New Assessment of transboundary pollution by toxic substances: …en.msceast.org/reports/1_2020_datrep.pdf · 2020. 7. 21. · MSC‐E Data Report 1/2020 July 2020 Assessment of transboundary

Data 1 20Report /20

Assessment of transboundary pollutionby toxic substances:Heavy metals and POPs

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SUPPLEMENTARY MATERIALS FOR HEAVY METALS

Part I

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Cover Photo: Michael Gauss

MSC‐E Data Report 1/2020

July 2020

Assessment of transboundary pollution by toxic substances: Heavy metals and POPs

PART I

SUPPLEMENTARY MATERIALS FOR HEAVY METALS

I. Ilyin, O. Rozovskaya, O.Travnikov, I.Strijkina

Meteorological Synthesizing Centre ‐ East

2nd Roshchinsky proezd 8/5, 115419 Moscow, Russia Phone.: +7 926 906 91 78; Fax: +7 495 956 19 44; e‐mail: [email protected]; www.msceast.org

2

3

Contents Introduction 5

1. Pollution of the EMEP domain in 2018 7

1.1. Lead 7

1.2. Cadmium 8

1.4. Mercury 9

2.TRANSBOUNDARY POLLUTION OF THE EMEP COUNTRIES 10

2.1. Lead 10

2.2. Cadmium 12

2.3. Mercury 14

3. SOURCE‐RECEPTOR TABLES 16

Lead 17

Cadmium 21

Mercury 25

4. EVALUATION OF MODELLING RESULTS VS. OBSERVATIONS 29

4.1. Lead 29

4.1.1. Air concentrations 29

4.1.2. Wet deposition 35

4.2. Cadmium 41



4.3. Mercury 53



5. POLLUTION OF MARGINAL SEAS 59

5.1. Lead 59

5.2. Cadmium 60

5.3. Mercury 61

6. ECOSYSTEM‐SPECIFIC DEPOSITION 62

6.1. Lead 63

6.2. Cadmium 65

6.3. Mercury 67

4

5

Introduction

This report is a supplement to the EMEP Status Report 2/2020 and summarizes the main output modeling results for 2018 on lead (Pb), cadmium (Cd) and mercury (Hg), presented in a form of maps, graphs and tables. Besides, the report contains evaluation of the calculated concentrations and deposition against measurements. The modelling results are based on meteorological data related to 2018, and emission data related to 2017 (the numerical data are available in the internet: http://en.msceast.org/index.php/pollution‐assessment/emep‐domain‐menu?id=119). The updated Information based on emissions for 2018 will be available on the internet (www.msceast.org).

In Chapter 1 maps of annual mean air concentrations, total and wet deposition of Pb, Cd and Hg are presented. Spatial resolution of the maps is 0.1°x0.1°.

Chapter 2 is focused on transboundary aspects of atmospheric pollution in the EMEP region. It presents country‐averaged deposition fluxes split in three components: contribution of EMEP anthropogenic emissions, secondary sources (wind re‐suspension and natural emission) within the EMEP region and sources outside the EMEP countries (non‐EMEP sources). Furthermore, for each EMEP country fraction of anthropogenic deposition caused by national and foreign sources is presented. Finally, export of emitted lead, cadmium and mercury to other countries is characterized. Deposition to the EMEP region caused by sources of each EMEP country is presented as a sum of two parts. First part is a mass deposited within national’s territory. The second part means mass of a pollutant emitted by a country and deposited to other EMEP countries.

Source‐receptor tables are presented in Chapter 3. The tables give information about contribution of emission sources of each EMEP country to deposition in other EMEP counties. The columns of the table reveal deposition from a country to other countries. The rows contain deposition to a country from countries‐contributors.

Chapter 4 is focused on the evaluation of modelling results against concentrations and wet deposition observed at the EMEP monitoring stations. The chapter contains tables with statistical indicators for each station, diagrams showing comparison of modelled and observed annual mean air concentrations or annual sums of wet deposition, and time series of modelled and measured monthly mean pollution levels. The possible reasons of the discrepancies between calculated and observed levels are discussed.

Statistical indicators used in the chapter for evaluation of the agreement between modelled (M) and observed (O) parameters include Mean Relative Bais (MRB), Pearson’s correlation coefficient (Rc) and Normalized root mean square error (NRMSE), calculated by formulae (1), (2) and (3), respectively:

( ) %100⋅−

=OOMMNB (1)

( ) ( )

( ) ( )∑∑

∑

−⋅−

−⋅−=

NN

N

OOMM

OOMMRc

1

22

1

1

(2)

6

( )

N

OM

ONRMSE

N

iii∑ −

⋅=

2

1 (3)

Besides, fraction of fitting modelled and observed values within two‐fold or three‐fold difference (F2, F3) was calculated.

Maps of deposition of Pb, Cd and Hg to marginal seas (the Baltic, Black, Caspian, North and Mediterranean) of the EMEP region and maps of ecosystem‐dependent deposition are presented in Chapters 5 and 6, respectively.

1. Poll

1.1. Le

a

c

Fig. 1.1.

ution of t

ead

Concentratio

he EMEP

ons in air (a), t

domain in

total (b) and w

7

n 2018

b

wet (c) deposittion flux of Pbb in 2018

1.2. Ca

a

c

Fig. 1.2.C

admium

Concentrationss in air (a), tottal (b) and we

8

et (c) depositioon flux of Cd inn 2018

1.4. M

a

c

Fig. 1.3.C

ercury

Concentrationss in air (a), neet deposition f

9

b

flux (b) and weet deposition fflux (c) Hg in 22018

10

2.TRANSBOUNDARY POLLUTION OF THE EMEP COUNTRIES

2.1. Lead

Fig. 2.1. Country‐average deposition fluxes of Pb to EMEP countries in 2018

Fig. 2.2. Relative contribution of national sources and transboundary transport to Pb deposition in the EMEP

countries in 2018

00.10.20.30.40.50.60.70.80.91

Pb dep

osition flu

xes, kg/km

2 /y Non‐EMEP sources

Secondary sources in the EMEP region

EMEP anthropogenic sources

00.10.20.30.40.50.60.70.80.91

0%10%20%30%40%50%60%70%80%90%100%

Pb dep

osition

, kg/km

2 /y

Contrib

ution, %

National sources Foreign sources Anthrop. Deposition

11

Fig. 2.3. Contribution of EMEP countries to transboundary transport of Pb. Red circle ‐ fraction of total

anthropogenic deposition to the EMEP countries exported outside the country in 2018

0

20

40

60

80

100

0

100

200

300

400

500

Expo

rt fractio

n, %

Pb national e

missions, t

Deposited to own territoryDeposited to the other EMEP countriesExport fraction

0

20

40

60

80

100

02468

101214161820

Expo

rt fractio

n, %

Pb nationa

l emission

s, t

12

2.2. Cadmium

Fig. 2.4. Country‐average deposition fluxes of Cd to EMEP countries

Fig. 2.5. Relative contribution of national sources and transboundary transport to Cd deposition in the EMEP

countries

0

5

10

15

20

25

30

35

Cd dep

osition

fluxes, g/km




0

5

10

15

20

25

30

0%10%20%30%40%50%60%70%80%90%100%

Cd dep

osition

, g/km

2 /y

Contrib

ution, %


13

Fig. 2.6. Contribution of EMEP countries to transboundary transport of Cd. Red circle ‐ fraction of total

anthropogenic deposition to the EMEP countries exported outside the country.

0102030405060708090100

0

10

20

30

40

50

60

70

80

Expo

rt fractio

n, %

Cd national e

missions, t


0

20

40

60

80

100

0

0.2

0.4

0.6

0.8

1

1.2

Expo

rt fractio

n, %

Cd national e

missions, t

14

2.3. Mercury

Fig. 2.7. Country‐average deposition fluxes of Hg to EMEP countries

Fig. 2.8. Relative contribution of national sources and transboundary transport to Hg deposition in the EMEP

countries

0

5

10

15

20

25

Hg de

position

fluxes, g/km




012345678910

0%10%20%30%40%50%60%70%80%90%100%

Hg de

positio

n, g/km

2 /y

Contrib

ution, %


15

Fig. 2.9. Contribution of EMEP countries to transboundary transport of Hg. Red circle ‐ fraction of total

anthropogenic deposition to the EMEP countries exported outside the country.

0

20

40

60

80

100

0

1

2

3

4

5

6

Expo

rt fractio

n, %

Hg national e

missions, t


0

20

40

60

80

100

0

0.05

0.1

0.15

0.2

0.25

0.3

Expo

rt fractio

n, %

Hg national e

missions, t

16

3. SOURCE‐RECEPTOR TABLES

Table 3.1. Codes of countries, regions and seas

Country/Region/Sea Code Country/Region/Sea Code Albania AL Monaco MC Armenia AM Montenegro ME Austria AT Netherlands NL Azerbaijan AZ Norway NO Belarus BY Poland PL Belgium BE Portugal PT Bosnia and Herzegovina BA Moldova MD Bulgaria BG Romania RO Croatia HR Russian Federation RU Cyprus CY Serbia RS Czech Republic CZ Slovakia SK Denmark DK Slovenia SI Estonia EE Spain ES Finland FI Sweden SE France FR Switzerland CH Georgia GE North Macedonia MK Germany DE Tajikistan TJ Greece GR Turkey TR Hungary HU Turkmenistan TM Iceland IS Ukraine UA Ireland IE United Kingdom GB Italy IT Uzbekistan UZ Kazakhstan KZ Kyrgyzstan KY Latvia LV Lithuania LT Luxembourg LU Malta MT

17

Table 3.2. Matrix of Pb country‐to‐country deposition from anthropogenic sources in 2018, kg

R e c e p t o r s E m i t t e r s

code AL AM AT AZ BA BE BG BY CH CY CZ DE DKAL 1520.7 0.6 10.8 0.3 111.3 2.0 565.1 1.3 5.3 8.7 8.1 34.7 1.3AM 0.7 658.3 0.8 75.0 2.2 0.6 11.0 0.4 0.6 46.8 0.7 6.2 0.4AT 20.0 0.7 4528.4 0.4 342.7 66.4 205.2 17.8 581.1 2.8 562.8 6027.8 29.5AZ 1.0 165.7 1.6 314.1 4.5 1.0 22.6 1.6 1.3 46.4 1.5 13.0 0.8BA 103.3 0.9 155.0 0.4 11084.9 10.8 608.3 11.1 27.6 7.1 125.0 327.9 15.2BE 0.5 0.0 28.8 0.0 4.6 3464.8 3.4 3.0 66.1 0.1 34.5 2607.6 20.6BG 84.0 5.7 81.9 5.1 340.6 10.6 29281.4 29.7 19.8 44.4 57.2 249.1 9.8BY 23.8 4.6 126.9 3.4 287.7 75.5 483.3 2300.0 67.5 13.5 239.9 1348.8 102.1CH 3.3 0.1 128.2 0.1 23.7 66.6 13.2 1.8 3797.0 0.7 35.2 3022.0 4.8CY 0.8 0.3 0.4 0.1 2.0 0.1 7.0 0.1 0.4 1475.8 0.3 2.2 0.1CZ 17.8 0.9 861.4 0.6 380.6 101.2 249.9 36.4 187.8 1.7 4339.5 6206.0 78.5DE 19.3 0.9 1375.4 0.6 220.3 2980.0 170.5 89.6 2115.1 1.5 1776.2 96310.2 502.3DK 2.0 0.1 39.1 0.1 19.8 210.4 21.4 10.8 38.9 0.2 67.8 2352.7 1478.2EE 2.6 0.5 27.8 0.4 35.3 33.3 47.7 75.0 13.3 1.0 47.1 470.7 57.9ES 10.7 0.7 40.6 0.2 89.3 395.5 57.3 5.7 105.7 4.2 34.3 1467.2 40.6FI 6.5 3.0 71.8 1.9 99.2 110.1 140.3 136.1 46.0 4.1 135.3 1545.5 185.3FR 26.9 1.3 306.3 0.5 195.3 3636.4 163.4 21.8 2156.0 5.4 257.6 14721.9 147.3GB 2.2 0.3 66.4 0.2 21.9 868.7 19.1 19.9 98.6 0.5 75.1 2942.0 199.6GE 2.8 166.5 4.6 43.5 15.2 1.5 99.1 1.8 2.7 81.2 2.6 21.0 1.3GR 245.7 3.5 33.1 1.9 181.2 7.0 2489.1 8.7 16.9 64.2 25.7 127.5 3.7HR 67.8 0.7 310.4 0.3 2029.9 11.2 381.8 10.7 37.0 4.7 157.5 415.8 11.9HU 50.1 1.2 525.8 1.0 911.9 18.3 932.8 31.0 65.4 3.7 359.8 851.1 23.8IE 0.3 0.1 10.0 0.0 3.1 75.3 2.6 2.8 15.5 0.1 11.6 378.3 29.4IS 0.9 0.1 8.6 0.1 6.8 42.0 9.3 1.6 9.9 0.3 7.1 205.5 20.2IT 266.6 2.4 653.3 0.9 1985.5 92.4 732.2 18.4 786.2 25.8 228.4 2575.9 20.1KY 1.4 20.2 2.0 13.0 4.8 1.2 24.4 1.4 2.9 20.7 1.8 19.7 0.9KZ 23.9 227.3 52.2 162.7 122.4 35.4 515.7 82.2 45.9 175.7 63.7 554.1 31.9LI 0.0 0.0 2.7 0.0 0.1 0.3 0.1 0.0 18.3 0.0 0.3 25.9 0.0LT 5.0 1.0 65.6 0.6 75.0 58.3 93.0 420.4 31.0 1.3 121.4 883.9 106.1LU 0.1 0.0 4.4 0.0 0.6 50.1 0.4 0.3 11.7 0.0 5.7 388.3 1.0LV 4.5 0.8 49.5 0.5 60.4 60.3 73.3 210.6 23.7 1.3 87.2 820.6 101.5MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0MD 4.4 2.0 10.5 2.4 25.5 2.5 164.8 16.8 4.5 6.4 11.4 63.6 3.8ME 114.9 0.2 12.0 0.1 458.6 1.6 236.9 1.2 4.6 3.2 8.5 33.8 1.4MK 266.8 0.6 8.5 0.3 65.7 1.7 1420.5 1.5 3.5 3.1 6.8 29.2 1.2MT 0.1 0.0 0.1 0.0 0.3 0.0 0.4 0.0 0.1 0.0 0.0 0.3 0.0NL 0.7 0.0 24.8 0.0 8.4 1720.9 5.4 4.5 49.2 0.1 35.2 3406.0 38.7NO 4.2 1.4 79.7 0.8 50.7 347.4 68.3 31.6 78.0 1.2 143.0 3195.3 579.3PL 46.9 3.6 733.9 2.9 719.2 437.1 709.6 624.4 282.5 5.5 2613.2 10677.8 569.3PT 0.9 0.1 3.7 0.0 5.5 37.9 3.8 0.7 8.0 0.3 3.2 161.6 6.2RO 85.0 7.8 310.2 7.8 772.2 29.2 3160.9 73.7 67.8 35.0 202.9 908.2 33.8RS 169.1 2.3 145.9 1.4 1698.2 11.7 4273.2 14.7 26.3 4.4 107.7 377.5 17.3RU 195.1 493.6 630.6 376.4 1391.7 485.5 4509.2 1897.8 414.8 460.0 821.4 7365.9 680.6SE 11.8 3.7 184.1 2.3 139.6 444.9 220.2 163.2 110.3 4.5 370.0 5295.0 1588.3SI 12.7 0.3 423.7 0.1 221.9 5.9 83.5 3.5 24.8 1.4 64.3 282.9 4.7SK 21.2 0.6 345.6 0.6 394.1 22.6 308.3 23.5 56.0 1.6 603.8 915.9 24.9TJ 0.6 9.7 0.9 6.7 2.0 0.5 8.4 0.6 1.1 10.2 0.7 7.9 0.3TM 1.6 34.9 2.2 32.5 5.2 1.1 25.2 1.8 2.0 22.1 2.0 18.2 1.1TR 76.4 652.6 72.5 80.6 215.4 25.7 1903.1 36.8 42.3 3038.1 48.7 363.6 17.8UA 85.2 42.5 329.7 36.6 655.2 82.9 2226.8 611.8 134.8 109.1 410.6 2013.8 124.2UZ 2.1 35.8 3.0 25.9 7.6 1.9 46.6 3.5 3.0 27.8 3.1 29.2 1.6SUM, t 3.6 2.6 12.9 1.2 25.5 16.1 56.8 7.1 11.7 5.8 14.3 182.1 6.9Emiss 2017, 5.9 3.7 15.7 2.1 33.8 25.1 72.7 8.0 14.9 18.5 17.0 235.0 12.1 code AL AM AT AZ BA BE BG BY CH CY CZ DE DK

18

Table 3.2. Matrix of Pb country‐to‐country deposition from anthropogenic sources in 2018, kg (continued)


code EE ES FI FR GB GE GR HR HU IE IS IT KY KZAL 1.5 92.8 0.3 47.6 5.2 0.7 142.5 18.9 11.1 0.2 0.0 1258.6 0.0 9.0AM 1.1 3.3 0.3 3.0 1.2 227.7 2.4 0.4 0.5 0.0 0.0 19.5 0.2 161.5AT 25.2 137.3 6.9 530.4 113.3 1.1 12.3 268.4 271.0 2.7 0.1 5596.6 0.1 26.4AZ 5.7 4.9 1.2 4.6 2.5 138.2 2.8 0.8 1.0 0.1 0.0 32.4 2.9 808.0BA 11.1 126.4 2.4 157.9 31.0 1.2 40.5 556.8 267.3 0.8 0.0 2631.0 0.0 18.5BE 11.0 94.7 3.6 1942.0 575.6 0.0 0.3 2.2 3.4 9.1 0.3 140.9 0.0 1.5BG 44.6 96.9 7.5 81.6 22.7 8.3 232.7 45.0 102.4 0.6 0.1 857.8 0.4 220.1BY 449.7 62.5 81.4 235.2 186.9 5.1 28.6 60.3 126.5 4.8 0.5 1409.1 2.3 524.2CH 4.7 169.5 1.0 1196.5 56.9 0.1 2.2 11.8 4.4 1.6 0.1 5475.5 0.0 2.5CY 0.4 6.3 0.1 3.1 0.3 0.2 6.3 0.4 0.2 0.0 0.0 35.6 0.0 1.5CZ 55.8 72.8 14.9 402.3 167.7 0.9 12.9 133.8 328.0 3.8 0.3 1053.3 0.1 46.9DE 260.1 547.8 71.1 6240.8 2821.9 1.0 12.7 74.4 148.6 61.2 2.4 3129.9 0.2 52.7DK 40.5 57.4 13.6 327.6 684.0 0.1 1.3 4.5 10.0 16.9 0.8 106.5 0.0 4.9EE 2514.1 12.9 336.0 61.9 136.1 0.5 2.5 8.5 15.7 2.8 0.3 125.4 0.4 67.2ES 18.5 40064.6 5.5 3681.3 1117.2 0.8 11.1 34.8 17.1 44.3 0.8 2268.5 0.1 8.2FI 3824.4 86.6 6061.6 266.1 513.8 2.7 7.3 22.1 42.9 13.6 2.8 406.0 2.1 316.1FR 65.0 8197.8 21.2 46207.6 3379.8 1.4 17.0 89.4 33.4 75.5 1.9 10346.1 0.1 20.7GB 81.5 756.9 26.8 2909.2 24818.9 0.3 1.6 8.2 13.5 606.6 5.9 331.9 0.1 10.8GE 2.8 10.1 0.8 8.5 2.8 656.0 7.4 2.4 3.1 0.1 0.0 79.7 0.3 194.2GR 13.3 170.6 2.2 107.3 16.5 4.9 1664.8 33.6 33.7 0.5 0.0 1838.2 0.1 77.7HR 14.3 148.4 3.1 198.9 28.2 1.1 29.7 1649.7 347.0 0.8 0.0 3633.6 0.0 13.8HU 40.6 91.7 11.5 170.7 40.5 1.6 36.0 298.1 2092.8 1.0 0.1 1998.9 0.1 52.3IE 14.5 160.6 4.9 265.8 1401.5 0.1 0.2 1.1 2.2 1331.2 1.2 45.2 0.0 2.8IS 13.5 57.1 4.5 103.4 278.1 0.1 0.8 1.5 2.0 18.6 392.7 72.8 0.0 7.1IT 20.9 1660.4 5.9 3008.9 182.2 3.1 146.4 815.5 206.2 5.0 0.2 95073 0.1 28.6KY 4.1 15.0 1.3 10.2 5.2 10.9 2.6 1.0 0.9 0.1 0.0 61.6 2761 13494.6KZ 329.3 157.4 80.5 175.1 126.7 153.2 36.7 22.5 32.9 3.3 1.4 967.0 2204 241781LI 0.0 0.6 0.0 3.7 0.3 0.0 0.0 0.0 0.0 0.0 0.0 14.1 0.0 0.0LT 270.1 26.2 58.4 106.3 184.9 0.9 5.2 21.7 48.2 4.4 0.3 316.9 0.4 91.7LU 0.8 9.6 0.3 168.9 20.4 0.0 0.0 0.3 0.6 0.4 0.0 20.7 0.0 0.2LV 759.2 19.9 136.4 96.2 179.9 0.9 4.6 15.6 32.4 4.1 0.4 209.3 0.5 96.6MC 0.0 0.1 0.0 1.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.3 0.0 0.0MD 14.5 10.2 2.7 14.7 6.1 2.6 12.3 5.1 10.5 0.2 0.0 156.3 0.3 180.0ME 1.4 43.4 0.3 30.5 3.7 0.3 19.4 26.4 17.7 0.1 0.0 733.6 0.0 4.1MK 2.2 34.0 0.4 23.6 4.1 0.7 152.6 9.3 12.8 0.1 0.0 385.9 0.0 11.5MT 0.0 0.6 0.0 0.6 0.0 0.0 0.2 0.1 0.0 0.0 0.0 6.5 0.0 0.0NL 12.3 79.2 4.6 1121.5 1003.6 0.0 0.5 3.4 4.2 17.6 0.5 130.4 0.0 1.6NO 301.2 184.3 138.4 756.6 2063.0 1.3 3.6 12.0 27.3 54.5 13.6 217.2 0.6 93.6PL 593.4 185.2 156.5 970.3 883.9 3.5 37.0 214.1 555.5 19.6 1.3 2480.2 1.0 336.3PT 2.3 1355.4 0.7 208.9 189.1 0.1 0.9 2.2 1.0 9.8 0.2 133.6 0.0 0.8RO 82.0 144.5 18.1 214.2 65.3 10.0 124.4 149.4 553.2 1.6 0.2 2298.9 0.9 450.1RS 18.1 95.8 3.9 105.3 34.5 2.9 102.5 169.8 407.4 0.9 0.0 1408.6 0.1 50.1RU 14317.6 822.7 3532.1 1582.4 1772.1 541.4 279.2 269.7 443.9 45.0 17.1 7888.9 765.3 207166.0SE 1612.6 185.7 1062.5 811.4 1971.3 3.2 11.5 36.3 91.8 48.2 4.9 624.0 2.0 294.1SI 5.2 54.8 1.5 95.2 13.2 0.5 6.0 481.4 90.4 0.4 0.0 1895.6 0.0 5.5SK 30.2 48.9 9.0 125.8 42.8 0.7 14.0 108.8 557.9 1.0 0.1 925.8 0.1 40.2TJ 1.8 5.5 0.5 3.9 1.9 4.5 1.1 0.4 0.4 0.0 0.0 25.0 86.5 1237.7TM 7.0 8.2 1.8 6.7 3.7 19.8 2.6 0.9 1.2 0.1 0.1 49.1 22.0 2843.9TR 75.6 361.2 14.9 221.5 47.9 199.0 457.0 39.7 52.7 1.3 0.2 2209.4 1.2 925.1UA 394.6 203.7 80.0 387.8 197.6 64.4 146.3 132.3 379.1 4.2 0.7 3116.5 12.6 3803.8UZ 14.1 12.9 3.3 10.7 6.1 21.2 3.8 1.4 1.6 0.1 0.1 81.9 213.0 6481.8SUM,t 26.4 57.0 12.0 75.4 45.4 2.1 3.8 5.9 7.4 2.4 0.5 164.3 6.1 482.1Emiss 2017, t 34.1 100.1 15.6 113.1 94.6 2.8 8.2 8.0 8.6 5.1 2.0 274.8 12.2 696.0 code EE ES FI FR GB GE GR HR HU IE IS IT KY KZ

19



code LI LT LU LV MC MD ME MK MT NL NO PL PTAL 0.0 0.2 0.2 0.2 0.0 4.4 139.2 100.9 1.1 0.6 0.1 96.8 13.0AM 0.0 0.1 0.0 0.1 0.0 0.7 0.2 0.3 0.0 0.2 0.1 14.8 0.8AT 2.2 4.4 11.3 3.8 0.1 6.1 16.4 8.4 0.3 23.5 3.3 3209.5 13.4AZ 0.0 0.2 0.0 0.3 0.0 1.3 0.5 0.6 0.0 0.4 0.2 33.3 1.0BA 0.0 2.5 1.1 2.0 0.1 10.0 271.9 26.6 1.0 3.9 1.3 1422.2 16.8BE 0.1 1.3 78.7 1.5 0.0 0.1 0.3 0.2 0.0 325.8 1.9 427.6 9.6BG 0.0 4.0 0.8 4.0 0.0 130.1 40.6 85.0 0.9 4.0 1.7 717.4 18.7BY 0.1 168.2 5.0 113.3 0.1 114.4 19.2 12.6 0.3 28.2 13.2 8691.9 10.5CH 6.9 0.7 11.9 0.6 0.2 0.2 2.0 0.7 0.1 15.4 0.7 267.6 21.3CY 0.0 0.0 0.0 0.0 0.0 0.3 0.3 0.3 0.1 0.0 0.0 3.8 0.6CZ 0.4 9.4 14.5 9.1 0.0 6.8 16.7 10.1 0.2 36.1 6.2 13153.5 7.5DE 3.6 39.4 367.6 41.9 0.1 7.8 14.8 7.8 0.2 1192.3 28.4 18533.7 56.8DK 0.1 7.9 7.1 9.8 0.0 1.5 1.5 1.0 0.0 105.8 15.1 1346.6 8.0EE 0.0 48.7 1.2 192.5 0.0 5.6 2.6 1.6 0.0 18.7 10.4 1397.7 1.6ES 0.1 2.3 17.3 2.7 0.2 0.7 7.1 2.8 0.8 92.3 3.9 557.9 6579.6FI 0.1 67.3 5.4 152.7 0.0 16.6 6.2 3.7 0.1 51.6 107.2 3848.7 12.6FR 1.3 9.5 292.8 10.4 3.7 3.1 16.7 7.8 1.4 675.0 11.4 2980.0 766.2GB 0.1 10.6 19.1 13.5 0.0 0.9 1.5 0.8 0.1 305.7 27.1 1651.5 168.5GE 0.0 0.3 0.1 0.3 0.0 4.7 1.3 1.8 0.1 0.5 0.2 56.0 1.9GR 0.0 1.1 0.6 1.2 0.0 25.8 43.5 134.3 2.9 2.3 0.6 324.1 26.2HR 0.1 2.6 1.5 2.1 0.1 8.1 73.7 17.3 1.1 4.1 1.1 1576.7 17.5HU 0.1 6.7 2.4 5.7 0.1 30.9 50.0 35.5 0.6 6.8 2.5 3980.7 10.7IE 0.0 1.8 2.6 2.5 0.0 0.1 0.2 0.1 0.0 27.9 3.3 261.3 53.2IS 0.0 0.8 1.1 1.3 0.0 0.4 0.5 0.3 0.0 15.0 11.9 122.6 13.8IT 1.4 4.7 12.2 4.1 2.7 11.0 187.8 52.8 9.5 29.8 2.8 2235.2 211.0KY 0.0 0.3 0.1 0.4 0.0 0.6 0.6 0.8 0.0 0.4 0.5 34.3 2.9KZ 0.1 13.7 2.1 16.6 0.1 31.1 12.5 13.4 0.4 13.6 17.8 1413.3 27.1LI 0.2 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 1.9 0.1LT 0.0 680.1 2.4 170.3 0.0 13.5 4.1 2.6 0.0 24.4 8.3 4714.6 5.5LU 0.0 0.1 87.3 0.1 0.0 0.0 0.0 0.0 0.0 9.8 0.1 53.3 0.9LV 0.0 245.4 2.0 944.2 0.0 11.0 4.0 2.4 0.1 29.0 11.3 2920.4 2.6MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0MD 0.0 2.1 0.2 1.7 0.0 395.1 2.3 2.6 0.1 1.1 0.6 297.2 1.5ME 0.0 0.2 0.1 0.2 0.0 2.3 707.2 17.9 0.6 0.5 0.1 102.4 5.5MK 0.0 0.2 0.1 0.2 0.0 6.1 24.1 433.0 0.4 0.6 0.1 90.1 6.9MT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7 0.0 0.0 0.3 0.1NL 0.1 2.3 20.2 2.4 0.0 0.3 0.5 0.3 0.0 1217.5 3.2 609.2 8.5NO 0.1 18.4 14.2 28.3 0.0 3.2 3.2 2.5 0.0 172.4 1700.3 3048.1 30.9PL 0.5 142.3 26.8 101.1 0.1 58.6 40.3 27.0 0.4 169.5 39.7 113701.0 30.5PT 0.0 0.4 1.6 0.5 0.0 0.0 0.5 0.2 0.0 10.0 0.8 56.2 10270.7RO 0.1 12.5 2.9 10.8 0.1 412.6 58.6 62.3 1.0 11.8 4.9 2982.3 19.9RS 0.0 3.2 1.1 3.0 0.1 36.3 335.5 287.4 0.7 4.6 1.5 1346.2 13.5RU 0.6 350.0 26.2 611.5 0.4 379.5 120.2 113.4 2.7 214.3 330.7 23021.8 135.8SE 0.2 105.1 15.6 161.7 0.0 16.9 9.2 7.1 0.1 227.8 497.6 10441.3 25.2SI 0.0 0.9 0.9 0.7 0.1 2.4 9.9 3.4 0.2 2.4 0.5 556.1 4.5SK 0.1 4.8 2.6 4.2 0.0 13.1 21.7 12.3 0.2 8.8 2.4 6446.5 5.4TJ 0.0 0.1 0.0 0.1 0.0 0.3 0.2 0.3 0.0 0.2 0.2 14.4 1.2TM 0.0 0.3 0.1 0.4 0.0 1.4 0.6 0.8 0.0 0.5 0.4 41.7 1.4TR 0.1 4.8 1.6 5.2 0.1 110.1 26.7 40.3 5.0 8.9 3.7 865.5 68.6UA 0.2 62.5 5.9 55.3 0.1 694.8 54.4 48.8 1.3 35.0 19.0 12931.7 29.3UZ 0.0 0.7 0.1 0.8 0.0 1.6 0.9 1.3 0.0 0.8 0.7 69.3 2.2SUM,t 0.0 2.0 1.1 2.7 0.0 2.6 2.4 1.6 0.0 5.1 2.9 252.7 18.7Emiss 2017, t 0.0 2.5 1.4 3.5 0.0 3.2 3.6 2.2 0.2 8.6 5.3 305.5 40.7

code LI LT LU LV MC MD ME MK MT NL NO PL PT

20



code RO RS RU SE SI SK TJ TM TR UA UZ SUM, tAL 100.4 474.9 58.0 0.4 6.7 41.0 0.1 3.5 515.1 99.7 0.8 5.5AM 6.3 4.1 40.7 0.3 0.4 2.5 1.5 183.8 600.8 22.9 29.8 2.1AT 186.1 767.1 101.6 7.7 949.6 2166.2 0.3 7.0 148.8 111.5 3.2 27.1AZ 11.7 7.8 188.2 0.7 0.8 4.8 18.3 841.3 546.4 60.9 197.6 3.5BA 420.6 3013.5 111.1 3.8 86.1 818.7 0.2 6.0 443.5 200.1 2.4 23.2BE 2.6 6.6 18.1 4.7 3.5 39.6 0.0 0.3 4.4 4.0 0.3 10.0BG 3729.3 1820.2 1226.4 6.2 29.9 361.2 1.9 95.9 5151.1 2235.8 29.5 47.6BY 605.0 618.3 4547.7 61.8 57.8 654.6 14.6 78.4 1140.3 2929.3 66.1 28.2CH 7.6 20.5 10.7 1.2 16.3 35.0 0.0 0.9 43.2 6.0 0.4 14.5CY 3.1 2.1 7.9 0.0 0.3 1.1 0.0 1.1 557.7 9.7 0.2 2.1CZ 237.9 1044.4 210.1 18.2 144.5 3027.0 0.4 10.3 98.2 149.1 5.3 33.0DE 159.3 499.6 442.1 91.0 123.9 1213.1 0.9 10.9 122.0 188.1 7.4 142.1DK 14.8 41.6 56.5 62.7 5.8 75.7 0.2 1.0 9.2 21.0 1.0 7.3EE 45.1 65.3 518.4 79.9 8.3 103.2 1.9 7.5 86.6 139.8 7.7 6.8ES 24.8 61.6 46.5 9.5 32.2 78.0 0.3 3.0 184.0 25.3 1.4 57.3FI 140.9 203.0 2687.6 1003.5 21.7 281.8 11.3 37.7 206.1 332.1 44.1 23.3FR 77.1 150.6 136.4 32.7 100.8 247.8 0.6 6.9 252.5 60.5 3.5 95.9GB 13.0 28.8 119.7 50.8 12.8 116.9 0.4 2.5 28.3 28.5 2.4 36.5GE 47.1 29.5 149.2 0.8 2.3 12.1 1.6 197.1 1533.1 161.6 35.1 3.6GR 353.8 528.8 466.3 1.8 17.7 129.8 0.5 29.0 8750.6 742.4 7.4 18.8HR 282.8 2119.5 79.1 3.4 473.5 1002.8 0.2 4.3 276.2 132.3 2.0 15.6HU 1026.5 3493.6 289.8 8.4 191.5 4965.5 0.7 18.1 249.1 524.3 8.4 23.5IE 2.2 4.4 23.8 7.6 1.6 18.6 0.1 0.6 4.5 4.0 0.5 4.2IS 4.2 9.4 25.9 9.1 1.6 13.1 0.3 1.1 17.0 12.0 1.1 1.5IT 313.1 1223.9 172.0 7.4 871.6 955.9 0.5 11.9 1694.7 239.5 3.2 116.8KY 7.9 7.2 160.7 1.0 1.1 4.8 5876.9 435.9 240.9 35.5 27645.5 50.9KZ 286.7 226.7 16958.9 46.6 22.1 177.6 6841.8 4502.9 3101.5 1924.4 33466.5 317.3LI 0.0 0.1 0.1 0.0 0.1 0.2 0.0 0.0 0.2 0.0 0.0 0.1LT 99.1 170.0 617.5 55.2 22.9 312.9 2.5 13.4 144.4 319.5 10.4 10.4LU 0.3 1.0 1.6 0.3 0.5 6.0 0.0 0.1 0.4 0.6 0.0 0.8LV 77.9 119.7 769.7 84.4 15.5 209.2 2.7 10.6 164.6 294.4 10.7 9.0MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0MD 364.9 68.0 480.9 2.4 4.4 48.0 1.4 45.5 702.8 1322.1 20.8 4.5ME 76.0 442.7 25.0 0.4 6.3 53.9 0.0 1.6 197.7 47.3 0.5 3.4MK 145.6 559.8 80.0 0.4 4.4 41.6 0.1 4.8 418.7 141.1 1.2 4.4MT 0.1 0.2 0.1 0.0 0.1 0.1 0.0 0.0 1.5 0.2 0.0 0.0NL 3.9 11.3 18.4 6.7 4.6 38.7 0.0 0.6 5.7 6.5 0.4 9.6NO 43.3 101.6 389.6 362.4 13.9 190.0 4.4 14.9 60.9 80.6 16.1 14.7PL 691.9 1902.7 1650.8 168.0 224.1 4403.6 5.1 55.3 340.9 1332.9 36.8 149.0PT 1.5 4.6 5.2 1.5 2.1 6.1 0.0 0.3 16.9 1.6 0.1 12.5RO 12438.1 3734.7 1656.0 18.0 111.1 1584.8 4.8 141.6 3478.0 3512.5 65.3 40.1RS 1657.2 16173.9 276.7 5.0 56.2 935.6 0.4 21.9 707.4 583.9 6.4 31.7RU 3564.5 2681.5 219349.0 1260.2 264.2 2329.4 3097.9 6467.8 17193.7 22938.7 12955.7 576.6SE 170.9 345.0 1507.6 3838.5 43.0 643.1 12.1 57.7 214.3 360.5 50.2 34.0SI 66.7 353.3 20.5 1.5 1508.8 328.3 0.1 1.6 70.6 34.9 0.6 6.7SK 342.1 1186.6 198.4 8.2 92.9 7677.9 0.4 12.5 75.0 274.8 7.1 21.0TJ 3.0 3.0 70.0 0.4 0.5 2.0 16469.9 397.9 101.7 16.4 5928.7 24.4TM 11.7 9.1 273.7 1.2 1.0 6.2 973.7 2622.1 309.2 67.2 3594.1 11.0TR 1061.5 539.8 2831.8 11.9 31.7 223.4 7.0 465.3 121699.0 3491.4 101.1 142.8UA 2902.8 1581.6 12518.2 71.7 121.0 1903.9 69.6 751.7 9270.2 39029.7 441.9 98.4UZ 17.2 12.7 421.5 2.1 1.5 8.2 4543.4 1120.6 388.9 88.9 23644.2 37.4SUM,t 31.9 46.5 272.0 7.4 5.7 37.5 38.0 18.7 181.6 84.3 108.5Emiss 2016, t 38.7 54.8 336.7 10.8 7.2 43.7 63.7 39.0 353.0 102.4 184.8

code RO RS RU SE SI SK TJ TM TR UA UZ

21

Table 3.3. Matrix of Cd country‐to‐country deposition from anthropogenic sources in 2018, kg


code AL AM AT AZ BA BE BG BY CH CY CZ DE DKAL 42.5 0.0 0.8 0.0 4.1 0.1 11.4 0.1 0.4 0.0 0.5 1.8 0.0AM 0.0 38.6 0.1 2.9 0.1 0.0 0.2 0.0 0.0 0.1 0.0 0.3 0.0AT 0.7 0.0 359.5 0.0 15.5 3.3 4.3 1.4 45.9 0.0 48.1 335.7 1.2AZ 0.0 10.8 0.1 16.4 0.2 0.0 0.5 0.1 0.1 0.1 0.1 0.7 0.0BA 4.2 0.0 14.5 0.0 516.1 0.5 11.6 0.8 2.1 0.0 7.7 18.0 0.6BE 0.0 0.0 2.0 0.0 0.2 223.6 0.1 0.2 5.0 0.0 2.2 156.3 1.1BG 2.3 0.2 6.4 0.2 14.2 0.5 678.1 2.2 1.5 0.1 3.5 13.2 0.4BY 0.8 0.3 9.3 0.2 13.0 3.7 10.6 224.6 5.1 0.0 14.3 73.6 5.4CH 0.1 0.0 9.7 0.0 1.0 3.1 0.3 0.1 319.8 0.0 2.5 176.4 0.2CY 0.0 0.0 0.0 0.0 0.1 0.0 0.2 0.0 0.0 2.5 0.0 0.1 0.0CZ 0.6 0.0 80.6 0.0 16.6 5.5 5.3 2.9 15.0 0.0 353.7 371.5 3.3DE 0.6 0.0 101.5 0.0 8.7 180.9 3.3 7.0 168.4 0.0 128.9 5421.8 29.5DK 0.1 0.0 2.5 0.0 0.8 10.9 0.4 0.9 2.8 0.0 4.2 132.8 127.8EE 0.1 0.0 2.0 0.0 1.5 1.5 1.0 6.4 0.9 0.0 2.9 25.0 2.8ES 0.3 0.0 2.7 0.0 3.6 16.7 1.2 0.4 7.3 0.0 2.0 74.8 1.6FI 0.2 0.2 5.1 0.1 4.1 5.1 3.0 10.4 3.2 0.0 7.8 79.8 8.7FR 0.8 0.1 19.5 0.0 7.7 178.0 3.4 1.6 163.6 0.0 16.6 834.8 6.6GB 0.1 0.0 4.7 0.0 0.9 41.6 0.4 1.5 7.5 0.0 4.9 170.0 12.4GE 0.1 12.0 0.3 2.0 0.6 0.1 2.3 0.1 0.2 0.2 0.2 1.1 0.1GR 7.2 0.2 2.5 0.1 7.2 0.3 62.5 0.7 1.3 0.2 1.5 6.8 0.1HR 2.7 0.0 29.7 0.0 106.5 0.6 7.7 0.8 2.8 0.0 10.6 23.6 0.5HU 1.7 0.1 55.2 0.0 44.1 0.9 19.4 2.2 4.9 0.0 22.7 46.9 0.9IE 0.0 0.0 0.7 0.0 0.1 3.9 0.1 0.2 1.2 0.0 0.7 21.5 1.8IS 0.0 0.0 0.6 0.0 0.3 2.0 0.2 0.1 0.7 0.0 0.5 11.3 1.2IT 9.0 0.1 48.2 0.0 78.8 4.1 14.7 1.3 60.0 0.1 13.5 130.5 0.8KY 0.0 1.1 0.1 0.6 0.2 0.1 0.5 0.1 0.2 0.1 0.1 0.9 0.0KZ 0.7 13.4 3.5 7.9 4.6 1.7 10.8 6.4 3.4 0.6 3.4 28.8 1.4LI 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 1.5 0.0 0.0 1.5 0.0LT 0.2 0.1 5.1 0.0 3.5 2.7 2.0 39.1 2.4 0.0 7.5 48.6 5.7LU 0.0 0.0 0.3 0.0 0.0 4.2 0.0 0.0 0.9 0.0 0.4 22.5 0.1LV 0.2 0.1 3.8 0.0 2.7 2.8 1.6 18.5 1.8 0.0 5.5 44.9 5.1MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0MD 0.2 0.1 0.8 0.1 1.1 0.1 4.6 1.3 0.4 0.0 0.7 3.5 0.2ME 5.9 0.0 0.9 0.0 19.0 0.1 4.7 0.1 0.3 0.0 0.5 1.8 0.1MK 6.5 0.0 0.7 0.0 2.5 0.1 27.3 0.1 0.3 0.0 0.4 1.6 0.0MT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0NL 0.0 0.0 1.7 0.0 0.3 117.0 0.1 0.4 3.8 0.0 2.2 202.8 2.3NO 0.1 0.1 5.5 0.0 2.1 16.8 1.3 2.5 5.5 0.0 9.1 173.2 37.6PL 1.5 0.2 57.6 0.1 32.2 22.1 14.6 55.4 21.1 0.0 165.7 607.8 28.5PT 0.0 0.0 0.2 0.0 0.2 1.7 0.1 0.1 0.6 0.0 0.2 8.3 0.3RO 2.8 0.3 25.8 0.4 36.1 1.5 84.8 6.0 5.3 0.1 13.6 50.1 1.4RS 7.2 0.1 12.9 0.1 77.9 0.5 81.0 1.1 2.0 0.0 7.0 20.6 0.6RU 6.2 29.7 44.0 19.0 56.9 22.8 100.4 160.4 30.6 1.4 46.4 388.1 32.0SE 0.4 0.2 13.5 0.1 6.1 21.7 4.5 12.6 8.1 0.0 23.4 290.0 93.4SI 0.5 0.0 34.6 0.0 10.4 0.3 1.7 0.3 1.9 0.0 4.5 15.7 0.2SK 0.8 0.0 32.7 0.0 19.2 1.1 6.9 1.9 4.4 0.0 39.2 50.6 1.0TJ 0.0 0.5 0.0 0.3 0.1 0.0 0.2 0.0 0.1 0.0 0.0 0.4 0.0TM 0.0 2.1 0.1 1.6 0.2 0.1 0.6 0.1 0.1 0.1 0.1 1.0 0.0TR 2.1 30.5 5.1 2.9 8.7 1.2 52.6 2.8 3.1 8.6 2.9 18.6 0.8UA 2.9 2.7 24.6 1.8 29.0 4.1 53.7 52.5 9.9 0.3 24.8 107.9 6.2UZ 0.1 2.2 0.2 1.2 0.3 0.1 1.0 0.3 0.2 0.1 0.2 1.5 0.1SUM 112.5 146.4 1032.4 58.4 1159.3 909.6 1296.9 628.0 927.8 15.0 1007.4 10219.0 424.1Emiss 2017 193.7 208.9 1219.8 100.3 1481.3 1344.2 1661.4 696.8 1161.2 53.2 1167.4 13087.8 775.2 code AL AM AT AZ BA BE BG BY CH CY CZ DE DK

22

Table 3.3. Matrix of Cd country‐to‐country deposition from anthropogenic sources in 2018, kg (continued)


code EE ES FI FR GB GE GR HR HU IE IS IT KY KZAL 0.0 4.2 0.0 1.6 0.2 0.1 20.5 1.3 1.7 0.0 0.0 44.1 0.0 0.1AM 0.0 0.1 0.0 0.1 0.0 9.0 0.4 0.0 0.1 0.0 0.0 0.6 0.0 2.4AT 0.5 6.0 0.3 14.6 4.0 0.1 2.0 27.1 47.5 0.2 0.0 72.3 0.0 0.4AZ 0.1 0.2 0.1 0.1 0.1 8.6 0.4 0.1 0.1 0.0 0.0 1.0 0.1 12.1BA 0.2 6.0 0.1 5.6 1.0 0.1 6.4 60.8 42.9 0.0 0.0 69.0 0.0 0.3BE 0.2 3.8 0.2 60.0 26.2 0.0 0.1 0.2 0.4 0.6 0.0 2.8 0.0 0.0BG 0.7 4.3 0.3 2.6 0.8 0.8 41.7 4.9 15.3 0.0 0.0 30.1 0.0 3.2BY 10.1 2.6 4.3 6.4 7.1 0.5 4.9 7.2 20.9 0.3 0.0 28.8 0.1 7.6CH 0.1 7.3 0.0 28.8 2.1 0.0 0.4 1.0 0.7 0.1 0.0 85.0 0.0 0.0CY 0.0 0.3 0.0 0.1 0.0 0.0 1.1 0.0 0.0 0.0 0.0 2.1 0.0 0.0CZ 1.2 3.2 0.7 11.0 6.3 0.1 2.1 15.0 53.5 0.2 0.0 20.8 0.0 0.7DE 5.4 22.2 3.4 178.7 122.3 0.1 2.0 7.0 21.1 3.8 0.1 58.1 0.0 0.7DK 0.9 2.2 0.7 9.1 28.2 0.0 0.2 0.4 1.4 1.1 0.0 1.9 0.0 0.1EE 130.5 0.5 16.9 1.6 4.8 0.1 0.4 0.9 2.5 0.2 0.0 2.8 0.0 1.0ES 0.3 1605.9 0.2 86.2 40.9 0.1 1.7 3.2 2.5 2.7 0.0 39.8 0.0 0.1FI 90.7 3.2 431.0 6.6 17.7 0.3 1.1 2.2 6.5 0.8 0.1 7.5 0.1 4.4FR 1.3 340.2 1.0 1231.9 142.7 0.1 2.5 7.6 4.8 4.7 0.0 232.3 0.0 0.3GB 1.7 27.4 1.4 77.7 1177.6 0.0 0.2 0.8 2.0 41.1 0.1 6.6 0.0 0.1GE 0.0 0.4 0.0 0.2 0.1 67.9 1.2 0.2 0.4 0.0 0.0 2.4 0.0 2.9GR 0.2 8.0 0.1 3.5 0.6 0.5 288.0 2.7 5.0 0.0 0.0 96.4 0.0 1.1HR 0.3 7.0 0.1 7.2 1.0 0.1 4.6 201.9 63.7 0.0 0.0 90.4 0.0 0.2HU 0.7 4.1 0.5 5.4 1.5 0.1 5.7 42.6 397.0 0.1 0.0 47.7 0.0 0.7IE 0.3 5.9 0.2 6.4 72.2 0.0 0.0 0.1 0.3 71.7 0.0 1.0 0.0 0.0IS 0.3 2.1 0.2 2.7 11.2 0.0 0.1 0.2 0.3 1.1 9.4 1.6 0.0 0.1IT 0.4 79.8 0.3 103.5 5.9 0.3 22.3 66.6 30.3 0.3 0.0 2028.1 0.0 0.4KY 0.1 0.6 0.1 0.3 0.2 0.8 0.4 0.1 0.1 0.0 0.0 1.5 92.9 222.6KZ 5.5 6.3 3.9 4.9 4.3 12.0 5.6 2.0 4.6 0.2 0.0 22.9 83.0 4041.0LI 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.0 0.0LT 6.8 1.0 2.9 2.8 6.8 0.1 0.9 2.7 7.9 0.3 0.0 6.3 0.0 1.3LU 0.0 0.4 0.0 5.2 0.9 0.0 0.0 0.0 0.1 0.0 0.0 0.4 0.0 0.0LV 24.0 0.8 6.8 2.6 6.6 0.1 0.8 1.9 5.3 0.2 0.0 4.7 0.0 1.4MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0MD 0.3 0.4 0.1 0.5 0.2 0.2 2.3 0.5 1.7 0.0 0.0 4.2 0.0 2.6ME 0.0 2.0 0.0 1.0 0.1 0.0 2.9 1.8 2.7 0.0 0.0 24.5 0.0 0.1MK 0.0 1.5 0.0 0.8 0.1 0.1 25.0 0.7 2.0 0.0 0.0 13.5 0.0 0.2MT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7 0.0 0.0NL 0.3 3.1 0.2 34.6 46.3 0.0 0.1 0.3 0.6 1.1 0.0 2.4 0.0 0.0NO 6.1 7.1 7.7 19.8 76.6 0.1 0.5 1.2 4.0 3.3 0.3 4.4 0.0 1.3PL 12.4 7.5 7.4 25.4 35.2 0.3 6.0 25.3 91.6 1.2 0.0 48.2 0.0 5.0PT 0.0 59.4 0.0 4.9 7.2 0.0 0.1 0.2 0.1 0.6 0.0 2.5 0.0 0.0RO 1.5 6.6 0.8 7.2 2.4 0.9 22.4 18.9 102.5 0.1 0.0 61.4 0.0 6.6RS 0.3 4.4 0.2 3.5 1.2 0.2 16.8 21.2 67.5 0.0 0.0 40.0 0.0 0.7RU 284.2 32.9 199.7 42.9 61.9 52.6 45.8 27.5 68.5 2.6 0.4 182.4 31.6 3150.8SE 35.1 7.1 60.6 21.5 74.4 0.3 1.6 4.0 14.0 3.0 0.1 11.5 0.1 3.9SI 0.1 2.5 0.1 3.2 0.4 0.0 0.9 52.7 15.5 0.0 0.0 37.8 0.0 0.1SK 0.6 2.2 0.4 3.6 1.6 0.1 2.3 14.0 108.6 0.1 0.0 21.3 0.0 0.6TJ 0.0 0.2 0.0 0.1 0.1 0.3 0.2 0.0 0.0 0.0 0.0 0.6 3.8 17.8TM 0.1 0.3 0.1 0.2 0.1 1.5 0.4 0.1 0.2 0.0 0.0 1.4 1.2 44.5TR 1.3 16.4 0.7 6.8 1.6 14.7 80.3 3.8 8.0 0.1 0.0 111.1 0.1 13.5UA 7.7 8.7 3.8 11.2 7.3 7.4 26.4 14.8 66.9 0.2 0.0 78.0 0.6 55.7UZ 0.2 0.5 0.2 0.3 0.2 1.6 0.6 0.1 0.2 0.0 0.0 2.1 10.7 101.2SUM 632.9 2319.4 758.1 2054.9 2010.5 181.9 652.2 648.0 1293.5 142.0 10.8 3657.5 224.6 7709.9Emiss 2017 803.6 4221.0 955.9 3168.1 4048.9 245.1 1397.9 830.2 1460.2 300.9 46.7 7460.8 492.8 11056.4 code EE ES FI FR GB GE GR HR HU IE IS IT KY KZ

23



code LI LT LU LV MC MD ME MK MT NL NO PL PTAL 0.0 0.0 0.0 0.0 0.0 0.2 1.3 6.3 0.0 0.0 0.0 4.0 1.4AM 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.1AT 0.3 0.6 0.5 0.6 0.0 0.4 0.4 0.5 0.0 2.0 0.2 118.3 1.3AZ 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 1.3 0.1BA 0.0 0.3 0.0 0.3 0.0 0.6 8.1 1.5 0.0 0.3 0.1 58.4 1.7BE 0.0 0.2 4.6 0.2 0.0 0.0 0.0 0.0 0.0 33.7 0.2 14.2 0.9BG 0.0 0.5 0.0 0.6 0.0 8.2 1.1 4.8 0.0 0.3 0.1 28.0 1.9BY 0.0 26.7 0.2 23.3 0.0 7.6 0.6 0.7 0.0 2.4 1.1 397.7 1.0CH 1.1 0.1 0.5 0.1 0.0 0.0 0.0 0.0 0.0 1.3 0.1 8.2 2.0CY 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1CZ 0.1 1.3 0.7 1.4 0.0 0.4 0.5 0.6 0.0 3.2 0.5 457.6 0.8DE 0.6 5.5 20.1 6.3 0.0 0.5 0.4 0.4 0.0 125.2 2.4 561.3 5.2DK 0.0 1.2 0.4 1.5 0.0 0.1 0.0 0.1 0.0 9.0 1.4 46.8 0.8EE 0.0 7.6 0.1 37.7 0.0 0.4 0.1 0.1 0.0 1.4 0.9 56.7 0.1ES 0.0 0.3 0.8 0.4 0.0 0.0 0.1 0.2 0.0 7.2 0.3 19.2 680.4FI 0.0 9.3 0.2 23.3 0.0 1.0 0.2 0.2 0.0 4.0 7.7 152.8 1.1FR 0.2 1.2 14.2 1.5 0.1 0.2 0.3 0.4 0.0 58.8 0.9 94.8 71.5GB 0.0 1.5 1.0 2.1 0.0 0.0 0.0 0.0 0.0 25.7 2.4 59.1 17.1GE 0.0 0.0 0.0 0.0 0.0 0.3 0.0 0.1 0.0 0.0 0.0 2.2 0.2GR 0.0 0.1 0.0 0.2 0.0 1.6 0.7 8.6 0.0 0.2 0.0 12.7 2.8HR 0.0 0.3 0.1 0.3 0.0 0.5 1.5 1.0 0.0 0.4 0.1 65.2 1.8HU 0.0 0.8 0.1 0.8 0.0 2.0 1.7 1.9 0.0 0.6 0.2 161.3 1.1IE 0.0 0.3 0.1 0.4 0.0 0.0 0.0 0.0 0.0 2.3 0.3 9.1 4.8IS 0.0 0.1 0.1 0.2 0.0 0.0 0.0 0.0 0.0 1.2 0.9 4.5 1.1IT 0.2 0.5 0.5 0.5 0.1 0.6 3.3 3.0 0.1 2.3 0.2 80.9 22.5KY 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.3KZ 0.0 1.7 0.1 2.4 0.0 1.9 0.3 0.7 0.0 1.1 1.2 54.0 2.5LI 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0LT 0.0 125.6 0.1 34.6 0.0 0.9 0.1 0.1 0.0 2.0 0.7 211.4 0.5LU 0.0 0.0 4.9 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.0 1.5 0.1LV 0.0 44.4 0.1 201.7 0.0 0.7 0.1 0.1 0.0 2.3 1.0 125.8 0.2MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0MD 0.0 0.3 0.0 0.3 0.0 34.2 0.1 0.2 0.0 0.1 0.0 13.3 0.2ME 0.0 0.0 0.0 0.0 0.0 0.1 10.5 1.0 0.0 0.0 0.0 4.1 0.6MK 0.0 0.0 0.0 0.0 0.0 0.3 0.3 26.6 0.0 0.0 0.0 3.7 0.7MT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0NL 0.0 0.3 1.2 0.4 0.0 0.0 0.0 0.0 0.0 122.6 0.3 21.3 0.8NO 0.0 2.6 0.7 4.4 0.0 0.2 0.1 0.1 0.0 13.6 153.4 98.9 3.0PL 0.1 20.7 1.3 16.0 0.0 3.8 1.3 1.5 0.0 14.7 3.2 5054.0 2.7PT 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.8 0.1 2.0 1238.9RO 0.0 1.6 0.1 1.6 0.0 31.4 2.1 3.6 0.0 1.0 0.4 125.0 2.0RS 0.0 0.4 0.1 0.4 0.0 2.1 9.8 14.1 0.0 0.4 0.1 55.4 1.4RU 0.1 48.4 1.2 102.6 0.0 23.7 3.4 6.4 0.0 16.8 23.7 943.1 12.7SE 0.0 15.8 0.7 26.2 0.0 1.1 0.3 0.4 0.0 18.2 40.3 410.9 2.3SI 0.0 0.1 0.0 0.1 0.0 0.2 0.2 0.2 0.0 0.2 0.0 22.6 0.5SK 0.0 0.6 0.1 0.6 0.0 0.9 0.7 0.7 0.0 0.7 0.2 276.5 0.5TJ 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.1TM 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 1.7 0.1TR 0.0 0.6 0.1 0.8 0.0 6.9 0.6 2.3 0.0 0.7 0.3 34.1 7.1UA 0.0 8.3 0.3 8.4 0.0 51.8 1.7 2.8 0.0 2.8 1.5 575.2 2.8UZ 0.0 0.1 0.0 0.1 0.0 0.1 0.0 0.1 0.0 0.1 0.1 2.6 0.2SUM 2.9 329.8 55.5 502.3 0.2 185.2 52.2 91.4 0.2 481.1 246.5 10453.6 2102.4Emiss 2017 3.6 395.7 69.9 623.8 0.4 223.6 72.5 126.1 1.0 764.8 430.1 12365.0 4601.6 code LI LT LU LV MC MD ME MK MT NL NO PL PT

24



code RO RS RU SE SI SK TJ TM TR UA UZ SUMAL 4.5 21.3 14.6 0.0 0.5 1.0 0.0 0.0 27.0 3.5 0.0 221.3AM 0.3 0.2 16.6 0.0 0.0 0.1 0.0 0.9 20.6 0.7 0.4 95.8AT 15.7 36.2 25.5 0.4 82.7 53.4 0.0 0.0 8.1 3.0 0.0 1341.0AZ 0.7 0.4 91.1 0.0 0.1 0.1 0.1 4.6 20.3 2.2 3.5 176.8BA 27.0 152.1 26.4 0.2 6.8 20.2 0.0 0.0 23.4 5.9 0.0 1102.3BE 0.2 0.3 4.4 0.2 0.3 0.9 0.0 0.0 0.3 0.1 0.0 545.8BG 171.2 89.3 310.7 0.3 2.5 8.4 0.0 0.5 285.0 83.6 0.5 1824.9BY 56.3 30.0 1165.3 3.2 5.1 17.9 0.1 0.4 64.9 122.0 1.1 2389.4CH 0.5 1.0 2.7 0.1 1.2 0.8 0.0 0.0 2.5 0.2 0.0 661.3CY 0.2 0.1 2.1 0.0 0.0 0.0 0.0 0.0 22.5 0.4 0.0 32.3CZ 18.7 46.8 50.1 0.9 12.4 80.4 0.0 0.1 5.5 4.2 0.1 1655.9DE 11.5 21.1 102.0 4.7 9.5 27.9 0.0 0.1 7.2 5.2 0.1 7392.6DK 1.5 1.9 13.4 3.4 0.4 1.7 0.0 0.0 0.5 0.6 0.0 414.1EE 4.1 3.0 127.3 4.1 0.7 2.7 0.0 0.0 5.0 4.3 0.1 462.8ES 1.6 2.7 11.5 0.4 2.5 1.8 0.0 0.0 9.6 0.7 0.0 2634.1FI 13.0 9.1 598.4 36.7 1.7 7.1 0.1 0.2 11.3 9.9 0.8 1587.9FR 4.5 6.5 33.2 1.5 7.4 5.8 0.0 0.0 13.4 1.8 0.1 3520.3GB 1.0 1.2 25.4 2.7 1.1 2.8 0.0 0.0 1.6 0.8 0.0 1726.6GE 2.9 1.4 98.7 0.0 0.2 0.3 0.0 1.0 68.2 5.2 0.5 276.4GR 18.8 25.5 131.5 0.1 1.4 3.0 0.0 0.1 441.3 28.4 0.1 1173.9HR 22.7 102.5 19.4 0.2 41.8 25.6 0.0 0.0 14.1 3.9 0.0 863.6HU 115.1 169.1 67.6 0.4 19.0 136.3 0.0 0.1 13.8 13.0 0.1 1410.2IE 0.2 0.2 4.8 0.4 0.1 0.4 0.0 0.0 0.3 0.1 0.0 212.4IS 0.3 0.4 6.3 0.4 0.1 0.3 0.0 0.0 0.9 0.5 0.0 63.9IT 19.1 54.7 43.8 0.3 63.5 21.6 0.0 0.1 88.8 7.7 0.1 3113.6KY 0.5 0.3 42.4 0.0 0.1 0.1 28.1 2.9 9.1 1.1 460.9 870.4KZ 18.4 10.4 4863.4 1.8 1.6 4.2 34.3 29.2 139.3 68.1 595.6 10114.7LI 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.8LT 9.0 7.8 164.2 3.1 2.2 8.5 0.0 0.1 9.1 9.9 0.2 746.9LU 0.0 0.0 0.4 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 43.7LV 7.4 5.6 193.3 4.6 1.4 5.7 0.0 0.1 9.7 9.2 0.2 755.7MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1MD 34.2 3.3 126.1 0.1 0.4 1.3 0.0 0.2 42.9 50.4 0.3 333.9ME 4.0 23.0 6.1 0.0 0.5 1.3 0.0 0.0 10.1 1.5 0.0 131.5MK 6.0 25.8 19.4 0.0 0.4 1.0 0.0 0.0 24.3 4.7 0.0 196.9MT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 1.1NL 0.3 0.5 4.3 0.3 0.3 0.9 0.0 0.0 0.4 0.2 0.0 573.8NO 3.8 4.4 88.4 19.7 1.1 4.6 0.0 0.1 3.0 2.3 0.3 790.9PL 69.3 86.7 422.1 8.6 19.9 143.8 0.0 0.3 21.2 32.5 0.6 7196.4PT 0.1 0.2 1.3 0.1 0.2 0.1 0.0 0.0 0.8 0.0 0.0 1331.6RO 1155.6 183.6 428.4 0.8 10.2 42.5 0.0 0.7 218.5 125.7 1.0 2795.6RS 104.3 824.6 68.1 0.2 5.0 23.4 0.0 0.1 38.3 19.5 0.1 1534.5RU 254.5 128.0 65610.5 51.6 20.9 58.6 15.6 37.1 940.8 801.9 234.2 74457.7SE 16.7 15.6 327.7 212.6 3.6 16.5 0.1 0.3 10.6 10.2 0.8 1841.9SI 5.4 17.0 5.5 0.1 133.3 8.1 0.0 0.0 3.8 1.0 0.0 381.8SK 37.4 58.9 47.6 0.4 8.9 270.8 0.0 0.1 4.3 6.1 0.1 1029.3TJ 0.2 0.1 18.3 0.0 0.0 0.0 76.6 2.8 3.6 0.5 103.6 231.3TM 0.7 0.4 88.1 0.0 0.1 0.2 5.0 24.3 12.1 2.5 75.5 267.5TR 63.0 26.4 872.1 0.5 2.5 5.2 0.0 2.3 7213.7 132.1 1.5 8770.8UA 266.3 76.9 3508.3 3.5 10.2 54.3 0.4 3.9 577.6 1446.8 7.8 7220.8UZ 1.0 0.6 123.2 0.1 0.1 0.2 23.0 8.9 15.8 3.1 459.4 764.1SUM 2569.7 2277.0 80021.6 368.7 483.6 1071.8 183.5 121.5 10465.0 3037.4 1950.0Emiss 2017 3000.5 2654.0 95560.6 517.9 596.7 1215.4 313.4 247.9 18807.8 3696.3 3277.1 code RO RS RU SE SI SK TJ TM TR UA UZ SUM

25

Table 3.4. Matrix of Hg country‐to‐country deposition from anthropogenic sources in 2018, kg


code AL AM AT AZ BA BE BG BY CH CY CZ DE DKAL 11.5 0.0 0.2 0.0 2.0 0.0 2.0 0.0 0.1 0.0 0.4 0.7 0.0AM 0.0 15.4 0.0 2.1 0.1 0.0 0.1 0.0 0.0 0.0 0.1 0.2 0.0AT 0.1 0.0 94.0 0.0 6.5 1.0 0.6 0.1 7.5 0.0 36.8 73.4 0.2AZ 0.0 3.1 0.1 21.9 0.1 0.0 0.1 0.0 0.0 0.0 0.1 0.4 0.0BA 0.9 0.0 2.5 0.0 300.5 0.2 1.5 0.1 0.3 0.0 5.6 5.3 0.1BE 0.0 0.0 0.4 0.0 0.1 57.4 0.0 0.0 0.7 0.0 2.5 48.6 0.2BG 0.4 0.1 1.2 0.1 6.5 0.2 104.5 0.2 0.3 0.0 3.0 4.5 0.1BY 0.1 0.1 2.0 0.1 5.2 0.9 1.5 20.0 0.9 0.0 12.2 24.9 0.8CH 0.0 0.0 2.2 0.0 0.5 0.8 0.1 0.0 48.9 0.0 2.4 33.4 0.0CY 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.0 0.1 0.0CZ 0.1 0.0 14.4 0.0 6.1 1.4 0.7 0.2 2.0 0.0 328.1 104.8 0.6DE 0.1 0.0 21.9 0.0 3.8 40.4 0.5 0.5 23.2 0.0 146.5 1373.9 4.6DK 0.0 0.0 0.4 0.0 0.3 1.9 0.1 0.1 0.4 0.0 3.8 34.9 18.8EE 0.0 0.0 0.4 0.0 0.5 0.4 0.1 0.4 0.2 0.0 2.5 7.6 0.5ES 0.1 0.0 0.7 0.0 1.7 3.3 0.3 0.1 1.2 0.0 2.6 20.4 0.3FI 0.1 0.1 1.6 0.1 2.5 1.6 0.7 1.0 0.8 0.0 8.9 29.7 1.7FR 0.2 0.0 4.1 0.0 3.5 38.9 0.6 0.2 24.4 0.0 17.5 211.4 1.0GB 0.0 0.0 0.9 0.0 0.4 7.1 0.1 0.1 1.0 0.0 4.7 45.1 1.6GE 0.0 5.5 0.1 1.5 0.3 0.0 0.4 0.0 0.1 0.1 0.2 0.6 0.0GR 1.1 0.1 0.6 0.0 3.5 0.2 10.9 0.1 0.3 0.0 1.5 2.8 0.0HR 0.5 0.0 5.4 0.0 55.6 0.2 0.9 0.1 0.4 0.0 7.7 6.6 0.1HU 0.3 0.0 9.5 0.0 19.2 0.3 2.5 0.2 0.7 0.0 18.7 13.3 0.2IE 0.0 0.0 0.1 0.0 0.0 0.5 0.0 0.0 0.1 0.0 0.7 4.9 0.2IS 0.0 0.0 0.2 0.0 0.2 0.5 0.0 0.0 0.2 0.0 0.7 4.7 0.2IT 2.0 0.1 10.3 0.0 34.0 1.2 2.5 0.1 9.8 0.0 11.3 30.7 0.2KY 0.0 0.3 0.1 0.3 0.1 0.1 0.1 0.0 0.1 0.0 0.2 0.7 0.0KZ 0.2 3.4 1.4 4.2 3.1 1.0 2.4 0.7 1.0 0.2 4.8 14.4 0.5LI 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.3 0.0 0.0 0.3 0.0LT 0.0 0.0 0.9 0.0 1.1 0.6 0.3 3.1 0.3 0.0 6.3 15.3 0.8LU 0.0 0.0 0.1 0.0 0.0 0.8 0.0 0.0 0.1 0.0 0.4 6.1 0.0LV 0.0 0.0 0.6 0.0 0.8 0.6 0.2 1.2 0.3 0.0 4.6 13.2 0.8MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0MD 0.0 0.0 0.2 0.0 0.4 0.1 0.7 0.1 0.1 0.0 0.6 1.1 0.0ME 1.3 0.0 0.2 0.0 10.1 0.0 0.7 0.0 0.1 0.0 0.5 0.6 0.0MK 1.3 0.0 0.2 0.0 1.3 0.0 5.1 0.0 0.1 0.0 0.4 0.6 0.0MT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0NL 0.0 0.0 0.3 0.0 0.1 23.9 0.0 0.0 0.5 0.0 2.4 54.3 0.3NO 0.0 0.0 1.2 0.0 1.0 3.6 0.2 0.3 0.9 0.0 9.7 54.9 5.7PL 0.3 0.1 9.2 0.1 10.3 4.5 2.1 4.6 2.7 0.0 140.5 218.5 4.4PT 0.0 0.0 0.1 0.0 0.1 0.3 0.0 0.0 0.1 0.0 0.2 2.1 0.0RO 0.5 0.1 4.0 0.2 15.7 0.5 12.8 0.5 0.8 0.0 10.5 14.3 0.3RS 1.2 0.0 2.2 0.0 39.6 0.2 12.2 0.1 0.3 0.0 5.4 5.9 0.1RU 1.5 7.7 12.4 9.3 28.3 9.2 17.4 13.1 6.8 0.5 52.2 159.3 7.2SE 0.1 0.1 2.8 0.1 2.6 4.5 0.7 1.0 1.5 0.0 21.8 89.0 13.7SI 0.1 0.0 8.4 0.0 4.1 0.1 0.2 0.0 0.3 0.0 3.3 3.8 0.0SK 0.1 0.0 5.5 0.0 7.3 0.3 1.0 0.1 0.6 0.0 33.0 14.5 0.2TJ 0.0 0.1 0.0 0.1 0.1 0.0 0.1 0.0 0.0 0.0 0.1 0.3 0.0TM 0.0 0.5 0.1 1.0 0.2 0.1 0.1 0.0 0.1 0.0 0.2 0.7 0.0TR 0.5 9.9 1.7 1.4 5.1 0.6 9.0 0.3 0.9 2.6 3.6 8.9 0.2UA 0.5 0.6 4.6 0.7 12.5 1.4 8.1 4.3 1.6 0.1 20.8 35.8 1.0UZ 0.0 0.5 0.1 0.6 0.2 0.1 0.2 0.0 0.1 0.0 0.3 0.9 0.0SUM 25.4 48.2 229.4 44.3 597.5 210.9 204.5 53.1 142.7 5.0 940.5 2798.4 67.0Emiss 2017 189.9 338.5 1053.6 260.1 1734.6 1049.5 865.8 270.0 664.0 100.0 2606.9 9356.7 284.7 code AL AM AT AZ BA BE BG BY CH CY CZ DE DK

26

Table 3.4. Matrix of Hg country‐to‐country deposition from anthropogenic sources in 2018, kg (continued)


code EE ES FI FR GB GE GR HR HU IE IS IT KY KZAL 0.0 1.0 0.0 0.5 0.1 0.0 13.2 0.3 0.6 0.0 0.0 8.6 0.0 0.1AM 0.0 0.1 0.0 0.1 0.1 3.2 0.1 0.0 0.0 0.0 0.0 0.3 0.0 0.7AT 0.2 1.8 0.1 5.4 1.9 0.0 1.0 3.0 12.1 0.1 0.0 50.2 0.0 0.3AZ 0.0 0.1 0.0 0.1 0.1 2.3 0.2 0.0 0.1 0.0 0.0 0.5 0.0 3.6BA 0.1 1.4 0.0 1.4 0.5 0.0 3.0 7.2 12.0 0.0 0.0 21.8 0.0 0.2BE 0.1 1.1 0.0 21.2 8.2 0.0 0.0 0.0 0.1 0.2 0.0 1.3 0.0 0.0BG 0.3 1.3 0.1 1.0 0.6 0.1 16.3 0.6 4.5 0.0 0.0 7.0 0.0 1.1BY 3.5 1.0 0.9 2.4 2.8 0.1 2.0 0.9 5.9 0.1 0.0 11.0 0.0 2.9CH 0.0 2.0 0.0 12.2 0.9 0.0 0.2 0.3 0.3 0.0 0.0 84.7 0.0 0.1CY 0.0 0.1 0.0 0.0 0.0 0.0 0.4 0.0 0.0 0.0 0.0 0.3 0.0 0.0CZ 0.4 1.0 0.1 3.9 2.6 0.0 0.9 1.2 14.7 0.1 0.0 8.3 0.0 0.4DE 1.7 6.9 0.6 61.9 38.1 0.0 0.9 1.0 5.9 1.2 0.0 31.9 0.0 0.9DK 0.3 0.7 0.1 2.4 8.2 0.0 0.1 0.0 0.3 0.3 0.0 0.9 0.0 0.1EE 30.8 0.2 2.4 0.6 1.8 0.0 0.2 0.1 0.6 0.1 0.0 1.1 0.0 0.5ES 0.2 412.5 0.1 25.8 14.2 0.0 1.0 0.6 1.0 0.9 0.0 16.0 0.0 0.2FI 32.0 1.8 67.0 3.6 8.4 0.1 0.8 0.5 2.7 0.4 0.0 6.0 0.0 3.6FR 0.5 81.5 0.2 466.5 48.3 0.0 1.5 1.5 1.7 1.5 0.0 74.1 0.0 0.4GB 0.5 8.8 0.2 21.6 485.2 0.0 0.1 0.1 0.6 12.2 0.0 3.5 0.0 0.4GE 0.0 0.2 0.0 0.2 0.1 15.9 0.6 0.1 0.2 0.0 0.0 1.0 0.0 0.9GR 0.1 2.0 0.0 1.2 0.5 0.1 170.8 0.5 1.7 0.0 0.0 12.5 0.0 0.5HR 0.1 1.5 0.0 1.6 0.5 0.0 2.1 25.8 17.0 0.0 0.0 28.9 0.0 0.2HU 0.3 1.1 0.1 1.6 0.7 0.0 2.5 3.7 158.2 0.0 0.0 15.1 0.0 0.5IE 0.1 2.5 0.0 1.7 22.1 0.0 0.0 0.0 0.1 29.7 0.0 0.5 0.0 0.1IS 0.1 0.9 0.1 1.1 4.1 0.0 0.1 0.0 0.1 0.4 4.1 0.9 0.0 0.2IT 0.2 15.9 0.1 21.5 3.0 0.1 10.4 14.9 8.7 0.1 0.0 1130.7 0.0 0.5KY 0.0 0.3 0.0 0.2 0.2 0.1 0.2 0.0 0.1 0.0 0.0 0.8 17.0 59.6KZ 2.6 3.1 1.3 3.4 4.0 2.0 3.5 0.6 2.5 0.2 0.0 11.9 18.3 2156.5LI 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0LT 2.1 0.4 0.5 1.0 2.3 0.0 0.4 0.2 1.8 0.1 0.0 2.2 0.0 0.6LU 0.0 0.1 0.0 1.9 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0LV 6.4 0.4 1.0 0.9 2.4 0.0 0.4 0.2 1.2 0.1 0.0 1.6 0.0 0.7MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0MD 0.1 0.2 0.0 0.2 0.1 0.0 0.9 0.1 0.5 0.0 0.0 1.2 0.0 0.8ME 0.0 0.5 0.0 0.3 0.1 0.0 1.4 0.3 0.9 0.0 0.0 5.4 0.0 0.0MK 0.0 0.4 0.0 0.3 0.1 0.0 14.3 0.1 0.7 0.0 0.0 2.8 0.0 0.1MT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0NL 0.1 0.9 0.0 9.0 13.3 0.0 0.0 0.0 0.2 0.3 0.0 1.3 0.0 0.0NO 2.4 2.8 1.8 6.6 27.6 0.0 0.3 0.2 1.2 1.2 0.1 2.8 0.0 1.3PL 3.9 2.7 1.1 8.0 12.1 0.1 2.7 1.9 24.3 0.5 0.0 16.7 0.0 2.5PT 0.0 17.2 0.0 1.3 2.2 0.0 0.1 0.0 0.1 0.2 0.0 0.9 0.0 0.0RO 0.6 1.9 0.2 2.3 1.3 0.1 9.2 1.9 26.2 0.1 0.0 18.3 0.0 2.5RS 0.1 1.2 0.1 1.1 0.7 0.0 7.7 2.2 20.0 0.0 0.0 10.6 0.0 0.4RU 111.0 16.9 33.8 24.0 39.1 7.4 25.0 4.8 24.3 2.1 0.3 78.4 5.7 1768.3SE 11.6 2.9 13.3 7.4 24.9 0.1 0.9 0.4 3.5 1.0 0.1 6.4 0.0 2.8SI 0.0 0.6 0.0 0.8 0.2 0.0 0.4 6.8 3.7 0.0 0.0 14.9 0.0 0.1SK 0.2 0.6 0.1 1.2 0.8 0.0 1.0 1.2 41.8 0.0 0.0 7.1 0.0 0.3TJ 0.0 0.1 0.0 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.4 0.6 5.4TM 0.1 0.2 0.0 0.2 0.2 0.3 0.2 0.0 0.1 0.0 0.0 0.7 0.3 20.6TR 0.5 5.7 0.2 3.5 1.8 2.4 28.5 0.8 3.3 0.1 0.0 19.6 0.0 4.7UA 3.0 3.3 1.0 4.6 3.8 0.7 11.6 1.9 18.9 0.2 0.0 26.0 0.1 16.5UZ 0.2 0.3 0.1 0.2 0.2 0.3 0.3 0.0 0.1 0.0 0.0 1.0 1.9 48.5SUM 216.7 610.0 127.1 737.9 790.8 35.7 337.6 86.5 424.7 53.6 4.9 1748.3 44.0 4110.7Emiss 2017 587.2 4222.6 578.9 3794.5 3984.5 207.2 1647.4 435.2 1341.9 336.6 61.6 9159.6 811.3 18666.5 code EE ES FI FR GB GE GR HR HU IE IS IT KY KZ

27



code LI LT LU LV MC MD ME MK MT NL NO PL PTAL 0.0 0.0 0.0 0.0 0.0 0.0 0.4 4.1 0.0 0.0 0.0 1.5 0.2AM 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.0AT 0.0 0.1 0.1 0.0 0.0 0.1 0.2 0.2 0.0 0.5 0.0 42.1 0.3AZ 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0BA 0.0 0.0 0.0 0.0 0.0 0.1 4.6 0.8 0.0 0.1 0.0 15.1 0.3BE 0.0 0.0 1.3 0.0 0.0 0.0 0.0 0.0 0.0 7.3 0.0 5.0 0.2BG 0.0 0.1 0.0 0.0 0.0 1.2 0.6 3.2 0.0 0.1 0.0 9.4 0.4BY 0.0 1.7 0.1 1.1 0.0 1.1 0.3 0.4 0.0 0.6 0.1 104.6 0.2CH 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.0 3.2 0.4CY 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0CZ 0.0 0.1 0.2 0.1 0.0 0.1 0.2 0.3 0.0 0.7 0.1 191.1 0.2DE 0.0 0.5 4.8 0.3 0.0 0.1 0.2 0.2 0.0 23.0 0.3 259.2 1.2DK 0.0 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 1.7 0.2 14.5 0.2EE 0.0 0.6 0.0 1.5 0.0 0.0 0.0 0.0 0.0 0.3 0.1 15.1 0.1ES 0.0 0.1 0.2 0.0 0.0 0.0 0.1 0.1 0.0 1.5 0.1 8.4 74.9FI 0.0 1.0 0.1 1.2 0.0 0.3 0.1 0.2 0.0 1.2 0.9 50.6 0.4FR 0.0 0.1 3.9 0.1 0.2 0.0 0.2 0.3 0.0 11.6 0.2 33.4 10.0GB 0.0 0.1 0.2 0.1 0.0 0.0 0.0 0.0 0.0 5.6 0.3 19.3 2.1GE 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.0 0.0 0.9 0.1GR 0.0 0.0 0.0 0.0 0.0 0.3 0.3 6.3 0.0 0.1 0.0 4.8 0.5HR 0.0 0.0 0.0 0.0 0.0 0.1 0.7 0.5 0.0 0.1 0.0 16.9 0.3HU 0.0 0.1 0.0 0.0 0.0 0.3 0.9 1.0 0.0 0.2 0.0 44.2 0.2IE 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.0 2.7 0.7IS 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.1 2.2 0.3IT 0.0 0.1 0.1 0.0 0.1 0.1 1.5 1.8 0.2 0.6 0.1 25.8 3.0KY 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.1KZ 0.0 0.3 0.1 0.2 0.0 0.5 0.2 0.6 0.0 0.6 0.3 23.3 0.8LI 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0LT 0.0 11.4 0.0 1.9 0.0 0.1 0.0 0.1 0.0 0.4 0.1 51.1 0.1LU 0.0 0.0 1.7 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.6 0.0LV 0.0 4.9 0.0 9.8 0.0 0.1 0.0 0.1 0.0 0.5 0.1 32.8 0.1MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0MD 0.0 0.0 0.0 0.0 0.0 8.6 0.0 0.1 0.0 0.0 0.0 4.1 0.0ME 0.0 0.0 0.0 0.0 0.0 0.0 5.1 0.5 0.0 0.0 0.0 1.4 0.1MK 0.0 0.0 0.0 0.0 0.0 0.1 0.2 18.3 0.0 0.0 0.0 1.4 0.1MT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0NL 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 32.9 0.0 7.6 0.2NO 0.0 0.3 0.2 0.3 0.0 0.1 0.1 0.1 0.0 2.9 19.0 36.0 0.7PL 0.0 1.7 0.3 0.8 0.0 0.6 0.5 0.8 0.0 3.1 0.4 1529.1 0.7PT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.9 132.3RO 0.0 0.2 0.0 0.1 0.0 5.7 1.1 2.2 0.0 0.3 0.1 37.4 0.4RS 0.0 0.0 0.0 0.0 0.0 0.3 5.7 9.4 0.0 0.1 0.0 15.1 0.3RU 0.0 5.1 0.5 5.6 0.0 4.4 2.0 4.2 0.1 6.2 3.6 310.1 4.2SE 0.0 1.5 0.2 1.3 0.0 0.2 0.2 0.2 0.0 3.8 4.2 117.1 0.6SI 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 6.1 0.1SK 0.0 0.1 0.0 0.0 0.0 0.1 0.3 0.4 0.0 0.2 0.0 73.6 0.1TJ 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.0TM 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.1TR 0.0 0.1 0.0 0.1 0.0 1.2 0.4 1.6 0.1 0.3 0.1 13.4 1.4UA 0.0 0.7 0.1 0.5 0.0 9.9 0.9 1.6 0.0 0.8 0.2 159.5 0.7UZ 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 1.3 0.1SUM 0.1 31.0 14.8 25.5 0.5 35.8 27.4 59.9 0.8 109.0 30.9 3294.7 239.4Emiss 2017 0.3 145.7 62.7 107.7 4.3 155.8 94.6 191.9 26.4 592.9 241.9 9577.6 2090.1

code LI LT LU LV MC MD ME MK MT NL NO PL PT

28



code RO RS RU SE SI SK TJ TM TR UA UZ SUMAL 0.9 4.3 1.2 0.0 0.1 0.4 0.0 0.0 4.0 1.4 0.0 60.0AM 0.1 0.1 0.8 0.0 0.0 0.0 0.0 0.4 10.1 0.4 0.1 35.0AT 3.1 9.7 3.0 0.1 9.9 25.2 0.0 0.0 2.4 2.2 0.0 395.7AZ 0.2 0.2 3.0 0.0 0.0 0.1 0.0 2.2 10.2 1.3 0.7 51.7BA 5.2 42.2 2.4 0.0 0.9 7.0 0.0 0.0 4.1 2.3 0.0 450.0BE 0.1 0.1 0.4 0.0 0.0 0.3 0.0 0.0 0.1 0.1 0.0 157.0BG 30.5 26.2 17.4 0.1 0.3 2.9 0.0 0.2 43.3 25.5 0.1 315.7BY 7.5 8.5 91.3 0.7 0.6 5.6 0.0 0.2 10.7 49.4 0.3 387.4CH 0.2 0.4 0.5 0.0 0.2 0.3 0.0 0.0 0.9 0.2 0.0 195.8CY 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 8.2 0.1 0.0 10.9CZ 3.6 11.7 4.3 0.2 1.2 35.1 0.0 0.0 1.4 2.8 0.0 745.4DE 2.4 6.0 10.8 0.9 1.1 9.8 0.0 0.0 2.6 3.8 0.1 2094.0DK 0.2 0.4 1.1 0.8 0.0 0.5 0.0 0.0 0.1 0.4 0.0 94.6EE 0.5 0.8 8.6 0.8 0.1 0.8 0.0 0.0 0.9 1.9 0.0 83.0ES 0.5 1.1 2.3 0.1 0.3 0.9 0.0 0.0 3.2 0.8 0.0 598.1FI 2.7 3.7 71.1 6.4 0.3 3.1 0.0 0.1 5.2 9.5 0.3 334.3FR 1.0 2.0 4.1 0.3 0.8 2.2 0.0 0.0 4.0 1.6 0.0 1055.9GB 0.2 0.5 3.5 0.4 0.1 1.0 0.0 0.0 0.6 0.7 0.0 629.3GE 0.6 0.5 2.5 0.0 0.0 0.2 0.0 0.4 40.9 2.1 0.1 76.6GR 3.5 7.3 7.7 0.0 0.2 1.2 0.0 0.1 56.9 9.2 0.0 309.7HR 4.2 28.2 1.8 0.0 5.4 9.3 0.0 0.0 2.5 1.6 0.0 226.7HU 24.8 51.0 5.8 0.1 2.2 63.1 0.0 0.1 3.3 7.3 0.0 453.1IE 0.0 0.1 0.7 0.1 0.0 0.1 0.0 0.0 0.1 0.1 0.0 68.5IS 0.1 0.2 1.2 0.1 0.0 0.1 0.0 0.0 0.3 0.3 0.0 24.1IT 4.2 14.8 5.0 0.1 8.2 7.8 0.0 0.1 17.1 4.3 0.0 1403.3KY 0.2 0.2 3.4 0.0 0.0 0.1 4.3 0.9 5.5 0.9 150.0 247.2KZ 4.6 4.5 351.3 0.7 0.3 2.4 5.4 10.9 71.5 45.0 199.7 2970.5LI 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9LT 1.2 1.8 11.3 0.6 0.2 2.3 0.0 0.0 1.5 4.4 0.1 128.9LU 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 12.6LV 0.9 1.3 13.4 0.9 0.1 1.6 0.0 0.0 1.5 3.9 0.1 109.8MC 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0MD 4.5 0.9 8.0 0.0 0.0 0.5 0.0 0.1 8.2 21.3 0.1 64.2ME 0.9 5.9 0.6 0.0 0.1 0.5 0.0 0.0 1.5 0.6 0.0 39.7MK 1.2 5.9 1.4 0.0 0.0 0.4 0.0 0.0 3.7 1.7 0.0 62.5MT 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2NL 0.1 0.1 0.6 0.1 0.0 0.3 0.0 0.0 0.1 0.1 0.0 149.6NO 0.8 1.4 14.6 4.0 0.1 1.6 0.0 0.1 1.6 2.6 0.1 212.4PL 11.4 20.5 34.5 1.7 1.8 47.6 0.0 0.1 5.6 24.7 0.2 2159.5PT 0.0 0.1 0.3 0.0 0.0 0.1 0.0 0.0 0.2 0.1 0.0 159.2RO 231.8 53.9 29.4 0.2 1.0 14.3 0.0 0.3 36.4 51.9 0.3 592.2RS 23.4 266.1 5.4 0.1 0.6 8.3 0.0 0.1 6.6 7.0 0.0 460.2RU 44.2 42.0 4611.5 11.4 2.9 23.5 2.5 14.8 390.2 483.1 72.7 8510.8SE 2.4 4.1 38.6 39.5 0.4 5.0 0.0 0.2 4.2 7.4 0.4 444.8SI 1.0 4.3 0.6 0.0 17.3 3.0 0.0 0.0 0.8 0.5 0.0 81.8SK 7.7 16.1 4.0 0.1 0.9 125.2 0.0 0.0 1.2 4.5 0.0 351.7TJ 0.1 0.1 1.5 0.0 0.0 0.0 14.5 0.8 2.5 0.4 35.7 63.9TM 0.2 0.2 7.6 0.0 0.0 0.1 1.3 14.3 6.0 2.2 40.7 99.9TR 12.2 9.2 43.8 0.2 0.4 2.6 0.0 0.9 2570.1 43.4 0.4 2817.8UA 35.8 22.5 270.0 0.8 1.2 18.2 0.0 1.4 149.5 825.0 1.7 1684.7UZ 0.3 0.3 11.4 0.0 0.0 0.1 5.1 3.0 8.1 2.4 209.3 298.0SUM 459.0 671.4 5241.1 76.6 60.7 590.4 32.1 49.3 3425.2 7389.9 669.7 Emiss 2017 1.45 1.94 26.48 0.41 0.17 1.73 0.57 0.41 15.82 24.16 5.85 code RO RS RU SE SI SK TJ TM TR UA UZ

29

4. EVALUATION OF MODELLING RESULTS VS. OBSERVATIONS

4.1. Lead

4.1.1. Air concentrations

Table 4.1. Annual mean modelled and observed Pb air concentrations, ng/m3, temporal correlation coefficient (Rc and relative bias (Bias)) at EMEP stations in 2018

Station name Code Longitude Latitude Observed Modelled Rc Bias Koksijde BE0014R 2.66 51.12 5.34 6.23 0.5 16.7 Kosetice (NOAK) CZ0003R 15.08 49.57 3.38 3.41 0.72 0.9 Churanov CZ0005R 13.6 49.07 1.57 1.70 0.55 8.3 Westerland DE0001R 8.31 54.93 2.03 2.60 0.71 28.1 Waldhof DE0002R 10.76 52.8 3.65 3.48 0.86 ‐4.7 Schauinsland DE0003R 7.91 47.91 1.21 3.38 0.52 179.3 Neuglobsow DE0007R 13.03 53.17 3.42 3.37 0.88 ‐1.5 Schmucke DE0008R 10.77 50.65 2.12 3.08 0.68 45.3 Zingst DE0009R 12.72 54.44 2.76 2.72 0.77 ‐1.4 Riscoe DK0012R 12.09 55.69 1.80 4.46 0.72 20.6 Anholt DK0008R 11.52 56.72 1.36 1.64 0.63 147.8 Lahemaa EE0009R 25.9 59.5 1.69 0.70 ‐0.08 ‐58.9 San Pablo de los Montes ES0001R ‐4.35 39.55 1.58 1.05 ‐0.11 ‐33.5 Viznar ES0007R ‐3.53 37.23 1.25 1.47 0.61 17.6 Niembro ES0008R ‐4.85 43.44 2.48 1.74 ‐0.06 ‐29.8 Campisabalos ES0009R ‐3.14 41.28 0.70 0.93 0.5 32.5 ElTorms ES0014R 0.72 41.4 1.13 1.77 0.1 56.6 Virolahti III FI0018R 27.67 60.53 2.49 0.76 0.56 ‐69.4 Pallas (Matorova) FI0036R 24.24 68 0.64 0.14 0.18 ‐77.6 Hyytiälä FI0050R 24.28 61.85 1.32 0.32 0.14 ‐76.1 Yarner Wood GB0013R ‐3.71 50.6 2.27 1.80 0.75 ‐20.7 Heigham Holmes GB0017R 1.62 52.72 4.18 3.41 0.76 ‐18.4 Auchencorth Moss GB0048R ‐3.24 55.79 1.03 1.25 0.64 21.4 Chilbolton Observatory GB1055 ‐1.44 51.15 3.58 2.99 0.7 ‐16.5 K‐puszta HU0002R 19.58 46.97 7.51 3.56 0.58 ‐52.6 Vestmannaeyjar IS0091R ‐20.28 63.4 0.11 0.70 0.63 520.4 Rucava LV0010R 21.17 56.16 1.25 1.33 ‐0.44 6.4 Bilthoven NL0008R 5.2 52.12 4.54 4.24 0.76 ‐6.6 Birkenes II NO0002R 8.25 58.39 0.75 0.59 0.37 ‐21.9 Zeppelin mountain (Ny‐Alesund) NO0042G 11.89 78.91 0.14 0.22 0.26 58.7 Alomar NO0090R 16.01 69.28 0.23 0.37 ‐0.3 61.7 Diabla Gora PL0005R 22.07 54.15 2.61 2.55 0.71 ‐2.3 Zielonka PL0009R 17.93 53.66 4.09 4.38 0.79 7.1 Bredkälen SE0005R 15.33 63.85 0.38 0.15 0.07 ‐60.5 Råö SE0014R 11.91 57.39 1.38 1.22 0.39 ‐11.6 Hallahus SE0020R 13.15 56.04 1.76 2.04 0.59 15.9 Iskrba SI0008R 14.87 45.57 2.12 2.18 0.11 2.8 Chopok SK0002R 19.58 48.93 2.59 1.93 ‐0.03 ‐25.5 StarГЎ LesnГЎ SK0004R 20.28 49.15 4.83 2.62 0.6 ‐45.8 Starina SK0006R 22.27 49.05 3.77 1.66 0.07 ‐56.0 Topolniki SK0007R 17.86 47.96 7.91 5.67 0.67 ‐28.3

30

Fig. 4.1. Modelled and observed annual mean concentrations of Pb in air at the EMEP stations in 2018

0123456789

BE0014R

CZ0003R

CZ0005R

DE0001R

DE0002R

DE0003R

DE0007R

DE0008R

DE0009R

DK0008R

DK0012R

EE0009R

ES0001R

ES0007R

ES0008R

ES0009R

ES0014R

FI0018R

FI0036R

FI0050R

GB0013R

GB0017R

GB0048R

GB1055

HU0002R

IS0091R

LV0010R

NL0008R

NO0002R

NO0042G

NO0090R

PL0005R

PL0009R

SE0005R

SE0014R

SE0020R

SI0008R

SK0002R

SK0004R

SK0006R

SK0007R

Pb air co

ncen

trations, ng/m

3 Observed

Modelled

0

5

10

15

20

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

BE0014Obs

Mod

0

1

2

3

4

5

6

7

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

CZ0003Obs

Mod

0

0.5

1

1.5

2

2.5

3

3.5

4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air con

centration

s, ng

/m3

CZ0005

Obs

Mod

0

1

2

3

4

5

6

7

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

DE0001Obs

Mod

0

1

2

3

4

5

6

7

8

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

DE0002Obs

Mod

0

1

2

3

4

5

6

7

8

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

DE0003Obs

Mod

31

0

1

2

3

4

5

6

7

8

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3DE0007

Obs

Mod

0

1

2

3

4

5

6

7

8

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

DE0008Obs

Mod

0

1

2

3

4

5

6

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

DE0009

Obs

Mod0

0.5

1

1.5

2

2.5

3

3.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

DK0008Obs

Mod

0

2

4

6

8

10

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

DK0012Obs

Mod

0

1

2

3

4

5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

EE0009Obs

Mod

0

2

4

6

8

10

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

ES0001Obs

Mod

0

0.5

1

1.5

2

2.5

3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

ES0007

Obs

Mod

0

1

2

3

4

5

6

7

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

ES0008Obs

Mod

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

ES0009Obs

Mod

32

0

0.5

1

1.5

2

2.5

3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3ES0014Obs

Mod

0

1

2

3

4

5

6

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

FI0018Obs

Mod

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

FI0036Obs

Mod

0

0.5

1

1.5

2

2.5

3

3.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air co

ncen

trations, ng/m

3

FI0050Obs

Mod

0

0.5

1

1.5

2

2.5

3

3.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

GB0013

Obs

Mod0

2

4

6

8

10

12

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

GB0017Obs

Mod

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

GB0048

Obs

Mod0

1

2

3

4

5

6

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

GB1055

Obs

Mod

0

2

4

6

8

10

12

14

16

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

HU0002Obs

Mod

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

IS0091Obs

Mod

33

0

0.5

1

1.5

2

2.5

3

3.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3LV0010Obs

Mod

0

2

4

6

8

10

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

NL0008Obs

Mod

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

NO0002Obs

Mod

0

0.1

0.2

0.3

0.4

0.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

NO0042Obs

Mod

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

NO0090Obs

Mod

0

1

2

3

4

5

6

7Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

PL0005Obs

Mod

0

1

2

3

4

5

6

7

8

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

PL0009

Obs

Mod0

0.2

0.4

0.6

0.8

1

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

SE0005Obs

Mod

0

0.5

1

1.5

2

2.5

3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

SE0014Obs

Mod

0

0.5

1

1.5

2

2.5

3

3.5

4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

SE0020

Obs

Mod

34

Fig. 4.2. Modelled and observed monthly mean concentrations of Pb in air at the EMEP stations in 2018

0

1

2

3

4

5

6

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3SI0008

Obs

Mod

0

1

2

3

4

5

6

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb air concen

trations, ng/m

3

SK0002Obs

Mod

0

2

4

6

8

10

12

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

SK0004Obs

Mod

0

1

2

3

4

5

6

7

8

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

SK0006Obs

Mod

0

2

4

6

8

10

12

14

16

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb air concen

trations, ng/m

3

SK0007Obs

Mod

35

4.1.2. Wet deposition

Table 4.2. Annual sums of modelled and observed Pb wet deposition fluxes, g/km2/y, temporal correlation coefficient (Rc) and relative bias (Bias) at EMEP stations in 2018

Station name Code Longit Latit Observedflux

Modelledflux

R Bias

Koksijde BE0014R 2.66 51.12 344.3 317.5 0.3 ‐7.8 Kosetice(NOAK) CZ0003R 15.08 49.57 565.0 220.2 0.40 ‐61.0 Westerland DE0001R 8.31 54.93 221.8 263.2 0.45 18.7 Waldhof DE0002R 10.76 52.8 218.4 224.3 0.59 2.7 Schauinsland DE0003R 7.91 47.91 303.2 455.2 0.84 50.1 Neuglobsow DE0007R 13.03 53.17 261.4 210.5 0.29 ‐19.5 Schmucke DE0008R 10.77 50.65 458.5 370.6 0.53 ‐19.2 Zingst DE0009R 12.72 54.44 194.0 163.2 0.41 ‐15.9 Riscoe DK0012R 12.09 55.69 346.4 232.2 0.21 ‐33.0 Sepstrup Sande DK0022R 9.42 56.08 259.5 243.7 0.16 ‐6.1 Anholt DK0008R 11.52 56.72 386.5 188.3 0.19 ‐51.3 Vilsandi EE0011R 21.82 58.38 296.9 184.8 0.28 ‐37.8 Lahemaa EE0009R 25.9 59.5 334.0 92.9 0.39 ‐72.2 Niembro ES0008R ‐4.85 43.44 1636.6 178.9 0.65 ‐89.1 Campisabalos ES0009R ‐3.14 41.27 2208.4 91.6 0.40 ‐95.9 Hyytiälä FI0050R 24.28 61.85 206.3 94.5 0.12 ‐54.2 Chilbolton Observatory GB1055 ‐1.44 51.15 127.5 246.7 0.8 93.4 Yarner Wood GB0013R ‐3.71 50.6 182.1 202.0 0.92 11.0 Heigham Holmes GB0017R 1.62 52.72 218.8 202.9 0.81 ‐7.3 Auchencorth Moss GB0048R ‐3.24 55.79 81.2 112.0 0.34 37.9 LoughNavar GB0006R ‐7.87 54.44 144.8 109.8 0.56 ‐24.2 K‐puszta HU0002R 19.58 46.97 1139.7 350.7 0.42 ‐69.2 Vestmannaeyjar IS0091R ‐20.28 63.4 1470.5 284.3 0.07 ‐80.7 Rucava LV0010R 21.17 56.16 196.7 139.4 0.21 ‐29.1 Aluksne LV1000R 27.04 57.44 160.3 96.7 0.54 ‐39.7 Dobele LV2000R 23.32 56.62 154.6 102.0 0.17 ‐34.0 Skriveri LV5000R 25.13 56.64 223.7 96.1 0.32 ‐57.1 Riga LV6000R 24.1 56.95 1168.2 186.0 0.49 ‐84.1 Vredepeel NL0010R 5.85 51.54 553.5 253.7 0.66 ‐54.2 De Zilk NL0091R 4.5 52.3 239.2 274.1 0.54 14.6 Birkenes NO0001R 8.25 58.38 788.0 351.4 0.90 ‐55.4 Kårvatn NO0039R 8.88 62.78 180.3 73.2 0.09 ‐59.4 Hurdal NO00056R 11.08 60.37 452.8 179.3 0.77 ‐60.4 Leba PL0004R 17.53 54.75 183.8 231.5 0.35 26.0 Diabla Gora PL0005R 22.07 54.15 273.1 266.4 ‐0.20 ‐2.4 Råö SE0014R 11.91 57.39 218.7 246.7 0.39 12.8 Hallahus SE0020R 13.15 56.04 238.7 247.8 0.7 3.8 Bredkälen SE0005R 15.33 63.85 96.7 79.0 0.21 ‐18.3 Chopok SK0002R 19.58 48.93 1972.4 410.2 0.07 ‐79.2 StarГЎ LesnГЎ SK0004R 20.28 49.15 420.5 560.0 0.43 33.2 Starina SK0006R 22.27 49.05 1150.9 407.0 0.41 ‐64.6 Topolniki SK0007R 17.86 47.96 176.6 494.3 0.62 179.9

36

Fig. 4.3. Modelled and observed annual wet deposition fluxes of Pb at the EMEP stations in 2018

0

200

400

600

800

1000

BE0014R

CZ0003R

DE0001R

DE0002R

DE0003R

DE0007R

DE0008R

DE0009R

DK0012R

DK0022R

DK0008R

EE0011R

EE0009R

ES0008R

ES0009R

FI0050R

GB1

055

GB0

013R

GB0

017R

GB0

048R

GB0

006R

HU0002R

IS0091R

LV0010R

LV1000R

LV2000R

LV5000R

LV6000R

NL0010R

NL0091R

NO0001R

NO0039R

NO00056R

PL0004R

PL0005R

SE0014R

SE0020R

SE0005R

SK0002R

SK0004R

SK0006R

SK0007R

Pb wet dep

osition, g/km

2 Observed

Modelled

1637 2208 1140 1470 1168 1972 1151

0

10

20

30

40

50

60

70

80

Jan

Feb

Mar

Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition

, g/km

2

BE0014Observed

Modelled

0

20

40

60

80

100

120

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

CZ0003Observed

Modelled

0

10

20

30

40

50

60

70

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

DE0001Observed

Modelled

0

10

20

30

40

50

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

DE0002Observed

Modelled

0

20

40

60

80

100

120

140

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

DE0003Observed

Modelled

0

10

20

30

40

50

60

70

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

DE0007Observed

Modelled

37

0

20

40

60

80

100

120

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2DE0008

Observed

Modelled

0

5

10

15

20

25

30

35

40

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

DE0009Observed

Modelled

0

20

40

60

80

100

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

DK0008Observed

Modelled

0

10

20

30

40

50

60

70

80

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition

, g/km

2

DK0012Observed

Modelled

0

20

40

60

80

100

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

DK0022Observed

Modelled

0

20

40

60

80

100

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

EE0009Observed

Modelled

0

10

20

30

40

50

60

70

80

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

EE0011Observed

Modelled

0

100

200

300

400

500

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

ES0008Observed

Modelled

0

100

200

300

400

500

600

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

ES0009Observed

Modelled

0

5

10

15

20

25

30

35

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition, g/km

2

FI0050Observed

Modelled

38

0

5

10

15

20

25

30

35

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition, g/km

2GB0006Observed

Modelled

0

20

40

60

80

100

120

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition, g/km

2

GB0013Observed

Modelled

0

10

20

30

40

50

60

70

80

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition, g/km

2

GB0017Observed

Modelled

0

5

10

15

20

25

30

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition, g/km

2

GB0048Observed

Modelled

0

10

20

30

40

50

60

70

80

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition

, g/km

2

GB1055Observed

Modelled

0

100

200

300

400

500

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition

, g/km

2

HU0002Observed

Modelled

0

50

100

150

200

250

300

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition

, g/km

2

IS0091Observed

Modelled

0

10

20

30

40

50

60

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition

, g/km

2

LV0010Observed

Modelled

0

10

20

30

40

50

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition, g/km

2

LV1000

Observed

Modelled

0

10

20

30

40

50

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition, g/km

2

LV2000Observed

Modelled

39

0

10

20

30

40

50

60

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Pb wet dep

osition, g/km

2LV5000

Observed

Modelled

0

50

100

150

200

250

300

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

LV6000

Observed

Modelled

0

20

40

60

80

100

120

140

160

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

NL0010Observed

Modelled

0

10

20

30

40

50

60

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

NL0091Observed

Modelled

0

50

100

150

200

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

NO0001Observed

Modelled

0

5

10

15

20

25

30

35

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

NO0039Observed

Modelled

0

20

40

60

80

100

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

NO0056Observed

Modelled

0

10

20

30

40

50

60

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

PL0004Observed

Modelled

0

20

40

60

80

100

120

140

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

PL0005Observed

Modelled

0

5

10

15

20

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

SE0005Observed

Modelled

40

Fig. 4.4. Modelled and observed monthly wet deposition fluxes of Pb at the EMEP stations in 2018

0

5

10

15

20

25

30

35

40

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2SE0014

Observed

Modelled

0

10

20

30

40

50

60

70

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

SE0020Observed

Modelled

0

100

200

300

400

500

600

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

SK0002Observed

Modelled

0

20

40

60

80

100

120

140

160

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition, g/km

2

SK0004Observed

Modelled

0

50

100

150

200

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

SK0006Observed

Modelled

0

20

40

60

80

100

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

SK0007

Observed

Modelled

41

4.2. Cadmium


Table 4.3. Annual mean modelled and observed Cd air concentrations, ng/m3, temporal correlation coefficient (Rc) and relative bias (Bias) at EMEP stations in 2018

Station name Code Longit Latid Observed Modelled R Bias Koksijde BE0014R 2.66 51.12 0.17 0.22 0.44 26.6 Kosetice (NOAK) CZ0003R 15.08 49.57 0.10 0.12 0.75 18.2 Churanov CZ0005R 13.6 49.07 0.04 0.09 0.47 96.3 Westerland DE0001R 8.31 54.93 0.06 0.09 0.86 44.1 Waldhof DE0002R 10.76 52.8 0.10 0.12 0.83 14.9 Schauinsland DE0003R 7.91 47.91 0.03 0.12 0.47 331.8 Neuglobsow DE0007R 13.03 53.17 0.10 0.10 0.86 ‐0.6 Schmucke DE0008R 10.77 50.65 0.05 0.11 0.61 91.0 Zingst DE0009R 12.72 54.44 0.08 0.09 0.83 3.8 Anholt DK0008R 11.52 56.72 0.04 0.06 0.55 30.5 Riscoe DK0012R 12.09 55.69 0.05 0.14 0.71 158.0 Lahemaa EE0009R 25.9 59.5 0.06 0.04 0.57 ‐38.9 San Pablo de los Montes ES0001R ‐4.35 39.55 0.02 0.03 0.23 52.9 Viznar ES0007R ‐3.53 37.23 0.03 0.03 ‐0.12 1.4 Niembro ES0008R ‐4.85 43.44 0.09 0.04 0.41 ‐59.2 Campisabalos ES0009R ‐3.14 41.28 0.02 0.03 0.21 55.2 ElTorms ES0014R 0.72 41.4 0.03 0.05 ‐0.15 51.3 Virolahti III FI0018R 27.67 60.53 0.07 0.04 0.67 ‐50.4 Pallas (Matorova) FI0036R 24.24 68 0.02 0.01 0.4 ‐68.0 Hyytiälä FI0050R 24.28 61.85 0.05 0.01 0.45 ‐70.4 Yarner Wood GB0013R ‐3.71 50.6 0.06 0.07 0.45 2.3 Heigham Holmes GB0017R 1.62 52.72 0.10 0.12 0.63 19.2 Auchencorth Moss GB0048R ‐3.24 55.79 0.03 0.04 0.77 43.2 Chilbolton Observatory GB1055R ‐1.44 51.15 0.09 0.10 0.63 2.3 K‐puszta HU0002R 19.58 46.97 0.17 0.18 0.78 3.0 Vestmannaeyjar IS0091R ‐20.28 63.4 0.00 0.02 0.57 388.0 Rucava LV0010R 21.17 56.16 0.07 0.07 0.62 ‐1.7 Bilthoven NL0008R 5.2 52.12 0.13 0.18 0.8 35.8 Birkenes II NO0002R 8.25 58.39 0.03 0.02 0.51 ‐38.1 Zeppelin mountain (Ny‐Alesund) NO0042G 11.89 78.91 0.02 0.01 ‐0.15 ‐56.2 Alomar NO0090R 16.01 69.28 0.01 0.01 0.01 81.5 Diabla Gora PL0005R 22.07 54.15 0.10 0.09 0.81 ‐15.6 Zielonka PL0009R 17.93 53.66 0.52 0.14 0.8 ‐73.1 Bredkälen SE0005R 15.33 63.85 0.01 0.01 0.4 ‐55.5 Råö SE0014R 11.91 57.39 0.04 0.04 0.43 1.5 Hallahus SE0020R 13.15 56.04 0.05 0.06 0.56 42.5 Iskrba SI0008R 14.87 45.57 0.07 0.10 0.47 29.1 Chopok SK0002R 19.58 48.93 0.17 0.07 0.32 ‐56.1 StarГЎ LesnГЎ SK0004R 20.28 49.15 0.12 0.09 0.8 ‐28.7 Starina SK0006R 22.27 49.05 0.11 0.07 0.48 ‐34.5 Topolniki SK0007R 17.86 47.96 0.15 0.16 0.79 4.2

42

Fig. 4.5. Modelled and observed annual mean concentrations of Cd in air at the EMEP stations in 2018

0

0.05

0.1

0.15

0.2

0.25

BE0014R

CZ0003R

CZ0005R

DE0001R

DE0002R

DE0003R

DE0007R

DE0008R

DE0009R

DK0008R

DK0012R

EE0009R

ES0001R

ES0007R

ES0008R

ES0009R

ES0014R

FI0018R

FI0036R

FI0050R

GB0013R

GB0017R

GB0048R

GB1055R

HU0

002R

IS0091R

LV0010R

NL0008R

NO0002R

NO0042G

NO0090R

PL0005R

PL0009R

SE0005R

SE0014R

SE0020R

SI0008R

SK0002R

SK0004R

SK0006R

SK0007R

Cd air concen

trations, ng/m

3 Observed

Modelled

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd air co

ncen

trations, ng/m

3

BE0014Obs

Mod

0

0.05

0.1

0.15

0.2

0.25

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd air concen

trations, ng/m

3

CZ0003Observed

Modelled

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd air con

centration

s, ng

/m3

CZ0005Observed

Modelled

0

0.03

0.06

0.09

0.12

0.15

0.18

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd air concen

trations, ng/m

3

DE0001Obs

Mod

0

0.05

0.1

0.15

0.2

0.25

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

DE0002Obs

Mod

0

0.05

0.1

0.15

0.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd air concen

trations, ng/m

3

DE0003Obs

Mod

43

0

0.05

0.1

0.15

0.2

0.25

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3DE0007

Obs

Mod

0

0.05

0.1

0.15

0.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

DE0008Obs

Mod

0

0.05

0.1

0.15

0.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

DE0009Observed

Modelled

0

0.02

0.04

0.06

0.08

0.1

0.12

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

DK0008Obs

Mod

0

0.05

0.1

0.15

0.2

0.25

0.3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd air co

ncen

trations, ng/m

3

DK0012Obs

Mod

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

EE0009Observed

Modelled

0

0.01

0.02

0.03

0.04

0.05

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

ES0001

Observed

Modelled0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

ES0007Observed

Modelled

0

0.05

0.1

0.15

0.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

ES0008Observed

Modelled

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

ES0009Observed

Modelled

44

0

0.02

0.04

0.06

0.08

0.1

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3ES0014

Observed

Modelled

0

0.05

0.1

0.15

0.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

FI0018Observed

Modelled

0

0.01

0.02

0.03

0.04

0.05

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

FI0036Observed

Modelled

0

0.02

0.04

0.06

0.08

0.1

0.12

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

FI0050Observed

Modelled

0

0.02

0.04

0.06

0.08

0.1

0.12

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

GB0013

Obs

Mod0

0.05

0.1

0.15

0.2

0.25

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

GB0017Observed

Modelled

0

0.01

0.02

0.03

0.04

0.05

0.06

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

GB0048

Observed

Modelled0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

GB1055

Observed

Modelled

0

0.1

0.2

0.3

0.4

0.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

HU0002Observed

Modelled

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

IS0091Observed

Modelled

45

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3LV0010Observed

Modelled

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

NL0008Observed

Modelled

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

NO0002Observed

Modelled

0

0.01

0.02

0.03

0.04

0.05

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air concen

trations, ng/m

3

NO0042Observed

Modelled

0

0.005

0.01

0.015

0.02

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

NO0090

Observed

Modelled

0

0.05

0.1

0.15

0.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

PL0005Observed

Modelled

0

0.2

0.4

0.6

0.8

1

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

PL0009Observed

Modelled

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

SE0005Observed

Modelled

0

0.02

0.04

0.06

0.08

0.1

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

SE0014Observed

Modelled

0

0.02

0.04

0.06

0.08

0.1

0.12

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

SE0020Observed

Modelled

46

Fig. 4.6. Modelled and observed annual mean concentrations of Cd in air at the EMEP stations in 2018

0

0.05

0.1

0.15

0.2

0.25

0.3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3SI0008

Obs

Mod

0

0.2

0.4

0.6

0.8

1

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

SK0002Observed

Modelled

0

0.05

0.1

0.15

0.2

0.25

0.3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

SK0004Observed

Modelled

0

0.05

0.1

0.15

0.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

SK0006Observed

Modelled

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Cd air co

ncen

trations, ng/m

3

SK0007Observed

Modelled

47


Table 4.4. Annual sums of modelled and observed Cd wet deposition fluxes, g/km2/y, temporal correlation coefficient (Rc) and relative bias (Bias) at EMEP stations in 2018


Modelledflux

R Bias

Koksijde BE0014R 2.66 51.12 11.6 10.1 0.5 ‐13.2 Kosetice(NOAK) CZ0003R 15.08 49.57 14.0 7.2 0.8 ‐48.2 Churanov CZ0005R 13.6 49.07 19.9 16.0 0.8 ‐19.8 Westerland DE0001R 8.31 54.93 8.5 10.6 0.7 24.2 Waldhof DE0002R 10.76 52.8 7.1 8.4 0.6 17.7 Schauinsland DE0003R 7.91 47.91 13.6 17.3 0.8 27.4 Neuglobsow DE0007R 13.03 53.17 11.4 7.4 0.7 ‐35.1 Schmucke DE0008R 10.77 50.65 15.5 13.6 0.7 ‐12.2 Zingst DE0009R 12.72 54.44 7.5 5.9 0.6 ‐21.7 Keldsnor DK0005R 10.74 54.75 25.8 6.6 0.1 ‐74.5 Anholt DK0008R 11.52 56.72 13.5 6.5 0.2 ‐52.3 Riscoe DK0012R 12.09 55.69 13.7 7.4 0.2 ‐46.0 Sepstrup Sande DK0022R 9.42 56.08 11.6 10.0 0.3 ‐14.3 Lahemaa EE0009R 25.9 59.5 55.2 3.8 0.3 ‐93.2 Vilsandi EE0011R 21.82 58.38 26.7 6.8 0.5 ‐74.6 Niembro ES0008R ‐4.85 43.44 89.5 4.4 0.1 ‐95.1 Campisabalos ES0009R ‐3.14 41.27 37.6 2.6 0.2 ‐93.0 Hyytiälä FI0050R 24.28 61.85 8.4 3.6 0.4 ‐57.1 LoughNavar GB0006R ‐7.87 54.44 5.8 3.8 0.4 ‐34.3 Yarner Wood GB0013R ‐3.71 50.6 6.3 8.0 0.9 28.1 Heigham Holmes GB0017R 1.62 52.72 9.0 6.0 0.9 ‐32.9 Auchencorth Moss GB0048R ‐3.24 55.79 5.6 3.9 0.2 ‐29.5 Chilbolton Observatory GB1055R ‐1.44 51.15 5.5 8.3 0.8 52.1 K‐puszta HU0002R 19.58 46.97 18.4 14.4 0.5 ‐22.0 Vestmannaeyjar IS0091R ‐20.28 63.4 24.5 9.1 0.3 ‐62.7 Rucava LV0010R 21.17 56.16 9.8 5.1 0.1 ‐47.9 Aluksne LV1000R 27.04 57.44 9.1 4.3 0.4 ‐52.4 Dobele LV2000R 23.32 56.62 8.3 4.7 0.4 ‐44.0 Skriveri LV5000R 25.13 56.64 10.1 3.8 0.1 ‐62.5 Riga LV6000R 24.1 56.95 21.8 10.1 0.3 ‐53.8 Vredepeel NL0010R 5.85 51.54 22.4 10.7 0.7 ‐52.1 De Zilk NL0091R 4.5 52.3 6.8 9.8 0.6 44.8 Birkenes NO0001R 8.25 58.38 30.2 11.8 0.8 ‐60.8 Kårvatn NO0039R 8.88 62.78 8.4 2.6 0.7 ‐69.3 Hurdal NO00056R 11.08 60.37 17.4 6.1 0.7 ‐64.7 Leba PL0004R 17.53 54.75 10.9 7.5 0.6 ‐30.6 Diabla Gora PL0005R 22.07 54.15 20.4 10.9 0.2 ‐46.3 Bredkälen SE0005R 15.33 63.85 8.4 3.1 0.2 ‐63.5 Råö SE0014R 11.91 57.39 15.8 8.2 0.2 ‐47.8 Hallahus SE0020R 13.15 56.04 29.2 7.7 0.0 ‐73.5 Iskrba SI0008R 14.87 45.57 19.6 28.2 0.0 44.1 Chopok SK0002R 19.58 48.93 44.2 13.8 0.5 ‐68.8 StarГЎ LesnГЎ SK0004R 20.28 49.15 4.4 18.5 0.1 322.4 Starina SK0006R 22.27 49.05 11.9 14.6 0.5 22.7 Topolniki SK0007R 17.86 47.96 1.1 16.1 0.5 1374.3

48

Fig. 4.7. Modelled and observed annual wet deposition fluxes of Cd at the EMEP stations in 2018

0

5

10

15

20

25

30

35

BE0014R

CZ0003R

CZ0005R

DE0001R

DE0002R

DE0003R

DE0007R

DE0008R

DE0009R

DK0005R

DK0008R

DK0012R

DK0022R

EE0009R

EE0011R

ES0008R

ES0009R

FI0050R

GB0006R

GB0013R

GB0017R

GB0048R

GB1055R

HU0002R

IS0091R

LV0010R

LV1000R

LV2000R

LV5000R

LV6000R

NL0010R

NL0091R

NO0001R

NO0039R

NO00056R

PL0004R

PL0005R

SE0005R

SE0014R

SE0020R

SI0008R

SK0002R

SK0004R

SK0006R

SK0007R

Cd wet dep

osition, g/km

2 Observed

Modelled

8955 44

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

BE0014

Observed

Modelled0

0.5

1

1.5

2

2.5

3

3.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2CZ0003

Observed

Modelled

0

0.5

1

1.5

2

2.5

3

3.5

4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

CZ0005Observed

Modelled

0

0.5

1

1.5

2

2.5

3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

DE0001Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

DE0002

Observed

Modelled

0

1

2

3

4

5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

DE0003Observed

Modelled

49

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2DE0007

Observed

Modelled

0

1

2

3

4

5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

DE0008Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

DE0009Observed

Modelled

0

2

4

6

8

10

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

DK0005Observed

Modelled

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

DK0008Observed

Modelled

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

DK0012

Observed

Modelled

0

0.5

1

1.5

2

2.5

3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

DK0022

Observed

Modelled

0

2

4

6

8

10

12

14

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd w

et dep

osition, g/km

2

EE0009Observed

Modelled

0

1

2

3

4

5

6

7

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

EE0011Observed

Modelled

0

5

10

15

20

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

ES0008Observed

Modelled

50

0

1

2

3

4

5

6

7

8

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2ES0009Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

FI0050Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

GB0006Observed

Modelled

0

0.5

1

1.5

2

2.5

3

3.5

4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

GB0013Observed

Modelled

0

0.5

1

1.5

2

2.5

3

3.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

GB0017Observed

Modelled

0

0.2

0.4

0.6

0.8

1Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

GB0048Observed

Modelled

0

0.5

1

1.5

2

2.5

3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

GB1055Observed

Modelled

0

0.5

1

1.5

2

2.5

3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

HU0002

Observed

Modelled

0

0.5

1

1.5

2

2.5

3

3.5

4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

IS0091Observed

Modelled

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

LV0010

Observed

Modelled

51

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2LV1000

Observed

Modelled

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

LV2000

Observed

Modelled

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

LV5000Observed

Modelled

0

0.5

1

1.5

2

2.5

3

3.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

LV6000Observed

Modelled

0

1

2

3

4

5

6

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Pb wet dep

osition

, g/km

2

NL0010Observed

Modelled

0

0.5

1

1.5

2Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

NL0091Observed

Modelled

0

1

2

3

4

5

6

7

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

NO0001Observed

Modelled

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

NO0039Observed

Modelled

0

0.5

1

1.5

2

2.5

3

3.5

4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

NO0056Observed

Modelled

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

PL0004Observed

Modelled

52

Fig. 4.8. Modelled and observed monthly wet deposition fluxes of Cd at the EMEP stations in 2018

0

2

4

6

8

10

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2PL0005Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

SE0005Observed

Modelled

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

SE0014Observed

Modelled

0

2

4

6

8

10

12

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

SE0020Observed

Modelled

0

1

2

3

4

5

6

7

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

SI0008Observed

Modelled

0

0.5

1

1.5

2

2.5

3Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

SK0002Observed

Modelled

0

0.5

1

1.5

2

2.5

3

3.5

4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

SK0004Observed

Modelled

0

0.5

1

1.5

2

2.5

3

3.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

SK0006Observed

Modelled

0

0.5

1

1.5

2

2.5

3

3.5

4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Cd wet dep

osition

, g/km

2

SK0007Observed

Modelled

53

4.3. Mercury


Table 4.5. Annual mean modelled and observed Hg air concentrations, ng/m3, temporal correlation coefficient (Rc) and relative bias (Bias) at EMEP stations in 2018

Station Name Code Longitude Latitude Observed Modelled R Bias Waldhof DE0002R 10.76 52.8 1.56 1.51 ‐0.53 ‐3.0 Schauinsland DE0003R 7.91 47.91 1.29 1.52 ‐0.58 17.1 Schmucke DE0008R 10.77 50.65 1.52 1.54 ‐0.42 1.4 Zingst DE0009R 12.72 54.44 1.49 1.58 ‐0.11 6.6 Pallas (Matorova) FI0036R 24.24 68 1.31 1.43 ‐0.1 9.8 Auchencorth Moss GB0048R ‐3.24 55.79 1.39 1.45 ‐0.59 4.9 Diabla Gora PL0005R 22.07 54.15 1.42 1.48 0.13 4.7 Bredkälen SE0005R 15.33 63.85 1.29 1.41 ‐0.23 9.2 Halla SE0020R 13.15 56.04 1.37 1.54 0.29 12.4

Fig. 4.9. Modelled and observed annual mean concentrations of Hg in air at the EMEP stations in 2018

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Hg air concen

trations, ng/m

3

Observed

Modelled

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov

Dec

Hg air con

centration

s, ng

/m3

DE0002

Obs

Mod

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg air co

ncen

trations, ng/m

3

DE0003

Obs

Mod

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg air co

ncen

trations, ng/m

3

DE0008

Obs

Mod

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg air co

ncen

trations, ng/m

3

DE0009

Obs

Mod

54

Fig. 4.10. Modelled and observed monthly mean concentrations of Hg in air at the EMEP stations in 2018

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg air co

ncen

trations, ng/m

3FI0036

Obs

Mod0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg air co

ncen

trations, ng/m

3

GB0048

Obs

Mod

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg air co

ncen

trations, ng/m

3

PL0005

Obs

Mod0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg air co

ncen

trations, ng/m

3

SE0005

Obs

Mod

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg air co

ncen

trations, ng/m

3

SE0020

Obs

Mod

55


Table 4.6. Annual sums of modelled and observed Hg wet deposition fluxes, g/km2/y, temporal correlation coefficient (Rc) and relative bias (Bias) at EMEP stations in 2018


Modelledflux

R Bias

Kosetice(NOAK) CZ0003R 15.08 49.57 6.63 10.95 0.54 65.23 Westerland DE0001R 8.31 54.93 3.16 6.69 0.84 112.10 Waldhof DE0002R 10.76 52.80 2.48 5.01 0.79 102.31 Schauinsland DE0003R 7.91 47.91 6.73 14.36 0.64 113.33 Schmucke DE0008R 10.77 50.65 5.91 9.87 0.77 67.10 Zingst DE0009R 12.72 54.44 2.42 4.38 0.69 80.63 Lahemaa EE0009R 25.90 59.50 4.38 3.86 0.55 ‐11.83 Niembro ES0008R ‐4.85 43.44 5.05 5.33 0.61 5.50 Pallas (Matorova) FI0036R 24.24 68.00 3.90 5.86 0.06 50.50 Yarner Wood GB0013R ‐3.71 50.60 4.25 8.33 0.55 95.98 Heigham Holmes GB0017R 1.62 52.72 6.08 6.11 0.24 0.51 Auchencorth Moss GB0048R ‐3.24 55.79 2.88 4.67 0.55 61.95 Chilbolton Observatory GB1055R ‐1.44 51.15 3.29 5.92 0.63 79.98 Rucava LV0010R 21.17 56.16 2.72 3.15 0.29 15.90 De Zilk NL0091R 4.50 52.30 5.15 5.77 0.85 11.96 Birkenes NO0001R 8.25 58.38 8.18 10.60 0.75 29.47 Diabla Gora PL005R 22.07 54.15 1.17 7.74 0.66 563.76 Bredkälen SE0005R 15.33 63.85 4.66 5.35 0.31 14.84 Råö SE0014R 11.91 57.39 5.20 6.09 0.74 17.11 Hallahus SE0020R 13.15 56.04 7.55 4.82 ‐0.02 ‐36.18 Iskrba SI008R 14.87 45.57 4.58 13.60 0.50 197.31

Fig. 4.11. Modelled and observed annual wet deposition fluxes of Hg at the EMEP stations in 2018

0

2

4

6

8

10

12

14

16

Hg wet dep

osition, g/km

2 Observed

Modelled

56

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2CZ0003

Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

DE0001Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

DE0002

Observed

Modelled

0

0.5

1

1.5

2

2.5

3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

DE0003

Observed

Modelled

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition

, g/km

2

DE0008Observed

Modelled

0

0.2

0.4

0.6

0.8

1Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition

, g/km

2

DE0009Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

EE0009Observed

Modelled

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

ES0008Observed

Modelled

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

FI0036

Observed

Modelled

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

GB0013

Observed

Modelled

57

0

0.5

1

1.5

2

2.5

3

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2GB0017

Observed

Modelled

0

0.2

0.4

0.6

0.8

1

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

GB0048Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

GB1055Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

LV0010Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition

, g/km

2

NL0091Observed

Modelled

0

0.5

1

1.5

2

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition

, g/km

2

NO0001Observed

Modelled

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

PL0005Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

SE0005Observed

Modelled

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

SE0014Observed

Modelled

0

0.5

1

1.5

2

2.5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2

SE0020Observed

Modelled

58

Fig. 4.14. Modelled and observed monthly wet deposition fluxes of Hg at the EMEP stations in 2018

0

1

2

3

4

5

Jan

Feb

Mar Apr

May Jun Jul

Aug

Sep

Oct

Nov Dec

Hg wet dep

osition, g/km

2SI0008Observed

Modelled

5. POL

5.1. Le

a

Fig. 5.

LLUTION O

ead

c

e

.1. Lead atmo

OF MARGI

ospheric input

NAL SEAS

to the Baltic (

59

S

b

(a), Black (b),

b

b

Caspian (c), NNorth (d) and Mediterranea

an (d) Seas

5.2. Ca

a

Fig. 5.2. C

admium

c

e

Cadmium atmmospheric inpu

ut to the Baltic

60

c (a), Black (b)

b

d

), Caspian (c), North (d) andd Mediterrane

ean (d) Seas

5.3. M

a

Fig. 5.3. M

ercury

c

e

Mercury atmoospheric input

t to the Baltic

61

(a), Black (b),

b

d

Caspian (c), NNorth (d) and Mediterranea

an (d) Seas

62

6. ECOSYSTEM‐SPECIFIC DEPOSITION

Table 6.1. Classification of land‐cover types used for modelling of ecosystem‐dependent deposition [Strahler et al, 1999]

Land‐cover type DescriptionEvergreen Needleleaf Forests

Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees remain green all year. Canopy is never without green foliage.

Evergreen Broadleaf Forests

Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Almost all trees and shrubs remain green year round. Canopy is never without green foliage.

Deciduous Needleleaf Forests

Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of seasonal needleleaf tree communities with an annual cycle of leaf‐on and leaf‐off periods.

Deciduous Broadleaf Forests

Lands dominated by woody vegetation with a percent cover >60% and height exceeding 2 meters. Consists of broadleaf tree communities with an annual cycle of leaf‐on and leaf‐off periods.

Mixed Forests Lands dominated by trees with a percent cover >60% and height exceeding 2 meters. Consists of tree communities with interspersed mixtures or mosaics of the other four forest types. None of the forest types exceeds 60% of landscape.

Closed Shrublands Lands with woody vegetation less than 2 meters tall and with shrub canopy cover >60%. The shrub foliage can be either evergreen or deciduous.

Open Shrublands Lands with woody vegetation less than 2 meters tall and with shrub canopy cover between 10‐60%. The shrub foliage can be either evergreen or deciduous.

Woody Savannas Lands with herbaceous and other understory systems, and with forest canopy cover between 30‐60%. The forest cover height exceeds 2 meters.

Savannas Lands with herbaceous and other understory systems, and with forest canopy cover between 10‐30%. The forest cover height exceeds 2 meters.

Grasslands Lands with herbaceous types of cover. Tree and shrub cover is less than 10%. Permanent Wetlands

Lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water.

Croplands Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type.

Urban and Built‐Up Lands

Land covered by buildings and other man‐made structures.

Cropland/Natural Vegetation Mosaics

Lands with a mosaic of croplands, forests, shrubland, and grasslands in which no one component comprises more than 60% of the landscape.

Snow and Ice Lands under snow/ice cover throughout the year.

Barren Lands with exposed soil, sand, rocks, or snow and never has more than 10% vegetated cover during any time of the year.

Water Bodies Oceans, seas, lakes, reservoirs, and rivers. Can be either fresh or salt‐water bodies.

6.1. Le

Fig. 6.1. Abuilt‐up l

Fig. 6.3. Asavannas

Fig. 6.5. Ashrubland

ead

Annual total dands in the EM

Annual total ds in the EMEP

Annual total dds in the EME

deposition of PMEP region in

deposition of Pregion in 201

deposition of PEP region in 20

Pb on urban a 2018, kg/km2

Pb on woody 8, kg/km2/y

Pb on open 018, kg/km2/y

63

and 2/y

Figin t

Figthe

y Figthe

. 6.2. Annual the EMEP regi

. 6.4. Annual e EMEP region


total depositioion in 2018, kg

total deposition in 2018, kg/k


on of Pb on wg/km2/y

on of Pb on sakm2/y

on of Pb on grkm2/y

water bodies

avannas in

rasslands in

Fig. 6.7. Acropland/region in

Fig. 6.9. Aneedlelea

Fig. 6.11.broadleaf

Annual total d/natural vege2018, kg/km2

Annual total daf forests in th

. Annual total f forests in the

deposition of Petation mosaic2/y

deposition of Phe EMEP regio

l deposition ofe EMEP region

Pb on cs in the EMEP

Pb on evergreon in 2018, kg/

f Pb on decidun in 2018, kg/

64

P Figthe

een /km2/y

Figin t

uous /km2/y


. 6.10. Annuathe EMEP regi


l total deposition in 2018, kg

on of Pb on crkm2/y

tion of Pb on mg/km2/y

roplands in

mixed forests

6.2. Ca

Fig. 6.12.built‐up l

Fig. 6.14.savannas

Fig. 6.16.shrubland

admium

. Annual total ands in the EM

. Annual total s in the EMEP

. Annual total ds in the EME

l deposition ofMEP region in

l deposition ofregion in 201

l deposition ofEP region in 20

f Cd on urban 2018, g/km2/

f Cd on woody8, g/km2/y

f Cd on open 018, g/km2/y

65

and /y

Figin t

y Figthe

Figthe


. 6.15. Annuae EMEP region


l total deposition in 2018, g/

l total depositn in 2018, g/km


tion of Cd on w/km2/y

tion of Cd on sm2/y

tion of Cd on gm2/y

water bodies

savannas in

grasslands in

Fig. 6.18.cropland/region in

Fig. 6.20.needlelea

Fig. 6.22.broadleaf

. Annual total /natural vege2018, g/km2/

. Annual total af forests in th


l deposition ofetation mosaic/y

l deposition ofhe EMEP regio


f Cd on cs in the EMEP

f Cd on evergron in 2018, g/k

f Cd on decidun in 2018, g/k

66

P Figthe

reen /km2/y

Figin t

uous km2/y





tion of Cd on cm2/y

tion of Cd on m/km2/y

croplands in

mixed forests

6.3. M

Fig. 6.23.built‐up l

Fig. 6.25.savannas

Fig. 6.27.shrubland

ercury

. Annual total ands in the EM

. Annual total s in the EMEP

. Annual total ds in the EME

l deposition ofMEP region in

l deposition ofregion in 201

l deposition ofEP region in 20

f Hg on urban 2018, g/km2/

f Hg on woody8, g/km2/y

f Hg on open 018, g/km2/y

67

and /y

Figin t

y Figthe

Figthe







tion of Hg on /km2/y

tion of Hg on m2/y

tion of Hg on m2/y

water bodies

savannas in

grasslands in

Fig. 6.29.cropland/region in

Fig. 6.31.needlelea

Fig. 6.33.broadleaf

. Annual total /natural vege2018, g/km2/

. Annual total af forests in th


l deposition ofetation mosaic/y

l deposition ofhe EMEP regio


f Hg on cs in the EMEP

f Hg on evergron in 2018, g/k

f Hg on decidun in 2018, g/k

68

P Figthe

reen /km2/y

Figin t

uous km2/y





tion of Hg on m2/y

tion of Hg on /km2/y

croplands in

mixed forestss

Documents

New Assessment of transboundary pollution by toxic substances: …en.msceast.org/reports/1_2020_datrep.pdf · 2020. 7. 21. · MSC‐E Data Report 1/2020 July 2020 Assessment of transboundary