The Danish eulerian hemispheric model — a three-dimensional air pollution model used for the arctic

Pergamon PII:

Atmospheric Environment Vol. 31, No. 24, pp, 4169-4191, 1997 © 1997 Elsevier Science Ltd All rights reserved. Printed in Great Britain S1352-2310(97)00264-1 1352-2310/97 $17.00 + 0.00

THE D A N I S H E U L E R I A N H E M I S P H E R I C M O D E L - - A T H R E E - D I M E N S I O N A L AIR P O L L U T I O N M O D E L U S E D F O R THE ARCTIC JESPER HEILE CHRISTENSEN National Environmental Research Institute, Department of Atmospheric Environment, Frederiksborgvej 399, DK-4000 Roskilde, Denmark (First received 22 October 1996 and in final form 18 May 1997. Published September 1997)

Abstract--A three-dimensional Eulerian hemispheric air pollution model, the Danish Eulerian Hemispheric Model (DEHM), is in development at the National Environmental Research Institute (NERI). The model has been used to study long-range transport of air pollution in the Northern Hemisphere. The present version of the model includes long-range transport of sulphur dioxide (SO2) and particulate sulphate (SO]-). The chemistry in the model is described by a simple linear oxidation of SO2 to SOl-, and the wet deposition of SO2 and SO]- is estimated based on the amount of precipitation, which is calculated from the contents of liquid cloud water (see Christensen, Air Pollution Modelling and its Applicatioons, Vol. X, pp. 119-127, Vol. XI, pp. 249-256, Plenum press, New York; 1995, Ph.D. thesis, National Environmental Research Institute, Denmark). The model has been used to study the air pollution in the Arctic. Results from 3~ yr simulation with an analysis of the results is presented: the model results are verified by comparisons to measurements not only from the Arctic region but also from Europe and Canada. Some examples of episodes in the Arctic including analysis of the meteorological conditions during the episodes are presented. Finally, the model has been used to estimate the contribution from the different source regions on the northern hemisphere to the Arctic sulphur pollution. © 1997 Elsevier Science Ltd. Key word index: Arctic, sulphur long-range transport model, 5 0 2 ,

1. INTRODUCTION Over the years there has been a considerable scientific interest for air pollution in the Arctic. One major reason for this is that the Arctic area is rather sensitive to pollution, with respect to the environment, the stratospheric ozone layer and the climate. Therefore, there is a need for studying the air pollution levels in the Arctic and to evaluate the future development as well as the effects of different actions towards the pollution releases on the Northern Hemisphere. The environment in the Arctic reflects the sharp balance between its physical, chemical and ecological components. Because of this sensitive balance, the Arctic may act as an early warning system for the global changes (see Roederer, 1991). During the last 20 yr period several groups have measured air pollution in the Arctic (see, i.e. AGASP, 1984; AGASP II, 1989; Arctic Air Chemistry, 1985, 1989, 1993). These measurements show that the air pollution has a large seasonal variation with relatively high concentrations during winter and early spring and very low concentrations during summer. The air pollution is characterized by an episodic nature due to the domination from long-range transport. Long-range transport models are needed for studying properly the transport and physical and chemical

SO 2-,

Arctic air pollution modelling.

processes in the atmosphere, and to make quantitative estimates of the origin of Arctic air pollution. However, only few attempts have been made to develop long-range transport models that are able to describe the transport of air pollution to the Arctic in a reliable way. There are two groups of long-range transport models: trajectory models and Eulerian models. Trajectory models are relatively easy to construct, and they are useful tools, especially to study simple transport and chemistry to a limited number of receptor points. The main problem with trajectory models in this context is that they are not able to connect the emission areas with the arctic areas, because trajectories longer than 4 to 5 d in the lower part of the troposphere are highly unreliable. An example of a trajectory model applied to the Arctic area is the model as given in Barrie et al. (1989), and is based on the three-dimensional AES trajectory model (from the Canadian Atmospheric Environment Services (Olson et al., 1978; Voldner et al., 1981)). The model is used to describe transport of SO2 and SO 2-. Eulerian models include complex mathematics and are generally very computing demanding. The Eulerian models have different advantages. It is possible to treat diffusion, both the vertical diffusion, which is

4169

4170

J.H. CHRISTENSEN

a result of the vertical turbulence in the boundary layer and inside the clouds, and the horizontal diffusion due to fluctuations (and uncertainties) in the horizontal wind-field, which are not resolved in the meteorological input. One of the problems with Eulerian models is the difficulties with the treatment of plumes from point sources. An example of a Eulerian model, used for the Arctic, is the model developed by Trond Iversen (Iversen,

1987, 1989: Tarrason and lversen, 1992). This model is a three-dimensional model that covers most of the Northern Hemisphere. The model has 10 vertical layers in isentropic coordinates. The model has two chemical species: SO, and SO~, , where the oxidation of SO2 to SO~ is described as a first order reaction. The model includes a meteorological preprocessor that estimates heating (i.e. vertical velocity across the isentropic levels) and precipitation

D ,pV'*

t P

t

Above 800,0 e00.0 - e0GO 4 0 U - e0Go ~o.0

- ,Ioo.0

lO0,O - 20GO a 0 . 0 - 100.0 2 8 . 0 - 6GO 1 0 . 0 - 2fL0 6 . 0 - 10.0 Below 6.0

Fig. 1. The model area and the anthropogenic SO2 emissions in 1000 tonne S (grid-square*year) 2 important Arctic sources and the location of 3 Arctic monitoring stations.

~ with

The Danish Eulerian hemispheric model from analyses of the meteorological input. One of the advantages with isentropic coordinates is that the transport nearly follows the isentropic surfaces. This is because the vertical velocity in the free troposphere defined in the isentropic coordinates is smaller compared to terrain following coordinates, as e.g. a-coordinates. This means that the numerical error in solving the vertical advection is small. Isentropic coordinates, however, also introduce some problems, mainly the treatment of the surface. It is possible in the model to have transport through the surface, because the potential temperature at the surface is not constant. It is further necessary to redefine the isentropic levels in the model as function of season, to minimize the model domain below the surface. Another Eulerian model is the global sulphur model by Dastoor and Pudykiewicz (1996). This global model, using a-coordinates as vertical coordinates, includes a meteorological model, based on the canadian global spectral model. The chemistry contains a sulphur part, which includes SO2, sulphate in air, in-cloud sulphate, and first order gas- and aqueous-phase transformation. The model simulates the important dynamics in the atmosphere to give a realistic description of the long-range transport of sulphur to the Arctic. It was decided that the Danish Eulerian Hemispheric Model (DEHM) had to be a full three-dimensional Eulerian model with a-coordinates in the vertical. As a simplification of the complex chemistry the model had only to include SO2 and SO~- as in

~' S ~'¢~"

4171

the hemispheric model by Iversen (1987, 1989) and Tarrason and Iversen (1992).

2. G E N E R A L D E S C R I P T I O N O F D E H M

The model is based on a set of continuity equations for each species, which are coupled through the chemical reactions, condensation of humidity and evaporation of cloud water, and wet scavenging. The continuity equation is given by (see e.g. Pudykiewicz, 1991) ~q' _ ( u -if=

+

~_~qx~4. v~y~ 4. d-~a~)

K ~ x 2 + Ky 63y2

6~ff

4- Pi( t , x , y , a , ql . . . . ) - Qi( t , x , y , a , ql .... ),

i = 1,nq where qi is the mass mixing ratio for species i: qi = cliP, where c~ is the concentration and p is the density of air, x and y the horizontal coordinates and a is the terrain-following vertical coordinate (a = PIPs, where p is the present pressure and ps surface pressure), u and v are the horizontal velocities and b is the vertical velocity in a-coordinates. Kx and Ky are the horizontal diffusivities (assumed to be constant:

"~'~'.~..%

.%,%,

m . summer "'"

spring/autumn

winter 0.4

% %.%. N.

". "-% .-. 0.3

",

_

,,,

N.

%

0.0" 0

10

20

30

40

(1)

50

60

70

80

90

Latitude

Fig. 2. The oxidation of SO2 to SO 2- in d - ~ as function of the latitude for the four seasons.

I

J

I

4172

J.H. CHRISTENSEN

Kx = K s, - 1 x 10 s m e s ~, somewhat large values due to the crude meteorological input and the constants are the same as in Piedelievre et ell. (1990)), and K: is the vertical diffusivity. V - d a / d z is given by -,q/)/p,, q a / R T (assuming hydrostatic equilibrium and introducing the ideal gas law). y is the acceleration due to gravity, R is the gas constant and T the air temperature. Pi and Qi are the production and loss terms for species i. nq is the number of species. In the present version nq = 4, where the four species are SO2, SO 2-, humidity and cloud water, respectively. The Northern Hemisphere is treated as a plane through a polar stereographic projection that is true at 60' North. The horizontal domain (see Fig. 1) is defined on a regular 96 x 96 grid that covers most of

the Northern Hemisphere with a grid-resolution of 150 km at 60°N. The size of the domain is chosen to be large enough to include all important source regions in the Northern Hemisphere for the Arctic air pollution. The vertical grid is an irregular grid with 12 layers from the surface up to approximate 7 km. The time integration is performed by splitting equation (1) into several sub-models, which are treated separately in each time step. However, the splitting procedure causes some errors which cannot be evaluated in an easy manner. Splitting is commonly used in air pollution models (see, e.g. McRae et al., 1982). The three-dimensional advection equation is solved by a pseudospectral algorithm (see, e.g. Christensen,

c o n c e n t r a t i o n for 1 9 9 0 to 1 9 9 4 of S02

Above

4.0

2.0 - 4.0 1.0 - 2.0 I

I

0.8 - 1.0 0.4 - 0.8

units: p p b V

0.2-0.4

Sdow O~ Fig. 3. The mean distribution during October 1990 to May 1994 of SO2 and SO,~ at the surface level.

The Danish Eulerian hemispheric model

4173

c o n c e n t r a t i o n for 1 9 9 0 to 1 9 9 4 of SO,

| mm mm

II

Above 1.00 - J ~ O 0 . 5 0 - 1.00 O . U - O.SO 0.18 - 0.25

anita:

0.10 - 0.18 0.10

Fig. 3b.

1993, 1995) for the horizontal space derivatives and by a one-dimensional finite element method for the vertical space derivatives (Pepper et al., 1979; Christensen, 1993, 1995). The time integration of the advection equation is performed by a predictor-corrector method with several correctors (Zlatev, 1984; Christensen, 1993, 1995). The time step is typical between 500 and 3600 s, depending on Courant Number and an error estimate based on the predictor-corrector method (Zlatev, 1984). A horizontal mass-conservative Forester filter is applied in order to reduce spurious oscillations after each time step (Forester, 1976). This combination of the pseudospectral method and a Forester filter gives a very accurate numerical solution to the horizontal transport equation (Chock and Winkler, 1994; Dabdub and Seinfeld, 1994).

The pseudospectral algorithm demands periodical boundary conditions, which are imposed by some artificial sinks on the horizontal boundaries (Zlatev et al., 1992; Christensen, 1993). The boundary conditions at the ground are defined by fluxes out of or into of the model domain which are only due to the dry deposition and the surface emission: ~qi K~ -~a = - FVd ql + F Es P

(2)

where Vd is the dry deposition velocity and Es is the surface emission. Free boundary conditions are applied for the upper boundary. The model was tested carefully (Christensen, 1993, 1995) and found to work satisfactorily well with regard to numerical efficiency and numerical error.

4174

J.H. CHRISTENSEN 3. M E T E O R O L O G I C A L INPUT, PHYSICAL AND CHEMICAL PROCESSES

All meteorological data are obtained from the European Centre for Medium-range Weather Forecasts (ECMWF). The meteorology include two data sets, ECMWF/TOGA Basic Level III Consolidated Data Set and the ECMWF/TOGA Supplementary Fields Data Set, both on a 2.5 ° x 2.5 c' latitude-longitude grid. All the meteorological data are linearly interpolated in space and time, a crude but simple procedure. This could be improved by using a meteorological driver as, e.g. MM5 (see, e.g. Grell et al., 1995). The ECMWF/TOGA Basic Level III Consolidated Data Set are uninitialized analysed data with a time resolution of 12 h (at 00 UTC and 12 UTC) and con-

tain two parts: upper air data and surface data. The upper air data are defined for 14 or 15 levels (15 levels after 1/1 1992, the new level is at 925 hPa): 1000, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, and 10 hPa, and they contain the latitude and longitude components of the wind, vertical velocity, temperature, geopotential, and relative humidity. The surface data contain surface pressure, mean-sealevel pressure, temperature at the ground and in 2 m, dewpoint in 2 m, surface geopotential, latitude and longitude components of wind in 10 m, and land-sea mask. The ECMWF/TOGA Supplementary Fields Data Set contains additional surface data and fluxes data derived from short-range forecasts and used as firstguess data for the analyses. The data have a time resolution of 6h (at 00, 06, 12 and 18 UTC) and

Total d e p o s i t i o n for 1 9 9 0 to 1 9 9 4 of S

mm

Above 100 60 - 100 2 0 - 60 1 0 - 20 410 24 Below 2

units: mg Slm 21month

Fig. 4. The total deposition of sulphur during the period October 1990 to May 1994.

4.0

25-

0

*

Fig. 5. The mean fluxes through

< 4.5

-3.5--2s

-25--1.6

-1.5-45

1.0

0.0

ao-

-as-

l.O- 25

55

>ss

4.0-

6

the 75” latitude

circle as a function

of the longitude

Summerflux in kT SM%cm/month

in kT S (15”longitude*km)-’

month -I for the summer

period (left) and the winter period

Winterflux in kT S/l 5%rnhnonth

(right).

e 2

J. H. C H R I S T E N S E N

4176

Table. 1. S u m m a r y of the budget of s u l p h u r for the area north of 75 N for the s u m m e r and winter season. Summer (kTSmonth -l} Flux in Flux out Wet dep. Dry dep. Loss in top Emission Mass c h a n g e

83 41 - 34 9 2 1 1

Chemistry

- 12

Total mass

Winter Half-life (d)

(kTSmonth

x)

188 128 48 12 + 3 0 1

6 8 30 105

5

18

13 k T S

Half-life (d)

5 15 58 241

19

33 kT S

6 HOUR MEAN SOx AT 12 GMT, 9 OF JANUARY 1991

> 8.0 8.O-8.O

25 m/s:

'

0.5-1.0 < o,s Fig. 6. F o u r e x a m p l e s of t r a n s p o r t of SOt to the Arctic. The c o n c e n t r a t i o n s are for the surface level in ppbV, the c o n t o u r lines indicate the mean-sea-level pressure, and the windfield is at 600 m altitude.

The Danish Eulerian hemispheric model

4177

6 HOUR MEAN SOx AT 18 GMT, 12 OF MARCH 1992

> 8.0 8.0-80

25 mls:'--*

1,0 - 8,0 0,8-1.0

Fig. 6b.

contain cloud cover, surface layer wind stress, latent and sensible heat flux. The vertical diffusion is parameterized by Kz profiles, based on Monin-Obukhov similarity theory coupled to either observations or computational generated data (see, e.g. Seinfeld, 1986) for the surface layer. This Kz profile is extended to the whole boundary layer by using a simple extrapolation, which ensures that Kz is decreasing in the upper part of the boundary layer and results in quite similar K~ profiles as, e.g. given in Seinfeld (1986). The actual expression for the profile is (see Hertel et al., 1995)

fKu*z(1-~),O.lm2s-1) K~ = max ~ (---~

(3)

where (b(z/L) is the similarity function for heat, x is the von Karman constant, u. is the friction velocity, z is the height above the surface, Zmlxis the height of the mixing layer, and L is the Monin-Obukhov length. It is well known that there are some limitations to this parameterization (local K-theory), especially for fine scale dispersion. A physically more correct parameterization would be based the concept of non-local closure as, e.g. described by Stull (1991). However, this is disregarded in the present model. The mixing layer height is calculated by a simple parameterization similar to Berkowicz and Olesen (1990) and Gryning and Batchvarova (1990), which is based on a simplified energy balance equation for the

4178

J. H. CHRISTENSEN

6 HOUR MEAN SOx AT 06 GMT, 2 OF FEBRUARY 1993

> B.O 8.0 - 8.0 I.O - ~ o 0 . 5 - 1.0 <

25

0.5

Fig. 6c.

internal boundary-layer N2..

d2mi x

u~

--+1.9 -m~x dt

dzmi x

Zmix dt

• ~, b/, ~ / ( : Z m i x CZmi x O.~mix N 2 2mix + | . ~ ' - - l l ~ + u ~ q- t : ~ -}- w / Zmix/\ ( t (X 6y //

w~ Zmi x

1.25u~, + - Zmi x

mls: --~

u~

o.5 we

T

T

(4)

where N is the Brunt-Vaisala frequency, N 2 =yg/T(? is the lapse rate and T is the temperature), w is the vertical velocity at Zmix, W, =(,q/Tmax(Hs~n/(pcp),O)" Zmix)1/3 is the turbulent velocity scale and v is the dissipation time scale ( = 1100 s). The effect of entrainment is ignored in equation (4). The first term on 1.h.s. of equation (4) is the increase in the boundary layer

potential energy per time unit (buoyancy force, N2zmix, times the increase of mixing height per time unit, dzm~x/dt), and the second t e r m is the increase in kinetic energy, which is assumed to be proportional with u 2. The first term on the r.h.s of equation (4) is the convective energy input due to buoyancy, and the second term is the mechanical energy input, and the last two terms is the dissipation of mechanical and convective energy. This is similar to the procedure in the new Eulerian E M E P model at E M E P M S C / W (Jakobsen et al., 1995). The applied emission inventory for anthropogenic SO2 is based on a combination of several emission inventories. The fundamental inventory is the global G E I A inventory for sulphur emissions version 1A for the year 1985 by Benkovitz et al. (t996), which are on a 1~ × 1~' latitude longitude grid. These emissions are

The Danish Eulerian hemispheric model

4179

6 HOUR MEAN SOx AT 12 GMT, 22 OF FEBRUARY 1994

l l mm

8.0-8.0 1.0 - 8.0 0 . 6 - 1.o < o.8

25 m/8:---,"

Fig. 6d.

redistributed to the model grid. EMEP emissions for 1990 (Sandness and Styve, 1992) are used for the area which covers the EMEP grid. The anthropogenic sulphur emissions are shown in Fig. 1. The important anthropogenic sources for the pollution in the Arctic region are the large industrial complexes at Norilsk and at the Kola Peninsula (see Fig. 1), which both have large copper-nickel smelters, and the rest of the emission from the former USSR. The total emissions for 1990 from Norilsk were about 1.2 million tonnes S and for Kola Peninsula they were about 0.4 million tonnes S, which can be compared to the total European emissions of about 20 million tonnes S in 1990. The emissions are distributed evenly up to 800 m above the surface, and are assumed constant in time. The reason to choose a constant height and not the

mixing height is that during stable conditions with small mixing heights, a large part of the emission will be emitted above the mixing layer, which is more correct for many of the high sources. The EMEP model (Sandness and Styve, 1992) assume a seasonal variation of the emissions, where the winter emissions for Europe are a factor of two higher than the summer emissions, but this is not correct for the southern part of Europe and for North America, where perhaps the opposite variation would be a more appropriate assumption. It is assumed that 95% of the anthropogenic sulphur emissions are emitted as SO2 and 5% as SO~ . The biogenic sulphur emissions, especially dimethyl sulphide (DMS) from the oceans are important on global scale, because the oceans cover a large part of the Earth's surface. The biogenic emissions are

4180

J.H. CHRISTENSEN

especially important in remote marine regions such as the North Atlantic and Arctic Sea in the late spring and early summer, because of the large biogenic activity of phytoplankton at that time of year (Hertel et al., 1994; Tarrason et al., 1995). Therefore the flux of DMS between air and ocean is included in the model as a function of the concentration of DMS in the ocean (c..... ) and the wind speed at 10 m (Ulo) (EDMs)~ = KU2oC . . . . .

The emissions of sulphur due to volcanic activities are ignored in the present version of the model. In reality the chemistry of sulphur is complex. SO2 is oxidized to SO4z- by two different pathways (gasand aqueous-phase), but in the model the chemistry of SO, is simplified by using a linear first-order oxidation rate as a function of the solar zenith angel (0(lat, T), where lat is the latitude and T is the time of the year), at midday. This spatial and temporal variation of the oxidation rate involves both variations in O H concentrations in gas phase, and H202 and 03 in liquid phase. This linear chemistry is similar to the chemistry of other models (e.g. Zlatev and Christensen, 1989; Iversen, 1989). The actual expression for the oxidation rate is

(5)

where K is an empirical constant with the value K = [0.15x0.01/3600]sm -~ (Hertel et al., 1994). Two types of oceans are taken into account, open oceans, and shelf and coastal regions. The concentrations of D M S in the water for the two types of oceans are somewhat different and are given in Tarrason ez al. (1995); the DMS concentration has a large spatial variability, and therefore the emissions of DMS are highly uncertain. It is assumed that 44% of the DMS flux is decomposed instantaneously to SO2 and 4% to SO4z- (Hertel et al., 1994). In the model by Tarrason and Iversen (Tarrason et al., 1995) 66% of the DMS emissions are decomposed to SO2.

OXso = z

I

/ sin(O(lat,r)) 4.7x 10 ~'max/0., p \ sin(0(50:N,23june ]

+ 0.3xl0-°ls

~

(b)

This oxidation rate is expressed in a way that ensures a rate close to the one in the EMEP-model (Sandness and Styve, 1992) at 50°N and during the Arctic night the rate is close to the one in the hemispheric model

Total 1990-1993 csj

9-

/

8-

//

7-

6OE (/)

~4g 8

DE2

3-

,/ /

2-

IT 4

/

NL 2DE17

DE4

.

PT4 ES I

" OH 2

/ ,, E S / ~/ ./~1~. 11"2

o

i

0

I

1

i

DEI~

DE 3 I

2

i

I

3

(a) NUMBER OF STATIONS IS COMPUTED MEAN OBSERVED MEAN CORRELATION FACTOR

i

I

4

i

I

i

5

t

6

i

l

7

~

i

8

I

9

Calculated SO2 in ppb 30 2.33 1.65 0.92

Fig. 7. Scatterplots for the comparison between the average concentrations from October 1990 to December 1993 of SO, and SO ] as monitored by EMEP and calculated by DEHM.

The Danish Eulerian hemispheric model

4181

Total 1990-1993

2.02

1.75

1.5-

" 1.25" ._c og -

//

1.0-

/ 0 0.75-

/

/;

/

FR10/

/

DE12

DE4 DE17 DE18

-~U "~'

z j-"

0.5,

0.25

0.0

Itlli=ii~i=ll=lVit

0.0

0.25

0.5

=It

0.75

(b)

II=lllt

1.0

1.25

ilii]~ltlt

1.5

tit

1.75

2.0

Calculated SO, in ppb NUMBER OF STATIONS IS COMPUTED MEAN OBSERVED MEAN CORRELATION FACTOR

29 0.91

0.81 0.87

Fig. 7b.

by Iversen (Iversen, 1987, 1989; Tarrason and Iversen, 1992). Figure 2 shows the rate as a function of the latitude for the four seasons. Normally the dry deposition velocity has considerable variability determined by variations in meteorology and differences in surface characteristics. Dry deposition of SO2 can be parameterized by an analogy to a series of electric resistances by assuming that the dry deposition velocity is inversely proportional to the sum of three resistance terms (see, e.g. Walcek et al., 1986) Vd(2rn) =

ra-'k rbq- re

(7)

where ra is the aerodynamic resistance to pollutant transport at the reference height of 2 m, i.e. the lowest level in the model (see, e.g. Voldner et al., 1986), rb is the laminar-resistance (see, e.g. Voldner et al., 1986), and rc is the bulk surface resistance and depends on surface characteristics. The applied land use database is classified in 8 surface types (see Voldner et al., 1986): coniferous forest, deciduous forest, cultivated land, grassland, urban, swamp, open water and snowfice, based on land use data from Wilson and Henderson-

Sellers (1985). The roughness length for the different land use categories is given in Voldner et al. (1986), and is used to calculate u. and ra for the various surface types, rs is also given in Voldner et al. (1986), with an extra surface resistance term (see Wesely, 1989), which ensures that the surface resistance increases markedly when the surface temperature decreases below - 2°C. Dry deposition of SO~- depends on two types of surface: open water and the rest. The dry deposition to open water is given by the formula in Slinn and Slinn (1980) assuming a mass mean radius near 1/~m for the sulphate aerosols Vd,o (2m) = 1.3 x 10-3Ulo

(8)

with the restriction that deposition is limited by the aerodynamic resistance for SO 2-. Over non-open water surfaces the dry deposition is calculated by using (see Walcek et al., 1986; Seland et al., 1995)

-~ / Vd~°,(2m) =

t

2/3 U_~.

a

for L > 0

(9)

4182

J. H CHRISTENSEN

where a is 500 (except for a forest with leaves, where a is 100), and L is the Monin-Obukhov length. Wet deposition is an important removal process for sulphur. A simple parameterization, which is based on a scavenging ratio formulation (see, e.g. Iversen, 1989; Tarrason and Iversen, 1992), is applied in DEHM for the wet deposition. For both SO2 and SO42- at a given u-level the scavenging coefficient is given as

(A~oP.(a) ~H

p,,.

=)Aoe(a) LH

removal rate inside the clouds, because SOl is a h~groscopic aerosol, p,~ is the density of water. Two parts of the condensation scheme described in Sundqvist et al. (1989), the stratiform precipitation and a simple parameterization of convective precipitation, are included in the hemispheric model. Each 12 h a new humidity field is read from the meteorological input as an initial condition for the scheme. Release of humidity into the atmosphere is a surface emission and is given by the latent heat flux from the meteorological input. After calculation of transport of humidity and cloud water contents, the scheme starts at the top oi each vertical column ( = aT) and goes through the different o--levels down to the surface. The first step in the scheme at a given a-level is to estimate a new value for the humidity, depending on cloud cover, land masks and altitude. If the transported humidity exceeds the estimated humidity then this excess humidity condensates as cloud water, otherwise an evaporation of cloud water takes place. The precipitation is released if the cloud water contents inside the clouds exceed some predefined thresholds, which depends on the type of clouds and temperature. Finally

below cloud scavenging (10t in cloud scavenging

Pw

where P~,(a) is the total precipitation at the level, P(a) is the precipitation created inside the cloud layer, H is an effective thickness for scavenging ( = 1000m), Abe is the below cloud scavenging ratio and has the value between 1 × 105 to 3 x 103, depending on season due to the variation in H202, for SO_, and 1 × 105 for SO~-, A~ is the in-cloud scavenging ratio and for SO2 it is twice the one for below cloud scavenging and for SO]- it is seven times higher due to the enhanced

Total 1990-1994

3.5-

LO

3.0

2.5 t-,

EGB

.~ 2.0 ~

o" 09 "o

1.5

/

e~

//

o

CHA SUT

/

/

1.0-

//

//

"KEJ MTM~J 0.5-

//0.0

II

0,0

I

I

II

[

0.5

I I I I I I l l I I I I I I / I I I ' I P l

1.0

(a) NUMBER OF STATIONS IS COMPUTED MEAN OBSERVED MEAN CORRELATION FACTOR

1.5 2.0 2.5 Calculated SO2 in ppb

liil

3.0

I

3.5

7 1.66 1.42 0.99

Fig. 8. Scatterplots for the comparison between the average concentrations from October 1990 to May 1994 of SO2 and SO~- as monitored by Atmospheric Environment Services in Canada and calculated by DEHM.

The Danish Eulerian hemispheric model

4183

T o t a l 1990-1994

/

1.0.

/' ~m.0.75 a.

/

/

/

/

/i

/

dffJ ~ 0.5-

,,o

0

/

/

fjz

0.25-

0.0 0.0

0.25

(b)

0.5 0.75 Calculated SO, in ppb

NUMBER OF STATIONS IS COMPUTED MEAN OBSERVED MEAN CORRELATION FACTOR

1.0

8 0.65 0.65 0.95

Fig. 8b.

there is a possible evaporation from precipitation. For further details see Christensen (1995) and Sundquist et al. (1989). This gives a crude estimate of the precipitation, and could be improved by using a real dynamic atmospheric model as, e.g. MM5 (see, e.g. Grell et al., 1995).

4. T H E N U M E R I C A L R E S U L T S

The model runs have been performed for the period October 1990 to May 1994. First the spatial distribution of the concentrations of SO2 and SO 2- and the total depositions is discussed, then a discussion of the fluxes into the Arctic and the sulphur budgets is given. Afterwards some examples of episodes in the Arctic are presented, and a comparison of the calculated concentrations with observation is given. Finally, there is a discussion of the source regions to Arctic air pollution. 4.1. The mean distribution of sulphur Figure 3 shows the mean concentrations of SO2 and SO 2- at surface level calculated for the period October 1990 to May 1994. The results show, especially for SO2, that the Arctic area is under the influ-

ence of emissions from especially Norilsk and the other sources of USSR, and that sources in North America are of minor importance. The main pathway for transport of sulphur is from USSR north into the Arctic (see also Fig. 5). The total deposition of sulphur for the whole period is shown in Fig. 4. This figure shows that the total deposition in the Arctic is relative small, from about 20 mg S m - 2 m o n t h - ~ in Russia to less than 4 mg S m - 2 m o n t h - 1 in the Canadian Arctic. This is also the reason for the relatively high concentrations of sulphur in the Arctic troposphere. If the deposition was higher, the concentrations levels would be much lower. There are two areas with deposition larger than 50 mg S m - z month - 1, which are the Norilsk area and Kola Peninsula. Close to the smelters the deposition is even higher, but these areas cannot be resolved by a model with a grid resolution of 150 km × 150 km. For comparison the deposition in Denmark is ~ 100 mg S m - 2 m o n t h - 1 (month = 30d). 4.2. The fluxes into the Arctic and the budgets In Fig. 5 the vertical distribution of the mean sulphur fluxes (based on the gridded fluxes) for the winter

4184

J. H. CHRISTENSEN

(November to April) and the summer period through the 7 5 latitude circle as a function of the longitude. The figure shows the difference in the fluxes between the two seasons with large flux into the Arctic area from Russia and a minor flux from North America west of Greenland and a large flux out at North America and east of Greenland for the winter season. For the summer season the fluxes are much smaller with the largest flux into the area at the Norilsk area, and the largest flux out east of Greenland. These results are somewhat similar to results presented by Barrie et al. (1989). In Table 1 the summary of the total S O , (SO2 + SO ] ) budget for the Arctic, the budget for the chemical transformation of SO2, and the total mean mass of SOx for the two seasons, are given. The flux in and out is based on the total fluxes for each month. For the winter period the netto flux is 6l k T S m o n t h ~, and for the summer period the netto flux is 43 kT S month The main difference between winter and summer is that the fluxes are much higher in winter (2 3 times higher), the chemical half-life of SO2 is much higher (3 times) and half-life due to the deposition processes are a factor of two higher. In the summer period the

half-life of the sulphur is comparable with the halt-life due to transport. 4.3. The episodes in the Arctic There are two sets of conditions that have to be fulfilled in order to obtain episodes of pollution at the surface levels in the Arctic. (1) The horizontal wind must have the right direction, and (21 the air masses at the emission areas should have nearly the same temperature as the arctic area, otherwise the warmer air will rise above the cold Arctic air (i.e. the emissions area should be within the Polar Front). Four situations in which the conditions obey these two requirements are shown in Fig. 6. They represent four typical episodes of transport of SOx 1SO2 + SO~,- ), one for each winter period. The figure shows the 6 h mean concentration of SO., together with the wind field, contour lines for the mean-sea-le~el pressure, and L and H indicate low and high pressure systems. In the winter a rather persistent high-pressure system is built up over Siberia and the East Siberian Sea. These high pressure systems block the westerly flows and the low-pressure systems from the Atlantic. The episodes typically occur when these low-pressure systems stay in the North Atlantic, the Norwegian Sea or the

25t

.~ 1.5

~I.O

f

9.o F ;

= , , , , MARCH

,

OCTOBER

~

" " JANUARY

AUGUST 1991

..

:......i ='= = =ii=i.ji , = . ...=-. , , , , , , , , , , ,.~ , , , ~,-, JUNE NOVEMBER APRIL SEPTEMBER FEBRUARY 1992 1993

1.25l 10

a, 0.75

8 0.5

O b9

0.25-

,.~

•"~

~ ..

O.O~

.:

'

i! m":: ".': ~

"'

~

~

'

i!ii!

~J ~ i,J e~R

~

"

i

OCTOBER

MARCH

so~ SO4 Calculated Observed Correlation

"':

0.21 0.14 0.61

0.17 0.14 0.73

AUGUST 1991

JANUARY

JUNE 1992

NOVEMBER

APRIL

SEPTEMBER FEBRUARY 1993 I - - observed [--- calculated

Fig. 9. Comparisons of observed and calculated weekly mean of SO2 and SO42 for Ny-Alesund at Spitzbergen.

i

'2,

The Danish Eulerian hemispheric model Barents Sea; this results in the right wind for the transport to the Arctic. Between the low- and highpressure systems there is a strong northern flow, which gives a transport of pollution into the Arctic. This is quite similar to an observed Arctic episode which is described in Heintzenberg and Larssen (1983); see also Dastoor and Pudykiewics (1996). In the late spring the persistent high-pressure systems over Siberia break down, and therefore the low-pressure systems from the North Atlantic are moving far east and north, and they are more infrequent and not so very deep. Together with the higher temperature over the former USSR and European sources, this results in limited transport at the surface layers to the Arctic from these areas. In the summer period transport of a small amount of sulphur to the Arctic takes place only at higher altitudes. 4.4. Verification of model results The calculated concentrations of SO2 and SO42have been compared to the European measurements of EMEP and Canadian background stations. These comparisons show that there is good agreement between the calculated and measured concentrations, both on seasonally/monthly and even daily basis for

4185

many EMEP and s o m e Canadian stations (see Christensen, 1995, 1996); the agreement for the wet depositions is not as good for the air concentrations, probably due to uncertainties in the calculated precipitation. Figure 7 shows as an example two scatter plots with the total calculated and observed mean concentrations of SO2 and SO~- during the period October 1990 to December 1993 for the European stations, which have measured continuously for the whole period. This figure shows that there is good correlation between observed and calculated concentrations of SO2 and SO~-. Similar figures for the Canadian background monitoring stations show a good correlation between observed and calculated concentrations of SO2 and SO 2-, see Fig. 8. For the Arctic areas the model calculations are compared to measurements from three sites: Station Nord in northeastern Greenland (81 ° 36'N, 16° 40' W) for the whole period, see W~hlin (1993), NyAlesund at Spitzbergen (78 ° 54' N, 11 ° 53' E) during October 1990 to December 1993, see Schaug et al. (1992, 1993, 1994) and L6vblad et al. (1995), and Alert in Northwest Territories, Canada, (82 ° 50' N, 62 ° 30 W) during the period October 1990 to June 1993 and only of SO~-, see Li and Barrie (1993). For all

2.5-

2.0 ¸

e.

il ¢:~ 1.5 .c

ii ,. !k

iEj!

~1.0 O r./) 0.5

,

.¢~ i , , , , MARCH

0.0 OCTOBER

,-~-, AUGUST

,

'.

, , ,, JANUARY

I

,

JUNE

1991

NOVEMBER

I I I I SEPTEMBER

APRIL

I

I I I I FEBRUARY

I

1993

1992

0.75-

~ o.~. T'i-'l,,"ii.,' s ~n. l' '

ii,

i;

'

,

0,0 I I OCTOBER

Calculated Observed Correlation

I

I

I I I MARCH

SOt

SO,

0.23 0.15 0.58

0.20 0.17 0.7g

I

I

I I I AUGUST

1991

I

~ "

I I I I JANUARY

I

I

I I JUNE 1992

I

I

~n .,!~ .,,mlY'l ,-q

!i i~ iiis~, n i ~J! .~'2 t F ~i

'.

u

I I I I NOVEMBER

,5% t

I

| I APRIL

I

I

I I | I SEPTEMBER

1993

I

o,

I I I I FEBRUARY

~

observed

---

calcu ated

Fig. 10. Comparisons of observed and calculated weekly mean of S02 and SO~- for Station Nord in northeastern Greenland.

I

4186

J.H. CHRISTENSEN

three stations there is a rather good agreement between the calculated a n d observed c o n c e n t r a t i o n s of SO2 and especially for S O l - , see Figs 9-11. 4.5. Sources to Arctic air pollution of,sulphur The vertical distribution of SOx concentrations, averaged over the area n o r t h of 7 5 N , and the contri-

butions from the different sources for the s u m m e r a n d winter season are given in Fig. 12. The figure shows a big difference between the two seasons, with low c o n c e n t r a t i o n s in the s u m m e r season with maximal concentration a b o u t 0.25 p p b V at 2 k m and only small vertical variations except for the surface levels, and for the winter the high concentrations are a b o u t

n

,5-

ii

i']

ii

'1

~1,O

{/)0.5" ""I "'l~t I

fJl

i

OCTOBER

,~.,-i '*'i

ii'i

MARCH

AUGUST 1991

JANUARY

JUNE 1992

I"

I

I

I

I

I

I

NOVEMBER

I

I

I

I

APRIL

I

I -" I

I

I

I

I

SEPTEMBER 1993

I

I

"1~

I

FEBRUARY

0.75-

0.5

.c

g 8 d

03 0.25-

t 0.0 I I OCTOBER

I

SO~ Calculated Observed Correlation

7_\

I

I

I

MARCH SO 4 0.19 0.20 0.82

f

I

I

I

I

AUGUST 1991

I

I

I

I

I

I

JANUARY

I

JUNE 1992

NOVEMBER

APRIL

SEPTEMBER 1993 !~ i""

FEBRUARY

Fig. iI. The calculated SO2 and the comparisons of observed and calculated weekly mean of SO ] Alert, Northwest Territories Canada.

61

°i

51

observed , calcu ated

for

\

~q '\,,

\'\,

f~ :!

.\ ',\ \'\, ",.,

~4

2-

I

0 (8

025 0.5 0 75 0 25 50 75 100 so, ¢orlcentrationin ppbV Contrlbution in % to SO. A s i & ~ M S mm K01aPen i N America ~ Europe Russiai l l Nonlsk

00

(b )

r) 25

05

\

\ 0 75

0

SO, concentrationin ppbV

~.~4:~Asia i

DMS i

KolaPen

~N America

25 50 75 Contribution ,n %to SO EurQpe Russiam Norilsk

Fig. 12. Vertical distribution of SO~ in ppbV, averaged over the area north of 75 N, and the relative contributions from the different sources to the vertical distribution for the summer (left) and winter period (right).

The Danish Eulerian hemispheric model 0.9 ppbV for the lowest 600 m and with a large vertical decrease in the upper levels. These results are similar to the results from the model by Iversen and Tarrasbn for two specific months in 1983 (see Iversen, 1993). The other parts of Fig. 12 shows the contribution from different sources (Norilsk, Kola Peninsula, the other parts of USSR, Europe, North America, Asia and DMS from oceans) to these vertical distributions. Common for the two seasons is the large contribution from Norilsk to the surface levels, because it is a local source in the Arctic, while the contributions from Europe, North America and Asia increase in the vertical directions. The big difference between the two seasons is the relative contribution from the rest of the former part of USSR is a factor of two lower in the summer season compared to the winter season. Overall, one could say that the contribution from the former USSR to the concentration of SO= in the Arctic Boundary layer is about 80% in the winter season and about 60% in the summer season. The total deposition of sulphur, averaged over the area north of 75°N for the whole period is about

4187

6 mg S m - 2 m o n t h - 1. The contributions from the different sources to the total deposition are shown in Fig. 13. The figure shows that the rest of the former USSR and Europe contributes both by about 28%, while Norilsk and Kola Peninsula contributes by 17%. It is quite interesting for Kola Peninsula that although the contribution to surface concentration is as low as 3 - 5 % , the contribution to the total deposition is 17%. This is the opposite for Norilsk. The reason for these low concentrations is the higher precipitation rate close to Kola Peninsula compared to the Norilsk area, which results in a mean half-life for the whole period of SOx from the Kola Peninsula on only 2 d compared to the half-life of SOx from Norilsk on 11 d. The time evolution in the monthly mean concentration of SOx in the Arctic boundary layer, averaged over the area north to 75 °, and the source contributions from different source areas are given in Fig. 14. There is a large seasonal variation in the concentrations ranging from 0.1 ppbV during the summer period and up to 1-2 ppbV during the winter period. The

Contribution from DMS I

0.1 mg S/m=/month I 1.7%

l

Contribution fr

I

0.2 mg S/m=J 2.7%

Contdbution from North America

I

0.3 mg S/m=/month 5.5%

Contribution from Kola 1.0 mg S/m=/monm 17.0%

I

The total deposition is 6 mg S/m2/month Fig. 13. The contribution from the different sources to the total deposition, averaged over the area North of 75°N from October 1990 to May 1994.

4188

J.H. CHRISTENSEN

1.5

0.5

00 OCTOBER

I

I

I

MARCH

I

AUGUST

JANUARY

JUNE

1991

NOVEMBER

I

I

APRIL

SEPTEMBER

1992

I

FEBRUARY

1993

10 ~

m

7

.c ~5 c

82

OCTOBER

MARCH

AUGUST

JANUARY

JUNE

1991 il

DMS ~

Asia ~

N Americai

NOVEMBER

APRIL

1992 Kola Pen.

SEPTEMBER FEBRUARY

1993

Europe E-:] Russi:a I l l Norilsk

Fig. 14. The calculated concentrations of SO,. for the arctic boundary layer (upper), averaged over the area North of 75°N, and the contributions from the different sources to the concentrations (lower).

time variations of the contribution from the different sources show that Norilsk seems to have a small seasonal variation, with a somewhat smaller contribution during the winter period. The sources from the rest of the former USSR have a large seasonal variation from about 15% during the summer period to more than 50% during the winter period, indicating the importance of the sources in USSR to the high concentrations in the winter period. This shows that in the winter the Polar Front has moved south and many sources from USSR are north of the front and the wind has the right direction for injections of Sulphur into the Arctic. The time variation in the contribution from the European sources show a seasonal variation from 15% in winter up to 40% in summer. The contributions from the other sources have a similar variation from totally 2% in the winter to 25% in the summer. Figure 15 is similar to Fig. 14 but for the total depositions. The seasonal variation in the total depositions is smaller than for the concentrations, indicating that during the summer period, the atmospheric transport to the Arctic occurs at higher altitudes and that the deposition rates are larger (see also Table 1). For most of the sources the seasonal variations in the contribution to the deposition is correlated with the

similar variations in the concentrations, except for thc sources on the Kola Peninsula, because these concentrations depend very much on the wet deposition, and therefore this anti-correlation.

5. C O N C L U D I N G

REMARKS AND PLANS

FOR THE F[ TURE

A Eulerian long-range model, covering most of the Northern Hemisphere, was presented. A model run for a 3½ yr period from October 199(I to May 1994 has been performed. The model calculations of sulphur species have been compared to measurements in Europe (EMEP stations), Canadian background stations and to three monitoring stations in the Arctic. The model reproduced very well the measured concentrations both in Europe, Canada and in the Arctic. The model is able to describe the large seasonal variation in the concentrations of Sulphur in the Arctic boundary layer. The main reason for this variation in the Arctic is: the variation in the global scale flow, where in the winter and early spring there is a persistent anticyclone over Northern Asia (e.g. Blanchet, 1989), which forces some of the air pollution

The Danish Eulerian hemispheric model

4189

o 10.0

o~ 7.52

E .=_

g

:~

5.0

~ 2.5 I-0.0

i i OCTOBER

!

I

I

I

I

MARCH

I

I

I I I AUGUST

I

I I I I JANUARY

I

I

I I JUNE

1991

I

I

! I I I NOVEMBER

I

I

I I APRIL

1992

I

I

I I I I SEPTEMBER

I

I I I I FEBRUARY

I

1993

100

~. o

75

50

._c

.~z5 ,5

C~

0 OCTOBER

MARCH

AUGUST

JANUARY

JUNE

1991

I"'

DMS

1

Asia ~

N. A m e r i c a

NOVEMBER

APRIL

1992 I

Kola Pen. i

Europe

~

Russia BIB N o r i l s k

SEPTEMBER

FEBRUARY

1993

I

Fig. 15. The calculated total depositions of SOx (upper), averaged over the area North of 75°N, and the contributions from the different sources to the depositions (lower).

in Europe and Russia to Arctic, and that the cold Arctic air mass covers these source areas, and finally that the removal rate of sulphur due to deposition is very low in the dry and ice covered Arctic. During the summer period there is a small transport of S O ~ - to the Arctic, but this is at the higher altitudes. Plans for the future are improvement of the parameterization of the physical processes. It is planned to extend the model for other species, which are especially important for the Arctic: Persistence Organic Pollutants, Heavy Metals, and to improve the chemistry, both the gas phase and the aqueous phase.

Acknowledgements--The model development is a contribution to the Danish part of the International Arctic Monitoring and Assessment Programme, AMAP. The computing expenses were funded by the Danish Science Research Council. The ECMWF is acknowledged for the meteorological data: "ECMWF 1994. The Description of the ECMWF/ WCRP Level III-A Global Atmospheric Data Archive". Len Barrie and Bill Sukloff at Atmospheric Environment Service in Canada have provided the measurements at Alert and the Canadian background stations. Jan Schaug and Anne Hjelbrekke at NILU, Norway, provided the EMEP measurements, especially from Spitzbergen. The staff at NERI and especially the field staff at Station Nord are acknowledged for the measurements from Station Nord.

REFERENCES

AGASP (1984) Special issue, ed. R. C. Schnell. Geophysics Research Letters 11, 359-472. AGASP II (1989) Special issue on the America Arctic gas and aerosol sampling program. Journal of Atmospheric Chemistry 9. Arctic Air Chemistry (1985) Special issue, ed. K. A. Rahn. Atmospheric Environment 19, 1987-2208. Arctic Air Chemistry (1989) Special issue, ed. K. A. Rahn. Atmospheric Environment 23, 2345-2638. Arctic Air Chemistry (1993) Proceedings of the 5th International Symposium on Arctic Air Chemistry, Copenhagen, Denmark, 8-10 September 1992, ed. N. Z. Heidam. NERI Technical Report NO. 70, National Environmental Research Institute, P. O. Box 358, Frederiksborgvej 399, DK-4000 Roskilde, Denmark. Barrie, L. A., Marvin, M. P. and Oikawa, K. K. (1989) The flux of anthropogenic sulphur into the arctic from midlatitudes. Atmospheric Environment 23, 2505-2512. Benkowitz, C. M., Scholtz, T., Pacyna, J., Tarras6n, L., Dignon, J., Voldner, E., Spiro, P. A. and Graedel, T. E. (1996) Global gridded inventories of anthropogenic emissions of sulphur and nitrogen. Journal of geophysical Research 101, 29239-29253. Berkowicz, R. and Olsen, H. R. (1990) Modelling the internal boundary layer at a coastal site. In Preprint from the Ninth Symposium on Turbulence and Diffusion, April 30 - May 3, 1990, Rise, Denmark. Blanchet, J.-P. (1989) Toward estimation of climatic effects due to arctic aerosols. Atmospheric Environment 23, 2609-2625.

4190

J.H. CHRISTENSEN

Chock, D. P. and Winkler, S. L. (1994) A comparison of advection algorithms coupled with chemistry. Atmospheric Environment 28, 2659-2675. Christensen, J. (1993) Testing advection schemes in a three dimensional air pollution model. Mathematical Computation Modelling 18, 75-88. Christensen, J. (1994) A three dimensional hemispheric air pollution model used for the arctic. In Air Pollution Modelling and its Applications X, eds S.-E. Gryning and M. M. Mill~m, pp. 119-127. Plenum Press, New York. Christensen, J. (1995) Transport of air pollution in the troposphere to the arctic. Ph.D. thesis, National Environmental Research Institute, DK-4000 Roskilde, Denmark. Christensen, J. (1996) The Danish eulerian hemispheric model. In Air Pollution Modelling and its Applications X I, eds. S.-E. Gryning and F. A. Schiermeier, pp. 249 256 Plenum Press, New York. Dabdub, D. and Seinfeld, J. H. (1994) Numerical advective schemes used in air quality models - sequential and parallel implementation. Atmospheric Environment 28, 3369 3385. Dastoor, A. P. and Pudykiewicz, J. (1996) A numerical global meteorological sulphur transport model and its application to arctic air pollution. Atmospheric Environment 30, 1501 1522. Forester, C. K. (1976) Higher order monotonic convective difference schemes. Journal of Computational Physics 23, 1 22. Grell, G. A., Dudhia, J. and Stauffer, D. R. (1995) A description of the fifth-generation Penn State/NCAR mesoscale model (MM5). NCAR/TN 398 + STR. NCAR Technical Note, Mesoscale and Microscale Meteorology Division. National Center for Atmospheric Research, Boulder, Colorado, 122 pp. Gryning, S. E. and Batchvarova, E. (1990) Analytical model for the growth of the coastal internal boundary layer during onshore flow. Quaterly Journal ~/' Meteorological Society 116, 187 203. Heintzenberg, J. and Larssen, S. (1983) SO 2 and SO 4 in the arctic: intepretation of observations at three Norwegian arctic-subarctic stations. Tellus 35B, 255 265. Hertel, O., Christensen, J. and Hov, 0. (1994) Modelling of the endproducts of the chemical decomposition of DMS in the marine boundary layer. Atmospheric Environment 28, 2431 - 2449. Hertel, O., Christensen, J., Runge, E., Asman, W. A. H., Berkowicz, R., Hovmand, M. and Hov, O. (1995) Development and testing of a new variable scale air pollution modeI-ACDEP. Atmospheric Environment 29, 1267- 1290. lversen, T. (1987) A model for long range transport of sulphur dioxide and particulate sulphate in the atmosphere a technical description. NILU Report: NILU: OR 82/86. Reference: O-8515. ISBN: 82-7242-762-9. Norwegian Institute for Air Research, P.O. Box 64, N-2001 Lillestrom, Norway. Iversen, T. (1989) Numerical modelling of the long range atmospheric transport of sulphur dioxide and particulate sulphate to the arctic. Atmospheric Environment 23, 2571 --2595. Iversen, T. (1993) Meteorology and transport of air masses in artic regions. In The Tropospheric Chemistry of Ozone in the Polar Region, eds. H. Niki and K. H. Becket, pp. 57-75. Springer, Berlin. Jakobsen, H. A., Berge, E., Iversen, T. and Sk~lin, R. (19951 Status of the development of the multilayer eulerian model. Note No 3/95. EMEP Meteorological Synthesizing Centre-West, Norwegian Meteorological Institute, PO Box 43, Blindern, N-0313 Oslo 3, Norway. Li, S.-M. and Barrie, L. A. (1993) Eleven years of methane sulphonic acid observations in the high arctic. In Proceedings of the 5th International Symposium on Arctic Air Chemistry, ed. N. Z. Heidam, Copenhagen, Denmark.

8 10 September 1992. NERI Technical Report NO. 70. National Environmental Research Institute, P.O. Box 358, Frederiksborgvej 399, DK-4000 Roskilde, Denmark. L6vblad, G., Hjellbrekke, A.-G.. Sj~Sberg,K., Skjelmoen, J. E. and Schaug, J. (1995) Data Report 1993. Part 2: Monthly and Seasonal Summaries, EMEP/CCC-Report 8/95. Norwegian Institute For Air Research. PO Box 100, N-2007 Kjeller, Norway. McRae, G. J., Goodin, W. R. and Seinleld, J. H. (1982) Numerical solution of the atmospheric diffusion equation for chemically reacting flows. Journal ~!f Computational Physics 45, l 42. Olson. M. P., Oikawa, K. K., Macafee, A. W. t1978) A trajectory model applied to the long-range transport of air pollutants. Report of Atmospheric Environmental Services, Canada. Pepper, D. W., Kern. C. D. and Long, Jr, P. E. 11979) Modelling the dispersion of atmospheric pollution using cubic spline and chapeau functions. Atmospheric Environment 13, 223-237. Piedelievre, J., Musson-Genon, L. and Bombay, F. (1990) MEDIA an eulerian model of atmospheric dispersion: first validation on the chernobyl release. Monthly Weather Review 29, 1205 1220. Pudykiewicz, J. (1991) Environmental prediction systems: design, implementation aspects and operational experience with application to accidental releases. In Air Pollution Modelling and its Applications VIlI, eds H. van Dop and D. G. Stein, pp. 145 159. Plenum Press, New York. Roederer, J. G. (1991) Understanding the arctic: research policies and responsibilities. In Pollution of the arctic atmosphere (Environmental Management Series), ed. W. 1. Sturgess, pp. 1 12. Elsevier, UK. Sandnes, H. and Styve, H. [1992) Calculated budgets l'or airborne acidifying components in europe, 1985, 1987, 1988, 1989, 1990 and 1991, Report No 1/92. EMEP Meteorological Synthesizing Centre West, Norwegian Meteorological Institute, PO Box 43. B[indern, N-0313 Oslo 3, Norway. Schaug, J., Pedersen, U., Skjelmoen, J. E. and Kvalv~tgnes, 1. (1992) Data Report 1990. Part 2: Monthly and Seasonal Summaries, EMEP/CCC-Report 3/92. Norwegian Institute For Air Research, PO Box 64, N-2001 LiI[estrom. Norway. Schaug, J., Pedersen, U., Skjelmoen, J. E. and Kvalv~_gnes,1. [1993) Data Report [991. Part 2: Monthly and Seasonal Summaries, EMEP/CCC-Report 5/93. Norwegian Institute For Air Research, PO Box 64, N-2001 Lillestrom. Norway. Schaug, J., Pedersen, U., Skjelmoen, J. E. and Arnesen, K. [1994) Data Report 1992. Part 2: Monthly and Seasonal Summaries, EMEP/CCC-Report 5/94. Norwegian Institute For Air Research, PO Box 100, N-2007 Kjeller, Norway. Seinfeld, J. H. (1986) Atmospheric Chemistry and Physics ol Air Pollution. Wiley, New York. Seland, O., Pul, A., Sorteberg, A. and Tuovinen, J.-P. ([995) Implementation of a resistance dry deposition module and a variable local correction factor in the lagrangian EMEP model. Report No 3/95. EMEP Meteorological Synthesizing Centre-West, Norwegian Meteorological Institute, PO Box 43~ Blindern, N-0313 Oslo 3, Norway. Slinn, A. A. and Slinn, W. G. N. (1980) Predictions for particle deposition on natural waters. Atmospheric Environment 14, 1013 1016. Stull, R. B. (1991) Review of non-local mixing in turbulent atmospheres: transilient turbulence theory. BoundaryLayer Meteorology 62, 21-96. Sundqvist, H., Berge, E. and Kristjansson, J. E. (1989) Condensation and cloud parametrization studies with a mesoscale numerical weather prediction model. Monthly Weather Review 117, 1641 -1657.

The Danish Eulerian hemispheric model Tarrasbn, L. and Iversen, T. (1992) The influence of North American anthropogenic sulphur emissions over Western Europe. Tellus, 44B, 114-132. Tarras6n, L., Turner, S. and Fl~isand, I. (1995) Estimation of seasonal dimethyl sulphide fluxes over the North atlantic ocean and their contribution to european pollution levels. Journal of geophysical Research 11~, 11623-11639. Voldner, E. C., Barrie, L. A, and Sirois, A. (1986) A literature review of dry deposition of oxides of sulphur and nitrogen with emphasis on long-range transport modelling in North America. Atmospheric Environment 20, 2101-2123. Voldner, E. C., Olson, M. P., Oikawa, K. K. and Loiselle, M. (1981) Comparison between measured and computed concentrations of sulfur compounds in Eastern North America. Journal of geophysical Research 86, 5339-5346. Whhlin, P. (1993) A receptor model applied to aerosol data from Northeastern Greenland. In Proceedings of the 5th International Symposium on Arctic Air Chemistry, ed. N. Z. Heidam, Copenhagen, Denmark, 8-10 September 1992, NERI Technical Report NO. 70, National Environmental

4191

Research Institute, P.O. Box 358, Frederiksborgvej 399, DK-4(K~ Roskilde, Denmark. Walcek, C. J., Brost, R. A., Chang, J. S. and Wesely, M. L. (1986) SO 2, sulfate and HNO a deposition velocities computed using regional landuse and meteorological data. Atmospheric Environment 20, 949-964. Wesely, M. L. (1989) Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models. Atmospheric Environment 23, 1293-1304. Wilson, M. F. and Henderson-Sellers, A. (1985) A global archive of land cover and soils data for use in general circulations models. Journal of Climate 5, 119-143. Zlatev, Z. (1984) Application of predictor-corrector schemes with several correctors in solving air pollution problems. BIT, 24, 700-715. Zlatev, Z. and Christensen, J. (1989) Studying the sulphur and nitrogen pollution over Europe. In Air Pollution Modelling and its Applications VII, ed. H. van Dop, pp. 351-360. Plenum Press, New York. Zlatev, Z., Christensen, J. and Hov, 0. (1992) A Eulerian air pollution model for Europe with nonlinear chemistry. Journal of Atmospheric Chemistry 15, 1-37.