Abstract. 1 Introduction

Transcription

1 The role of temporal operation profiles on the study of SO^ pollution from domestic heatingin Thessaloniki, Greece A. Karagiannidis, K. Karatzas, N. Moussiopoulos, P. Sahm Laboratory ofheat Transfer and Environmental Engineering, Aristotle University Thessaloniki, Thessaloniki, Greece Abstract The Gaussian dispersion model PAL is applied to study SC>2 pollution due to domestic heating in Thessaloniki alternatively assuming a constant fuel consumption and a reasonable temporal variation of the fuel consumption during the heating period. In the latter case, the heating period divided into subperiods, a typical day being assumed to represent each of the subperiods. For each of the days considered, the diurnal variation profile of actual burner operation is extracted from a source measurement programme conducted in a part of the urban area of Thessaloniki. SC>2 pollution levels due to domestic heating calculated for the above two scenarios are then compared with available measurements. This comparison reveals that the accuracy in predicting air pollution levels may be significantly improved by using suitable diurnal variation profiles of the emission rates. 1 Introduction Although not considered as a critical polluter, diesel-oil fired domestic heating (DODH) has a noticeable contribution to the SC>2 pollution in large urban areas. The starting point for the investigation of this contribution is the evaluation of the emission rate on the basis of fuel consumption and emission factors. The latter are usually found in literature, though they could also be directly calculated from the amount of sulphur in the fuel. For a more detailed study of air pollution due to the DODH operation, it is necessary to take into account that domestic furnaces have different patterns of operation during the heating period. By distinguishing individual subperiods

2 32 Air Pollution Engineering and Management possible to simulate the above patterns by extracting diurnal operation profiles for these days. Due to the lack of central control and, therefore, explicit overview, this goal can only be achieved by a comprehensive programme aiming at the investigation of the performance of DODH systems and the estimation of air pollutant emissions. This field work can be conducted in an efficient way by using trained personnel, eventually equipped with a suitably developed questionnaire [1]. A necessary condition for the credibility of the results from such a programme is the representativity of the examined sample for the urban area under consideration. The present study aims to demonstrate the usefulness of collecting data associated with the temporal variation of DODH operation for predicting the levels of atmospheric pollution. Specifically, in the present paper the SOi pollution levels are examined. 2 Case study area With more than one million inhabitants, Thessaloniki, the capital of Macedonia, is the second largest city in Greece. It stretches over twenty kilometres in a bowl formed by low hills facing a bay that opens into Thermaikos gulf. Mt. Hortiatis lies to the E, with the Asvestohori hills at NE and the valley of theriversgallikos-axios-aliakmonas at NW. The study area is shown in Figure 1 as subdomain "A". Meteorological observations in the city have shown January to be the coldest month (average temperature: 5.8 C) and July to be the hottest (average temperature: 26.3 C) [2]. Dominating winds are N-NW in the cold period of the year (October-March), whereas in the warm period (April-September) an increased frequency of S winds is observed which is most probably attributed to the sea breeze circulation. In winter, low temperature inversions are frequently observed. A permanent network of monitoring and measuring stations is operating in the city for the observation of meteorological conditions and atmospheric pollution [3]. The air pollution problem in the Greater Thessaloniki area (GTA) has become considerable during the last years, as a result of the increase in population and traffic. SO% emissions in the GTA are mainly due to traffic, DODH and industry. Traffic contributes to the SOi emissions through dieseloil fired vehicles (taxis, trucks, buses, trains and ships). In spite of its significance in the city centre, this contribution is rather small when compared to the other two sources. Industrial activity is concentrated in the N-NW of the city, although some smaller industrial plants are also located to the E. Though being the source of only 30% of the total SO% emissions in the GTA, DODH is responsible for up to 85% of the SOi concentrations in the city centre in winter, due to the particular spatial distribution of these emissions in the urban area [4].

3 Air Pollution Engineering and Management 33 3 Emission-related data The present study is based on data on the temporal distribution of DODH operation, which were collected in the frame of the programme "Prevention and Abatement of Atmospheric Pollution" organised by the Municipality of Thessaloniki [5]. The required sampling took place in the period March 5 until May 27, 1993 within the limits of the Municipality of Thessaloniki. The samples taken can be considered as representative for the whole urban area of the city. The heating period in Thessaloniki was assumed to last from October 20 until April 20. It was further divided into three subperiods according to the outdoor temperature: - Subperiod 1: December, January, February (duration: three months). - Subperiod 2: November, March (duration: two months). - Subperiod 3: October, April (duration: one month). The collected data referred to phases of "permissible" burner operation (within each of the three subperiods), as they are mainly determined by the various (daily - or weekly - based) timer mechanisms installed at the DODH installations. In order to determine the corresponding phases of "actual" burner operation, it was assumed that, for each phase of operation, the burner operates continuously during the first hour and then for thirty minutes in hourly intervals [6]. This approach allows calculating the percentage of continuously operating burners for each hour and for each one of the three typical days. By assuming sample representativity, these percentages were regarded as equal to the probability that a DODH burner is operating within the corresponding hour in the GTA. The extracted diurnal variation profiles of actual burner operation (cf. Figure 2) were applied to the overall seasonal emissions of SO2 from domestic heating in the GTA (cf. section 4). The spatial distribution of these emissions was calculated from data valid for each municipality in the GTA [7]. 4 Simulation of SC>2 dispersion The dispersion of SO2 was simulated with the multisource Gaussian atmospheric dispersion model PAL which is recommended by the US Environmental Protection Agency [8]. The use of a Gaussian model instead of a 3-D Eulerian dispersion model (which would require extensive meteorological input data from a prognostic mesoscale model [9]) is justified by the fact that in the present work a statistical analysis is undertaken; by other words, the intention is to calculate mean values over a longer period rather than to describe specific pollution episodes. Concerning the required meteorological input data, calculations could either be based on measurements from the International Airport of Thessaloniki, or on measurements taken on the roof of the Town Hall in the

4 34 Air Pollution Engineering and Management centre of the city. The first alternative would have the advantage of the availability of a long time series that would lead to statistically safe values concerning the mean diurnal variation of the basic meteorological quantities (wind speed and direction, air temperature) for each month separately. Thus, in the calculations the yearly variation of meteorological data could be taken into account in conjunction with that of DODH emissions. Due to the large distance from the city, meteorological data from the airport are, however, not representative for the situation in the urban area, this being a severe disadvantage in the frame of the present work. For this reason, it was decided to use the Town Hall measurements, in spite of the shortage of the relevant time series. As the latter would not allow safely describing the mean diurnal variation of basic meteorological quantities for each month of the year separately, a mean diurnal variation of these quantities during the winter months was derived from measurements in the winter [10] and was used in all calculations. This approach has the advantage that the main question posed in the present study, i.e., to what extent the knowledge of DODH operation profiles affects urban air pollution levels, can be answered independently from influences related to the variability of meteorological quantities. In conclusion, identical meteorological conditions were considered for the whole heating period (although they were naturally assumed to vary in the course of the day). It should be mentioned that north winds are found to be dominant for the whole day with speeds in the range 0.8 to 1.8 m/s, while very low wind speeds occur during the night. Correspondingly, the mixing height was assumed to increase during the day from its minimum value (200 m) to 360 m. In the simulations the stability classes B and C (unstable and slightly stable) were assumed for daytime and night, respectively. 5 Simulation results In order to evaluate to what extent the temporal variation of DODH operation affects the SO% pollution levels in Thessaloniki, the mean contribution of DODH operation to the SO% concentration was calculated (a) for the whole heating period assuming constant emissions (Figure 3a) and (b) for each of the three subperiods that were taken into account (Figure 3b-d, assuming the daily variations of the mean percentages of operation shown in Figure 2). All four simulations show a similar pattern regarding the aforementioned contribution. Maximum values are found in the southern part of the city, which is characterised by a high population density, and to the south of the western part. The maximum DODH contribution to the SO2 concentration is 94 jug/ir^ in the cold period (December to February) and 65 jig/m^ in the warm period (October, April). If constant emissions are assumed, the maximum DODH contribution is approximately 88 ig/nf. Figure 3e-f show simulation results for the DODH

5 Air Pollution Engineering and Management 35 contribution to the SO] pollution in the time intervals 7:00-8:00 and 19:00-20:00 for the cold subperiod. The maximum values detected here are 350 and 150 jug/m\ respectively. This difference between morning and evening pollution levels is most probably attributed to the lower values of wind speed and mixing depth during the morning. In Figure 4 simulation results for the mean DODH contribution to the SO] pollution levels for both time dependent and constant emissions are compared with monthly mean concentrations based upon measurements at the Venizelou and Martiou stations in the year 1990 [10]. Moreover, Figure 5 shows simulation results for the diurnal variation of the DODH contribution to the SO] pollution levels in the cold subperiod compared with the mean observed diurnal variation of SO] concentration in the same areas. In the case of the Venizelou station, the calculated values are lower than the corresponding measurements for the whole heating period. A possible explanation for this underestimation is the fact that Venizelou is not far from the harbour of Thessaloniki and is crossed by main streets with heavy diesel vehicle traffic. Specifically, the existence of significant SO] sources other than DODH in the surroundings of the Venizelou station explains sufficiently the underestimation of calculations for the hours 11-18, when traffic load is high and DODH emissions relatively low. In the case of the Martiou area, where SO] pollution sources other than DODH are negligible, simulation results for both the yearly and the diurnal variation of SO] pollution are in better agreement with measurements. 6 Conclusions and perspectives In this paper the contribution of diesel-oil fired domestic heating to the SO] pollution levels in Thessaloniki is analysed. Comparisons of simulation results with measurements show that taking into account the time dependence (diurnal and annual variation) of DODH emissions leads to an improved quality of simulation, i.e. more accurate results of mathematical dispersion models with regard to the pollutant concentrations. Consequently, more effort towards gathering detailed information about time variation of DODH and other pollution sources can be recommended. The diurnal variation of DODH operation used in the present study was based on samples taken It is suggested that future sampling activities of this kind be combined with the collection of additional information (e.g. analysis of the exhaust gases). Such activities should cover a larger geographical territory, the aim being to improve the sample representativity. Furthermore, future activities could focus to refining the method used to describe the diurnal variation of DODH operation e.g. by taking into account socio-economic parameters, meteorological quantities and aspects related to regional planning.

6 36 Air Pollution Engineering and Management References 1. Bayerisches Staatsministerium fur Landesentwicklung und Umweltfragen, Emissions-kataster, Erlangen-Furth-Nurnberg, TUV Bay em e.v. (in German), Kouremenos, D.A. & Antonopoulos, K.A. Temperature data for 35 Greek cities, Foibos publications, (in Greek), Athens, Moussiopoulos, N. & Proyou, A.G. Measurements of the Permanent Monitoring Network during Field Measurement Campaign in Thessaloniki '91 Field Measurement Campaign, (ed. N. Moussiopoulos & G. Kaiser), pp , Bilateral Seminars of the International Bureau, 9, KFA Julich, Stamelos, K. The Air Pollution Abatement Programme of Thessaloniki, in Monitoring and Modelling in the Mesoscale, (ed. N. Moussiopoulos & G. Kaiser), pp , Bilateral Seminars of the International Bureau, 9,. KFA Julich, Karagiannidis, A. Temporal distribution of central heating operation, Final Report, Municipality of Thessaloniki, Bureau for International Relations Studies and EEC, (in Greek with English Abstract) Thessaloniki, Ta Nea, "Adjust and profit - 5 ways to limit fuel consumption",, pg. 20 (in Greek), 16/11/ Sahm, P. Modelling Atmospheric Mesoscale Dispersion in the Greater Thessaloniki Area, Diploma Thesis, Laboratory of Heat Transfer and Environmental Engineering, pg.!3&53 (in German), Thessaloniki, Petersen, W.B. & Rumsey, D. User's Guide for PAL 2.0, A Gaussian Plume Algorithm for Point, Area and Line Sources, Meteorology and Assessment, Environmental Sciences Research Laboratory, Research Triangle Park, North Carolina EPA/600/8-87/009, NTIS Accession number PB87-168, no. 787/AS. March Moussiopoulos, N. The EUMAC Zooming Model, a tool for local-toregional air quality studies, Meteorology and Applied Physics, in press, Petrakakis, M., Kelesis, A., Kanellopoulou, Z., Koutsari, E., Tsaknia, A. & Tzoumaka P. Measurements of the Municipal Network for the Control of Air Pollution and the Monitoring of Meteorological Parameters: Year 1990, Technical Report, Municipality of Thessaloniki, Bureau of Environment, (in Greek), Thessaloniki 1993.

7 Air Pollution Engineering and Management 37 Figure 1: The city of Thessaloniki. Subdomain A is indicating the area of study containing the entire urban area with its various municipalities. The locations of the two measurement sites (Venizelou and Martiou) are also shown i} -, -I 1 1 D, J, F ON, M DO, A -,, 1 n _ 1 ; : ]} } 1 } - m c n r o M m m m m m m m M r o r o r o r ot^ m c o o o co r-l Hours of a typical day (additionally, mean values for the time interval 06:00-24:00 and 07:00-22:00) Figure 2: Diurnal variation profiles of actual burner operation in GTA for a typical day for each one of the three heating subperiods: D,J,F: December, January, February (sampling size 158); N,M: November, March (sampling size 234); O,A: October, April (sampling size 140). ^ I -i 1 -j

8 38 Air Pollution Engineering and Management Figure 3: Spatial distribution of the DODH contribution to the SO% pollution (in ug/m^). (a) Mean value for the whole heating period, (b) Mean value for subperiod 1 (December-February), (c) Mean value for subperiod 2 (November, March), (d) Mean value for subperiod 3 (October, April), (e) Distribution for the time interval 07:00-08:00 for a typical day of subperiod 1. (f) Distribution for the time interval 19:00-20:00 for a typical day of subperiod 1. f

9 Air Pollution Engineering and Management 39 OCT NOV DEC JAN FEB MAR APR OCT NOV DEC JAN FEB MAR APR Figure 4: Comparison of simulation results for the mean DODH contribution to the SO] pollution levels with measured monthly mean concentrations at the Venizelou and Martiou stations. M = measurement, A = calculation for time dependent emissions, B = calculation for constant emissions.

10 40 Air Pollution Engineering and Management Calculations I Observations Martiou Calculations Observations Venizelou Figure 5: Simulation results for the diurnal variation of the DODH contribution to the SC>2 pollution levels at the Venizelou (up) and Martiou (down) stations for the cold subperiod, compared to measurements. Values in j