FFrom experience of rom experience of emission emission inventory inventory preparation preparation

inin Belarus Belarus

JOINT ACCENT/GEIA Workshop on Anthropogenic emissions for non-OECD countries in global inventories

8-10 February 2006, IIASA, Laxenburg, Austria

Sergey KakarekaInstitute for Problems of Natural Resources Use & Ecology

Minsk, Belarus

Issues considered

1. State emission inventory system in Belarus: main features

2. Emission inventory for EMEP in Belarus

3. Regional inventory: experts estimates

4. Connections between inventories: national and RAINS

5. Sources of uncertainty and prioritizing

Institutional arrangements of state emission inventory in Belarus

Emission inventory system in Belarus is based on annual

statistical reporting of enterprises. Primary reporting forms are

summarized by regional offices of the Ministry on Statistics

and Analysis.

Main office of the Ministry on Statistics and Analysis

generalize reports of the regional offices and produce annual

report on air protection in the split of regions, branches of

economy, cities and ministries.

The data on emissions in annual reports includes data on

emission of main pollutants (SO2, CO, NOx, hydrocarbons and

VOC) and specific pollutants (more than 70).

Data on emission of the main pollutants is given divided into

emission from fuel combustion and emission from

technological and other processes.

Additional information in the annual report: number of reported

enterprises, number of sources of emission, level of

abatement etc.

Annual emission reporting system summarizes data from

more than 2000 enterprises; it is assumed that they represent

about 95% of total emission.

Specific features of state emission inventory system in Belarus

- Emissions in national statistics are summarized according to

branches classification scheme (so-called OKONH) which did

not coincide with SNAP and NFR classification schemes.

Additional information is necessary for distribution of emission.

- Mobile sources emission are not reported. They are estimated

by the consumption of fuel on the national and region levels.

- Domestic sources (for instance, heating) are not taken into

account.

- Agriculture sources (collective farms, agricultural activities on the whole) are not taken into account in a regular way.

- Waste management and disposal are not accounted

regularly (except CH4 in GHG inventory and waste

incineration).

- Solvents and paints application generally are not considered

except industrial activities.

- There are no information on emission of some pollutants (all

POPs, HM – mercury, Zn, Se, PM10 and PM2.5)

EMEP emission inventory

EMEP inventory report is prepared using the following

methodology:

1. Emission data on pollutants which sources are rather

completely covered by statistics

This data was distributed by SNAP and NFR classification

schemes and reported as-is (main pollutants – SOx, NOx,

CO). VOC emission data was also prepared by this approach.

2. Emission data on pollutants some sources of which are not

covered by national statistics (NH3, TSP, heavy metals)

For these sources emissions were calculated by the simplest

approach (using emission factors) and these values were

incorporated in common reporting table together with statistical

information.

3. Emission data for pollutants for which there are no any

information in statistics (all POPs)

For these pollutants emissions were calculated by simplest

approach using emission factors and included into the report.

Initial statistical data for emission calculation

Data of the Ministry on Statistics and Analysis, data of the

Ministry on Natural Resources and Environmental Protection,

Ministry on Emergency and some others are used for

emission assessment.

Emission factors are taken from the Atmospheric Emission

Inventory Guidebook (2002) and by results of own emission

sources testing as a contribution to EMEP (Belarusian

contribution to EMEP 1996-2004) – for heavy metals and POPs.

Parallels between national and SNAP (NFR) sources classifications Emission report on the Ministry on Statistics and Analysis gives main pollutants distributed by fuel combustion emission and technological process emissions. This makes possible to reclassify emissions into SNAP and NFR formats using the following aggregation;- category “combustion in energy production and transformation” was considered as equivalent of the SNAP sector 1;- category “sold to population” – as category SNAP 0202;- category “combustion in residential and communal sector” – as category SNAP 0201;- category “used for transport” – as analogous of the sector 07+08;- difference between “used directly as fuel” and sum of “combustion in residential-communal sector” and “used for transport” – as SNAP 0301.

Emission report of Belarus: 2002 sampleTABLE IV 1A: National sector emissions: Main pollutants, particulate matter and heavy metalsVersion 2002-1

COUNTRY: BY (as ISO2 code)DATE: 29.01.2004 (as DD.MM.YYYY)YEAR: 2002 (as YYYY, year of Emmissions)

Nox CO NMVOC Sox NH3 TSP PM10PM2.5 Pb Cd Hg

Gg NO2 Gg Gg Gg SO2 Gg Mg Mg Mg Mg Mg Mg

1 A 1 a (a) 1 A 1 a Public Electricity and Heat Production 29,11 4,56 0,28 27,18 0,01 155,0 NE NE 2,18 0,11 0,13

1 A 1 b (a) 1 A 1 b Petroleum refining 0,495 0,27 0,00 0,53 0,00 0,0 NE NE NE NE NE

1 A 1 c (a) 1 A 1 c Manufacture of Solid Fuels and Other Energy Industries 0,32 1,14 0,00 0,48 0,00 0,0 NE NE NE NE NE

1 A 2 (a) 1 A 2 Manufacturing Industries and Construction

A10,94 28,4 0,38 20,29 0,00 10627,0 NE NE 22,60 0,83 0,40

1 A 3 a ii (i) 1 A 3 a ii Civil Aviation (Domestic, LTO) IE IE IE IE IE IE NE NE IE IE IE

1 A 3 a ii (ii) 1 A 3 a ii Civil Aviation (Domestic, Cruise)IE IE IE IE IE IE NE NE IE IE IE

1 A 3 b (a) 1 A 3 b Road Transportation A 82,1 35,2 166,4 35,20 0,01 25500,0 NE NE 1,07 0,01 0,00

1 A 3 c (a) 1 A 3 c Railways IE IE IE IE IE IE NE NE IE IE IE

1 A 3 d ii 1 A 3 d ii National Navigation IE IE IE IE IE IE NE NE IE IE IE

1 A 3 e (a) 1 A 3 e Other (Please specify in a covering note)

ANE NE NE NE NE NE NE NE NE NE NE

1 A 4 a (a) 1 A 4 a Commercial / Institutional 5,02 20,4 0,62 16,981 0,01 6731,0 NE NE 0,24 0,02 0,02

NFR sectors to be reported to CLRTAP

A =

Allo

wabl

e Ag

greg

atio

n

Yearly minimum reportingMain Pollutants Particulate matter Priority metals

An assessment of completeness of EMEP inventory

According to guidelines as missing the sources reported as NE are

considered.

 1 A 4 b Residential - SO2, Nox, CO, NMVOC PM, POPs and HM

emissions were calculated.

3 A PAINT APPLICATION - Important for NMVOC

3 B DEGREASING AND DRY CLEANING - Important for NMVOC

4 B MANURE MANAGEMENT (c) - All Except NH3

4 D AGRICULTURAL SOILS - most

4 F FIELD BURNING OF AGRICULTURAL WASTES – most

5 B FOREST AND GRASSLAND CONVERSION – All Important for

GHG only

6 A SOLID WASTE DISPOSAL ON LAND – All

6 B WASTE-WATER HANDLING - Maybe can be shown as

IE: this sector emission can’t be extracted from tota

Greatest missing sources in emission inventory are in sectors

1A4b (Residential – some subsectors), 3A (Paint application),

3B (Degreasing and dry cleaning), 4D (Agricultural soils).

 

Main contribution of missed emission sources for main

pollutants are expected into NMVOC. Some missing are also

into PM, SO2, NOx and CO.

Expert emission estimates: regional emission inventory

Here is an example of expert estimates of emission of certain pollutants for improvement of data completeness (INTAS project ).

Pollutants: key heavy metals (mercury, lead, cadmium).

Base years: 1990, 1995, 1997.

Region: 12 Former Soviet Union countries

Emission estimation domain

Methodology and procedure

Methodology of emission estimation was based on emission factors and production statistics application.

Heavy metals emission statistics for NIS especially for Central Asia is very scarce. Only lead data can be found. Emission from vehicles and sometimes from non-ferrous industry are estimated. Obtaining of full information on production and usage statistics is troubled by statistics imperfection in the NIS countries. For instance, there is a scarce information on leaded gasoline usage.

Spatial types of emitters

Area sources

Stationary fuel combustion, mobile sources, some ferrous industry processes (gray iron foundries, electric steel plants), mineral products industry, most of chemical products industries, some others have been considered as area sources.

Administrative regions (provinces or the whole small countries, capitals and some large cities were considered as elemental units of area sources. Area sources emissions were distributed according to density of population (rural and urban).

Large point sources

Ferrous and non-ferrous works, and some others (SNAP 010406, 030203, 030301, 030304, 030305, 030306, 030307, 030308, 040205, 040206, 040301, 040413) are considered as point sources of HM emission.

Additional information for this category was gathered in order to obtain more precise estimates of emissions and their spatial distribution

Some resultsLead emission

Annual anthropogenic lead emissions were decreased in the

countries of the FSU from 24903.0 tonnes in 1990 up to 9652.5

tonnes in 1997).

Share of European NIS in total lead emission of the NIS

decreased from 19% in 1990 to 12% in 1997. Share of Russia

was rather stable within 53-55%, share of Central Asia NIS

increased from 24% to 32%.

Greater contributions among the source categories were fulfilled

by road traffic due to use of leaded gasoline (48% in 1990 and

26% in 1997) and production of non-ferrous metals (30% in 1990

and 50% in 1997).

Lead emission in the NIS by sectors

1990

1997

Road & other transport

48%

Non-ferrous metals indus try

30%

Others5%

Ferrous metals indus try

17%

Road & other transport

26%

Fe rrous metals industry

19%

Non-fe rrous metals industry

50%

Othe rs5%

Lead emission in 1995 by 1x1 degree grid, tonnes

Trends in spatial structure of lead emission in European NIS

Differences between current and previous estimates of

anthropogenic lead emissions are mainly within 30-70% for

European NIS although presented data for the Ukraine are 2.6

times lower for 1995 and 1997 than ones mined from other

sources. The results of presented estimates for Central Asia NIS

(Kazakhstan and Uzbekistan) are significantly higher than data

prepared by national experts (World Bank, 1998). This differences

are appeared due to the fact, that non-ferrous metal industry

rather developed in these countries was not almost taken into

consideration in that document because road transport was

ultimately considered as the most important lead emission source

with correspondent inputs of 62-72% in Kazakhstan and 86-95%

in Uzbekistan.

Comparison of lead emission estimates for 1997

Comparison of lead emission estimates for 1997

0

20

40

60

80

100

120

140

160

tonn

Aze rba ijan Armenia Georgia Moldova

EMEP da taba se Current estimate

0

500

1000

1500

2000

2500

3000

3500

4000

tonn

Russia Ukra ine

EMEP da tabase Current estimate

RAINS analysis and application

RAINS analysis was performed to test its applicability for PM emission inventory for Belarus.

Were checked:

- fuel totals and distribution of fuels by sectors;

- distribution of fuels by type of installations;

- activity projection;

- control options and types of abatement used;

- PM emission factors.

1. Fuel balanceShare of solid and liquid fuels seems overestimated

2. Shares of fuels consumption by sectors

Generally share of small combustion is underestimated and

share of power generation is overestimated.

3. Shares of fuel consumption by type of installation.

Some approaches and routines were elaborated for estimation

of the share of stoves, fireplaces, small and medium boilers etc.

in residential sector. Generally share of grate firing and stoves

is underestimated. 

3.Level and types of abatement installation used for fuel

combustion

Generally RAINS is based on analysis of West Europe situation

with abatement and control options and levels of abatements

used for Belarus are too high.

 

4. Emission factors

The analysis of emission factors is in progress because no PM

speciated emission factors available for Belarus.

Comparison of TSP estimates for Belarus, ktonnes

Source category 1990 1995 2000

RAINS National RAINS National RAINS National

Stationary 226.9 132.1 122.4 50.9 111.1 38.0

Mobile 17.2 52.6 13.0 41.1 14.2 26.5

Total 244.1 184.7 136.6 92.0 125.3 64.5

SNAP source categoryRAINS

2000Statistics

(2002 )

Combustion in energy and transformation industries 20 0.16

Non industrial combustion plants 23.63 15.0+(13.5)

Combustion in manufacturing industry 10.66

10.63

Production processes 20.05 14.92

Extraction and distribution of fossil fuels 3.66 3.03

Road transport 8.55 25.50

Other mobile sources and machinery 5.63

Waste treatment and disposal 9.55

Agriculture 23.62 (8.0)

Total 125.34 69.3+(21.5)

Comparison of TSP estimates for Belarus, ktonnes

For future discussion:Sources of uncertainty in international emission

inventoriesInternational inventories generally contains not emissions but

statistical data (projections) and EF (technologies parametrization).

So uncertainties result from quality of last datasets.

Statistical datasets

- quality of international statistics is unequal for different years;

- generally out of date in comparison with national.

Emission factors and their parametrization

- type of abatement and its efficiency,

- distribution of installations by type etc.

Prioritizing in emission inventories

- high accuracy of estimates (to estimate only reliable sources with

good emission ) or completeness (to estimate all sources)?

- good national totals (main attention to priority sectors) or good

sector estimates?

- accurate estimates for certain years or reliable estimates (same

quality) for a raw of years (to detect trends)?

- hard common format or listing of distinct sources?

- common format for all pollutants or distinct source;

- requirements to spatial distribution?

In general how to measure quality of inventories (intercomparison?)