analysis of the daily variations of wintertime air pollution concentrations in the city of graz,...

*Corresponding author.E-mail address: [email protected] (R.A. Almbauer).

Atmospheric Environment 34 (2000) 4581}4594

Simulation of the air quality during a "eld studyfor the city of Graz

R.A. Almbauer*, D. Oettl, M. Bacher, P.J. Sturm

Institute for Internal Combustion Engines and Thermodynamics, Technical University Graz, Inweldgasse 25, A-8010 Graz, Austria

Received 7 September 1999; accepted 10 May 2000

Abstract

The research project DATE Graz (Dispersion of Atmospheric Trace Elements taking the city of Graz as an example)aimed at the investigation of mesoscale c pollution dispersion of a city in complex terrain. The winter episode investigatedhere was characterised by an anticyclonic fair weather situation. Local wind systems developed together with strongtemperature inversions. During such an episode air quality is dominated by emissions from within the city. The city ofGraz is situated in the southeast of the Alps in the transition area of mountainous to #at land. The city itself is located inthe valley of the river Mur, which forms a basin surrounded by small mountains. In order to understand theemitter}receptor relationship a mesoscale dispersion model was applied for the simulation of air quality during thewinter episode. Input for the simulation was the emission inventory and extensive meteorological measurement data.Results of the simulation re#ect the distinct patterns of daily variations of air quality level measured. The in#uence ofmeteorology, emission patterns and chemical reactions are evident and can be qualitatively and partly quantitativelysimulated by the model. A validation attempt was made using air quality data from the monitoring network. Theintroduction shows the importance of anticyclonic fair weather conditions on pollution dispersion in mountainousregions. Section 2 describes the meteorological situation and the instrumentation during the winter measurementcampaign. Section 3 deals with the simulation model, initial and boundary conditions and the emission inventory for thecity. In Section 4 the simulation results are compared to measurements. Finally conclusions are drawn. ( 2000 ElsevierScience Ltd. All rights reserved.

Keywords: Mesoscale model; Pollution dispersion; Urban air quality; Complex terrain

1. Introduction

For a city like Graz, which is situated in a mountain-ous region, high pollution levels can be expected duringfair weather conditions which results in local wind sys-tems and strong temperature inversions. In a researchproject the air quality of the city was investigated in thecourse of two periods with anticyclonic fair weatherconditions. The project consisted of two intensive mea-surement campaigns for meteorology and air pollution

and their numerical simulation. In order to adequatelyexplain the daily variations of pollution concentrations,a high temporal resolution of emission rates is just asimportant as data on meteorological parameters andchemical reactions of pollutants. This paper describesresults of the simulation for the winter measurementcampaign (10}13 January 1998) and their comparisonwith observations.

Although the city of 250,000 inhabitants is home tolittle industrial activity, tra$c and domestic heatingcause poor air quality during stagnant wind conditions.Air pollution studies for cities in di!erent mountainousareas (Wanner, 1991; Moussiopoulos et al., 1995) showthe great in#uence of local wind systems on air quality.Meteorological features like strong inversion layers,mountain-valley wind systems and katabatic wind

1352-2310/00/$ - see front matter ( 2000 Elsevier Science Ltd. All rights reserved.PII: S 1 3 5 2 - 2 3 1 0 ( 0 0 ) 0 0 2 6 4 - 8

Fig. 1. Orography and measurement sites of the Graz winter measurement campaign.

systems have di!erent e!ects on pollution dispersionaccording to the unique topography of an area.

1.1. Local wind systems

Local wind systems are important for air quality levelsunder the described meteorological situations. They aredetermined by the orographical situation. Three typicallocal wind systems can be distinguished for the city ofGraz (Almbauer et al., 1995a; Lazar and Podesser, 1999):

(a) Mountain-valley wind system: A dominant moun-tain-valley wind system exists in the Mur valleynortheast of Graz. The valley has a length of ap-proximately 190km (northeast of Graz) and has itsorigin in the Alps. The "rst 150 km are west}eastoriented, the last 40 km north of Graz are mainlynorth}south. Several basins and side valleys enterthe main valley. This means that production of coldair leads to a mountain wind, which can alreadybe measured in the city 2}3 h after sunset. The

maximum wind speed can be expected in the earlymorning hours and the mountain wind can last until2}3h after sunrise. The mountain wind system isimportant for the northwesterly part of the city,where the wind is channelled through the narrow&nozzle' of the Mur valley near measuring site 8 inFig. 1. During the day valley winds from the southdevelop.

(b) Drainage yows from the tributary valleys east ofGraz: The small valleys in the east of the cityproduce drainage #ows, which occur soon aftersunset. The valleys are of a typical length of10 km and the ridges are approximately 100m high-er than the valley grounds. This wind system isweaker than the mountain-valley wind system. Dur-ing the day the anabatic wind system of these valleysis often disturbed by the southerly winds in the Murvalley.

(c) Cold air from the southerly basin: During the nightand the early morning hours cold air #ows slowlyfrom the south to the north of the city forming

4582 R.A. Almbauer et al. / Atmospheric Environment 34 (2000) 4581}4594

a convergence zone. However, above this #ow fromthe south, the northwesterly mountain wind stillremains intact. There are di!erent driving forces forthis #ow. One is the production of cold air in the #atbasin south of Graz, which #ows to the city centre.A weak heat island e!ect also exists. Criteria for thedevelopment of country breezes are, that winds di-rected to the city centre should have velocities below2m s~1. In the north of the city of Graz wind speedsexceed this value due to the low-level jet. Furtherexaminations of Barlag and Kuttler (1990) in the cityof Dortmund showed a strong dependency on theseason, where the highest frequency of countrybreezes was detected in summer. This is in contra-diction to observations made in Graz (Piringer andBaumann, 1999). A case study with a non-hydros-tatic mesoscale model (OG ttl et al., 2000), showed thatthe most important e!ect is the recirculation of themountain wind on the lee-side of the mountain ridgewest of the city. This #ow generates a vortex witha vertical axis which induces a transport of cold airmasses to the city centre up to a height of 50}100m.The vortex is of importance for the air quality of thecity as it captures the emissions from ground level inthe south of the city and transports them to the citycentre. As this vortex depends on low internalFroude numbers it often occurs during winternights.

2. Graz winter measurement campaign (DATE-GrazProject)

The area investigated is characterised by a continuoustransition from the Alps to #atlands. The major part ofthe city is located in a basin surrounded by small moun-tains to the west and north (Fig. 1). From the east,tributary valleys enter the city basin coming from a smallnorth}south oriented ridge, which forms a barrier ap-proximately 10 km to the east. To the south the ovalbasin (25 km S}N and 15km W}E) is surrounded bysmall hills. The river Mur enters the basin in the north-west through a narrow gap, and leaves it in the south.The contour lines indicate the altitude in 50m intervals.The highest elevation is at a height of 1450m a.s.l. Theposition of the area within Europe is indicated in thesmall square in the lower part of Fig. 1. The Alpsare located northwest of this area.

The winter measurement campaign was designed tostudy a typical winter smog situation. The "rst anticyclo-nic weather episode during that winter started on 9 Jan-uary. The anticyclone in the 500hPa ridge was veryintense and prevented fog by the downdraft of dry aireven at ground level in the area under investigation. Theepisode ended with the advection of ground fog in thelate evening of 12 January. The measurements started at

6 p.m. of 9 January and ended after 82 h in the morning of13 January. During the three days of the "eld experiment,hourly vertical pro"les of wind speed and direction, tem-perature and humidity were measured at four locations(indicated by T-B in Fig. 1) in the chosen area. In addi-tion, one meteorological tower, two SODARs, one eddycorrelation measurement device and at least 15 meteoro-logical standard devices on the ground were in operation.At the same time 1 DOAS system and seven air qualitystations for the measurement of standard pollutants werein operation. Results of the winter measurement cam-paign are presented in comparison to simulation resultsin Section 4.

3. Simulation

3.1. Emission inventory for the city of Graz

The emission inventory for the city of Graz is based onthree source-groups: tra$c, domestic emissions and in-dustry (Sturm et al., 1999). Pollutants investigated arecarbon-monoxide (CO), volatile organic compounds(VOC), nitrogen oxide (NO), nitrogen dioxide (NO

2),

sulphur dioxide (SO2) and dust/soot. VOC is split into

groups according to the RADM2 chemical reactionmechanism (Stockwell, 1990). To ensure the practicalityof the emission inventory as a database for the calcu-lation of air quality a high temporal and spatial resolu-tion is used. Data was calculated at hourly intervals forthe present study and based on a spatial map consistingof quadrants 250]250m in size. All data is stored ina geographical information system. The term tra$c,comprises emissions from passenger cars, trucks, publicbus transport and diesel driven rail transport. Tra$c onindividual roads was determined using a capacity-depen-dent road selector. Tra$c emissions depend on para-meters like power and capacity of the engine, combustionprocess, fuel type, operating conditions, altitude andinclination of streets.

Household emissions include domestic heating andalso emission from all other private activities. Emissionsfrom domestic heating were calculated using statisticaldata from the regional government. This covered heatingsystems, living space and average ambient temperatures.Industry emission is divided into two parts: All the largerindividual emitters were investigated in a survey. The restis treated statistically using Selected Nomenclature forAir Pollution code (SNAP) and number of employees.Fig. 2 shows the share of the three source groups for thedi!erent pollutants for the year 1995 (Sturm et al., 1999).Approximately, 2/3 of NO

xis emitted by tra$c and 1/4

by industry.Fig. 3 shows an example of the spatial distribution of

the NO emission for two di!erent hours on an averageworking day. Di!erences between nighttime and the

R.A. Almbauer et al. / Atmospheric Environment 34 (2000) 4581}4594 4583

Fig. 2. Results of the emission inventory for the City of Graz.

Fig. 3. Spatial distribution of NO emissions at two di!erent hours for squares of 250]250m.

morning rush hour are evident. The city centre is morepolluted than the suburbs.

Fig. 4 shows the temporal variation of NOx-emissions

of the whole city together with the mean NO- and NO2-

concentrations during the measurement campaign. Thegreat di!erences in NO

x-emissions between individual

days can be explained by the fact that the "eld experi-ment started on 10 January, a Saturday, and ended on 13January, a Tuesday. Tra$c of private passenger cars andpublic buses on a Sunday is predicted by the emissioninventory to be approximately 40% of the level of anaverage workday, while tra$c of heavy duty vehicles isreduced to approximately 14%. This explains the low-level of NO

x-emission. Industrial emissions of NO

xare

also reduced at the weekend to a value of approximately20% of a mean working day. Values for Sundayare statistically less secure than on working days. OnMonday 12 January, NO

xemissions reached 108% of

a mean working day with all the expected features ofa morning rush hour and a second peak during the lateafternoon.

The comparison of inventory results show a goodcorrelation with the peaks of the measured NO-concen-trations for all three days.

3.2. Description of the mesoscale model

Simulations have been carried out using the mesoscalemodel GRAMM (Graz mesoscale model) developed atthe Technical University of Graz. A detailed descriptionof the model equations and numerics can be found inAlmbauer and Oettl (2000). Mass divergence is surfacecontrolled instead of volume controlled, thus a staggeredgrid is not necessary. The disadvantage is the increasednumber of grid points for which non-hydrostatic pressurehas to be computed (Almbauer, 1995b). For turbulencea local closure of an order of one and a half is used. Ona terrain following grid the prognostic equations for thethree cartesian wind velocities, humidity, potential tem-perature, turbulent kinetic energy and pollutants aresolved. The vertices of the lowest grid cells correspond toorographic height at that location. So orography is


Fig. 4. Temporal variation of NOx-emissions and concentrations of NO and NO

2.

smoothed randomly depending on horizontal grid re-solution. Advection is calculated using a TVD scheme.

Di!erent boundary conditions are implemented.For humidity, potential temperature, turbulent kineticenergy and boundary parallel wind components a zero#ux condition is assumed. Advection normal at theboundary is treated similar as in other mesoscale models(SchluK nzen, 1997; Adrian and Fiedler, 1991; Pielke, 1984)by use of the Orlanski condition at in#ow boundariesand use of the upstream scheme at out#ow boundaries.On the upper boundary, damping layers prevent upwardpropagating waves. So the horizontal wind componentsare forced towards the prevailing geostrophic wind, whilethe vertical wind reaches zero on the top of the modeldomain. Potential temperature and mixing ratio are setequal to larger scale values. The damping layer followsthe formulation of Ka> llberg (1977):

uD"u!a(u!u

S), (1)

a"1!tanhAaa

N!3[NK!k]B. (2)

Here uS

is the large-scale value of the variable, and uD

isthe damped one. a is the damping factor increasing withheight, NK is the total number of grid points in thevertical and k is the number of the actual grid point. Thevalue for N is set to 4 and for aa it is set to 0.6 (SchluK nzen,1988).

Pollution transport and chemical reaction of the pollu-tants are calculated in another section of the modelafterwards. In this section of the model the conservationequations are solved for 38 of 62 species of the RADM2reaction mechanism. Twenty species are assumed to beshort lived and in chemical equilibrium. N

2and O

2con-

centrations are treated as constant and water vapourand temperature are taken from the meteorologicalsimulation. Reaction velocities are calculated using theArrhenius equation. Photolysis rates are calculated

according to Madronich (1987). Emission rates aretaken from the emission inventory of Graz (Pischingeret al., 1997).

3.3. Initialization and model domain

The selected horizontal extension of the model domainwas 16 km in a west}east direction and 18 km insouth}north direction. The upper boundary was set at6860m above sea level. For the x-, y-, z-axes, 40]45]20grid points were used, respectively. This resulted ina horizontal grid spacing of 400m in each direction. Thevertical cell height is variable and starts with 20m for thecell closest to the surface and increases by a factor of 1.25from cell to cell towards the upper boundary. Landusedata were available for a grid spacing of 10]10m overthe model in coordinated information on the envir-onment (CORINE) format. In the mesoscale model 23di!erent land use categories are distinguished. A self-adapting time-step was used which varied between 1 and10 s.

In order to get a realistic simulation of transport andchemical reactions for various species without the nestingapproach from macroscale to mesoscale } c, initial andboundary conditions were directly obtained from thenumerous observations within the model domain by ob-jective analysis. For the mesoscale domain } {, Seaman etal. (1988) suggested the centre outward balancing tech-nique to produce wind "elds from observations in orderto avoid spurious oscillations. In a "rst step, mass diver-gence is reduced at each pressure level inside the modeldomain using the vertical component of the relative vor-ticity. Geostrophic balance is maintained at the upperpressure levels. In the surface layer no corrections weremade and in the other layers geostrophy was obtainedwhile taking a homogenous static stability into account.

In this application no corrections were made on theinterpolated wind "elds except that overall mass balance


Fig. 5. Time}height diagram of the measured O3

concentrations at site 15.

was ful"lled. The forcing of the wind "eld in themodel came only from lateral boundaries with a constantgeostrophic wind as in Adrian and Fiedler (1991) andAdrian (1994). On the lateral boundaries a radiationcondition with an additional term for changing large-scale values was implemented (Carpenter, 1982):

Lu

Lt"!Cr

Lu

Ln#

LuS

Lt#Cr

LuS

Ln(3)

with Cr being the phase velocity of u normal to theboundary, u

Sthe large-scale value, and n the direction

normal to the boundary.The last term on the right-hand side is interpreted

as relaxation towards the large-scale value on theboundary. A rather weak relaxation "gure was used hereresulting in high damping near the lateral boundaries.Evaluations of Kunz (1995) showed better results fora lower damping in idealised simulations, but with thedisadvantage of being numerically more unstable.

Since the soundings used for the interpolation areclosely spaced, di!erences in the measured temperaturesdue to systematic errors, etc., would have a great e!ect onthe simulations through spurious circulations. Henceonly the soundings of site 14 in the centre of the modeldomain were used to gain initial and boundary condi-tions for temperature. No analysis for the de"nition ofthe basic state for the temperature and pressure wasavailable for this study, so a static approximation wasmade without a horizontal gradient from the initial tem-perature and the mixing ratio, taking into account hy-drostatic balance but neglecting geostrophy. The error isof the order of the Coriolis force, which plays a minor

role in the boundary layer. Above this layer the imple-mented damping layers keep the error small in this re-gion. For intercomparison with observations the discretevalues in the model grid were linearly interpolated alongthe vertical axis.

Initial and boundary conditions for the pollution dis-persion model in GRAMM were as follows: At the begin-ning of the simulation and at lateral boundaries theconcentrations of all pollutants are kept to zero. Only forO

3was the concentration kept constant at a value of

40 ppb in the beginning and at all boundaries, accordingto the mean values of the vertical soundings.

4. Comparison of simulation and measurement results

4.1. Wind xelds

4.1.1. Measurement resultsMeasurement data of the winter campaign showed the

expected local wind systems. The mountain valley windsystem of the river Mur is clearly documented in theobserved vertical wind pro"les south (Fig. 5) and north(Fig. 6) of the city centre. The arrows in the diagramsshow the hourly measured horizontal wind direction andwind speed up to a height of 500m above ground level.Approximately, 2 h after sunset at 18:00 LST (Local Stan-dard Time) the mountain wind entered the basin of Graz.It reached ground level on 10 and 11 January in the northof the city centre at site 9. South of the city centresoutherly wind directions remained even at the beginningof the valley wind. During the night the southerly #owdeveloped and increased in depth up to a height ofapproximately 100m } as can be seen in Figs. 5 and 6.


Fig. 7. Time}height diagram of the observed (left) and modelled (right) wind "eld at site 9.

Fig. 6. Time}height diagram of the observed (left) and modelled (right) wind "eld at site 14.

Above, the low-level jet of the mountain wind withvelocities up to 8m s~1 remained during the night andended in the late morning. The centre of the low-level jetmoved to higher altitudes during both nights. During theday a weak valley wind from the south developed. Thedepth of the valley wind correlated well with the depth ofthe isothermal layer (Fig. 9).

The measured time height diagram of ozone (Fig. 5) andtemperature (Fig. 10) at site 14 indicate the build up ofa well-mixed layer during all three days (10}12 January)between 11:00 and 15:00 LST. During the night an inver-sion layer with a growing height was measured. Di!er-ences between the situations north and south of the cityare explained in detail in Piringer and Baumann (1999).

Di!erences are accounted for by the in#uence of the in-creased roughness length in the city on the mountain wind.

4.1.2. Simulation resultsThe dominant mountain-valley wind system of the

Mur valley is reproduced well in the simulation (Fig. 8).The arrows show the measured wind direction at a heightof 10m above ground level at "ve sites. The diameter ofthe circle gives the wind speed. Whereas the change fromup valley to down valley winds occurs rather quickly inreality, for 11 January, 19:00 LST, the simulation showsa somewhat slower change from southerly to north-easterly and northwesterly directions in the surface layer.Simulated wind speed of the up valley wind agrees well


Fig. 8. Modelled wind "elds 10 m above ground level at di!erent times.

with observations, but the low-level jet during the nightswas rather underestimated by the model (Figs. 6 and 7).

Right after sunset (Fig. 8: 11 Jan } 19:00 LST and 12Jan } 19:00 LST) southerly winds below the low-level jetform a convergence zone moving from south to northduring the night (Fig. 8: 11 January } 1:00 LST and 11

January } 7:00 LST; 12 January } 1:00 LST). The gainingin strength and depth of this #ow system in the course ofthe nights is simulated but with a lower extension in thevertical.

The observation site 9 is close to the narrow incomingvalley of the Mur river north of the city. The diurnal


Fig. 8. (Continued ).

change in wind direction caused by the mountain-valleywind system is also observed here. Again the simulationre#ects this wind system well (Fig. 7).

The change from down-valley wind to up-valley windoccurs apparently at lower heights "rst, approximately

at 11:00 LST. In comparison to the modelled wind "eld,actual measurement data revealed a delay of this change inwind direction in the surface layer of about 3h. The large-scale advection of cooler air beginning on 12 January atabout 22:00 LST is somewhat overestimated by the model.


Fig. 9. Time}height diagram of the observed (left) and modelled (right) temperatures at site 9 north of the city centre.

Fig. 8 shows simulated wind "elds 10 m above groundlevel at di!erent times. During the nighttime hoursa complex wind "eld developed with a convergence zonemoving north in the course of the night (Fig. 8: 11January 1:00 LST and 11 January 7:00 LST). In thenorthwestern part of the town channelling of the downvalley wind occurs in the narrow valley of the river Mur.As mentioned above, the smoothed orography usedin the model causes somewhat lower wind speeds thanactually observed. Local drainage #ows at the easternside of Graz are not reproduced by the model. Again thismight be attributed to the smoothed topography and/orto the limited area used in the simulation. The valleywind (Fig. 8: 11 January 13:00 LST and 12 January 13:00LST) is marked by southerly directions and lower windspeeds than the nocturnal low-level jet.

4.2. Temperature xelds

Modelled temperature at site 9 agrees well with obser-vations during nighttime hours, where an inversion layerwith a temperature increase of 6K within the "rst 250mabove ground level developed (Fig. 9). During the day-time the inversion breaks up and an isothermal strati"ca-tion is observed. The warming of the air after sunrise andalso the cooling in the afternoon is somewhat slower inthe simulation than in nature. Large-scale advection ofcold air in the afternoon of 12 January is however wellreproduced in general. Great di!erences prevail in thebeginning of the simulation. This is mainly due to thefact, that initial temperature was taken from the sound-ing at site 14 (south of the city centre), where the mea-sured temperature was some Kelvins lower than at site9 (north of the city centre). The reason for the highertemperatures at the latter site is the higher turbulencedue to channelling during the night, mixing warm airabove with cold with cold air below.

At site 14 (Fig. 10) the course of the temperature is inprincipal the same as at site 9. The cooling during night-time hours is somewhat less than observed. Taking intoaccount, that the speed of the southerly winds duringnighttime in the city of Graz was overestimated by themodel, it may be concluded, that the turbulence para-meterization for the surface layer underestimates theturbulent viscosity. However, the inversion break up withthe development of an isothermal strati"cation ismodelled satisfactorily.

4.3. Air quality values

Air quality results are presented for NO and NO2

asthey are the pollutants which are closest to exceedingpresent threshold values. Nitrogen oxide concentrationsare in#uenced by all of the following: (a) the daily andhourly variation of emission rates depending on tra$cand industry activity, (b) the complex #ow "eld deter-mined by the local wind system, (c) chemical reactionswhich are important for the conversion of NO to NO

2.

4.3.1. Measurement resultsIn order to explain in general the daily variations of

NO2-concentrations, the mean NO- and NO

2-concen-

trations for the whole city were calculated from sites 1, 2,3, 5 and 1 (DOAS) (Fig. 4). As the conversion of NO withO

3, HO

2and RO

2to NO

2occurs within minutes (Fin-

layson-Pitts and Pitts, 1986) both concentrations canonly be considered together. NO-concentrations duringboth nights from 10 to 11 January and from 11 to 12January are on a level of approximately 100lgm~3.NO

2-concentrations decrease from approximately

75lgm~3 in the evening to 40 lgm~3 in the early morn-ing. On Saturday and Sunday NO values increase onlya little in the morning hours. On Monday a strong


Fig. 10. Time}height diagram of the observed (left) and modelled (right) temperatures at site 14 south of the city centre.

Fig. 11. Calculated and measured NO- and NO2-concentrations at site 1.

increase over time, up to the daily maximum of morethan 400lgm~3 at about 8:00 LST was recorded. NO

2-

concentrations rise slowly after sunrise with a Monday-maximum of more than 120lgm~3, 3 h after the NOmaximum at about 11:00 LST. During that time theconversion rate from NO to NO

2dominates the in-

creased dispersion due to the growth of the well-mixedlayer. The fast conversion of NO to NO

2is caused by the

down-mixing of O3

from higher altitudes (Fig. 5). TheO

3concentration during all three days in the residual

layer above the inversion is about 30}40ppb. All threedays show a distinct minimum NO concentration duringnoon with values less than 40 lgm~3. NO

2-decrease

more slowly to values between 40 and 60lg m~3. Duringall three days NO-concentrations increase shortly afterthe breakdown of the well-mixed layer at 15:00 LST. OnSaturday and Sunday the maxima in the afternoon arehigher as a result of increased tra$c. On Monday thesecond NO maximum is lower. NO

2-concentrations

show the same behaviour as NO for their maxima on all

three days. The sum of NO and NO2

concentrationdecreases after 19:00 LST in line with the normal reduc-tion in emissions. NO-concentration shows a good coin-cidence with predicted emission rates. Vertical soundingsof O

3for the three days con"rmed the assumption of

O3

down-mixing (Fig. 5). During the "rst two days, theozone values in the lowest 150}200m increase with a rateof about 5 ppb per hour between 11:00 and 15:00LST.The maximum values reach up to 20 ppb. During the restof the days the ozone concentrations were at a level lessthan 1.5 ppb near ground. Daily mean values of ozoneconcentrations at the monitoring stations 2, 4 (at the cityground level) and 11, at a height of 210m a.g.l. showa strong vertical strati"cation. The temperature inversionand weak winds prevented an exchange of air masses.

4.3.2. Simulation resultsAir quality values are calculated using the results of

the emission inventory and of the mesoscale modelGRAMM. The meteorological results were calculated in




advance and stored in "les for every full hour. This datawas then read into that section of the model where thetransport and chemical reaction of pollutants are cal-culated. Results are presented in comparison to the airquality measured values at three monitoring stations inthe city (Fig. 1: sites 1, 2 and 6) at a height of 10m aboveground level. The simulations started at 8:00 LST on 10January and the presented concentrations increased rap-idly to their equilibrium. This is explained by the fact thatcity of Graz is the major pollution source, thereforeconcentrations are mainly dependent on local emissions.

Comparing the simulated NO and NO2-concentra-

tions at site 1 with measurement data, the followingresults can be seen (Fig. 11). The "rst strong increase ofconcentrations during the morning rush hours on Satur-day and on Monday is simulated well with respect totime and magnitude. The decrease of concentrations dur-ing the day is not reproduced by the model. This is alsotrue for NO

2. Obviously, this e!ect can be accounted for

by vertical dispersion, which is too weak in the model.The second peak during the afternoon is also not givencorrectly by the model for all three days. NO and NO

2-

concentrations are too small during the night from Satur-

day to Sunday. Emissions must have been under-estimated by the emission inventory due to leisure timetra$c. Sunday emission rates are uncertain as they de-pend on a variety of di!erent phenomena in#uencing theleisure-time activities, e.g. weather conditions. SimulatedNO

2match real observations quite well in terms of level.

Individual peaks for Saturday morning and evening andthe Monday morning rush hour are not simulated cor-rectly. Simulated results for site 2 (Graz-West) (Fig. 12)show similar behaviour. The decrease of concentrationsduring all three days due to the establishment of a well-mixed layer is not well reproduced by the model. Mea-sured NO-concentrations during both nights are higherthan simulated values. Individual peaks of NO-concen-trations are over- and underestimated. Simulated NO

2-

concentrations are in general too high during the day dueto weak turbulent mixing. Results for site 4 (Graz-Nord)are similar to sites 1 and 2.

Results for sites 3, 5 and 6 are similar to each other. Asan example the results for site 6 (Graz Ost) are shown inFig. 13. At all three sites NO-concentrations are under-estimated. The reason for this might be too low emissionrates or inadequately modelled dispersion conditions.


Reasons cannot be de"ned clearly yet. NO2-concentra-

tions "t measured values quite well. Again NO-concen-trations during the night from Saturday to Sunday areunderestimated by the model.

5. Conclusions

The research project for the City of Graz aimed at theinvestigation of small mesoscale pollution dispersion incomplex terrain during fair weather conditions. The areainvestigated is situated in the southeast of the Alps in thetransition area from mountains to #at land. The city itselfis located in the valley of the river Mur, which formsa basin surrounded by small mountains. The winter epi-sode investigated was characterised by an anticyclonicfair weather situation. Measurement data of the wintercampaign show the expected local wind system togetherwith strong temperature inversions in the basin. Duringsuch an episode, air quality is dominated by emissionsfrom the city.

The aim of the study was the accurate simulation of allin#uences on air quality during the experiment in orderto understand the emitter}receptor relationship. Airquality results are presented for NO and NO

2as they are

the pollutants which are closest to exceeding presentthreshold values. Nitrogen oxide concentrations are in-#uenced by all of the following: (a) the daily and hourlyvariation of emission rates depending on tra$c and in-dustry activity, (b) the complex #ow "eld determined bythe local wind system, (c) chemical reactions which areimportant for the conversion of NO to NO

2. The meso-

scale dispersion model GRAMM was applied for thesimulation. Instead of using a nesting procedure initialand boundary conditions were directly obtained from thenumerous observations within the model domain by ob-jective analysis.

As can be seen from the measurement results, it isnecessary to have an emission inventory with a goodspatial and temporal resolution. Therefore, data was re-corded at hourly intervals for the present study andbased on a spatial map consisting of quadrants250]250m in size. Almost 2/3 of the NO

xemission stem

from tra$c. Results for the investigated episode re#ectweekday in#uence on the tra$c emissions. As 11 Januarywas a Sunday, emissions from tra$c are considerablylower than on Monday.

In order to predict air quality values, it is a prerequisiteto simulate the complex #ow "elds correctly. The domi-nant mountain-valley wind system of the Mur valley withits characteristic diurnal change in wind direction fromnorthwesterly winds in the night to daytime southerlywinds, is reproduced well in the simulation. Simulatedwind speed of the up-valley wind agrees well with obser-vations. Local drainage #ows on the eastern side of Grazwere not reproduced by the mesoscale model. Modelled

temperature agreed well with observations during night-time hours, where an inversion layer with a temperatureincrease of 6K within the "rst 250m above ground leveldeveloped. During the day the inversion broke up and anisothermal strati"cation was observed. The warming ofthe air after sunrise and also the cooling in the afternoonis somewhat slower in the simulation.

Concerning the simulated NO- and NO2-concentra-

tions at site 1, 2, and 6 the following results can be seen.The "rst strong increase of concentrations during themorning rush hours on Saturday and the Monday issimulated well with respect to time and height. Thedecrease of concentrations during the day is not repro-duced well by the model. This is also true for NO

2concentrations. Obviously, this e!ect can be attributed tothe model's inability to accurately capture vertical dis-persion. The second peak during the afternoon is alsoincorrectly captured by the model for all three days.Simulated NO

2-concentrations "t quite well in terms of

their level. Individual peaks for Saturday morning andevening and the Monday morning rush hour are notcalculated correctly. Results for the other sites showsimilar behaviour. At most sites NO-concentrations areunderestimated. The reason for it might be too low emis-sion rates or wrong dispersion conditions.

In conclusion the whole exercise with the calculationof emissions, meteorology, dispersion and chemical reac-tions the results are reasonable good. Although the simu-lation can not predict peaks correctly, the average valuesare met well. Summing all possible sources of error inemissions, in meteorological dispersion conditions andin chemical reactions, it becomes clear that results mightbe wrong by a large factor. For NO and NO

2the results

can at least be used to investigate the emitter}receptorrelationship.

Acknowledgements

The research project DATE Graz (Dispersion of At-mospheric Trace Elements taking the city of Graz as anexample) was funded by the Austrian Science Fund(FWF) under project numbers P12168-TEC, P12169-TEC and P12170-TEC.

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