1. EMEP Case study: Assessment of HM pollution levels with fine spatial resolution in Belarus, Poland and UK
Ilia Ilyin, Olga Rozovskaya, Oleg Travnikov
Meteorological Synthesizing Centre - East

2. Country-scale pollution assessment
Case studies of HM pollution in selected EMEP countries
Netherlands
Approach:
Evaluation of pollution levels in a country with fine spatial resolution involving variety of national data
Czech Republic
Requirements:
Detailed emissions data (fine resolution, source categories, LPS)
Additional measurements from national monitoring networks
Participation of national experts in joint analysis of the results
Croatia
Belarus
Countries involved:
Country
Czech Rep
Croatia
Netherlands
Belarus
Poland
U.K.
Status
complete
in progress

3. Case study for Belarus (Pb, 2012)
Purpose:
Investigate changes in the model performance due to transfer from coarse to fine resolution
Provide the country with data on lead pollution levels with fine spatial resolution
Calculation of boundary concentrations for country-scale modelling domain
Official EMEP emission data used
0.1 1 10 50
Berezinskiy
Reserve (Belarus)
Pb air conc.
Model, ng/m 3
Observed, ng/m
Pb in air, 2012
EMEP domain
~ 40 stations
Factor of 2
Factor of 3
ng/m3
50x50 km2
- obs. sites
The model reasonably well reproduces Pb pollution in the EMEP region, keeping in mind existing uncertainties (EMEP/MSC-E status report 2014)

4. Emission data involved in the study
EMEP emission (CEIP) 50x50 km2
National data 10x10 km2
kg/km2/y
National emissions:
High-resolution totals
Gridded sector data
Large Point Sources
kg/km2/y
Total in Belarus: 68 t (2012)
Total in Belarus: 8.3 t
This value used in calculations

5. Monitoring data in modelling domain (Pb, 2012)
Berezinskiy Reserve (Belarus)
Monitoring data (conc. in air)
1 EMEP station in Poland (Diabla Gora, PL5)
1 background site (Berezinsky Reserve, Belarus)
5 background urban sites in Poland (EU AirBase data)
19 urban stations (Belarus)
BY urban stations (national experts)
Berezinskiy reserve (national experts)
EMEP station (CCC)
PL stations (AirBase)

6. Model output for Belarus with fine spatial resolution
Pollution levels with fine (10x10 km2) resolution
Source-receptor relationships for the country and its regions
Pollution from particular emission sectors
Contamination from particular LPS
Pollution of cities
Poland
52%
Slovakia 3%
Remaining
22%
Belarus 6%
Germany
Italy
Ukraine
11%

7. Concentrations in air (Pb, 2012)
Analysis of simulated pollution levels in the modelling domain (10x10 km2)
Diabla Gora
(EMEP site,PL5)
Berezinskiy Reserve (Belarus)
Urban sites, Poland
Concentrations in air (Pb, 2012)
Factor of 2
Factor of 3

8. Seasonal variations of modelled and observed air concentrations
EMEP station
(Belarus)
Berezinskiy Reserve – reference station for further analysis

9. Analysis of uncertainties
Three sources of uncertainties: 1) Measurements
2) Model
3) Emission data
Uncertainties of monitoring data
Data Quality Objectives for HM analytical methods:
±15-25% from expected (theoretical) value
Monitoring uncertainty of ‘Berezinskiy Reserve’ is unknown
Pb air conc. in 2012 (EMEP data)
Participation of national laboratory in intercomparison of analytical methods coordinated by CCC is appreciated
Air conc. in ‘Berezinskiy Reserve‘ are comparable with those in other parts of the EMEP region

10. Uncertainty of the model
Intrinsic model uncertainty
(without effect of emission)
Sensitivity coefficient
Intrinsic model uncertainty is ±30-40% for concentrations and deposition
Reference: Travnikov O. and I.Ilyin [2005], EMEP/MSC-E Report 6/2005

11. Uncertainties of the emission data
Average Pb emission flux
Emission in Belarus: national (8.3 t/y )
kg/km2/y
Observed urban Pb concentrations
Pb emissions in 2012
Pb emissions in 2012 and urban obs. sites
Observed air conc. in BY and other countries are comparable
Emission fluxes differ markedly

12. Emission sectors in Belarus and neighbouring countries (Pb, 2012)
Belarus (national data)
Latvia 6%
Poland
25%
75%
21% 4%
43% 2% 3% 6%
66%
19%
30%
Non-Industrial Combustion
Industry
Road transport
Other

13. Non-Industrial Combustion
Pb emissions from ‘Road Transport’ and ‘Non-industrial combustion’ sectors
Pb emission fluxes in 2012 in the EMEP region
Road Transport
Non-Industrial Combustion
Belarus:
Data from national experts
Other countries: CEIP

14. Spatial distribution in BY
Sensitivity study of modelled air concentrations at ‘Berezinskiy Reserve’ to emission
Model run
Emission in BY, t
Spatial distribution in BY
Base-case
8.3
10x10 km2 (as in national data)
Total value provided by national experts
Bias,%
-66
0.0
0.5
1.0
1.5
2.0
2.5
Obs.
Base Case
Air concentrations, ng/m 3
Modelled
Observed

15. Emission data for Belarus (68 t/y) is used
Scenario 1
Emission data for Belarus (68 t/y) is used
Spatial distribution of emissions: as in the national data in Belarus

16. Air concentrations, ng/m
Sensitivity study of modelled air concentrations at ‘Berezinskiy Reserve’ to emission
Model run
Emission in BY, t
Spatial distribution in BY
Base-case
8.3
10x10 km2 (as in national data)
Scenario #1 68
The same as officially reported value for 2012
Bias,%
-66
-56
0.0
0.5
1.0
1.5
2.0
2.5
Obs.
Base Case
Scenario #1
Air concentrations, ng/m 3
significant bias still remains
Modelled
Observed

17. Scenario 2 Purpose: Approach:
Fitting of modelled and observed air concentrations at station ‘Berezinskiy Reserve’
The aim is NOT to revise national emission data!
Approach:
Per capita Pb emission in 2012 in sectors ‘Non-Industrial Combustion’ and ‘Road Transport’
Emissions in sectors ‘Non-Industrial Combustion’ and ‘Road Transport’ are increased proportional to population density. Spatial distribution of emissions changed. 1 2 3 4
Poland
Slovakia
Latvia
Lithuania
Hungary
Czech Rep.
Germany
EMEP mean
Ukraine
Belarus
Russia
Pb emission, t per
million of people
Non-industrial Combustion
Road Transport
Total emission in Belarus changed from 8.3 to 137 t/y
The change of emissions took place only in Belarus, Ukraine and Russia

18. National emissions (8.3 t)
Spatial distribution of national and scenario emissions (Pb, 10x10 km2)
National emissions (8.3 t)
(Base-case run)
Scenario emissions (137 t) LV LV LT LT PL PL BY BY
kg/km2/y RU RU UA UA

19. Air concentrations, ng/m
Sensitivity study of modelled air concentrations at ‘Berezinskiy Reserve’ to emission
Model run
Emission in BY, t
Spatial distribution in BY
Base-case
8.3
10x10 km2 (as in national data)
Scenario #1 68
Bias,%
-66
-56
0.0
0.5
1.0
1.5
2.0
2.5
Obs.
Base Case
Scenario #1
Scenario #2
Air concentrations, ng/m 3
Modelled
Observed

20. Air concentrations, ng/m
Sensitivity study of modelled air concentrations at ‘Berezinskiy Reserve’ to emission
Model run
Emission in BY, t
Spatial distribution in BY
Base-case
8.3
10x10 km2 (as in national data)
Scenario #1 68
Scenario #2
137
10x10 km2 (Scenario)
Bias,%
-66
-56 -1
0.0
0.5
1.0
1.5
2.0
2.5
Obs.
Base Case
Scenario #1
Scenario #2
Air concentrations, ng/m 3
Joint efforts of the EMEP Centres, and national experts and TFEIP are needed for further analysis of emission data in EECCA countries
Modelled
Observed

21. Model output for Belarus with fine spatial resolution:
base-case vs. scenario #2
Air concentration of lead in 2012
Base-Case
Scenario #2
Emissions assumed in Scenario #2 led to significant increase of calculated pollution levels in Belarus

22. Conclusions and recommendations
Assessment of pollution level assessment for Belarus with fine spatial resolution was done. The country was provided with detailed country-specific information with fine (10x10 km2) resolution.
Analysis of the available national emission data shows that Pb emissions in Belarus and in neighbouring EECCA countries from sectors ‘Non-Industrial Combustion’ and ‘Road Transport’ are likely underestimated. Therefore, calculated lead pollution levels in Belarus may be underpredicted.
Model sensitivity study demonstrates that the modelled Pb pollution levels are sensitive not only to emission total values in countries but also to their spatial distribution.
The suggested emission scenario led to improvement of modelling results compared to observed levels. However, joint efforts of the EMEP Centres, national experts and TFEIP are needed for further analysis of emission data in the EECCA countries.

23. Conclusions and recommendations (cont.)
Evaluation of quality of measurement data in Belarus under supervision of CCC is appreciated.
Pollution levels in Belarus are strongly affected by emission sources in neighbouring countries. To better understand origin of pollution in Belarus, similar studies in other neighbouring countries (PL, UA, RU) would be helpful.
Similar case studies of pollution level assessment in Belarus could be carried out for other pollutants (e.g., for particulate matter). It could be useful to better understand peculiarities of atmospheric pollution in Belarus.

24. Pollution assessment for Poland (Cd) (in progress)
Purpose: Evaluate Cd pollution levels in Poland with fine spatial resolution (10x10 km2)
Emissions of Cd from point sources in 2012, kg/y
Available data:
Point-source emissions of Cd (provided by Poland)
- Power stations
- Production of coke
- Copper smelting
- Production of cement
Area sources (to be derived from EMEP data)
Cd total deposition from point sources
Monitoring data
- EMEP data
- AirBase
Modelling under preparation

25. Simulation of HM levels over the U. K
Simulation of HM levels over the U.K. (Centre of Ecology and Hydrology) with fine spatial resolution (preliminary results)
Main purposes:
Simulate Pb pollution levels with fine spatial resolution (10x10 km)
Compare modelling results of MSC-E and national FRAME model
Evaluate a role of wind re-suspension in HM levels in the U.K.
National data:
Emissions (1x1 km)
- Source categories
- Point sources
Monitoring data
- Air concentrations (32 sites)
- Wet deposition (8 sites)
Concentrations in soil
Pb total deposition in 2012 (10x10 km2)
More details: in the next presentation by Massimo Vienno

26. Thank you for attention!

27. Uncertainties of the emission data
Pb emission flux
kg/km2/y
Pb total emissions in 2012