“air-quality indicators” for uniform indexing of atmospheric pollution over large metropolitan...

Atmospheric Environment 33 (1999) 1861—1879

‘‘Air-quality indicators’’ for uniform indexingof atmospheric pollution over large metropolitan areas

P. Kassomenos!,*, A.N. Skouloudis", S. Lykoudis!, H.A. Flocas!

!University of Athens, Department of Applied Physics, Laboratory of Meteorology, Building PHYS-5, Panepistimioupolis, GR-157 84,Athens, Greece

"Environmental Monitoring, European Commission, Joint Research Centre Ispra, T.P. 250, I-21020 (VA), Italy

Received 23 December 1996; received in revised form 1 October 1998

Abstract

National and international authorities recommend a variety of air-quality standards that should not be exceeded inlocal and regional scales currently. With this work a uniform indexing scale is introduced which characterises severalurban pollutants in a simple and comparable manner. The ‘‘indicators’’ proposed are implemented at the AthensMetropolitan Area (AMA) which is an area with serious pollution problems. Hourly data from all available monitoringstations are analysed during 1983 and 1995. This analysis demonstrates that the status of air quality in Athens can becharacterised as acute with regards to photochemical pollutants while strong spatial and temporal variability isencountered for all pollutants. ( 1999 Elsevier Science Ltd. All rights reserved.

Keywords: Urban pollution assessment; Indicators; Monitoring atmospheric data; Athens Metropolitan Area; Stan-dards and indexing

1. Introduction

Large-scale industrialisation, population inflow inlarge metropolitan centres located in complex topogra-phic areas, and unfavourable meteorological conditionsinduce significant degradation of urban air quality. Be-cause of the health effects associated with these condi-tions it is of great interest to characterise the status of airquality for several pollutants such as O

3, CO, SO

2, NO

2,

particulate matter, etc.For determining the status of these pollutants,

monitoring stations are usually placed at the centre andperiphery of urban areas as well as in surrounding rural

*Corresponding author.

areas. The procedure of positioning these stations isdifferent from country to country and the measuringinstruments employed vary for the different pollutants. Inaddition, the spatial representativity of the measurementsdepends greatly on the complexity of topography and theexistence of nearby sources. For several European metro-politan areas this complexity prevents the establishmentof representative urban background stations in mostdomains. Furthermore, the annual availability of thesedata is not usually 100%.

However, for characterising the status of pollution andfor providing realistic forecasts it is essential to general-ise. This generalisation needs a uniform reference scalefor all pollutants which could be applicable in metropoli-tan and in relatively cleaner rural areas. It should beeasily understandable while able to account for spatialand temporal variations.

1352-2310/99/$ — see front matter ( 1999 Elsevier Science Ltd. All rights reserved.PII: S 1 3 5 2 - 2 3 1 0 ( 9 8 ) 0 0 3 5 5 - 0

Various studies have been carried out in the past forcharacterising the status of air quality. These attemptsfocused mainly on photochemical pollutants with anemphasis for ozone like the works of Comrie and Yarnal(1992), and Comrie (1994). Altshuller (1986), and Atkinsand Lee (1995) studied nitrogen oxides in United Statesand England respectively, while Lalas (1992), studied thelevels of atmospheric pollution in Mediterranean in com-parison with the health effects.

On the other hand, several international organisationssuch as the European Commission and the World HealthOrganisation have introduced standards or guidelinesfor air quality. These standards or guidelines should beapplicable throughout the member states in a uniformand comparable way. The actual values associated withthese standards and guidelines change frequently as moreinformation for health effects become available andprogressively become more strict in order to achievemaximum attainable conditions over the European terri-tory or in order to take into account appropriate healtheffects. But, until now, no complete reference scale for‘‘labelling’’ air quality has been established due to thescarcity of monitoring data from comparable urbanareas. These data were not usually representative fordifferent climatic conditions such as in North and SouthEurope. Furthermore, the level of public awareness onpollution problems varies enormously across differentcountries and there are complications in the aims ofcompetent authorities that are involved in analysingmonitoring data.

Based on the proposed standards and guidelinesrather simplistic scales can be introduced which are usu-ally for individual pollutants and are unfortunately ap-plicable only for polluted urban areas where these valuesare usually exceeded. On the other hand, the standardsand the guidelines set are usually for the highest percen-tile values over various averaging periods which arefrequently changing in order to implement new objec-tives. Thus, it is difficult to incorporate standards intoa reference scale. A study on the introduction of a set ofintegrated air quality indices, a long and a short term, forthe city of Stuttgart (Baumuller and Reuter, 1995),utilised groups of pollutants of relevance to the areaconsidered, namely SO

2, NO

2and dust. The methodo-

logy proposed allowed for the inclusion of othergroups of pollutants as long as appropriate data areavailable for the calculation of the weights relevant toeach pollutant. However, the scale proposed is based oneither the international limit values or arbitrary stricterlimits to account for the precaution character of plann-ing. The generalisation of this method for other urbandomains required that air quality is characterised bya similar group of pollutants with additive character-istics. On the other hand, meaningful limit of the indi-vidual components of the guidance pollutants should beappropriately selected.

Similar to Stuttgart, in Helsinki a simple air-qualityindex is operational on daily and monthly basis (Ott andHunt, 1976; Mignnacca et al., 1991; Makinen and Pihl-strom, 1995). The pollutants included are CO, NO

2, SO

2,

O3

and PM10

. Combined effects of the different pollu-tants are not included. Hence, the description of theoverall air pollution by an air pollution index is notpossible due to the nature of urban pollution and due tothe methodology used in each indexing system. In anycase it is absolutely necessary to indicate from whichpollutant and with which reference values this index iscomputed as well as the reference/averaging period foreach pollutant.

For planning purposes, and for advising the popula-tion about the status of air pollution in urban domains,an air pollution index is meaningful and helpful. Irre-spective of the position where measurements are takenand if the international standards are exceeded at thispositions, with this work a uniform indexing methodo-logy is proposed which results in comparable air-qualityindications. These are characterised by flexibility in ac-counting several pollutants, adaptability in seasonal/an-nual variations, generality in accounting different urbanconditions and simplicity in communicating statisticalparameters to the general public.

2. The methodology followed in setting air-qualityindicators

The knowledge of maximum-recorded concentrationsand the frequency of exceeding adopted limit values isnot usually enough for assessing atmospheric pollu-tion. This is true for metropolitan areas with severalmonitoring stations as well as for rural areas with scarcemonitoring network.

The status of environmental pollution in an area canbe described using comparable air-quality indicators.Such indicators can be related to the overall status of airpollution via pre-defined set of clearly identified criteria.These criteria should be universal and irrespective of thelevel of pollution where these indicators are applied.

Furthermore, the air-quality indicators should be suffi-ciently flexible to account different levels of populationexposure, variable meteorological and climatic condi-tions occurring in an area, the sensitivity of flora andfauna. The historical heritage of exposures is also ofinterest as well as economical details and medium- andlong-range transport from neighbouring areas.

The establishment of a reference scale characterisingthe status of air quality in the periphery of monitoringsites is a complex process (Skouloudis and Kassomenos,1995). This complexity arises from several pollutantsrequiring diverse abatement strategies, the physicaland chemical processes associated with them, the differ-ent aims for which standards are set, the number of

1862 P. Kassomenos et al. / Atmospheric Environment 33 (1999) 1861—1879

Table 1Selection of appropriate limits for the scale of air-quality indicators

Value Alternative 1 Alternative 2

CUL

Upper protection limit Upper protection limitCLL Lower protection limit Lower protection limitCTV Target value; set by standards Short term target valueC

AVAlert value; required by standards Alert value; 0.85 of the C

TVvalue

CIV

Intermediate value; (the limit for vegetation protection whenthis limit is lower than the value for health effects)

Intermediate value; approximated by (CTV

#CAM

)/2

CAM

Annual mean limit when specified by standards Annual mean value from recorded data

competent authorities introducing standards or guide-lines and the frequent modifications of such standardsintroduced by these authorities.

Due to the different consequences of each pollutant onhuman health the reference scale must treat each pol-lutant separately. For the establishment of this scalethe principal idea is to utilise, whenever possible, wellpre-established air-quality standards and at the sametime account for local conditions assessed via statisticalanalysis of data recorded in each monitoring stationseparately. The terms usually applied in characterisingvarious levels of exposure for humans and/or vegetation,according to the terminology utilised by the directives ofthe European Commission are:

f ‘‘Limit Value’’: This value is the limit to be avoided inorder to prevent or reduce harmful effects on humanhealth and/or the environment as a whole.

f ‘‘Target Value’’: A value to be attained wherever pos-sible.

f ‘‘Alert Threshold’’: Level indicating risk to human health.f ‘‘Guide Value’’: The value recommended below which

environmental effects are insignificant.

The principles on which the reference scale for air-quality indicators is instituted are:

f It is necessary to protect the most sensitive groups ofpopulation.

f Targets should be set for achieving better air-qualityenvironment.

f Warnings need to be issued whenever human health isendangered.

f Vegetation damage should be avoided.f Past air-quality conditions over rolling annual periods

should be accounted.

Based on the above principles the following distinctlevels of air-quality concentrations can be introduced.These limits follow directly from the aforementionedprinciples and are also summarised in Table 1.

f Annual mean concentration (CAM

). Annual conditionsfrom past measurements are used for examining tem-

poral variations on a regular basis during past years andnot purely on the basis of health- or vegetation-basedstandards. When such annual standards exist and areexceeded in polluted areas this value is set to the desiredC

AMaccording to the value required by the regulatory

authorities. When this standard is not exceeded or inthe absence of recommended annual mean conditions,statistical analysis of past data can be consulted andthe most frequent annual mean value can be used.

f The target value (CTV

) is usually related to the stan-dard limit values and is applicable to short averagingperiods. When a target value is not recommended it ispreferable to set this target value according to mostprobable daily concentrations.

f The upper (CUL

) and lower protection limits (CLL

) areboth values usually set by standards and guidelinesbased on health protection. The lower limit is set equalto the proposed standard limit value for health protec-tion, while the upper limit represents higher valuescorresponding to greater health risk and worse air-quality conditions. Should there be no national or localstandards for control measures associated with healthrisk during the two different averaging periods, or thereis no available air-quality data one might considerC

ULas double the value of C

LL.

f The intermediate range between the target concentra-tions and the annual mean conditions are characterisedby (C

IV). This is set equal to the concentration given for

the vegetation protection. When this value is morethan the limit for health effects the vegetation limit isconsidered as C

LLand the intermediate value is set half

way between the target and the value set for CAM

.f The final subdivision is between the target value

CTV

and the intermediate value CIV

. The purpose is tocharacterise situations where population needs to bewarned of critical conditions. This is achieved via alertconcentration (C

AV) which is set by competent authori-

ties for some pollutants. If such a limit value is notcommunicated it is set equal to 85% of C

TV.

The limits are set for each station and pollutant. Foreach pollutant, two alternative definitions are necessary

P. Kassomenos et al. / Atmospheric Environment 33 (1999) 1861—1879 1863

Fig. 1. Source attribution of NOx

emissions in the Metropolitan Area of Athens.

Table 2The indices of air-quality indicators scale and air-quality classes

Index Air-quality indicator Limits

7 Extreme C'CUL

6 Severe CUL

*C'CLL

5 Bad CLL*C'C

TV4 Critical C

TV*C'C

AV3 Poor C

AV*C'C

IV2 Moderate C

IV*C'C

AM1 Good C

AM*C

for setting the characteristic concentrations where noappropriate limits are available. Also, they account forthe cases when the site in which this scale should beapplied is located in a relatively clean ambient wherelimit values are never exceeded.

According to the above scale, indices characterisingthe status of air quality in an area can be introduced as inTable 2. The indices assigned to the scale of air-qualityindicators are in reverse order of severity and can be usedfor a deterministic categorisation. The critical indicatorat the middle of the scale characterises concentrationsapproaching the target value hence critical to enteringthe upper part of the scale with the worst air-qualityconditions.

Based directly on the measured concentrations at eachsite and their direct reference to the scale of air-qualityindicators, characteristic classes can be calculated.

In urban domains, the assessment method adoptedshould mainly address the population risk, while ina semi-urban or rural domain it should also account for

the effects on flora and fauna. Hence the alternatives inTable 1 primarily depend on the domain where monitor-ing stations are located.

3. The use of air-quality indicators in Athens

The method described above has been applied in anurban area characterised by well-known pollution prob-lems. The Athens Metropolitan Area (AMA) covers450 km2 and is inhabited by 3.6 million people. Thetopography with respect to air pollution is rather un-favourable because the main built-up area is located ina basin, surrounded by high mountains. These moun-tains cover three sides of the domain and only the southside is open to the sea (Kassomenos et al., 1995). In thisarea more than one million cars are registered. There arealso strips with medium size industrial activities in theSouth and Southwest suburbs of the Metropolitan Areaof Athens. Heavy industrial activities are mostly locatedat the nearby Thriassion plain which is located on theWest Side west of the metropolitan area.

Emissions in the area of Athens are mainly caused bytraffic (Vyras, 1995). This is also illustrated in Fig. 1 fromthe emission inventory of Auto-Oil 1 (1996) for NO

xwhere transport contributes 52% of annual emissionsover the AMA.

In the area of Athens an official monitoring network of11 air pollution stations has been operating since 1983.The main pollutants measured are SO

2, black smoke

(BS) and NO2, NO, and O

3. Details for the monitoring

methods can be found in PERPA (Hellenic Ministry ofthe Environment, 1989). In Fig. 2 the area and the posi-tions of the monitoring stations are shown. The position


https://www.researchgate.net/publication/222501085_Analysis_of_climatological_and_air_quality_observations_from_Greater_Athens_Area?el=1_x_8&enrichId=rgreq-fc86ad88-616c-4f30-9d80-daef815c4995&enrichSource=Y292ZXJQYWdlOzIyMzI0NDQzMDtBUzoxMDQyNzY4NTI0Nzc5NTZAMTQwMTg3Mjk0NzIyMA==

Table 3Operational air quality monitoring stations at the AMA

Codename Location Operated since Inlet height (m) Pollutants measured Description

ARI Aristotelous Str. 1994 5 NO2, SO

2, CO, BS Wide Road Heavy

TrafficATH Athinas Str. 1988 5 NO

2, O

3, SO

2, CO, BS Narrow street

Medium TrafficGEO Geoponiki 1983 4 NO

2, O

3, SO

2, CO, BS Wide Road Medium

TrafficLIO A. Liossia 1983 8 NO

2, O

3, SO

2, CO Rural Area

LYK Lykovrisi 1994 4 NO2, O

3, CO Residential Area

MAR Amarousion 1987 4 NO2, O

3, SO

2, CO, BS Urban Background

Station, ResidentialPAT Patission Str. 1983 8 NO

2, O

3, SO

2, CO, BS Wide Road Heavy

TrafficPEI Peireas 1984 4 NO

2, O

3, SO

2, CO, BS Heavy Traffic, Cross-

ing, SquarePER Peristeri 1990 4 NO

2, O

3, SO

2, CO, BS Wide Road, Square,

Medium TrafficREN Rentis 1983—1994 4 NO

2, O

3, SO

2, CO, BS Wide Road, Square,

Medium TrafficSMI Nea Smyrni 1983 4 NO

2, O

3, SO

2, CO, BS Wide Road, Medium

Traffic

Fig. 2. The area of the Athenian metropolis. The sites of thevarious air-quality stations with their abbreviation are shown.Contours are every 200 m.

of the monitoring stations, their description and the yearwhen these stations were installed are summarised inTable 3 together with all the pollutants measured at eachstation. For various operational and availability reasonsthe pollutants measured at each station differ during the

examined period. The details for each pollutant are givenin Tables 5—9.

In order to derive the air-quality indicators in Athens,the second alternative described in Table 1 is utilised.This is because the AMA can be regarded as an almostentirely urban area and no local limit values are set forvegetation.

The pollutants used for the assessment of air qualityare O

3, CO, BS, SO

2and NO

2. In Table 4 the limit

values for each category are presented as were applied forAthens. Following the recommendation from interna-tional authorities (WHO, 1987, 1995) for O

3and NO

2the 1 h maximum values were used. Similarly, for SO

2and BS the 24 h average were used and for CO the 8 hrolling average. BS was used because PM

10measure-

ments are not reported on a continuous basis in Athens.In European urban areas BS is well correlated withPM

10with a reported range of correlation ranging from

0.53 to 0.74, which is stronger during the winter months(Quality of Urban Air Group, 1996). Preliminary co-located measurements of PM

10and BS, at the station of

Aristotelous in Athens, during two winter months, re-vealed strong linear correlation — PM

10+0.83BS, cor-

relation coefficient 0.87 (Katsouyanni, 1997). Eventhough limit values for pollution control measures inAthens (Vyras et al., 1995) exist, in order to present amore general application, we utilised the upper limit astwice the lower limit value. The resulting upper limitswere the same as the limit values for the first stage of


Table 4Values used in Athens for the AQI scale

Index O3

(lg/m3)1h Max NO2

(lg/m3) 1 h Max CO (mg/m3) 8 h mean SO2

(lg/m3) 24 h meanBS (lg/m3)24 h mean

CUL

360 400 20 250 200C

LL180 200 10 125 100

CTV

90 100 5 63 50C

AV77 85 4.3 53 43

CIV

Per station Per station Per station Per station Per stationC

AMPer station Per station Per station Per station Per station

Table 5Annual mean concentrations for O

3(lg/m3)

O3

1987 1988 1989 1990 1991 1992 1993 1994 1995

ARIATH 53 56 35 30 25 36 45GEO 49 60 52 60 48 28 21 53 51LIO 64 76 94 79 71 66 68 62 62LYK 61 57MAR 22 36 46 69 59 54 61 64PAT 28 27 31 37 34 27 27 32 25PEI 36 50 56 49 42 43 45 41 50PER 38 43 29 51 51 58REN 42 55 62SMI 34 42 46 41 56 58 61 55 52

Table 6Annual mean concentrations for NO

2(lg/m3)

NO2

1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

ARI 93 98ATH 23 88 87 83 78 65 73 70 91GEO 28 36 34 46 58 62 66 55 74 49 44 39 50LIO 16 23 15 24 24 34 36 35 35 22 23 30 34LYK 33 36MAR 33 14 52 41 32 31 36 34 36PAT 95 104 112 107 105 117 121 120 109 117 106 102 95PEI 82 98 91 80 85 75 76 67 75 69 74 65PER 78 71 62 57 46 54 55REN 43 46 42SMI 18 23 20 28 33 40 42 29 37 51 37 51 48

measures, the ‘‘warning stage’’, except for O3, where the

upper limit is 360 lg/m3 and the first stage of measureslimit is 250 lg/m3. Similarly, for BS the correspondingvalues used for the same scales are 200 and 250 lg/m3,respectively. The alert limit is defined according toTable 1, as 85% of the target value and the intermediatevalue is established according to the second alternativeshown by the same table. The annual mean value

CAM

was calculated for each pollutant and each stationevery year. The corresponding values for C

AMare shown

in Tables 5—9.Basic statistical analysis was performed to examine

the consistency of the criteria, actual, values and forestimating the completeness of measured time series.Table 10 shows the most significant statistical para-meters for O

3.


Table 7Annual mean concentrations for CO (mg/m3)

CO 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

ARI 3.8 3.6ATH 4.2 4.9 4.1 4.9 6.7 3.6 3.5 3.2GEO 0.9 1.2 1.3 1.2 1.3 1.9 1.8 1.5 1.4 1.1 2.1 1.9 1.7LIO 1.1 1.3 1.1 1.1 1.3LYK 1.1 1.3MAR 1.2 1.2 0.9 2.2 1.7 1.7 3.4 2.4 1.6 1.6PAT 6.1 8.9 7.6 6.0 6.7 7.4 8.4 7.3 6.7 5.5 5.2 5.4 5.1PEI 3.5 4.2 4.4 4.3 4.7 4.5 4.0 4.0 3.2 4.4 3.5 2.5PER 2.7 2.8 3.8 2.6 1.7 2.7 2.0REN 2.0 1.8 1.6SMI 1.4 2.0 1.8 1.7 1.6 1.7 1.9 1.8 1.9 2.0 1.9 2.0 2.1

Table 8Annual mean concentrations for SO

2(lg/m3)

SO2

1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

ARI 55 33ATH 38 42 47 55 59 54 45 23GEO 7 18 26 16 21 21 34 15 22 33 34 22LIO 13 26 11 25 15 17 53 29 27 36 18 22 20LYKMAR 12 8 21 17 14 17 17 14 16PAT 39 55 47 45 58 82 88 79 67 87 61 57 45PEI 19 24 28 23 62 63 50 73 70 52 44 37PER 25 27 35 27 23 29 23REN 26 31 17SMI 8 17 20 14 18 21 22 21 38 48 33 43 36

Table 9Annual mean concentrations for BS (lg/m3)

BS 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

ARI 123 130 91 118 93 69 64 58 63 72 71 42ATH 63 45 43 54 59 49 50 38GEO 37 31 27 23 29LIOLYKMAR 21 20 19PAT 192 172 139 165 146 123 103 83 86 108 121 99PEI 89 83 60 70 62 37 42 35 33 46 48 47PER 21 33 31 43 32REN 45 43 33 37 37 28 28 18 28 37 23SMI 43 35 25 21 18 23 26 30 22

For each one of the 11 stations and for the five pollu-tants measured a daily index was calculated, according toTable 2. For each monitoring station the daily index forCO was set to the maximum value of eight hours rolling

averages observed during that day. For the overall indexcharacterising the whole domain on a specific day themedian value of the separate indices is used from the 11monitoring stations. For characterising the completeness


Table 10Mean, median, 75, 98 and 99%, maximum 1 h concentrations of O

3(lg/m3), between 1983 and 1995

ARI ATH GEO LIO LYK MAR PAT PEI PER REN SMI

Mean — 38 49 71 59 57 30 47 46 55 50Median — 28 34 64 57 50 22 39 36 50 4175% — 51 76 100 84 82 39 65 64 81 7798% — 125 164 183 142 163 100 137 138 141 14599% — 146 187 212 164 189 112 156 152 156 160Max — 296 392 385 400 420 190 285 304 246 386

of the data recorded over the domain we assumedthat the days where less than four stations gavemeasurements are characterised as days of ‘‘insufficientavailability’’.

4. Results and discussion

The aforementioned methodology was utilised at theMetropolitan Area of Athens for a comprehensive dataset between 1983 and 1995. The results are summarised inTable 11. According to this table for ozone, 45% of thevalid days were classified as ‘‘Bad’’ or ‘‘Extreme’’, 33% as‘‘Good’’ or ‘‘Moderate’’ and 22% in intermediate catego-ries. During 1983 and 1995 only 3% of the days areclassified as ‘‘Extreme’’.

The corresponding values for NO2

are 55% for ‘‘Bad’’or ‘‘Extreme’’, 18% for ‘‘Good’’ and ‘‘Moderate’’ and27% as ‘‘Critical’’ and ‘‘Poor’’ days. For NO

2, extreme

conditions were encountered during 7% of the dayswhereas the corresponding rate was only 3% for ozone.

For CO, almost 1/5 of the days were attributed to the‘‘Bad’’ and ‘‘Extreme’’ categories. Almost 60% of the dayswere characterised as ‘‘Good’’ and ‘‘Moderate’’ days.

For SO2

about 80% of the days are classified as‘‘Good’’ and ‘‘Moderate’’ with only 8% of days as ‘‘Bad’’.The percentages are different concerning BS. The‘‘Good’’ and ‘‘Moderate’’ conditions are occurring in42% of the days between 1983 and 1995 and a similarpercentage is attributed to ‘‘Bad’’ and ‘‘Extreme’’. Themain difference is that 3% of days were subject to ‘‘Se-vere’’ conditions concerning BS.

Due to anthropogenic activities and the climatology ofAthens the concentrations of various pollutants showstrong spatial and temporal variability. This variabilitywas examined, together with the seasonal variations oc-curring at each monitoring station and for each pollutantseparately. The aim of these comparisons is to show theimprovement or deterioration of the overall conditions inthe domain over time, and to examine the occurrence ofbad conditions for several pollutants simultaneously dur-ing different seasons.

Table 11Air-quality characterisation (% occurrence) for the period1983—1995

Index O3

NO2

CO SO2

BS

Extreme 0 0 0 0 3Severe 3 7 1 1 12Bad 43 48 17 8 26Critical 12 16 11 5 6Poor 9 11 12 6 11Moderate 21 13 29 25 6Good 12 5 30 55 36

4.1. Spatial considerations

The domain of the metropolitan area can be distin-guished spatially according to the type of anthropogenicactivities and the relevant population density. The threemain zones of the AMA are the central, the south and thenorth. The central zone is typical of European cities withheavy saturated traffic during the day. The south zone isa mixed residential and industrial area whereas the northis primarily residential. Due to this division five stationsmonitor the central zone: PAT; ATH; ARI; GEO; andPER (Table 3 and Fig. 2). Three monitoring stations arepositioned in the southern zone: PEI; REN; and SMI andthree in the northern zone of the Athens basin: LIO;LYK; and MAR.

For demonstrating the spatial variations of the air-quality indicators across the domain of the MetropolitanArea of Athens, the ‘‘average’’ daily indices from themonitoring stations were used during 1983—1995. Theair-quality indicators are discrete variables, so the bestway to describe the average conditions is by taking themedian daily concentrations since the arithmetic mean isinappropriate for discrete values. For the same reasonone cannot directly interpolate median air-quality indi-ces for obtaining the spatial distribution. Instead, foreach pollutant and for each station, the median of theappropriate maximum daily concentration for each pol-lutant was calculated during 1983—1995. Working with


the kriging interpolation technique (Webster et al., 1991)on the pollutants concentrations and afterwards byapplying the scale of air-quality indicators on thecalculations, a representative estimate of the medianindicators over a grid covering the area of Athens wasobtained. The median indicators were then mapped andpresented in Fig. 3. The different shades in Fig. 3 repres-ent different degrees of severity according to the air-quality indicators. The x and y scales are given in kmstarting from an arbitrary point of the origin.

According to Fig. 3, ‘‘Bad’’ air-quality conditions forCO are occurring only over a small central area ofAthens based on the median daily values. The area affec-ted would have been different in case the 98th percen-tile was used instead of the median daily indices orwhen we compared data only from the most recentyears (1993— 1995). However, the purpose of these com-parisons was to show the different spatial effects forvarious pollutants under a consistent system of repres-entation. Similarly, according to Fig. 3, the area of ‘‘Criti-cal’’ conditions covers a zone from the centre of Athensall the way down to the sea. The zone of ‘‘Poor’’ condi-tions is located in the western and eastern suburbs aswell as in the southern parts near the sea. The rest ofthe domain experiences ‘‘Moderate’’ or ‘‘Good’’ of COconditions.

Equally, as shown by the same figure, the central zoneof the AMA is exposed to ‘‘Poor’’ SO

2levels, while

almost all the Basin is ‘‘Good’’. Bad conditions for BS areshown in a more extensive area due to traffic hot spots.Significant area variations are observed for ozone inFig. 3. Two areas with ‘‘Bad’’ and ‘‘Extreme’’ conditionsare identified away from the central zone due to thedestruction of ozone precursors occurring at the centre ofurban areas. For ozone, the area of ‘‘Poor’’ air-qualityindicators extends over a larger area across the domainwhich for this pollutant reaches the main parts of thewestern and eastern suburbs.

For NO2

the median index of air quality is ‘‘Ex-treme’’ and ‘‘Bad’’ in the central area of the AMA, whilealmost all build up area experiences ‘‘Poor’’ air qualitylevels.

4.2. Seasonal variations

The level of air-quality indicators’ is also subject tostrong seasonal deviations due to different dispersionmechanisms, due to emission variations or due to photo-chemical activity. According to the definition of thewarm season (Lykoudis et al., 1996) for Athens, the yearwas divided into two main periods. The warm seasonwhich is characterised with strong photochemical activ-ity (May—September) and the cold season with weakphotochemical activity but with episodes of primary pol-lutants (November—March). The remaining months(April and October) were classified as ‘‘transitional

periods’’. The spatial distribution of the air-quality indi-cators for these periods is shown in Figs. 4—6.

The main source of CO in the Metropolitan Area ofAthens is traffic, and significant seasonal improvementsare achieved during the summer months when trafficrates are reduced at the city centre due to summervacations and high temperatures that keep people frommoving around. Each year, during the summer vacationperiod, usually between 1 July and 16 August, the popu-lation of the Metropolitan area diminishes to the 2/3of its normal (winter) size, while high temperatures(30—40°C) keep the remaining people in house. Com-parisons of CO indicators between winter and summerperiods (Figs. 4 and 5) show a reduction in pollutantconcentrations during the summer months. The levelsand the severity of CO indicators in Fig. 6 for thetransitional period is similar to the median value ofindicators observed between 1983 and 1995 (Fig. 3).

Significant seasonal variations are observed for SO2

(Figs. 4 and 5). ‘‘Bad’’ indicator levels are observed for thecentre of the metropolitan area and only for the winterseasons. The whole AMA is subject to ‘‘Moderate’’ condi-tions during the summer and transitional seasons (Figs. 4and 6). Similar but less profound seasonal changes areobserved at the respective figures for BS. During the coldseason, the air-quality indicator for BS is ‘‘Bad’’ or ‘‘Criti-cal’’ at the central and eastern areas of the Athens basin.SO

2and BS are produced mainly by domestic heating

during the winter months while during the warm monthsthe main source is industry. The emissions from domesticheating activity are reduced during the warm months andthe diesel fuel used for combustion contains little sulphuraccording to existing legislation. Throughout the year,the persistence of poor air-quality indices for BS in thecentral zone is attributed to saturated traffic conditionsincluding heavy-duty vehicles. The poor maintenance ofcar engines and the low average velocities at the citycentre are also contributing to enhanced particulateemissions.

As regards to the median levels of O3in winter seasons

over the 13 year period the ‘‘Poor’’ or ‘‘Critical’’ condi-tions are restricted only to a limited area at the northernzone (Fig. 5). On the contrary during summer the mainpart of the Athens basin is subject to ‘‘Bad’’ and ‘‘Criti-cal’’ air-quality levels (Fig. 4). For NO

2the differences be-

tween warm and cold periods (Figs. 4 and 5) are smallerthan for ozone. During all seasons the centre of Athens issubject to ‘‘Bad’’ air-quality conditions, while in almostall built-up area the air quality is characterised as ‘‘Criti-cal’’ for NO

2. For this pollutant, the area covered by the

same air-quality indicator during the warm and coldmonths varies less than 10%. This similarity is caused bydifferent mechanisms in summer and winter. During win-ter the NO

2deterioration is due to primary emissions

whereas the summer deterioration is subject to photo-chemical activity.


Fig. 3. Iso-lines of annual median air-quality indicators for (a) CO, (b) SO2, (c) BS, (d) O

3and (e) NO

2.

Ozone is a secondary pollutant formed with the aid ofultraviolet radiation. In Athens, ‘‘Bad’’ and ‘‘Good’’ air-quality conditions are expected to occur during warmand cold periods respectively due to solar irradiance and

due to the availability of NO2. The severity of ozone

conditions in northern suburbs is due to the prevailingmeteorological patterns in Athens. NO

2is formed in the

central area, it participates in the photochemical formation


Fig. 4. Iso-lines of median air-quality indicators for (a) CO, (b) SO2, (c) BS, (d) O

3and (e) NO

2during the summer months.

of O3

while it is also transported by the local southernwinds (sea breezes) to the north. The spatial distributionfound for O

3and NO

2is in good agreement with model-

ling studies in the area of Athens (Pilinis et al., 1993).

4.3. Pollutant weighting

For weighting the severity of atmospheric pollution inan urban domain it is customary, due to the complexity



3and (e) NO

2during the winter months.

of examining several pollutants simultaneously, to con-sider either primary pollutants (chemically inert undernormal atmospheric conditions) such as SO

2, or second-

ary pollutants such as O3. This is normally the case

because the scale of severity is not the same for allpollutants, there is a seasonal dependence on the natureof episodes and there are differences attributed only tothe positioning of the monitoring stations.



3and (e) NO

2during the transient months.

Figs. 7 and 8 show the daily indicators for O3, NO

2,

SO2, BS and CO. These pollutants are shown for three

monitoring stations representative of the north, centraland south zones of Athens. The daily status for two

months in the cold and warm season of 1993 and 1994 isshown respectively in Figs. 7 and 8.

For the cold season it is evident that episodeswith ‘‘Bad’’ and ‘‘Extreme’’ conditions are occurring


Fig. 7. Daily variation of all pollutants at representativemonitoring stations in north (MAR), central (PAT) and south(PEI) zones (November—December 1993).

Fig. 8. Daily variation of all pollutants at representativemonitoring stations in north (MAR), central (PAT) and south(PEI) zones (July—August 1993).


Fig. 9. The annual evolution of air-quality indicators between 1983 and 1995 for O3. The annual availability of data is also indicated in

brackets.

simultaneously for NO2, SO

2, BS and CO over the main

part of the domain. During these months the ozonestatus is either ‘‘Good’’ or ‘‘Moderate’’. However, at thenorthern zone ‘‘Bad’’ or ‘‘Critical’’ conditions might bereached mainly due to ozone transport and accumulationat this area. Naturally, simultaneous episodes of primarypollutants enhance this deterioration of ozone condi-tions. This can be seen by the simultaneous occurrence of‘‘Extreme’’ conditions for NO

2.

During the summer season of 1994 the concentrationsof CO, SO

2and BS were simultaneously reduced. An

exception to this is observed for BS at the city centre.This exception occurs only due to saturated emissionsfrom traffic which are similar in summer and winter.

The summer season is characterised by simultaneouslyoccurring episodes for ozone and NO

2. ‘‘Bad’’ ozone

conditions are recorded for the north, south and centralstations and is followed closely by the status of NO

2. Due

to reduced primary emissions in the northern zone thestatus for NO

2is between ‘‘Poor’’ and ‘‘Moderate’’ most

of the time. However, significant deterioration occurssimultaneously during episodes for ozone and NO

2. Dur-

ing these episodes deterioration is observed also for SO2

and BS, despite the fact that these pollutants in thesummer months are mostly in the ‘‘Moderate’’ status.Similar conclusions are made for all years analysed dur-ing this study and not only for the period 1993—94 shownby Figs. 7 and 8.

4.4. Temporal evolution

The improvement or deterioration of atmospheric pol-lution over the Metropolitan Area of Athens between1983 and 1995 is demonstrated by analysing the annualdistribution of indicators from all monitoring stations.For the characterisation of air quality we used the high-est indicator recorded over the domain. The percentageof occurrence of ‘‘Good’’ to ‘‘Severe’’ conditions is depic-ted in Figs. 9—13. The percentages within brackets on they-axis indicate the annual availability of data over thedomain.

It is evident from Figs. 9 and 10 for O3

and NO2

respectively that ‘‘Good’’ and ‘‘Moderate’’ conditions areoccurring roughly between 30 and 20% of the days. Thispercentage does not show dramatic improvements overthe year despite the abatement strategies. Also, from thesame set of figures it is concluded that between 40 and50% of the days are subject to ‘‘Bad’’ and ‘‘Extreme’’conditions. A notable improvement occurs only to theconditions classified as ‘‘Extreme’’. The introduction ofcatalyst cars in 1989 has certainly an impact but not as tocreate reversal towards conditions of the early eighties.

The same comparisons carried out for CO and SO2

(Figs. 11 and 12) show significant improvements since1989. ‘‘Good’’ and ‘‘Moderate’’ conditions are steadilyimproving and are occurring in 75 and 90% of the days,respectively. Unfavourable climatology during 1992


Fig. 10. The annual evolution of air-quality indicators between 1983 and 1995 for NO2. The annual availability of data is also indicated

in brackets.

Fig. 11. The annual evolution of air-quality indicators between 1983 and 1995 for CO. The annual availability of data is also indicatedin brackets.


Fig. 12. The annual evolution of air-quality indicators between 1983 and 1995 for SO2. The annual availability of data is also indicated

in brackets.

Fig. 13. The annual evolution of air-quality indicators between 1983 and 1995 for BS. The annual availability of data is also indicated inbrackets.


caused higher residential emissions, which increased theoccurrence of ‘‘Extreme’’ conditions during this year.Stations in the central zone of the Athens MetropolitanArea have confirmed this trend. The most significantchanges are occurring for BS as is shown in Fig 13. The‘‘Severe’’ conditions of the early 1980s are eliminated and‘‘Good’’ or ‘‘Moderate’’ conditions are occurring in morethan 60% of the days every year.

5. Conclusions

This work defines a new scale for classifying urban airquality. This scale can be applied in uniform way to anygeographical region and is based on air-quality stan-dards and guidelines introduced by WHO and the Euro-pean Commission. The scale takes into account aims andstrategies of local authorities (through locally introducedtarget values) and is flexible in incorporating new limitsproposed.

This methodology is applied over the MetropolitanArea of Athens, a Mediterranean city with typical winterand summer episodes characteristic of South Europeanconditions. The application of the method shows that thepollution in Athens can be characterised as ‘‘Bad’’ forO

3and NO

2for almost 50% of the days between 1983

and 1995. Similarly for SO2, CO and BS, the status of

air quality can be characterised as ‘‘Good’’ or ‘‘Moder-ate’’ for more than 50% of the days, between 1983 and1995.

A strong spatial and temporal variability of the air-quality levels is also detected. The central zone of theAthens Basin is subject, for almost all the species (exceptO

3), to ‘‘Bad’’ air-quality conditions, while the northern

zone is also affected by ‘‘Bad’’ conditions for ozone, forthe greatest part of the year.

During the warm season, the status of air qualityfor SO

2, CO and BS is characterised by indicators not

worse than ‘‘Poor’’, while for O3, 85% of the days

are labelled with ‘‘Bad’’ or ‘‘Extreme’’ air-quality indices.However, during the same season episodes with primarypollutants, namely SO

2, BS and CO, are not rare. During

these episodes bad indicators are recorded from all pollu-tants simultaneously. Due to the different mechanisms ofproduction of NO

2, no significant variations of the

area covered by bad air-quality indicators were noticedfor this pollutant during warm and cold periods of theyear.

Acknowledgements

This work is partly funded by DG XIII (ProgramEMMA Contract No EN 1005). Authors also thank theauthorities of PERPA for the data utilised in this study.

References

Auto-Oil 1, 1996. Air Quality Report of the Auto-Oil Pro-gramme, Subgroup-2. European Commission, DG-XI/D3.

Altshuler, A.P., 1986. The role of nitrogen oxides in non urbanozone formation in the planetary boundary layer over N.America, W Europe and adjacent areas of ocean. Atmo-spheric Environment 20, 245—268.

Atkins, D.H.F., Lee, D.S., 1995. Spatial and temporal variationof rural nitrogen dioxide concentrations across the UK.Atmospheric Environment 29, 223—239.

Baumuller, J., Reuter, U., 1995. Die summarische Bewetrungvon Luftschadstoffen durch einen Luftbelastungindex.Staub-Reinhaltung der Luft 55, 137—141.

Comrie, A.C., 1994. A synoptic climatology of rural ozone pollu-tion at three forest sites in Pennsylvania. Atmospheric Envi-ronment 28, 1601—1614.

Comrie, A.C., Yarnal, B., 1992. Relationships between synopticscale atmospheric circulation and ozone concentrations inMetropolitan Pittsburgh, Pennsylvania. Atmospheric Envir-onment 26, 301—312.

European Environment Agency, 1995. The assessment: air. PartII. In: Stenners, D., Bourdeau, P. (Eds.), Europe’s Environ-ment. The Dobris Assessment. EEA, Copenhagen, pp.27—53.

Hellenic Ministry of the Environment. Directorate of air pollu-tion and noise control PERPA, 1989. Database information.vol. 1. In: The Air Pollution in Athens area. Technical Note,Hellenic Ministry of the Environment, Athens.

Lalas, D.P., 1992. Climate, geography and air pollution in theMediterranean area. Air Pollution and Health in the Medi-terranean Countries. Workshop Proceedings, Athens, 8—10May 1992, pp. 36—53.

Lykoudis, S., Kassomenos, P., Petrakis, M., 1996. A method toestimate the onset of the warm period of the year. 3rdConference on Meteorology, Climatology and Physics of theAtmospheric Environment, pp. 260—264 (in Greek).

Kassomenos, P., Kotroni, V., Kallos, G., 1995. Analysis of clima-tological and air quality observations from Greater AthensArea. Atmospheric Environment 29, 3671—3688.

Katsouyanni, K., 1997. Personal communication. Laboratory ofEpidemiology, Medical School, University of Athens.

Makinen, A., Pihlstrom, M., 1995. Biomonitoring the effects ofair pollution on forest ecosystems in an urban area; HelsinkiFinland. Proceedings of the 10th World Clean Air Congress,28 May—2 June, Espoo Finland.

Mignacca, D., Fraser, D., Yap, D., Fudge, D. 1991. A Guide tothe Ontario Air-Quality Index System. Air-ResourcesBranch, Ontario, Ministry of the Environment, 33 pp.

Ott, W.R., Hunt, Jr., W.F., 1976. A quantitative evaluation of thepollutant standards index. Journal of Air-Pollution ControlAssociation 26, 1051—1054.

Pilinis, C., Kassomenos, P., Kallos, G., 1993. Modelling of thephotochemical pollution in Athens, Greece. Application ofthe RAMS-CALGRID modelling system. Atmospheric En-vironment 27B, 353—370.

Quality of Urban Air Group, 1996. Airborne Particulate Matterin the U.K. Department of the Environment.

Skouloudis, A.N., Kassomenos, P., 1996. EMMA Air QualityIndicators. Users Requirements Report. EN 1005, DGXIII,pp. 87.


Webster, R., Campbell, G.W., Irwin, J.G., 1991. Spatial analy-sis and mapping the annual mean concentrations ofacidity and major ions in precipitation over the UnitedKingdom in 1986. Envirorment Monitoring Assessment 16,1—17.

World Health Organisation (WHO), 1987. Air Quality Guide-lines for Europe. Regional Office for Europe. Copen-hagen.

World Health Organisation (WHO), 1995. Update and Revisionof the Air Quality Guidelines for Europe. Regional Office forEurope. Copenhagen.

Vyras, L., 1995. Atmospheric Environment. In: Hellenic Minis-try of the Environment (Eds.), Greece: Ecological and Cul-tural Reserve. Data, Actions and Programmes for theProtection of the Environment. Hellenic Ministry of theEnvironment, Athens, pp. 119—66.

Vyras, L., Nikolidakis, G., Fotopoulos, A., Froussou, M., 1995.Atmospheric Pollution in Athens — 1994. Ministry for theEnvironment and Public Works, p. 48 (in Hellenic).

Ziomas, I.C., Melas, D., Zerefos, C.S., Paliatsos, A., Bais, A.F., 1995.Forecasting peak pollutant levels using meteorological vari-ables and indexes. Atmospheric Environment 29, 3605—3617.


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