1 General emission scenario of Ravenna industrial area

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1 Data analysis and observation : critical concentrations due to an industrial district in a coastal zone D. Manco*, F. Babini*, M. Andretta\ F. Fortezza" "Environmental Science Institute, Bologna University, Via M. di - Montecatini (Environmental Research Center), via Giro 48, Marma #avef?ma(%7;, Aa/y *ARPA (Regional Agency for Environmental Protection), Ravenna Abstract In the present work we treat a procedure to evaluate and to forecast critical pollution events in the area of Ravenna (Italy). This procedure is based on the use of the Gaussian model ISC and of pollution roses elaborated by a wide spread detection network for the control of air quality The detection network consists of 15 stations which control the pollution concentration in the air in accordance with the Italian law. Furthermore, by this network, we can gather the meteo parameters that characterize the complex aspect of the area of Ravenna. Ravenna city is situated in the Po Valley and, feeling in the same time the effects of the coastal zone, requires a study aimed to consider both these climatic features. One of the most important industrial development district is placed in the rural zone of the city and produces the 90% of the global emissions in the same area. In this framework, it becomes a necessity to correlate many different emission scenarios with meteo climatic parameters, in order to plan interventions in case the air concentrations limits of pollutants exceed the pre-alarm level. By the continuous control of the industrial emissions and the ISC model fitted for the area of Ravenna, it is possible to evaluate pollutants that are typical products of industrial emissions. 1 General emission scenario of Ravenna industrial area The industrial area of Ravenna is one of the most important industrial site in Italy. Also for this reason, more than the 90% of the total air pollution

2 538 Air Pollution Modelling, Monitoring and Management emissions in this area is due to the existing industries. The most important air pollution emissions in the Ravenna area are sketched in table 1 (1995 estimate), illustrated in ARPA [1], Provincia di Ravenna [2]. Even if in the last years the total pollution due to the industrial emissions has been reduced, the previous table shows that more than the 90% of the global emissions in the Ravenna area comes from the existing industries. Furthermore, the most important industrial emissions are represented by sulfur dioxide emissions. Also for this reason, in this work we have used these emissions as the representative trace of the industrial pollution of the site. The most important SO: emissions are placed in the area of Ravenna neighborhood in the north-east side of the city. This area extends from the Ravenna suburbs, along the so called Canale Candiano, till Porto Corsini and Marina di Ravenna. Pollutant SO: NO* TSP CO VOC Industrial emissions T/year % Traffic emissions T/year % Civil - heat. Emissions T/year % Table 1. Source inventories in Ravenna area. TOTAL T/year Even if the pollution emissions from the existing industries represent the great part of the global pollution emissions in the area, their average effects to the general air quality in the site are not so great. This fact is principally due to the climatological situation of the area. In particular in winter, the prevailing winds come from west and north-west, and they drag the industrial pollutants away from the city, that is placed in the northeast direction respect to the industrial area. In winter, winds coming from this direction have, typically, high velocity and they are correlated to stormy weather that prevent from pollutants concentration at the ground level. In winter, some potentially critical situation can occur during the period of wind calm. Anyway, in this case the turbulence that is produced by the urban area prevent from the pollutants coming from the industrial area to concentrate at the ground level of the city. During the summer, the great atmospheric turbulence over the coast line make a great dilution of the pollutants also in the case of wind blowing from north-east. Obviously, this situation can be considered as a typical average situation. During the year, particularly critical situations from the point of view of the pollutants

3 Air Pollution Modelling, Monitoring and Management 539 concentration at ground level can occur in the area near Ravenna city. In this work we intend to study in a more detailed way some of these situations and to analyze the meteorological and emission conditions that can be responsible for some exceptional critical situation. 2 Analysis of critical concentrations in the area of Ravenna The present work aims to analyze the ground level concentrations of pollutants in the air to characterize the effects of the industrial emissions spread in the wide area of Ravenna. As already specified, almost the total amount of SO2 measured by the air quality monitoring network is due to the industrial sources, as both road traffic and house heating in winter have a low impact on SO2 concentrations. The study defines and analyses the correlation between high pollution events and specifically involved sources considering both the distribution of the sources and of the complex local meteorology. This analysis is based on three different factors: 1. analysis of meteorological variants or parameters 2. real time measures of SO2 concentrations 3. application of ISC diffusion model, EPA [3] For the first step we referred to the measures of the local monitoring network consisting of 5 meteo stations as indicated by the numbers in the maps. The cases we analyzed consider different types of days and hours in order to study particular meteo and topographic effects. For the second step we used data referring to the same local monitoring network, in particular we chose the sites with high environmental sensibility such as the city center and the touristic area of Marina di Ravenna. The correlation degree between the monitored concentrations and the meteorological conditions resulting from the available data has been verified by applying the ISC Gaussian model in the short-term version. This evaluation was necessary as, because of the distribution of the network on the area, in no cases two or more monitoring stations are downwind to the same source and, on the whole to the industrialized area To evaluate the source we referred to the data provided by the local control authority, that identified the industrial sources. The data are affected by the fact that the values are annual averages that in any case do not change considerably in time. Anyway we can not except that in the monitored period there have been some exceeding in the emissions as supposed in the analysis of the results. In order to improve the data of real emissions, for which no registration document is required, further controls will be necessary The concentration values are reported in table 2. 3 Results The ISC Gaussian model is very suitable to evaluate the fallings of pollutants

4 540 Air Pollution Modelling, Monitoring and Management caused by the typical industrial sources Its performances were better, more the meteorological conditions didn't change and more homogeneous the terrain was. Even though results are affected by the scarce reliability of the real amounts of the source emissions, we can in any case affirm that: there is a good correlation between the estimated and the real values measured by the monitoring stations of the rural areas. Nearer the monitoring station is to the principals emissive sources, better is the correspondence between the estimated and the measured values, as illustrated in table 2, for the case 3 (Marina di Ravenna); the ICS model is insufficient to motivate the rather high concentrations in the monitored points in the center of Ravenna. Considering the data of the meteo stations, infact, it would seem that the sources are cut off from the main wind direction, corresponding to the cases 4 and 5 (Piazza Resistenza and Stadio) in table 2 ; the concentration level, however, excludes that the responsible sources came from the city center as both road traffic and house heating contribute in an insignificant way to the concentration of SO2; we can suppose that the measure of the wind direction on surface layer would notfitthe behavior of the wind at high heights (from 50 to 200 meters) that changes its direction of several degrees. We can suppose also that the transport of pollutants coming from the elevated sources of the industrialized area would intercept the city and because of the high heating is widespread to the ground level by convective cells. This behaviour is confirmed by the high correlation between the concentrations in the city center and the solar global radiation, illustrated in figure 1. In this case, lacking both stationary and homogeneous conditions, the ICS diffusion model is completely insufficient to simulate the behavior of industrial sources on the city area. The figure shows the measured concentrations of SO2 and of the solar global radiation in a summer day, in this case the output concentrations of ISC are not present as they are comparable to the instrumental sensibility and therefore their value is almost zero. Figure 2 illustrates the pollution roses that individuate the responsibility for the air pollution levels : the power plant ENEL (monitoring station 1 and 4), chemical plant ENICHEM and ceramic industry (monitoring stations 1, 2, 3, 5 and 7). 4 Conclusions The present work showed that the only application of the ISC Gaussian model, in the area of Ravenna, is not sufficient to correlate the ground level concentrations of SO: coming from industrial sources, mainly from chemical, ceramic and power production plants. Anyway, we can observe that the ISC model has very good performances for the winds coming from NE and ENE directions that are responsible of the high

5 Air Pollution Modelling, Monitoring and Management 541 concentrations in the summer touristic site of Marina di Ravenna. The breeze complicates local meteorology making the analysis of the model less efficient more the distance from the emission sources increases. It can be said that, in spite of the scarce correlation between concentration and receptor, if we analyze the concentrations apart from their position, they result reliable, as appears from figures 3, 4, 5, 6. The analysis of the concentrations of SO: coming from the industrialized area on the city represents a peculiar case. In this case ISC would seem to exclude the responsibility of the industrial sources, but an accurate analysis of the possible local meteorological effects leads to the hypothesis that for surface winds, and in particular for the slow ones, coming from N, NW, both the presence of the city center and of the breeze contribute to the rotation of the wind directions. In a condition of strong radiation there could be a fumigation on the city (Oke [4]) of small proportions as the pollutants transported on the city have already had a good dilution in the atmosphere, as shown by the figures 1 and 5. The present work however needs further analysis in order to verify the above mentioned hypothesis, through the use of data including a check of the real emissions in the sampling days, temperature and wind profiles. Only in this way we will be able to quantify the contribution of the single industrial sources to the air quality in the area of Ravenna, in function of the position of the receptors. -O- Solar radiation -A- SO2 concentration 250 Figure 1. Daily behavior of solar radiation [W/rn^] and SO] concentration at Piazza Resistenza monitoring station in July the 13*, 1996.

6 542 Air Pollution Modelling, Monitoring and Management Figure 2. Pollution roses for year 1996: pollutant concentration in Source ' Monitoring stations : 0 - ARPA laboratory 1 - Marina di Ravenna 2 - Germani 3 -Marani 4 - Zorabini 5 - AGIP P.zza Resistenza 7 - Stadio

7 Air Pollution Modelling, Monitoring and Management ^ Figure 3. NOx iso-concentration levels, 4/18/ Figure 4. SO: iso-concentration levels, 2/8/1996.

8 544 Air Pollution Modelling, Monitoring and Management Figure 5. SO: iso-concentration levels, 7/23/1996. S</?*\ ; /:-: Figure 6. SO: iso-concentration levels, 7/13/1996.

9 Air Pollution Modelling, Monitoring and Management 545 Stations Coordinates,Time GERMANI (5368,3047) 1/6/96 hi 0 MARANI (315,5461) 4/1 8/96 h22 MARINA RA (6188,6868) 2/8/96 h8 P.RESISTENZA (-1442,-505) 7/13/96 h!6 STADIO (-1126,-! 187) 3/20/96 hi 1 ZORABINI (292,9228) 7/23/96 h!2 Wind direction [K] Stability class D D C B B C Concentrations [ng/m3] measured estimated max Table 2. Air concentration values and meteorological conditions in some sampling days. The coordinates are expressed in meters. To localize the monitoring stations refer to the map in the figure 3. Key words : air pollution, urban meteorology, gaussian model. References. 1. EPA - 450/ a, EPA user's guide to ISC, T. R Oke, Boundary layer climate, Routledge, ARPA Ravenna, Analisi e gestione della qualitd dell'aria a Ravenna, Provincia di Ravenna, La rete di rilevamento per il controllo della quahtd dell'aria di Ravenna, January 1996.