Transactions on Ecology and the Environment vol 4, 1994 WIT Press, ISSN

Transcription

1 A climatological dispersion study in the Canary Islands J. Moreno Santabarbara*, M. Wagensberg Lubinsky AMBIO, S.A. Barcelona, Spain "Present affiliation: ITEMA, U.P.C. Barcelona, Spain ABSTRACT The methodology and main results of a dispersion study made to estimate the environmental impact of two power plants to be built in the Canary Islands (Spain) are presented. As a part of the study, a set of six meteorological stations were placed in the area to record wind data for the dispersion models during approximately one year. A simple gaussian-plume model from EPA, USA, was applied to the complete set of data to obtain maps of the average concentration of pollutants. A more sophisticated gaussian-puff model from Ris0, Denmark, was applied to some selected data. The selection of the data was made based on a climatological study. Due to the special characteristics of the climate of the region the most pertinent features of the weather on each day could be classified into a few distinct types. For each weather-type, a data set was built and this was used to run the Danish model. The results of the two modelling procedures are presented and compared. The second method can be taken as a simple prognostic tool to assess the dispersion patterns in the area. That is, the weather-type forecast is coupled with the results of the dispersion models to give an estimate of the effect of the power plant emissions.

2 52 Pollution Control and Monitoring BACKGROUND The Spanish electricity utility UNELCO planned in 1990 to build two power plants on the south-east coast of the Tenerife and Gran Canaria islands. As a part of the obligatory Environmental Impact Assessment (EIA) studies for these projects, two dispersion studies were carried out to evaluate the concentration of pollutants due to the power plant emissions. This part of the EIA study was especially relevant since, on the lee side of the projected power plant sites (according to the general wind regime of the region) there are two important tourist and protected areas. Since the characteristics of the two sites are very similar the results of the two EIA studies are presented at the same time. Previous to the dispersion modelling, a climatological study was carried out. The results of this climatological study determinated the methodology of the dispersion study EXPERIMENTAL SET-UP The first step in the study was to collect the available meteorological information of the area. In despite of the large number of meteorological stations located on the islands, the continuity and quality of their data is very poor, instead it was decided to install a set of six instrumented masts (three on each island) measuring wind speed, direction and standard deviation of the direction. This set-up was operative for approximately one year. Several tests were made to check the spatial and temporal representativity of the obtained data. Four measurement campaigns (with a mobile anemometer and vane) were carried out to take samples of wind data from the areas around and between the stations in order to evaluate the spatial representativity of the meteorological masts sites. These sites were also visited by experts from the Danish Laboratory Ris0. In addition, several years of data from the nearby airports were also compared to the obtained data in order to check the temporal representativity of the studied year. As an example of this checking, figure (1) shows the wind roses calculated with the complete set of data for Gran Canaria. The rose labelled "Gando" corresponds to data from the airport, and the one labelled "Dorada Fish" from a factory in the area. The other three roses come from AMBIO stations data. It can be appreciated from this diagram that the southwest mast, labelled "Loma Brava/ Golf, has different behaviour from the rest of the stations. The majority of the stations show that the dominant regime of winds in the area (trade winds) are distorted by the presence of the island which forces the wind to follow the coastline. The southwest rose indicates a zone of wind-shadow the eastern boundary of which was detected in some of the sampling campaigns located near the Tarajalillo beach. A similar pattern was observed in Tenerife.

3 Pollution Control and Monitoring 53 Vertical soundings were carried out twice a day at the Meteorological Office base in the north of the islands. In Tenerife, a SODAR was installed in the area of study to check the validity of the sounding data concerning the mixed layer depth measurements. TYPES OF WEATHER Bibliographical research was carried out to determine the characteristics of the climate of the zone. This climate has been exhaustively studied and most authors agree in considering a small number of well-defined types of weather occurring in the area. These types were reduced to four for operative purposes: I. Trade winds II. Northern flow III. Atlantic low IV. Sahara flow These general types of weather were taken as a base to describe four standard local situations in the area of study with particular emphasis on the most relevant factors for the dispersion study: wind regime and stratification conditions. A special tool was developed for this purpose. That is, we displayed simultaneously the following information: -The synoptic surface chart. -The height and strength of the first inversion layer found in the vertical profiles and the wind at that height. -Two maps (one for each island) showing a progressive vector plot for each mast and a qualitative plume icon at the power plant site. Figure (2) is an example of these diagrams. The progressive vector plot was drawn by concatenation of the hourly wind vectors measured on each mast. It can be imagined as the daily trajectory of a hypothetical particle released from a mast whose movement was only driven by the wind measured at that mast. The qualitative plume icon is constructed with the standard deviation of the direction data measured at the nearest station to the power plant site. The longer and narrower the plume is, the more stable the conditions are. Based on the analysis of this information, 76 % of the days of the year of data were classified in one of the four weather types and local characteristics of these types were established. Obviously, this procedure is not free of subjectivity but the later results of the dispersion modelling confirm the reliability of the method.

4 54 Pollution Control and Monitoring The local description of each type of weather is the following (between parenthesis, the percentage of occurrence of the weather type): I. Trade winds (55%). The most common weather in the islands especially in the summertime. It is due to the presence of the well defined A gores high located to the north of the islands. The flow is from NE with a wind speed of around 10 m/s and tends to follow the islands SE coastline and disappear at the SW corner of them. Moderately stable stratification with mixed layer heights at around 1000 m. This situation can remain unchanged for 10 days or more. II. Northern flow (18%). Usually occurs in spring or autumn and it is mainly due to polar air advection. Similar wind regime to type I but with stronger N components. High mixed layer height, approximately 2000 m. III. Atlantic low (16%). More common in the wintertime, it shows the pass of fronts and can last two or three days. The presence of a low is usually clear on the surface map. Possibility of rain. Variable winds with W component. Very deep mixed layer. IV. Sahara flow (5%). Easterly flow from the continent. Very stable conditions and low winds. Figure (2) shows a resume of these weather characteristics. It is not only qualitative but quantitative in the sense that it was built by averaging the year of data after its classification. DISPERSION MODELLING Two dispersion models were applied to the meteorological data set to estimate the average concentration pattern. First is ISCST from the USA EPA. It is a simple gaussian plume model driven by a single source of meteorological data and where the topography is only considered at the reception points. Its simplicity reduces computing time sufficiently to allow the computation of all cases in the data base. A yearly average concentration map (based in a 100x100 grid) produced by ISCST for Gran Can aria is showed in figure (3.top). The package LINCOM-RIMPUFF from the Danish National Laboratory Ris0, is the other model used. RIMPUFF is a gaussian puff model driven by the output of the LINCOM flow model. LINCOM solves a linearized subset of Navier-Stokes set of equations taking the topography as the boundary condition. An objective analysisfittingprocedure is used to match the wind field with the measured data. This model is more sophisticated and it would be very time consuming to use it with the complete set of data as in the other case. Instead of this, a set of four days of data (one of each type) was chosen from the complete set. The model was applied to this data and the resulting maps were averaged

5 Pollution Control and Monitoring 55 after weighting by the percentage of occurrence of each weather type. The result of this process is shown in figure (3.bottom) The similarity between the two maps in figure (3) is good considering the difference in the method. The discordance in the values in the NE region could be due to a poor choice of the type Ill-weather day. PROGNOSTIC MODEL The procedure used with the LINCOM-RIMPUFF model gives the key for the development of a simple prognostic tool to estimate the concentration patterns in the zone. Based on the Meteorological Office synoptic forecast an expert could assign a weather-type corresponding to the on forthcoming days. This assignation will be subjective but simplified by the clear weather classification. A pre-calculated concentration pattern corresponding to the weather type would then be predicted. When concentration measurements are available a feed-back process can be implemented. By correcting the concentration maps with this data, the data base would be in a constant debugging process. REFERENCES AMBIO,S.A. Estudio de Impacto Ambiental de la Central Termica de GromoaWo ftemen/e/ UNELCO, AMBIO,S.A. Estudio de Impacto Ambiental de la Central Termica de Barramco de Tznyamo fgm% CWorm/ UNELCO, Font Tullot, I. Climatologia de Espana y Portugal. ESPASA, 1964.

6 56 Pollution Control and Monitoring FIGURE 1

7 Pollution Control and Monitoring 57 EVOLUCION SINOPTICA Analisis en superficie Perfil termico y viento en altu Tipo: I Tipo: II Tipo:lll Tipo: IV EVOLUCION LOCAl Gran Canada ' TIPO DE TIEMPO % Tipo: IV 1:55 II : 18 III : 16 IV : 11 FIGURE 2 Caracteristicas principales de los cuatro tipos de tiempo (representatives de 76% del total de dias estudiados).

8 58 Pollution Control and Monitoring MEDIA ANUAL. SO2 -«o> 4«c7 w*# -us* >i«4t o «M;»u MEDIA ANLJAL TIRO SO2 C.'omparaci<S-n en (re I;i siinulacirtii ric- los nivcirs mrdins anuatc.s dc inin-kio-n do SO, calculados utili/.ando los dalos incu-orol^^icos dr 352 dins, COTI lo.s obtenidos a prrtir dr los ciuilro dins lipo en quo e.stos sc clisihcan (Media anual lipo). FIGURE 3