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E mission E stimation of Solid Waste Disposal Sites According to - - PowerPoint PPT Presentation

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007 E mission E stimation of Solid Waste Disposal Sites According to the Uncertainty Analysis Methodology Janka Szemesov Slovak

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SLIDE 1

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

E mission E stimation of Solid Waste Disposal Sites According to the Uncertainty Analysis Methodology

Janka Szemesová Slovak Hydrometeorological Institute, Bratislava Martin Gera Faculty of Mathematics Physics and Informatics, Comenius University

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SLIDE 2

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Topics (1)

UNFCCC and KP Position of the SR National Inventory System Emission Trends (1990-2005) Key Categories 1990 - 2005 Sector Waste Overview

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SLIDE 3

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Topics (2)

Uncertainty Computation Monte Carlo Methods Initialisation of First Order Decay Model Data Sensitivity Results Conclusions

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SLIDE 4

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

UNFCCC and KP Position of the SR(1)

UN Framework Convention on Climate Change -

1992

SR: 1994, succession (after split of Czechoslovakia in

1993)

Annex I country of UNFCCC (developed countries)

Kyoto Protocol to the FCCC – 1997

SR: Signature 1998, Ratification 31 May, 2002 In force 16 February 2005 Annex B country of KP (reduction commitment 8%,

base year 1990) Not part of EU burden sharing agreement

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

UNFCCC and KP Position of the SR(2)

GHG emission trends compared with the Kyoto target (%)

92.0 40 60 80 100 120 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2008 2010 2012 Kyoto target CO2 emissions CH4 emissions N2O emissions

  • Aggreg. GHGs

emissions

■ Reduction Target Commitment 2008-2012 – 8%

Total reduction in 2005 – 34% (excluding LULUCF) 33% (including LULUCF)

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

UNFCCC and KP Position of the SR(3)

GHG emission trends with projections until 2010 (%) from Biennial Report 2007

■ Total GHGs in 1990 – 72,1 Mt (excluding LULUCF) ■ Total GHGs in 2005 – 47,9 Mt (excluding LULUCF)

60 65 70 75 80 85 90 95 100 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2008 2010 Total GHG Without Measures With Measures With Other Measures

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

National Inventory System SR (1)

  • In the line with IPCC GPG 2000, SR as Annex I country

National Inventory System was establish!

  • Single National Entity = Slovak Hydromet. Institute - according

to Act 478/2002, Art. 5 par. 7, Art. 7, par. 1) – Act on Air

  • Officially published in Vestnik MZP SR /No 3/2007
  • compilation of National Inventory Report,
  • compilation of emission inventory in CRFReporter,
  • inventory planning, preparation, management and archiving
  • QA/QC plan
  • ensure TCCCA as high quality as possible
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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Management of the NIS by the national

circumstances

  • DECENTRALIZED - sectoral experts make decisions

about methodology, activity data, uncertainty...,

  • OUT-SOURCED - research and academic institutions,

private companies, individual experts on contract basis...,

  • SINGLE AGENCY - Slovak Hydrometeorological Institute,

Department of Emissions

  • INTEGRATED - emission inventory of all pollutants

(GHGs, Basic & Other pollutants, Projections)

National Inventory System SR (2)

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

National Inventory System SR (3)

Official web page: www.ghg-inventory.gov.sk

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

National Inventory System SR (4)

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SLIDE 11

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

E mission Trends (1990-2005)

  • Total aggregated emissions by sectors:
  • Energy – 80% -36%
  • Industrial Processes – 8% +3%
  • Solvent Use – <1 NA
  • Agriculture – 8% -54%
  • Waste – 4% +40%
  • 20,000

20,000 40,000 60,000 80,000 1 9 9 1 9 9 1 1 9 9 2 1 9 9 3 1 9 9 4 1 9 9 5 1 9 9 6 1 9 9 7 1 9 9 8 1 9 9 9 2 2 1 2 2 2 3 2 4 2 5 CO2 eq. (Gg) Agriculture Waste LULUCF Solvent Use Industry Energy

The aggregated emissions of greenhouse gases by sectors in 1990-2005

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SLIDE 12

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Key Categories 2005 (1)

IPCC Source Categories Direct GHG Base Year Estimate (1990) Current Year Estimate (2005) Level Assesment Cumulative Total of Column E 1.A.2 Manufacturing Industries and Construction CO2 23,998.4378 12,253.7231 25.5999 25.5999 1.A.1 Energy Industries CO2 15,654.1783 11,274.9680 23.5551 49.1550 1.A.3.b Transport - Road Transportation CO2 4,500.9371 6,095.0000 12.7334 61.8884 1.A.4 Other sector CO2 10,520.3514 4,845.1305 10.1222 72.0106 4.D Agricultural Soils N2O 3,582.1515 1,688.8445 3.5283 75.5389 1.A.5.a Other non-specified CO2 1,679.0780 1,430.9723 2.9895 78.5284 2(I).B.2 Nitric Acid Production N2O 1,167.3050 1,254.3279 2.6205 81.1489 6.A Solid Waste Disposal on Land CH4 469.7700 1,249.9200 2.6113 83.7601 2(I).A.1 Cement Production CO2 1,438.0088 1,233.5090 2.5770 86.3371 4.A Enteric Fermentation CH4 1,990.1616 943.0329 1.9701 88.3073 6.B Wastewater Handling CH4 1,012.0541 686.3084 1.4338 89.7411 2(I).A.2 Lime Production CO2 770.4160 677.1150 1.4146 91.1557 1.B.1.b Fugitive Emission from Oil, Natural Gas and Other CH4 513.4961 671.0913 1.4020 92.5577 2(I).C.1 Iron and Steel Production CO2 420.2570 506.0000 1.0571 93.6148 2(I).A.7 Magnezite Use CO2 431.9363 475.9960 0.9944 94.6092 2(I).A.3 Limestone and Dolomite Use CO2 302.1217 471.1860 0.9844 95.5936

  • All key source categories are covered in inventory with the

higher attention!

Key sources by level assessment 2005: Tier 1 IPCC GPG – 16 sources

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SLIDE 13

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Key Categories 1990 - 2005 (2)

IPCC Source Categories Direct GHG Base Year Estimate (1990) Current Year Estimate (2005) Level Assessment Cumulative Total of Column E

1.A.2 Manufacturing Industries and Construction CO2 23,998.4378 12,253.7231 25.5999 25.5999 1.A.1 Energy Industries CO2 15,654.1783 11,274.9680 23.5551 49.1550 1.A.3.b Transport - Road Transportation CO2 4,500.9371 6,095.0000 12.7334 61.8884 1.A.4 Other sector CO2 10,520.3514 4,845.1305 10.1222 72.0106 4.D Agricultural Soils N2O 3,582.1515 1,688.8445 3.5283 75.5389 1.A.5.a Other non-specified CO2 1,679.0780 1,430.9723 2.9895 78.5284 2(I).B.2 Nitric Acid Production N2O 1,167.3050 1,254.3279 2.6205 81.1489 6.A Solid Waste Disposal on Land CH4 469.7700 1,249.9200 2.6113 83.7601 2(I).A.1 Cement Production CO2 1,438.0088 1,233.5090 2.5770 86.3371 4.A Enteric Fermentation CH4 1,990.1616 943.0329 1.9701 88.3073 6.B Wastewater Handling CH4 1,012.0541 686.3084 1.4338 89.7411 2(I).A.2 Lime Production CO2 770.4160 677.1150 1.4146 91.1557 1.B.1.b Fugitive Emission from Oil, Natural Gas and Other CH4 513.4961 671.0913 1.4020 92.5577 2(I).C.1 Iron and Steel Production CO2 420.2570 506.0000 1.0571 93.6148 2(I).A.7 Magnezite Use CO2 431.9363 475.9960 0.9944 94.6092 2(I).A.3 Limestone and Dolomite Use CO2 302.1217 471.1860 0.9844 95.5936 4.B Manure Management N2O 1,094.5573 426.7058 0.8915 96.4851 1.B.1.a Coal Mining and Handling CH4 571.1503 339.6246 0.7095 97.1946 2(I).C.3 Aluminium Production CO2 121.3200 230.6900 0.4819 97.6765 2(I).F HFCs emissions HFCs 0.0000 174.6451 0.3649 98.0414 1.A.3.b Transport - Road Transportation N2O 71.6100 174.6416 0.3649 98.4062 4.B Manure Management CH4 368.6568 160.8772 0.3361 98.7423 6.C Waste Incineration CO2 0.0000 145.6483 0.3043 99.0466 CO2 equivalents (Gg) %

Key sources by trend assessment 2005: Tier 1 IPCC GPG – 23 sources

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Sector Waste Overview (1)

6 Waste sector categories:

■ 6A Solid Waste Disposal on Land – 6A3 Other 59%:

■ Municipal Solid Waste (managed & unmanaged) 79% ■ Agricultural & Industrial Solid Waste 21%

■ 6B Wastewater Handling 34%

■ 6B1 Industrial Wastewater ■ 6B2 Domestic & Commercial Wastewater

■ 6C Waste Incineration 7%

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Waste Greenhouse Gases evaluation:

■ CO2 – only 6C 7% ■ Methane – 6A and 6B 92% ■ N2O – only 6B 1%

Sector Waste Overview (2)

Total share of CH4 emissions from Municipal Solid Waste in 2005 in Waste sector was 47%!

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Sector Waste Overview (3) - methodology

Method used in municipal solid waste on landfills

before 2006 – default method Tier 1 (IPCC 1996)

  • Based on the assumption that all potential CH4 is released in the

year the waste is disposed of!

  • No reasonable annual estimate if the amount and composition of

waste disposed of at SWDS is changing more rapidly over time!

  • No accurate trend!
  • Decreasing trend for the period 1990-2004

Not in line with the IPCC GPG 2000 (if the category is key source using Tier 2 is „good practice“)

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

New approach in municipal solid waste on landfills

after 2006 – Tier 2 First Order Decay

  • Based on kinetic model calculated with data on sites

from 1960!

  • Various national input factors which influence the rate

and extent of methane generation and release!

  • No measurements on sites!
  • Collected data on MSW do not include the needed

characterisation of SWDS

Sector Waste Overview (4) - methodology

Difficulties with accuracy of CH4 emission estimation and uncertainty

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SLIDE 18

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

  • From 2005 started new cooperation with the sectoral expert
  • Mr. FARKAŠ – Integrated Skills LtD.
  • As the most appropriate approach was selected the Second

version of FOD method, as it is defined in the IPCC 1996 Reference Manual page 6.10: Qt,x = ∑x[(A · k · MSWT(x) · MSWF(x) · Lo(x)) · e-k(t-x)] QT = (∑Q t,x – R(t)) (1 – Ox)

Lo - Methane generation potential, k - Methane generation rate constant, Ox – Oxidation factor, R – Recovery, MSWT – Total waste per year, MSWF – Waste fractionated on sites...

more....

  • J. Farkas, Integrated Skills LtD.: Methane Emissions from SWDS in 2005 –

Final Report, Bratislava, October 2006, www.ghg-inventory.gov.sk

Sector Waste Overview (5) - methodology

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Sector Waste Overview (6) - results

Tier 2 - Cumulative methane emissions from SWDSs

0.00 10.00 20.00 30.00 40.00 50.00 60.00 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004

Gg/yr Years 0.00 10.00 20.00 30.00 40.00 50.00 60.00 1 9 9 1 9 9 1 1 9 9 2 1 9 9 3 1 9 9 4 1 9 9 5 1 9 9 6 1 9 9 7 1 9 9 8 1 9 9 9 2 2 1 2 2 2 3 2 4 2 5 Municipal Waste Tier 1 Municipal Waste Tier 2

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Sector Waste Overview (7) - uncertainty

  • Activity data (5%) and emission factor (50%) uncertainty based
  • n default values from literature – Tier 1 estimating by source

with simplifying assumption ~ 50.25%!

  • From 2005 started new cooperation with the sectoral expert for

uncertainty management Mr. GERA – Faculty of Mathematic, Physic and Informatics

  • Tier 2 estimating by source category (SWDS) using Monte

Carlo analysis!

(-42%;+49%) in 2005

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SLIDE 21

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Total Uncertainty (1)

  • Emissions production is expressed by function F(Xi)

Xi are factors, which affect the sequential result of

emissions (i=1…N, N represents number for factors).

  • The function value and their uncertainties it can be expressed:

F(Xi)=F( +δ(Xi))

  • Question is how the uncertainties of Xi values will affect the

function value F(Xi) δ(F(Xi))

  • For multiplication

F(X1X2)~

⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

2 1 2 1 2 1

1 σ σ σ σ | X X | J

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

i

X

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SLIDE 22

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Total Uncertainty (2)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • To estimate the properties of δ (F(Xi)), linearized theory is

investigated:

ratio δ (Xi)/ represents percentual contribution to the total

uncertainty

  • The result is linear combination of these percentual

submissions.

linearized approach is effective to use only in the case when

|G( )|<<1.

it shows us that PDF’s of δ (Xi) can play important role within

process of uncertainty combination.

∑

≅

i i i i i

) X ( G X ) X ( ) X ( F δ δ

i

X

i

X

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Monte Carlo approach (1)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • The method Monte Carlo is convenient to use for uncertainty

problem solving.

  • One requirement is to know distribution function of uncertainties.
  • This approach allows us, simulate the complete properties of the

final probability distribution function δ(F(Xi)) and obtain required statistical characteristics.

  • In this point one should be attentive, how uncertainties are
  • specified. In the case when measurement of data is available

the situation is well solvable. In the case of data absence the special estimation is provided.

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Monte Carlo approach (2)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • The Monte Carlo method is based on the generation of multiple

trials to determine the expected value of a random value

  • In our case it can be said that this method is uncertainties

combination of probability distribution functions for activity data (AD) and emission factors (EF)

  • Total emissions are computed as combination of random

numbers for appropriate distribution function for assigned greenhouses gases

  • The advantage of this method is asymmetry allowance to the

statistical distribution

  • This advanced method is useful for data manipulation, when

proper input data quality is provided

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Uncertainty Model Initialization

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • For specification of probability distribution of AD and EF there

are variety of inputs

  • Expert consultation, source from measurement and from

experiences

  • For two parameters distributions the mean value and values

represented 95% confidence interval are directly expressed

  • For three parameters distribution there is place for 95%

confidence interval tuning

  • Majority time consumption
  • The number of trials is chosen
  • Variation (precision level or statistic) of total emission mean

value is examined for estimation of trials number

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Software tools

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • Software package, which works with probabilistic distribution

and their combination, was developed

  • With help of AuvTool software, they create useful tools for

uncertainties estimation

  • In developed packages the next statistical distributions are

supported now:

  • Gumbel, Exponential, Weibull
  • Lognormal, Uniform, Triangular
  • Beta, Binomial, Neg_binomial, Chisq, Nc_chisq
  • F, Nc_F, Gamma, T, Nc_T, Normal and Poisson
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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Basic model equations

First Order Decay method

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • L0 = MCF(x) · DOC(x) · DOCF · F · 16/12
  • Fk=(1–e–k) e-k(t-x)
  • MSWL(x) = MSWT(x) · MSWF(x)
  • Qt = Fk(t,x) · MSWL(x) · L0(x)

Developed by Mr. J. Farkaš

  • QT = (∑Qt – R(t)) (1 – OX(t))
  • Qt

methane generated in year t (Gg/yr)

  • t

year of inventory

  • x

years for which input data should be added

  • Fk

related with normalisation factor which corrects the summation

  • k

Methane generation rate constant (1/yr)

  • MSWT(x)

Total municipal solid waste (MSW) generated in year x (Gg/yr)

  • MSWF(x)

Fraction of MSW disposed at SWDS in year x

  • L0(x)

methane generation potential (Gg CH4/Gg waste)

  • MCF(x)

Methane correction factor in year x (fraction)

  • DOC(x)

Degradable organic carbon (DOC) in year x (fraction) (Gg C/Gg waste)

  • DOCF

Fraction of DOC dissimilated

  • F Fraction by volume of methane in landfill gas
  • 16/12

Conversion from C to CH4

  • R(t)

Recovered methane in inventory year t (Gg/yr)

  • OX

Oxidation factor (fraction)

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SLIDE 28

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Input data sensitivity (1)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • PDF’s profiles was modified for every input parameter (AD, EF)

to see the influence of PDF’s change to the total emissions

  • Every profile in beginning of our analysis was changed to

the normal or uniform distribution.

  • The mean values were retained.
  • Symetrical uncertainty was investigated
  • Results for sensitivity of input parameters are simply verified too.
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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Input data sensitivity (2)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

CH4/Param median average

  • st. dev.

2,50% Percent 97,50% Percent Abs.Min AbsMax DOCX 41.44 48.51 29.88 11.40

  • 76.49

126.31 160.38 3.89 220.16 MCF 41.50 48.51 29.72 11.62

  • 76.04

126.55 160.86 4.29 214.98 K 40.46 49.55 34.46 9.76

  • 80.31

142.70 187.97 3.34 280.49 F 41.23 48.50 29.92 11.34

  • 70.83

127.16 162.17 4.14 214.41 DOCF 41.41 48.44 29.77 11.48

  • 76.30

126.15 160.45 3.47 235.30 MSWL 41.22 48.44 29.64 11.58

  • 76.10

125.14 158.31 4.42 205.30 CH4/Param median average

  • st. dev.

2,50% Percent 97,50% Percent Abs.Min AbsMax

Nor.10

49.22 49.47 5.67 39.09

  • 20.98

61.33 23.97 32.97 77.63

Nor.50

43.87 48.75 26.47 12.04

  • 75.30

113.00 131.79 0.67 241.47

Uni.10

49.09 49.45 6.37 37.98

  • 23.20

62.98 27.36 31.91 73.39

Uni.50

39.56 48.48 33.90 9.50

  • 80.40

140.68 190.16 3.16 272.56

  • Uni. Tab

38.41 40.03 13.02 19.54

  • 51.19

69.19 72.85 12.99 90.86

Tabular

42.98 43.56 10.18 25.45

  • 41.57

64.81 48.78 16.77 84.37

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2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Activity Data Specification

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

CATEGORY AD_MEAN,VALUE AD_MIN/MAX DISTR_AD PARAM_DIST_AD __________________________________________________________________________________

  • K

100%,0.065

  • 45%:230% triangular NAN
  • FO

100%,0.5

  • 20%:20% triangular NAN
  • FN

100%,0.5

  • 0%:20% triangular NAN
  • MSWL

0.0

  • 1.959,1.959 normal NAN
  • DOCF

100%,0.6

  • 30%:28% triangular NAN
  • DOCX

100%,0.12

  • 50%:20% triangular NAN
  • MCFN

100%,1.0

  • 30%:0% triangular NAN
  • MCFO

100%,0.6

  • 50%:60% triangular NAN
  • OX

100%,0.05

  • 95%:100% normal NAN

P.S. Same table form is defined for EF

slide-31
SLIDE 31

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Results for solid waste disposal

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

84,375 88,079 92,336 87,385 76,668 77,048 77,227 72,915 77,958 79,636 AbsMax 16,765 17,506 18,357 17,377 15,250 15,306 14,826 12,977 12,363 11,054 Abs.Min 64,806 67,730 71,069 67,350 59,210 59,490 59,782 55,258 56,825 56,284 97,50% 25,454 26,599 27,893 26,404 23,162 23,225 23,381 21,114 20,691 18,732 2,50% 10,182 10,646 11,181 10,603 9,324 9,378 9,360 8,724 9,243 9,671

  • st. dev.

43,558 45,503 47,739 45,219 39,710 39,884 40,056 36,597 36,718 34,994 average 42,979 44,899 47,099 44,608 39,162 39,339 39,511 36,048 36,010 34,067 median 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 CH4

slide-32
SLIDE 32

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Uncertainty for CH4 from 1960 to 2005 (1)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

Waste Tier 2. (FOD) 10 20 30 40 50 60 70 80 90

1 9 6 1 9 6 2 1 9 6 4 1 9 6 6 1 9 6 8 1 9 7 1 9 7 2 1 9 7 4 1 9 7 6 1 9 7 8 1 9 8 1 9 8 2 1 9 8 4 1 9 8 6 1 9 8 8 1 9 9 1 9 9 2 1 9 9 4 1 9 9 6 1 9 9 8 2 2 2 2 4

Year Emission (Gg/yr)

Median Average

  • St. dev

P_2,5% P_97,5%

slide-33
SLIDE 33

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Uncertainty for CH4 from 1960 to 2005 (2)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

Frequency distribution for waste

20 40 60 80 100 120 16,8 20,1 22,4 24,7 27 29,3 31,6 33,9 36,2 38,5 40,8 43,1 45,4 47,7 50 52,3 54,6 56,9 59,2 61,5 63,8 66,1 68,4 70,7 73 75,3 77,6 79,9 emission (Gg/yr) frequency

slide-34
SLIDE 34

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Conclusion (1)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • Uncertainty of emissions are strongly dependent to the PDF’s

setting.

  • The data accuracy play important role to the computation of the

total uncertainty.

  • PDF’s selection in the case of symmetry uncertainty has no

significant influence to the total uncertainty

  • Increasing of partial uncertainties for input factors can

multiple total uncertainties in the symmetrical cases

  • Strongest influence to the total uncertainty is asymmetry

allowance.

  • In the case of asymmetry, total uncertainty could be smaller

than uncertainties of single input parameters.

slide-35
SLIDE 35

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Conclusion (2)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • Total uncertainty was reduced comparable to IPCC default

recommended value. This default value is 50% for total methane emissions from SWDS.

  • This default uncertainty is applicable to the Tier 1 default

method.

  • From this value in the Tier 1, the key sources are identified

by categories magnitude, which adds up to over 95% of the total emissions or emission trend.

  • In Tier 2 the 90% of the level or trend uncertainties are also

taken for the key sources specification.

slide-36
SLIDE 36

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Conclusion (3)

FAKULTA MATEMATIKY, FYZIKY A INFORMATIKY FACULTY OF MATHEMATHICS, PHYSICS AND INFORMATICS

  • Specification and identification of the key sources are important

for economy and government institutions to obtain overview of emissions unload.

  • During the uncertainty computation, the emitting of CH4

from underlayer and many other factors as meteorological condition, managing of sites are included. These dependences are expressed in FOD model, which was solved by Monte Carlo simulation.

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SLIDE 37

2nd International Workshop on Uncertainty in GHG Inventories, IIASA, Laxenburg, Austria, 27 - 28 September 2007

SLOVENSKÝ HYDROMETEOROLOGICKÝ ÚSTAV SLOVAK HYDROMETEOROLOGICAL INSTITUTE

Thank you for attention!

janka.szemesova@shmu.sk www.ghg-inventory.gov.sk www.shmu.sk +421 2 59415346 +421 905 693623 mgera@fmph.uniba.sk www.dmc.fmph.uniba.sk +421 2 60295863