analysis of uncertainty sources. ukraine case study · mapinfo profes sional 6.5 waste, …...
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Distributed inventory:Distributed inventory:analysis of uncertainty sources. analysis of uncertainty sources.
Ukraine case studyUkraine case study
R.R.BunBun, L., L.KujiiKujii, O., O.TokarTokar, , YaYa..TsybrivskyyTsybrivskyyState S&R Institute of Information Infrastructure, State S&R Institute of Information Infrastructure,
National Academy of Science of UkraineNational Academy of Science of UkraineLvivLviv,, UkraineUkraine
Main idea:Main idea:
Distributed inventoryDistributed inventory�
uncertainty estimationuncertainty estimation�
uncertainty decreasinguncertainty decreasing
Illustrations:Illustrations:
on the basis of IPCC Methodology on the basis of IPCC Methodology
Traditional inventoryTraditional inventory
� Inventory �
�Emissionvalue
E �++++ tyUniversali ? small-Large−−−−
Large or small country ?Large or small country ?
PolandUkraine S2S ⋅⋅⋅⋅≈≈≈≈
Ukraine2km 603,000
AustriaUkraine S5,7S ⋅⋅⋅⋅≈≈≈≈
25regions
650≈≈≈≈districts
Irregularity of industry locationIrregularity of industry location
Irregularity of emissions of harmful substances into the atmosphere per km2
1,7 67,7
Irregularity of forest fund andwood production
NonNon--uniform distributionuniform distributionGHGGHG sinkssinks emission sourcesemission sources
inventory dDistribute����
makers decisionfor tool Effective ����
Distributed inventory levels:Distributed inventory levels:
�� The highest inventory levelThe highest inventory level ——for the whole Ukrainefor the whole Ukraine
�� Middle inventory levelMiddle inventory level ——for separate regions/districtsfor separate regions/districts
�� The lowest inventory level The lowest inventory level ——for efor elementary plotslementary plots
The highest inventory levelThe highest inventory level ——for the whole Ukrainefor the whole Ukraine
Output data Model Input data (from database)
�,CH,COE 42==== )X(fE ====⇐⇐⇐⇐ �;industry;energyX ====⇐⇐⇐⇐
Traditional inventoryTraditional inventory
Middle inventory levelMiddle inventory level ——for separate region/for separate region/oblastoblast
Output data Model Input data (from database)
�,CH,COE 42region ==== )X(fE regionregion ====⇐⇐⇐⇐ �;industry;energyX ====⇐⇐⇐⇐
NonNon--traditional inventorytraditional inventory
The lowest inventory levelThe lowest inventory level
� �� �
� �� �
Elementary plot Elementary plot ——
Output data Model Input data (from database)
�,4CH,COE 2.el ====∆∆∆∆ )X(fE .el.el ∆∆∆∆====∆∆∆∆⇐⇐⇐⇐ �;industry;energyX .el ====∆∆∆∆⇐⇐⇐⇐
Distributed inventoryDistributed inventory
Relation between distributed and lumped models Relation between distributed and lumped models –– summing on all summing on all elementary plots yields result of traditional inventoryelementary plots yields result of traditional inventory
Technology of distributed inventoryTechnology of distributed inventoryData of statistics,mathematical models,calculation results andprognosis with the use ofneural networks methods
Vegetation
Relief
Population
MapInfo Professional 6.5
Waste, …
Agriculture,forestry, …
Industry(cement, …)
Energy(combustion, …)
IPCC Software(Ex�el)
Inventory by IPCCmethodology
By
sect
ors o
f IPC
C m
etho
dolo
gy
Organizinginput databasefor region,Ukraine
CH4
CO2
By
gree
nhou
se g
ases
Reflection on thedigital map (newlayers production)
New layersproduction
Total value in��2 equivalent
�
Digital map
Structural scheme of softwareStructural scheme of software GISGIS “GHG”“GHG”
Statistical data
Statistical data
Statistical data Energy
Industrial processes Agriculture
Land-use change and forestry Waste
MapInfo New layers generation for digital map of GIS “GHG”
Result
Other methodology, which take into account time dependences,
prognosis and models
���� methodology Sectoral reports
Prognosis under lack of data
ModuleGHGMap
ModuleGHGInvent
GIS “GHG”
InterrelationsInterrelations betweenbetween tablestables ofof thethedatabasedatabase GHGInvNNNNGHGInvNNNN..mdbmdb
Digital map of UkraineDigital map of Ukraine
Spatial database of Ukraine of scale 1:500 000
Major segments of the electronic mapMajor segments of the electronic map
�� Vegetation and soils Vegetation and soils �� Land reliefLand relief�� Settlements (inhabited localities) Settlements (inhabited localities) �� HydrographyHydrography and and hydroengineeringhydroengineering
constructionsconstructions�� Road network and constructionsRoad network and constructions�� Bounds, enclosures and separate natural Bounds, enclosures and separate natural
phenomenaphenomena
Experimental measurements:Experimental measurements:
As a physical map ...As a physical map ...
Distributed inventory resultsDistributed inventory resultsEnergy sector:Energy sector:
COCO2 2 emissions from stationary combustion (2000)emissions from stationary combustion (2000)
Distributed inventory resultsDistributed inventory resultsEnergy sector:Energy sector:
Mobile combustion Mobile combustion -- road vehicles, district level (2000)road vehicles, district level (2000)
Distributed inventory resultsDistributed inventory resultsAgriculture sector:Agriculture sector:
CHCH44 emissions from manure management (1990)emissions from manure management (1990)
Distributed inventory resultsDistributed inventory resultsForestry:Forestry:
Carbon sink into forest phytomass,, district leveldistrict level (1996)(1996)
Positive features of Positive features of approachapproach�� Convenient Convenient information for decision makers in a information for decision makers in a
countrycountry�� Efficiency for large area countries with highly Efficiency for large area countries with highly
nonnon--uniform location of GHG sources and uniform location of GHG sources and absorbersabsorbers
�� Transparency of inventory process on different Transparency of inventory process on different scales and convenience of reportingscales and convenience of reporting
�� Possibility of effective usage of remote sensing Possibility of effective usage of remote sensing datadata
�� Convenience of comparison with another resultsConvenience of comparison with another results�� combination of combination of geoinformationgeoinformation technologies and technologies and
IPCC methodologiesIPCC methodologies
Distributed inventoryDistributed inventoryandand
Uncertainty ???Uncertainty ???
Example :Example :
Energy sector, regional levelEnergy sector, regional level
Energy sector structureEnergy sector structureRegional levelRegional level
Regi-ons
Kinds of human activity
GHGs
IPCC: Good Practice Guidance and IPCC: Good Practice Guidance and Uncertainty Uncertainty Management in National Management in National
Greenhouse Gas InventoriesGreenhouse Gas InventoriesEnergy sectorEnergy sector
??? Leaders
Regi-ons
Kinds of human activity
GHGs
Regi-ons
GHGs
Regi-ons
Kinds of human activity
GHGs
Emissions iesuncertaint Relative
iesuncertaint Absolute
� �
�
Map of uncertaintiesMap of uncertaintiesCOCO2 2 emissions from stationary combustionemissions from stationary combustion
An influence of regional absolute uncertainty on country uncertaAn influence of regional absolute uncertainty on country uncertaintyinty
Leaders:Leaders:Absolute uncertainty COAbsolute uncertainty CO2 2 emissions from stationary combustionemissions from stationary combustion
1. 1. DonetskDonetsk region region -- 28,3 % 28,3 % 2. 2. DnipropetrovskDnipropetrovsk region region -- 15,1 % 15,1 % 3. 3. LuganskLugansk region region -- 9,6 % 9,6 %
----------------------------------� = 53,0 %� = 53,0 %
of all Ukraine GHG emissionof all Ukraine GHG emission
Numerical experimentNumerical experiment Ukraine
���� statistics Bad""
yUncertaint)sector (Energy
% 7,40U ====
Ukraine
����
Leaders
���� statistics Good""
���� Ukraine
% ,026U ====)sector (Energy yUncertaint Ukraine
% 1,38U ====∆∆∆∆
statistics Bad""
Summary of approachSummary of approach
Distributed inventory�
Leading region and leading activity�
Small investment for leaders�
Uncertainty decreasing
Thanks for your Thanks for your attention!attention!