Studying cumulative ozone exposures in Europe during a 7-year period

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 102, NO. D20, PAGES 23,917-23,935, OCTOBER 27, 1997

Studying cumulative ozone exposures in Europe during a 7-year period

Annemarie Bastrup-Birk, J0rgen Brandt, and Zahari Zlatev Department of Atmospheric Environment, National Environmental Research Institute, Roskilde, Denmark

Ignacio Uria LABEIN Technological Research Centre, Bilbao, Spain

Abstract. Ozone is one of the most harmful pollutants in the troposphere. High ozone concentrations can damage plants, animals and humans. The damaging effects depend on the magnitude of a critical level of a special parameter, the cumulative ozone exposure. This is why cumulative ozone exposures must be carefully studied. It is important to determine the relationships between relevant emissions (NOx emissions, human-made VOC emissions, and/or a combination of NOx emissions and human-made VOC emissions) and cumulative ozone exposures. All these issues are discussed in this paper. Meteorological data from seven consecutive years, from 1989 to 1995, have been used in the experiments with different scenarios for varying the emissions (the NOx emissions, the human-made VOC emissions, as well as both the NOx emissions and the human-made VOC emissions). The particular air pollution model used in this study is the Danish Eulerian Model. Several hundred runs with different input data (meteorological data and/or emission data) have been performed. Advanced visualization techniques are used to interpret the large amount of digital data collected in these runs and to show clearly different trends and relationships that are normally hidden behind millions and millions of numbers. The model results were compared with measurements taken at more than 80 stations located in different European countries. The experiments indicate that it is sufficient to carry out computations over 5 consecutive years in order to eliminate the influence of extreme meteorological conditions (very warm or very cold summer months) on the cumulative ozone exposures, while this effect is clearly seen if less than 5 years are used in the experiments. It is shown that the relationship between the emissions (NO• and/or human- made VOC emissions) and the cumulative ozone exposures is in general nonlinear. Finally, it is illustrated that the critical values for ozone exposures are exceeded in most of Europe (in many areas by more than 7 times).

1. Introduction

No one doubts that high concentrations and/or depositions of air pollutants can damage (either directly or indirectly) plants, animals, and humans. However, at what point do these concentrations go from acceptable levels to dangerous levels? Moreover, and this is probably much more important, at what point do these concentrations go from dangerous levels back to acceptable levels? Recent environmental studies show that in order to prevent ecosystem destruction, it is absolutely necessary to reduce the concentrations and/or the depositions of certain harmful air pollutants, at least in Europe and North America, to acceptable levels and to keep them there. These are urgent tasks: some damaging effects may soon become irreversible. On the other hand, because lowering pollution levels is expensive, they must be reduced to safe levels but no further.

Different simulations performed by advanced mathematical models can successfully be used to determine the relationships between the emissions in the domain of interest and the con-

centrations/depositions of certain harmful air pollutants. After that

Copyright 1997 by the American Geophysical Union.

Paper number 97JD01966 0148-0227/97/97JD-01966509.00

the relationships so found can be used to solve the tasks mentioned above in an optimal way (i.e., to find out how to perform the reductions needed by the cheapest possible actions).

A lot of work is needed to develop powerful and reliable mathematical models that can be applied in the solution of the problem to reduce in an optimal way the concentrations and/or the depositions of certain harmful pollutants to the acceptable levels. It is necessary to run such a model (1) many times (several hundred times and even several thousand times), (2) on a big spatial domain with a high spatial resolution, (3) oi1 a long time interval (sometimes a time interval of several consecutive years), (4) by using an appropriate representation of the important physical processes and advanced chemical schemes containing all relevant chemical species that react with the harmful pollutants studied, and (5) by using a sufficient number of vertical layers [Dimov et al., 1996; Zlatev et al., 1996a].

The problem of building a mathematical model that satisfies all conditions stated above (and it must be emphasized here that some other conditions have also to be satisfied) is still not solved. Scientific groups in different countries are working on this challenging problem. In the mean time, however, some compromi- ses, made according to the particular task that is to be solved, are to be used. Such a compromise, i.e., the use of the two-dimensional version of the Danish Eulerian Model [see Zlatev, 1995] in a simulation process for studying the relationships between (1) the

23,917

23,918 BASTRUP-BIRK ET AL.: CUMULATIVE OZONE EXPOSURES IN EUROPE

NOx and/or human-made VOC emissions in Europe and (2) the exposures to high ozone concentrations that may have damaging effects on agricultural crops, natural vegetation, and forest trees, will be described and discussed in this paper.

The paper is organized in the following way: two important concepts, the threshold concentration and the cumulative exposure, will be introduced in section 2. The calculation of the cumulative ozone exposure will also be discussed in section 2.

As mentioned above, the use of the Danish Eulerian Model in a simulation of this type is a compromise. Therefore it is necessary to carry out some experiments in order to show that the Danish Eulerian Model is able to produce reliable results. Results obtained in such experiments are presented and discussed in section 3. It must be stressed that the quantity studied is also used in the comparisons; that is, the calculated cumulative ozone exposures are compared with the measured cumulative ozone exposures. Many people compare calculated and measured ozone concentrations and conclude that a good agreement between these two quantities implies a good agreement between calculated and measured cumulative ozone exposures (an exception is Malik et al. [1996]). An example is given in section 2.6 to show that this is not necessarily true, and thus it is much better to compare directly the last two quantities.

The levels of the cumulative ozone exposure in Europe are discussed in section 4. Results from several experiments, which indicate that a 5-year period is sufficient to obtain representative cumulative ozone exposures (i.e., cumulative ozone exposures that do not depend strongly on extreme meteorological conditions, such as very hot or very cold summer months), are presented.

Different scenarios are used in section 5 to show the influence

of reductions of (1) the NOx emissions alone, (2) the human-made VOC emissions alone, and (3) both the NOx and the human-made VOC emissions on the levels of the cumulative ozone exposures in Europe.

The relationships between the relevant emissions (NOx emissions alone, human-made VOC emissions alone, and both NO• and human-made VOC emissions) and the corresponding cumulative ozone exposures are studied in section 6. The results presented in section 6 indicate that these relationships are nonlinear, at least in some parts of Europe. Finally, several remarks and some plans for future research are briefly discussed in section 7.

2. Calculating Cumulative Exposure for High Ozone Concentrations

Agricultural crops, natural vegetation, and forest trees can be damaged when they are exposed, during long time periods, to high ozone concentrations. The computational procedures used in the evaluation of the harmful exceedance of critical ozone

concentrations in different parts of Europe will be described in this section. The recommendations made in the "workshop summary" of the workshop on "Critical Levels for Ozone in Europe: Testing and Finalizing the Concepts" (held in Kuopio, Finland, 15-17 April, 1996; see K•irenIampi and Sk•irby [1996]), have been used to define the concepts of threshold concentration and cumulative exposure for agricultural crops, natural vegetation, and forest trees.

A threshold concentration is a concentration of a given pollutant in the atmosphere, the regular exceedance of which will have damaging effects on certain receptors (plants, ecosystems, or materials) according to the present knowledge. In the particular case where the pollutant studied is ozone and the damages under consideration are damages on plants, a threshold concentration of 40 ppb is often used (but some other values as, for example, 30 ppb have also been suggested and used in different studies [K•irenlampi and Sk2irby, 1996; Fuhrer and Achermann, 1994]).

Consider a period of N hours. A cumulative exposure over a given threshold concentration is the sum (from 1 to N) of the quantities by which the hourly mean concentrations exceed the threshold concentration. This means that the cumulative exposure is measured in concentration times time units (e.g., ppbxhours) and can be expressed by the following formula:

N

AOT(c) = • max(c/ - c, 0) , (1) i=1

where ci is the mean value of the concentration under consideration found in hour i, where i = 1, 2 ..... N, by either an air pollution model or at a given measurement station; c is the threshold concentration which has been found relevant for the

objectives of the particular study (note that if the objectives are changed, then the value of c may also change); AOT(c) stands for accumulated exposure over a threshold of c ppb (for a particular value of c the parentheses will be omitted; that is, we shall write A OT40 instead of A OT(40).

The concepts of threshold concentrations and cumulative exposures, which have been defined above, are valid for concentrations of any pollutant. However, we shall use these concepts only in connection with ozone concentrations.

2.1. Harmful Effects of High Ozone Concentrations on Agricultural Crops

Consider the case where harmful effects of high ozone concentrations on agricultural crops during the growing period are to be studied. Let us assume that the following conditions are satisfied: the time period under consideration contains 3 months (May, June, and July), the summation in (1) is performed only for the daytime hours (or, more precisely, the period from sunrise to sunset), and the threshold value of the ozone concentrations is set

to c = 40 ppb. It is believed that the ozone concentrations are harmful for the

most sensitive agricultural crops if the value of AOT40 obtained from (1) by using the three conditions imposed in this section is greater than 3000 ppbxhours. The critical value 3000 ppbxhours is derived by using newest experimental data [Ki•renlampi and Sk•irby, 1996]; it is more stringent than the old value, 5300 ppbxhours, which has been used, for example, by Zlatev et al. [1996b], Ashmore [1994], and Fuhrer and Achermann [1994].

2.2. Harmful Effects of High Ozone Concentrations on Natural Vegetation

For natural vegetation in different ecosystems, one can use the same critical exposure level, A OT40 = 3000 ppbxhours for the period containing May, June, and July, as for agricultural crops. It is assumed here that the most sensitive species in the natural ecosystems are damaged in a similar way as the most sensitive agricultural crops; see K•irenlampi and Sk•irby [ 1996].

2.3. Harmful Effects of High Ozone Concentrations on Forest Trees

Consider the case where harmful effects of high ozone concentrations on forest trees (during the summer period) are to be studied. Let us assume now that the following conditions are satisfied: (1) the time period under consideration contains 6 months (April, May, June, July, August, and September), (2) the summation in (1) is again performed for the daytime hours, and (3) the threshold value of the ozone concentrations is again set to c = 40 ppb.

It is believed that the ozone concentrations are harmful for the

forest trees if the value of A OT40 obtained from (1) by using the three conditions imposed in this section is greater than 10,000

BASTRUP-BIRK ET AL.' CUMULATIVE OZONE EXPOSURES IN EUROPE 23,919

ppbxhours. The definition of critical exposure given above is the same as that in the work of Ktirenlampi and Sktirby [1996]. It is slightly different from the old recommendations (where the summation is carried out both for the daytime hours and for the nighttime hours; see Zlatev et al. [1996b] and Fuhrer and Achermann [1994] and the references by Zlatev et al. [1996b], Fuhrer and Achermann [1994] and Sktirby [1994]).

2.4. Remarks About the Notation

It should be emphasized here that the same notation for the critical ozone exposure, A OT40, will often be used both in the case where harmful effects on agricultural crops are to be studied and in the case where harmful effects on forest trees are to be

studied. Of course, the values of the critical ozone exposure are different in these two cases. However, from the context it will be clear how the critical ozone exposure is calculated. If there is a danger for misunderstanding, then A OT40C will be used when harmful effects on agricultural crops are studied, while AOT40F will be reserved for the case where harmful effects on forest trees are studied.

2.5. Computing Cumulative Exposure in Different Parts of Europe

Formula (1) has been used to calculate A OT40C and A OT40F values, averaged over a 7-year period, in different parts of Europe. The hourly mean values of the ozone concentrations c, have been calculated by the Danish Eulerian Model. The model itself as well as results from comparison of calculated concentrations and depositions with measurements are discussed by Dimov et al. [1996], Harrison et al. [1994], Zlatev [1995], and Zlatev et al. [ 1992, 1993, 1994, 1996a]. A short description of the model is given below (more details can be found in the above references). It must be emphasized here that the two-dimensional version of the Danish Eulerian Model has been used in this paper.

The Danish Eulerian model is described mathematically by a system of partial differential equations. The number of equations is equal to the number of chemical species studied by the model. At present this number is 35. The condensed CBM IV chemical scheme, proposed by Gery et al. [1989], is used. All important physical processes (advection, diffusion, deposition, emissions, and chemistry) are adequately represented. The space domain of the model (it contains the whole of Europe together with parts of Asia, Africa, and the Atlantic Ocean) has been discretized by using a (96 x 96) grid. This means that (1) Europe is divided into 9216 grid squares and (2) the grid resolution is approximately 50 km x 50 km. The model is run with an advection time step of 900 s. This time step is too large for the chemical submodel. There- fore 6 chemical time steps per advection time step are carried out. Appropriate initial and boundary conditions are needed. If initial ...,,a;• ...... available (e.g., •"'--' a previous run •,•,Jll•.•l•,l•,JllO {.•1•,• 11•,Jlll •k.•l. •&&•.• l&&•..•..•.•l ,

then these are read from the file where they are stored. If initial conditions are not available, then a 5-day start-up period is used to obtain initial concentrations (that is, the computations are started five days before the desired starting date with some background concentrations, and the concentrations found at the end of this period are used as starting concentrations). The choice of lateral boundary conditions is in general very important. This issue has been discussed by Brost [1988]. However, if the space domain is very large, then the choice of lateral boundary conditions becomes less important; which is stated by Brost [1988, p. 2386]' "For large domains the importance of the boundary conditions may decline." The lateral boundary conditions are represented in the Danish Eulerian Model with typical background concentrations which are varied, both seasonally and diurnally. The use of background concentrations is justified by the fact that (1) the space domain is very large and (2) the boundaries are

located far from the highly polluted regions (in the Atlantic Ocean, North Africa, Asia, and the Arctic areas). Nevertheless, it would perhaps be better to use values of the concentrations at the lateral boundaries calculated by a hemispheric or global model. The upper boundary condition is the same as the third rule described by Zlatev et al. [1993], because the experiments indicate that this rule performs in general better than the other two rules. The input data (both the meteorological data and the emission data) have been obtained from EMEP (the European Monitoring and Evaluation Programme). The meteorological data contain horizontal wind fields, vertical wind velocities (at the top of the boundary layer), temperatures (both surface temperatures and temperatures of the boundary layer), cloud covers, relative humidities, preci- pitation fields, mixing heights and pressures. The resolution of the meteorological fields is coarser than the resolution used in the model: the time resolution is 6 hours, the spatial resolution is, roughly speaking, 150 km x 150 km. Simple linear interpolation rules are used both in time and in space. Five emission fields are used in the model: SO2 emissions, NOx emissions, human-made VOC emissions, ammonia-ammonium emissions, and natural VOC emissions (no other natural emissions are used in the model at present). The emission data are available on a 50 km x 50 km grid. However, only the annual human-made emissions are given. Simple rules are used to get seasonal variations for the SO2 emissions and for the ammonia-ammonium emissions. Both

seasonal variations and diurnal variations are simulated for the

NO x emissions and for the human-made VOC emissions. The natural VOC emissions are calculated on an hourly basis by using the mechanism proposed by Liibkert and Sch6pp [1989]. Infor- mation about the forest distribution in Europe and surface temperatures are used in this algorithm.

Formula (1) is used to calculate A OT40 values for every grid square. If the calculations with formula (1) are carried out 24 hours per day, then the value of N is 2208 when AOT40C is to be calculated, while N is 4392 in the calculations of AOT40F. The

actual figures are much smaller because formula (1) is used only during the daytime hours.

The periods, in which cumulative ozone exposure is calculated, are relatively short (3 months for the agricultural crops and 6 months for forest trees). This means that rather hot summer months or rather cold summer months may influence the calculated values of AOT40C and AOT40F in one or another

direction. Therefore it is important to make an attempt to achieve representative values of these quantities which can be used again and again in different studies. This important issue has been discussed in the "workshop summary" [see Kiirenlampi and Sk•irby, 1996]. To avoid the influence of particular meteorological conditions, it has been suggested by Kiirenlampi and Skiirby [1996] to calculate the A OT40 values (both A OT40C and A OT- 4OF) for 5 consecutive years and then to take the mean values. One ,-•' •h,• -,•i ........... •' ..... t,,4,, i• t,-, justify this •,,ooo•_ tion. Wc have calculated the values of AOT40C and AOT40F for

7 consecutive years, from 1989 to 199• and then compared the mcan values for each of the three •-ycar periods (from 1989 to 199•, from 1990 to 1994, and from 1991 to 199•) with the results for the ?-year period. These results as well as some related issues will bc discussed in section •.

All •ns have bccn carried out by using emissions for 1989. This action has been taken because we are interested in detecting the influence of the meteorological conditions on the results. In this way, the only difference between the runs for the different years is the use of different meteorological data. Therefore any difference in the values of AOT40C and AOT40F for the different

years is caused only by the different meteorological conditions. Changing the emissions from one year to another will not allow us to make correct conclusions concerning the influence of the meteorological conditions on the results. Anyway, the differences


between the emissions in the European countries for the different years in the period from 1989 to 1995 are relatively small, and thus the influence of these differences on the values of A OT40C

and A OT40F is also small.

2.6. Need for Small Time Steps and Accurate Computations

The calculation of cumulative ozone exposure is a much more stringent task than the calculation of ozone concentrations. A model that calculates reasonable approximations to the ozone concentrations may have difficulties with the calculation of good approximations to the cumulative ozone exposure. The two major difficulties in the calculation of cumulative ozone exposure are shortly discussed in this section.

1. The strong diurnal variations typical for ozone concentrations may cause difficulties for some trajectory models. The strong diurnal variations lead to a requirement for small time steps (one must have several instantaneous concentrations in order to calculate the desired hourly mean values of the concentrations). This requirement is always satisfied for the Eulerian models. For some trajectory models, however, this requirement is not satisfied, because in such models a few trajectories only arrive at the receptor points (typically only four trajectories: arriving at 0600, 1200, 1800, and 2400; see, for example, Simpson [1992, 1993]). Some interpolation rule can be used to obtain the intermediate hourly mean concentrations that are needed in (1), but this produces extra numerical errors.

2. Another difficulty arises because the differences c i - c are to be used in the calculation of (1). These differences may be in the range of uncertainty of the model even in the case where c, is sufficiently accurate. A simple example can be given to illustrate this statement. Consider the values of the exact concentration c, e•act

œ (tic

and the calculated concentration c i Assume that

exact talc

= 41, c, = 45, c = 40 (2)

Then the value of the relative error of the calculated ozone

concentration (in percent) is given by

exact talc

I exact

Ct

< 9.8 (3)

which in many cases is quite acceptable. Assume now that the contribution of hour i for the cumulative

ozone exposure is to be calculated. The exact contribution is

exact c, - c = 1 (4)

while the calculated contribution is

calc ci - c - 5 (5)

The relative error (in percent) of the contribution to the cumulative ozone exposure for hour i is given by

exact calc

1oo l c, -c, I

I Ct exact -- C I = 400 (6)

It is clearly seen that although the ozone concentration has been calculated in a sufficiently accurate way, the contribution to the cumulative ozone exposure for hour i is quite wrong.

Of course, this is an extreme situation. Nevertheless, this

example illustrates the fact that more accurate methods are to be used when cumulative ozone exposure is to be calculated (the same is true if cumulative exposures for some other pollutants are to be computed).

3. Comparing Model Results With Observations Before starting to use the results obtained by a mathematical

model, one should perform a series of tests in an attempt to verify the reliability of the model results. Both the accuracy of numerical algorithms used in the model and the correct description of the physical processes in the model must be checked. The accuracy of the numerical algorithms used in the model will not be discussed here. However, a lot of tests performed by Zlatev [1995] (see also references by Zlatev [1995]) indicate that sufficiently accurate numerical algorithms have been selected for the particular model, the Danish Eulerian Model, which will be used in this study. Even when the physical processes are correctly described in the model and the numerical methods used are suf-

ficiently accurate, one may get wrong results because the input data are not sufficiently accurate and/or because the boundary conditions are not correct. Also here a series of checks are needed

to show that the available input data and the selected boundary conditions will allow us to get reliable results. Such checks have been carried out by Harrison et al. [1994], Zlatev [1995], and Zlatev et al. [ 1992, 1993].

3.1. How to Carry out Comparisons

The correct description of the physical processes in large air pollution models is often indirectly checked by comparing the model results with observations taken at measurement stations in

different European countries. Many comparisons of model results with observations have been carried out (not only for ozone concentrations but also for other concentrations participating in chemical reactions that involve ozone; as, for example, nitrogen dioxide). Moreover, both comparisons of calculated and observed concentrations over land [Zlatev, 1995; Zlatev et al., 1992, 1993] and comparisons of calculated and observed concentrations over sea [Harrison et al., 1994] have been carried out.

It must be emphasized here that it is impossible to give an adequate answer to the question whether the calculated cumulative ozone exposures are reliable by using only direct comparisons of calculated and observed concentrations. The reason for this has

been explained in section 2.6, where it has been shown that there may occur situations in which the calculated concentrations are sufficiently accurate, but the cumulative ozone exposures may be quite wrong. Therefore it is absolutely necessary to carry out additional comparisons; comparisons of the calculated cumulative ozone exposures with the observed cumulative ozone exposures at measurement stations located in different European stations. This is why no comparisons between calculated and observed concentrations will be presented in this paper (however, let us reiterate that such comparisons have been reported in previous papers [see Harrison et al., 1994; Zlatev, 1995; Zlatev et al., 1992, 1993]. Instead of this we shall concentrate on a much more important issue: to compare directly calculated cumulative ozone exposures with observed cumulative ozone exposures.

It is necessary to check how the calculated and the measured exposures compare on long periods (say, for a 5-year period). However, it is also important to perform more detailed comparisons on much shorter periods (say, 1-month period). Finally, scatterplots, where the model results are compared with observed results at stations which have sufficiently many observations, provide very useful information. Therefore three types of comparisons, which are discussed in sections, 3.2, 3.3, and 3.4, have been carried out.

BASTRUP-BIRK ET AL.: CUMULATIVE OZONE EXPOSURES IN EUROPE 23,921

1,10 4 - _

(-- _

_

o 5'10 3- I-- -

0'10 ø , • , • , APR JUN AUG

1989

S04 Norra Kvill

APR J N AUG

1990

............... Measured

Calculated

APR JUN AUG APR JUN AUG APR JUN AUG

1991 1992 1993

1 '10 4

o 5'10 3

o

0'10 ø APR JUN AUG

1989

GB16 High Muffles

APR JUN AUG

1990


1991 1992 1993

1 '10 4-- _

_

• - _

o 5'10 3- I-- -

_

0'10 ø , • , • APR JUN AUG

1989

DK02 Ulborg

APR JUN AUG

1990

APR JUN AUG

1991

APR JUN AUG APR JUN AUG

1992 1993

1'10 4 a

o 5'10 3 ,'" ' O

0'10ø! APR JUN AUG APR JUN AUG

! 989 ! 99o


! 99 ! 1992 1993

Figure 1. • '•,- Comp.m..n of calculated and measured A OT40 values on monthly basis at four measurement stations over a period of 5 years.

3.2. Comparisons Over Long Time Periods

Comparisons of calculated and measured A OT40 values have been carried out for the period 1989-1993. For every month in the extended period of 6 months (April, May, June, July, August, and September) and for every year in the period chosen, the monthly A OT40 values calculated by the model have been compared with the corresponding measured values (when measurements have been reported) at 91 European measurement stations (measurements collected at the Norwegian Institute for Air Research (NILU), most of them are discussed by Hjel!brekke [1995], have

been used in this study). Some of the results, which have been obtained at four measurement stations in different European countries, are given in Figure 1.

3.3. Comparisons Over Short Time Periods

A typical summer month, June 1989, has been chosen. Consi- der any day in the June 1989 period. Formula (1) is applied, by using model results and observations, for the daytime hours at which observations are available. Each of the two values so found

is divided by the number of daytime hours at which measurements


60-

•40 -

S04 Norra Kvill

o & -'o l• 2'0 d• Day in xnon•h

Observed:

Calculated: iMeans: calculated= 4.41 measured= 5.05

60 DO8 Hohenwested .

•4o

'h .-.-.. o • •o • 2'0 d•

Observed:

Calculated:

60-

•40 -

DKO:2 Ulbor8

Day in month

ß/eans: calculated= 7.86 measured=

...... • 10 15 •0 Day in month

Observed:

Calculated:

60- IO 1 Ispra

l/eans: calculated= 6.16 measured= 4.00

:3'O

& -'o -'• 2'0 2'5 3'0 Day in mont•h

Observed:

Calculated: Means: calculated= 19.47 measured= 14.48

Figure 2. Comparison of calculated and measured average ppb values by which the critical value of 40 ppb is exceeded at every daytime hour for days 1, 2 ..... 30 in June 1989 at four measurement stations (the calculation of these values is discussed in section 3.3).

are available. Thus the quantities obtained by this procedure can be considered as approximations to the average ppb values by which the critical level of ozone concentrations (40 ppb) is exceeded at every hour of the day under consideration (exact average values will be obtained in days where all daytime ozone observations are available). The average ppb values obtained in this way are compared in Figure 2. The reason for comparing the quantities in this way is the fact that some stations have only a few measurements in some days, while all measurements are

available in other days. If daily AOT40 values are used (by taking into account only the daytime hours at which measurements are available), then (1) the values will vary in a very large range and (2) the AOT40 values calculated in this way may be very different from the real AOT40 values when many observations are missing. Using the average values described above provides much more realistic quantities. We are still able to see the periods where the ozone concentrations are high and, at the same time, to take into account the fact that there are missing observations.


7-year period: 1989-1995 Effects on crops

Plate 1. Distribution of the cumulative ozone exposure (percentages: 1 O0 xAOT40C/3000).


i i iiill i i i i1 ! i i i

Plate 3. Distribution of the cumulative ozone exposure (percentages: 100xA OT40C/3000 ).





23,924 BASTRUP-BIRK ET AL.' CUMULATIVE OZONE EXPOSURES IN EUROPE

7-year period: 1989-1995 Effects on forests

Plate 5. Distribution of the cumulative ozone exposure (percentages: 100xA OT4OF/10000 )


Plate 7. Distribution of the cumulative ozone exposure (percentages: 100xA OT4OF/10000 )


Plate 6. Distribution of the cumulative ozone exposure (percentages: 100xA OT4OF/10000 ).


Plate 8. Distribution of the cumulative ozone exposure (percentages: 100xAOT4OF/10000)


7--year period vs Slworst• 6-year period

Plate 9. Comparison of the mean exposures obtained in the 7-year period with the mean exposures of the 6-year period from 1990 to 1995.

7-year period vs S"worsL "• 3-year period

ß

..

ß

Plate 11. Comparison of the mean exposures obtained in the 7-year period with the mean exposures of the 3-year period from 1990 to 1992.

7-year period vs •orsL •' 5-year period

I •l • '•

i

_

7-year period vs "worsL '• 1-year period

DISCI•PANCI•S IN PERCgl• •==J •ao-

ß ß Plate 10. Comparison of the mean exposures obtained in the 7-year Plate 12. Comparison of the mean exposures obtained in the 7-year period with the mean exposures of the 5-year period from 1990 period with the exposures for 1989. to 1994.


'-,', JULY 1989 NO NITROGEN OXIDE CONCENTRATIONS

[ • •

Plate 13. Distribution of the concentrations of nitrogen oxide in Europe, July 1989.

, i i

30% VOCs reduction vs basic run

I J ma- •

Plate 15. Ratios, in percent (the AOT40F values found by reducing the VOC emissions by 30 percent over the AOT40F values for the basic run; both values are averaged over 7 years).

30% N0x reduction vs basic run

RATIO • PERCEh'T

Plate 14. Ratios, in percent (the AOT40F values found by reducing the NOx emissions by 30 percent over the AOT40F values for the basic run; both values are averaged over 7 years).

30T• NOx & 30% VOCs reduction vs basic run

BATIO I• PERCENT

Plate 16. Ratios, in percent (the AOT40F values found by reducing both the NOx emissions and the VOC emissions by 30 percent over


4-10 4

D05

3-10 4

2* 10 4

1'10 4

S102

CH03

D03

D13

A02

D17

CH02

CS01

101

A01

SI03 D10

$B10 GB02

E04 GB12

12

D15 GB08

CS02

CH01

B01

D06 D14

D07

D01• 11

B05

0-100

0* 10 ø 1 * 10 4 2* 10 4 3* 10 4 4* 104

Calculated AOT40C [ppb h]

No. of points = 83, means: calculated- 12573., measured - 9648.

correlation: 0.73, test statistic (H' corr=O) - 9.51

bias- 2925., NMSE- 0.41, FMT-63.00, FB- 0.26, FSD- 0.68

Figure 3. Comparison of calculated and measured AOT40C values at 83 measurement stations. "Test statistics (H: corr=0)" indicates that the correlation coefficient is very significant, the positive value of "bias" shows that the calculated values dominate over the measured, "NMSE" is the normalized mean square error, "FMT" is the figure of merit in time, "FB" is the fractional bias, and "FSD" is the fractional standard deviation (these quantities are used and discussed, for example, by Klug et al. [1992]).

3.4. Using Scatterplots

The calculated A OT40C values (for the 5-year period from 1989 to 1993) have been compared with the corresponding measured AOT40C values at 83 stations in Europe, see Figure 3. Similar comparisons have been performed for the AOT40F calculated and measured values at 82 stations in Europe, see Figure 4. As a rule the stations do not measure in all 5 years (see also Figure 1). Consider, for example, the results for High Muffles in Figure 1. Measurements are available for 4 years (1990, 1991, 1992, and 1993). The average value of the ozone exposure over these 4 years is compared with the average value of the ozone exposure calculated by the model (for the same 4 years) in Figure 3 and Figure 4. If the number of months for

which measurements are available is less than 6 for AOT40F and

3 for A OT40C for a given year, then the results for such a year are not taken into account. This situation occurs in 1990 and 1991

at Ulborg (Figure 1); therefore the average measured exposure at Ulborg for 1989, 1992, and 1993 is compared, in F.igure 3 and Figure 4, with the corresponding exposure calculated by the model (averaged over the same 3 years). When measured ozone exposures at a given station are available for all relevant 6 months of a given year, this does not mean that measurements are available for all daily hours during the 6-month period; there could be some missing observations. The numbers of missing observations in 1989 at many of the stations are given by Zlatev et al. [1996b, Tables 1-3]. In fact, we have not taken into account the measured A OT40F values at 9 of the 91 European measure-


7-10 4 D05

6-10 4 SI02

5'10 4

u_ 4'1½

o

'o 3-10 •

:• 2.10 •

D03

CH03

SlOl

A02

D17 SI03 D06 Dl1•07 A01

101

CH02 D' D04 CS01

B02

D13 D09 CS02

CH01 SI D•2

D02

GB08

D16 D01

1 * 1 0 • CH04 B03 NL04 B01 B05

•3B!0

GB02 E04

0-10 0

0-10 0 1'10 4 2'10 4 3'10 4 4'10 4 5'10 4 6'10 4 7'10 4

Calculated AOT40F [ppb h]

No. of points = 82, means' calculated = 21960., measured = 15771.

correlation = 0.74, test statistic (H: corr=O) = 9.89

bias= 6189., NMSE= 0.45, FMT=62.00, FB-0.33, FSD= 0.82

Figure 4. Same as Figure 3 except for AOT40F values at 82 measurement stations.

ment stations, because the numbers of available hourly A OT40F values are too small at these 9 measurement stations. For AOT40C

the corresponding number is 8. The following example illustrates this statement. In the period from May 1 to July 31, 1989, there are no measurements in 75.3% of the daily hours at the measurement station Offagne, Belgium. It is clear that in such a situation there is no sense to compare calculated and measured A OT40C values. On the other hand, we made many efforts to avoid the removal of many measurement stations. Therefore we accepted measurement stations with considerably many missing observations; removing only 9 when A OT40F values are compared (8 when AOT40C values are compared) of the 91 European stations which measured hourly mean ozone concentrations in the period 1989-1993. More precisely, we accepted all stations that have measurements in more than 50% of the daily hours of the appropriate period (3 months for the crops and 6 months for the forest trees) in at least 1 year in the 5-year period 1989-1993.

3.5. Main Conclusions From Comparisons Between Model Results and Measurements

Let us try to evaluate the results of the comparisons of cumulative ozone exposures calculated with the Danish Eulerian Model with the corresponding exposures measured at many European stations. Consider first the results given in Figure 1. If the following three factors are taken into account, (1) the emissions are rather uncertain (the uncertainty is often evaluated to be no less than 30%; the uncertainty is further increased, because different interpolation rules are to be applied in order to simulate the temporal variations needed in the models), (2) the difficulties mentioned in section 2.6, and (3) the measurements are not reported for all daytime hours at all stations, then the conclusion is that the results shown in Figure 1 are very good (in the sense that the discrepancies between calculations and measurements are as a rule of the same order as the uncertainties in the


input data; this is the best that can be obtained). The agreement at most of the other measurement stations is not so good as that at the stations in Figure 1, but the results are as a rule still quite reasonable.

Consider now the results shown in Figure 2. The first two difficulties (uncertain emissions and difficulties mentioned in section 2.6) are also present in these comparisons. We tried to deal with the third difficulty (missing measurements at some stations) by accumulating the calculated exposures only for the hours where measurements have been reported. Another problem arises in this case. We compare two different quantities: the mean exposures calculated by the model for the 50 km x 50 km grid square where the measurement station under consideration is located with the point value observed at the station. Of course, this problem existed also in the comparisons of the type of that illustrated by Figure 1. However, the time period between two consecutive exposures is long (monthly exposures are compared), which diminishes the significance of the fact that two different quantities are compared. The corresponding time period in Figure 2 is very short (daily mean values are compared). The influence of local sources on the results may sometimes be significant when the periods are so short. The results indicate that also in this difficult situation there is often a good agreement between model results and measurements.

The results in Figure 3 and Figure 4 are surprisingly good. It is seen that the calculated A OT40 (both A OT40C and A OT40F) values are in general greater than the measured A OT40 (again both AOT40C and AOT40F) values. However, this should be expected. Indeed, the summation in formula (1) is carried out for all daily hours for the period under consideration when model results are used, while only the daily hours in which measurements are available can be used when the AOT40 values

at a given station are calculated. This means that a quantity, which is less than the actual A OT40 value, will in general be calculated at a station where some measurements are missing. It is nevertheless seen that the results are very good at many of the measurement stations (this is especially true at the measurement stations where there are only a few missing observations; or no missing observation at all).

4. Are Averaged Over a 5-Year Period AOT40 Values Representative?

As mentioned above, it has been recommended by Ktirenlampi and Sktirby [1996] to carry out computations for 5 consecutive years and, after that, to take the mean AOT40 values for usage in different studies. An attempt is made by this action to avoid A OT40 values obtained in a year with unusual meteorological conditions (say, very warm summer months). The question is: Is averaging over a period of 5 years sufficient? We shall try to answer this question in this section.

4.1. Comparing Exposures Averaged Over Different Time Periods

The Danish Eulerian Model has been run over a period of 7 years (from 1989 to 1995). The mean A OT40 values for the 7-year period were compared with the mean A OT40 values for the three 5-year periods contained in the 7-year period (the periods from 1989 to 1993, from 1990 to 1994, and from 1991 to 1995). The results are given in Plates 1-4 for agricultural crops and in Plates 5-8 for forest trees. In fact, the percentages, by which the critical ozone exposure (3000 ppbxhours for the agricultural crops and 10,000 ppbxhours for the forest trees) is exceeded, are given in Plates 1-8.

The discrepancies between the A OT40F values averaged over 7 years and the AOT40F values averaged over shorter periods are

given in Plates 9-12. Denote the ozone exposure at a given grid point for the 7-year period by N. Consider a period of less than 7 years and denote the ozone exposure at the same grid point by

M. The quantity 100 I N - M I / Nhas been calculated at all grid points for all periods in which the number of years is less than 7 years. Let us assume that the periods of k consecutive years, where k < 7 are studied. We determined for each k < 7 the periods where the discrepancies are largest (by visual comparison of the appropriate color plots) and call these periods "worst" periods for the value of k under consideration. The quantities

100 I N - M I / N at each grid point for the "worst" periods with k = 1, 3, 5, 6 are given in Plates 9-12.

4.2. Conclusions From Comparisons Over Different Time Periods

It must be emphasized that further experiments, where the models are run over other time periods and/or longer time periods, have to be carried out. However, some conclusions can also be

derived from the experiments presented in this paper. Comparing Plates 1-8, it is seen that the pattern for the 4

different time periods is nearly the same. This indicates that a time period of 5 years seems to be sufficient in the efforts to obtain representative results (both for agricultural crops and for forest trees). This is illustrated in a very clear way in Plates 9-12. Plates 9 and 10 show that the results are very similar if the period of consideration is 7, 6, or 5 years. The discrepancies become larger when the period is only 3 years (Plate 11). Plate 12 shows that a period of 1 year could give results which may be quite different from these for a 7-year period.

Comparing the results shown in the first 4 plates, Plates 1-4, with the corresponding results in the next group of 4 plates, Plates 5-8, one can conclude that the harmful effects of ozone on agricultural crops are more pronounced than the harmful effects of ozone on forest trees.

The A OT40 values are increasing when we move from the northern parts of Europe to the southern parts (both for the agricultural crops and for the forest trees). The only regions where the cumulative ozone exposures do not exceed the critical ozone exposures are the central and the northern parts of Scandinavia, Finland, and the northern parts of Russia. This indicates that it is necessary to make some attempts to reduce the cumulative ozone exposures in very large parts of Europe, where the critical levels are exceeded by a factor up to 7 (and even by a factor greater than 7).

The A OT40 values in southern Europe are very high. There are different reasons for this, most of them are discussed by Kallos et al. [1995, 1996] and by Milan et al. [1996]. One must probably take into account the different climatological conditions in the southern Europe countries (and even in some countries in central El•rope3 and try to determine the AOTd{) val•oq nq a fi•ncticm c•f the latitude. Some other factors might also be taken into account (see also section 7.2). Note, for example, that the growth periods for the crops change when we move from north to south. This indicates that also the time period, in which the AOT40 values are calculated, could be varied when we move from north to south.

5. How to Reduce Cumulative Ozone Exposures in Europe

The levels of the ozone concentrations in the troposphere depend essentially on the amounts of the NO• and the VOC emissions. Therefore it is straightforward to try to regulate the cumulative ozone exposures in Europe by changing the NOx and the VOC emissions. Several experiments have been carried out by using various scenarios for these two types of emissions. Some results from these experiments will be discussed in this section.


Table 1. Four Major Scenarios Used in Section 5.1

Scenario NOn Human-made VOC Emissions, % Emissions, %

Basic 100 100 NO n reduced 70 100 Human-made VOC reduced 100 70 Both reduced 70 70

The basic scenario is obtained by using the emissions in Europe unchanged. In the other ttn'ee scenarios, one of the emissions or both emissions are reduced everywhere with a constant factor of 30%. Only the human-made VOC emissions are varied; the natural VOC emissions are kept unchanged.

It must immediately be stressed that the main purpose is only to show some trends in the relationship between emissions and cumulative ozone exposures in Europe (but not to describe quantitatively how to reduce the exposures to the critical exposures, which is a much more difficult task and a great challenge for future investigations).

5.1. Basic Scenarios Used in Experiments

Four primary emission scenarios with different NOn and VOC emissions have been considered in this study. These scenarios are shown in Table 1 (some other scenarios will be discussed in section 5.2). It should be mentioned that only the human-made VOC emissions have been reduced; the natural VOC are kept unchanged in all scenarios. Some results obtained in the experiments with the basic scenarios are given in Plates 13-16.

5.2. Conclusions From Experiments With Different Scenarios

If only the NO x emissions are reduced by 30%, then there are areas in Europe where the ozone exposures are in fact increased, see Plate 14. These areas are the highly polluted areas in Europe: compare Plate 14 with Plate 13 where the nitrogen oxide concentrations for July 1989 are shown.

If the human-made VOC emissions are reduced, then the reductions are largest precisely in the same areas where the ozone exposures are increased when only the NOx emissions are reduced: compare Plate 15 with Plate 14. There are also here some areas where the ozone exposures are increased. These are areas where (1) the human-made VOC emissions are either very small or missing and (2) the ozone exposures are very small also when the basic scenario is used: compare Plate 15 with Plate 5.

The greatest reductions are achieved when both the NO x emissions and the human-made VOC emissions are reduced:

compare Plate 16 with Plate 14 and Plate 15. The main tendency in this case is that the reductions are increased smoothly when one moves from south to north.

6. Is the Relationship Between Exposures and Emissions Linear?

It would be very convenient to have a linear relationship between the cumulative ozone exposures in Europe and the relevant emissions (the NOx emissions, the human-made VOC emissions, and the combination of NO x emissions and human-made VOC emissions). Assume, for example, that (1) only the NOx emissions can be regulated, (2) it has been established that the relationship between the NO x emissions and the ozone exposures is linear, and (3) the plot of the straight line that represents the relationship between the NOx emissions and the ozone exposures has been drawn, then it will be very easy to find out by how

much the NO x emissions should be reduced in order to obtain some prescribed reduction of the cumulative ozone exposures. The idea is very simple and it has been implemented in several models in the end of the 1970s and in the beginning of the 1980s [e.g., Alcamo et al., 1984, 1986]. However, such models have mainly been used in connection with studies of sulphur pollutants. The assumption about a linear relationship between sulphur emissions and sulphur depositions can be verified to a certain degree (or, at least, it can be shown that such an assumption is not quite wrong). On the other hand, ozone participates in many nonlinear reactions. This implies that it is necessary to study more closely the relationship between the relevant emissions and the cumulative ozone exposures in the summer months and in different parts of Europe. Some results obtained in such a study will be presented in this section.

6.1. Description of Additional Scenarios Used in This Section

It is necessary to carry out many experiments in order to obtain information which will allow us to determine what kind of

relationship takes place between emissions and ozone exposures. A factor that has been varied in the range r = 0.0(0.1) 1.0 has been used in three types of experiments: (1) to reduce all NO x emissions in all of Europe by a factor of r, (2) to reduce all VOC emissions in all of Europe by a factor of r, and (3) to reduce both the NO x emissions and the VOC emissions in all of Europe by a factor of r.

6.2. Presentation of Results From Additional Scenarios

The code has been run for August 1993. For every grid point and for each reduction, 11 values are available. This is quite sufficient to give an indication about most of the relationships. Some results are given in Figure 5-7.

1. The relationships obtained at the sites, selected when the NOx emissions are varied, are given in Figure 5.

2. The relationships obtained at the sites, selected when the VOC emissions are varied, are given in Figure 6.

3. The relationships obtained at the sites, selected when both the NO x emissions and the VOC emissions are varied, are given in Figure 7.

The locations of the sites selected for the plots in Figures 5-7 are given in Figure 8. The sites chosen can be divided into two groups: 6 in the highly polluted areas of central Europe and 6 far from the highly polluted areas of Europe. In each plot, one of the sites from the first group and one of the sites from the second group are given. It is clearly seen that the influence of emission reductions on the A OT40 values is in general much stronger at the sites from the first group.

6.3. Conclusions From Results From Additional Scenarios

It is clearly seen that the relationship between emissions and ozone exposures is not linear; at least in some parts of Europe. For some sites, mainly in the highly polluted parts of Europe (as,


2000

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0 20 40 60 80 100 % NOx emissions

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8OOO

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I --•- Algeria -',- Germany 1

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0 20 40 60 80 100 0 20 40 60 80 100 % NOx emissions % NOx emissions

[+Greece--- Poland I I-'•France •' Spain- I Figure 5. Relationship between the NOx emissions and the AOT40 values for August 1993 at 12 sites in Europe.

for example, sites in Germany, France, and the Netherlands), the relationship is highly nonlinear. For other sites (normally, for sites far away from the big sources as, for example, for sites in Finland and Algeria), the relationship seems to be close to linear.

It should be mentioned here that a procedure for exchange of ozone between the boundary layer and the free troposphere is implemented in the model (the upper boundary condition, see section 2.5). The amount of the ozone injected in the boundary layer is increasing from north to south. This explains why the ozone exposures in Greece and Algeria are not zero when the NO• emissions are reduced to zero.

6.4. Need for Running Scenarios Over Longer Time Periods

It must be reiterated that the runs with 11 different reductions have been run for a very short period: only 1 month (August 1993). Therefore the results presented in this section must be considered only as an indication that the relationships between the ozone exposures and the related emissions are in general nonlinear. Many more experiments (first end foremost, experiments over longer time periods) are needed in order to confirm the conclusions presented in the previous section.


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[----Greece---Poland I rFrance---Spain I Figure 6. Relationship between the human-made VOC emissions and the AOT40 values for August 1993 at 12 sites in Europe.

7. Plans for Future Work

The results could be improved in several different ways. Two issues are in our opinion very important: the use of a three-dimensional version of the model and the need to take into account

some additional factors (such as, for example, the moisture of the surface), which have been ignored in the first phase of the study; this phase is called "level I" in the work of Ktirenlampi and Sktirby [ 1996]. These two issues will shortly be discussed in this section.

7.1. Use of Three-Dimensional Model in Simulations

All experiments have been carried out with the two-dimensional version of the Danish Eulerian Model on a 96 x 96 grid. While the horizontal spatial resolution of this version, about 50 km x 50 km, is quite satisfactory, it is perhaps better to use the three-dimensional version of the model [Dimov et al., 1996; Zlatev et al., 1996a]. There are several reasons for this: (1) it would be possible to calculate vertical profiles of the concentrations, (2) the wind in the different layers has normally different


2000

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--• Denmark--- Finland

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0 20 40 60 80 100 0 20 40 60 80 100 % VOC, NOx emissions % VOC, NOx emissions

I--•- Greece -'- Pøland I I --•- France -'- Spain I Figure 7. Relationship between the combination of NO x and human-made VOC emissions and the AOT40 values for August 1993 at 12 sites in Europe.

directions and different velocities, and (3) the temperatures in the different layers are normally different (which is important for the chemical reactions). This list can be continued. However, there are nevertheless two important reasons for not using the three- dimensional version at present:

1. The experiments performed to obtain the results described in this paper are very time consuming. We performed many hundreds of runs. The use of the three-dimensional version will

be very demanding computationally (but not prohibitive). It is necessary to optimize better the three-dimensional version for ef-

ficient runs on the modern high speed computers, before starting to use this version manually in long simulations.

2. While it is difficult but still possible to run the three-dimensional version on high-speed computers, the problem with high-quality input data for the three-dimensional model is still open. Many people believe that a three-dimensional model solves automatically all the problems if we can just run it on a computer. This is unfortunately not true. The three-dimensional model is a necessary condition for obtaining better results; but it is not sufficient. All input data must be improved. This is especially true


Figure 8. Locations of the 12 sites used in the plots in Figures 5-7.

for the emissions. Better emission inventories with a good temporal resolution are absolutely necessary.

The hope is that it will soon be possible to use the three-dimensional version of the Danish Eulerian Model in similar

simulations. It is necessary to improve the efficiency of the numerical algorithms when these are used on high-speed computers in order to be able to accomplish such a task. It is even more important to obtain high-quality input data (both meteorological data and emission data).

7.2. Taking Into Account Additional Factors

Many experimental results indicate that if the critical cumulative ozone exposures (3000 ppbxhours for agricultural crops and natural vegetation as well as 10,000 ppbxhours for forest trees) are exceeded, then certain damages can be observed on the receptors. However, this is a qualitative conclusion only. It is desirable to get some reliable quantitative evaluations of the damages. In order to be able to do this, one should take into account (in the determination of the AOT40 values and, thus, also during the whole simulation process) the influence of some additional factors on the results. Such additional factors are

moisture of the surface, humidity of air, cloudiness of the sky, and many others (see more details about this in the work of Kiirenlampi and Skiirby [ 1996]). These parameters must be taken into account in the calculations of the A OT40 values; perhaps by introducing some appropriate factors in formula (1). Simulations of this type (and more precisely, the conditions under which such simulations are to be carried out) will be determined in a second phase of the studies of cumulative ozone exposures (called "level II" by Kiirenlampi and Skiirby [1996]). Such simulations will be carried out as soon as the concepts concerning the use of additional factors are precisely defined (we believe this will happen in the near future).

Acknowledgments. This research was partially supported by NATO (North Atlantic Treaty Organization) grant OUTR.CRG.960312, SMP (Danish Strategic Environmental Programme), two EU projects (WEPTEL Esprit 22727 and EUROAIR Esprit 24618), and the Danish Natural Sciences Research Council (SNF). The work of I. Uria has been supported by LABEIN (Bilbao, Spain), by a grant given from Bizkaiko Foru AldundiaJDiputacion Foral de Bizkaia. The input data (both the meteorological data and the emission data) have been received from the Norwegian Meteorological Institute (DNMI). The measurement data used in the comparisons have been received from the Norwegian Institute for Air Research (NILU). Two unknown referees made many helpful remarks concerning the improvement of the presentation of the results in this paper. The authors should like to thank them very much.

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A. Bastrup-Birk, J. Brandt, and Z. Zlatev, Department of Atmospheric Environment, National Environmental Research institute, Frederiksborgvej 399, P.O. Box 358, DK-4000 Roskilde, Denmark. (e-mail: [email protected]; [email protected]; [email protected])

I. Uria, LABEIN Technological Research Centre, Cuesta de Olaveaga 16, E-48013 Bilbao, Spain. (e-mail: [email protected])

(Received October 16, 1996; revised May 12, 1997' accepted June 21, 1997.)

Studying cumulative ozone exposures in Europe during a 7-year period

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