techniques have also been applied to the noise data in order to isolate the noise contribution of the analyzers itself to the overall L Aeq values. The measurements location is represented in fig. 1. It is placed in an important urban artery with traffic flow density varying from 889 to 1344 vehicles/h and slow-varying meteo-climatic conditions, characterized by a mean relative humidity of 52%, a mean temperature 1 t = 9.7 C and a mean wind speed v = 1.2ms in the time interval T from 9:00 to 17:30 of a typical day. We ll analyze, in this paper, the time history of noise statistical levels L 1, L 10, L 50, L 95, of L Aeq and, for each air pollutant s, of concentration percentiles levels P 1, P 10, P 50, P 95 and mean value C ms,, (with s= CONONO,, 2, NOx )

4 804 Urban Transport X all calculated on time intervals of duration T = 15 min. From the whole time interval T we have selected two representative sub-intervals: the first from 9:00 to 14:00 and the second from 16:00 to 17:30 that will be analyzed with respect to the traffic flow density variations. For each of them we have selected a number of representative intervals that will be analyzed in details. The analysis of the other intervals can be carried out in a similar way and therefore it will be not reported. Figure 1: Location of the measurement point. Figure 2: Traffic flow density time history in the intervals [9:15-14:00] and [16:00-17:30].

5 Urban Transport X 805 Figure 3: Time history of noise statistical levels L L. n and Aeq Figure 4: Time history of noise statistical levels L n and L Aeq. 3.1 Intervals analysis Interval 9:45-10:00 We observe a decrease of L Aeq, L 10 and L 50 with respect to their values in the previous interval, such that the difference LAeq increases and L10 LAeq is constant. The increase of LAeq indicates a higher traffic mean speed in

6 806 Urban Transport X according with the decrease of the bus and trucks flux. This causes a high diminution of all the pollutant concentration values. Figure 5: Time history of statistical levels and mean concentration of CO. Figure 6: Time history of statistical levels and mean concentration of NO Interval 10:00-10:15 The decrease of LAeq, with a constant value of L10 LAeq, shows a more congested traffic situation confirmed by the increase of cars, bus and trucks flow. This traffic scenario has a negligible influence on L Aeq value but, due to the reduction of mean speed, an important effect on the pollutant concentrations.

7 Urban Transport X 807 Figure 7: Time history of statistical levels and mean concentration of NO 2. Figure 8: Time history of statistical levels and mean concentration of NO x Interval 11:45-12:00 We see an increase of the number of all vehicles, in particular of motorbikes, transiting at an higher speed with respect to the other vehicles, as confirmed by the increase of the difference L 10 L Aeq ; nevertheless the reduction of global traffic speed, shown by the reduction of LAeq, determines the decrease of L Aeq. We correspondingly note the decrease of the pollutants mean concentrations in all the species. If we analyze the air pollutants statistical levels

8 808 Urban Transport X we see that, for nitrogen oxides, all the statistical levels and the mean values decrease while P 95 remains constant or increases. In the case of CO, we have a decrease of all the statistical levels except of P 50 that shows an increase. This means that the variations in air pollutants concentration levels happen at different time scale within the time interval, characterized by different wind speed values. In this case favourable traffic conditions for the production of a given pollutant correspond to adverse meteo-climatic conditions (characterized by an increases of the wind instantaneous speed up to 60% of its own mean value in the same interval, see fig. 9) for its accumulation and conversely Interval 12:15-12:30 This interval, in which we have a practically unchanged total vehicular flux with respect to the previous value but an high decrease of the number of bus, tracks, motorbikes and an increase of the mean traffic speed, is characterized by an increase of the mean values and statistical levels of all the air pollutants. If we analyze the behaviour of the air pollutants statistical levels (in particular P 95 ) we see that, in this case, the concentrations increment is not related to a traffic flow variation (that is negligible) but to an accumulation phenomena, produced, during the time interval, by the particularly unfavourable low-speed wind behaviour, whose profile is represented in fig Interval 13:15-13:30 This interval is characterized by an high reduction of total traffic flow, in particular of the cars, generating the decrease of the CO concentration level, with a number of bus and trucks unchanged. The decrease of the mean traffic speed, confirmed by the decrease of the difference LAeq (and of L 10 L Aeq also), determines an higher mean transit time of the cars and, in particular, of the bus and trucks, responsible of the increase of nitrogen oxides concentration values. 2,50 wind speed profile [m/s] 2,00 1,50 1,00 0,50 0,00 11,45 11,46 11,47 11,48 11,49 11,50 11,51 11,52 11,53 11,54 11,55 11,56 11,57 11,58 11,59 12,00 hour Figure 9: Wind speed profile in the time interval [11:45-12:00].

9 Urban Transport X 809 wind speed profile [m/s] 1,80 1,60 1,40 1,20 1,00 0,80 0,60 0,40 0,20 0,00 12,15 12,16 12,17 12,18 12,19 12,20 12,2112,2212,23 12,2412,25 12,2612,27 12,2812,29 12,30 hour Figure 10: Wind speed profile in the time interval [12:15-12:30]. 4 Conclusion The relationships between the air pollutants concentration values and the features of the traffic sources that produce them can be put in evidence by means of the choice of a suitable set of statistical levels of acoustics parameters and air pollutants concentration values, calculated on appropriate time intervals (of duration t = 15 min in the case of urban traffic). In fact, the study of the suggested noise statistical levels L 10, L 50 and L Aeq permit us to properly characterize the urban traffic features while the behaviour of the air pollutants percentiles values shows the variability of their concentrations as a function of the meteo-climatic conditions in the neighbourhood of the measurement location. References [1] L.M. Caligiuri, A. Sabato, The use of statistical analysis techniques in the study of urban vehicular traffic noise. Acoustics 2003 International Conference (Wessex Institute of technology Conference), Cadiz (Spain), June 2003; [2] ISO (1982) Acoustics Description and measurements of environmental noise Part 1: Basic quantities and procedures. [3] Abbott P.G. & Harris G.J., The Calculation of Road Traffic Noise Implication of changing to Laeq. Proc. of Institute of Acoustics Autumn Conference 1999, Transport Research Laboratory Crowthorne, Berkshire, United Kingdom.