Geoinformation Technologies and Spatial Analysis of GHG Emissions in Polish Regions Bordering Ukraine
The specificity of territorial distribution of the GHG emission sources has been analyzed for polish regions bordering Ukraine. Mathematical models and geoinformation technology for spatial analysis of GHG emissions in the Energy sector that consider the territorial distribution of GHG emission sour...
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irk-123456789-604312014-04-16T03:01:33Z Geoinformation Technologies and Spatial Analysis of GHG Emissions in Polish Regions Bordering Ukraine Lesiv, M. Bun, R. Интеллектуальные системы планирования, управления, моделирования и принятия решений The specificity of territorial distribution of the GHG emission sources has been analyzed for polish regions bordering Ukraine. Mathematical models and geoinformation technology for spatial analysis of GHG emissions in the Energy sector that consider the territorial distribution of GHG emission sources and the structure of statistical data for Polish regions Lublin and Subcapathian are developed. The results of spatial analysis for the Lublin and Subcapathian voivodeships are presented. Проаналізовано специфіку територіального розміщення джерел емісії парникових газів в польських регіонах, що межують з Україною. Розроблено математичні моделі емісії парникових газів в енергетичному секторі з врахуванням структури статистичної інформації та відповідні геоінформаційні технології для здійснення просторової інвентаризації в польських воєводствах: Люблінському та Підкарпатському. Представлено результати просторового аналізу для цих двох воєводств. Проанализирована специфика территориального размещения источников эмиссии парниковых газов в польских регионах, граничащих с Украиной. Разработаны математические модели эмиссии парниковых газов в энергетическом секторе с учетом структуры статистической информации и соответствующие геоинформационные технологии для осуществления пространственной инвентаризации в польских воеводствах: Люблинском и Подкарпатском. Представлены результаты пространственного анализа для этих двух воеводств. 2011 Article Geoinformation Technologies and Spatial Analysis of GHG Emissions in Polish Regions Bordering Ukraine / M. Lesiv, R. Bun // Штучний інтелект. — 2011. — № 4. — С. 244-252. — Бібліогр.: 11 назв. — англ. 1561-5359 http://dspace.nbuv.gov.ua/handle/123456789/60431 004.942:519.876.5 en Штучний інтелект Інститут проблем штучного інтелекту МОН України та НАН України |
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Интеллектуальные системы планирования, управления, моделирования и принятия решений Интеллектуальные системы планирования, управления, моделирования и принятия решений |
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The specificity of territorial distribution of the GHG emission sources has been analyzed for polish regions bordering Ukraine. Mathematical models and geoinformation technology for spatial analysis of GHG emissions in the Energy sector that consider the territorial distribution of GHG emission sources and the structure of statistical data for Polish regions Lublin and Subcapathian are developed. The results of spatial analysis for the Lublin and Subcapathian voivodeships are presented. |
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Lesiv, M. Bun, R. |
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Lesiv, M. Bun, R. |
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Lesiv, M. |
| title |
Geoinformation Technologies and Spatial Analysis of GHG Emissions in Polish Regions Bordering Ukraine |
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Geoinformation Technologies and Spatial Analysis of GHG Emissions in Polish Regions Bordering Ukraine |
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Geoinformation Technologies and Spatial Analysis of GHG Emissions in Polish Regions Bordering Ukraine |
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Geoinformation Technologies and Spatial Analysis of GHG Emissions in Polish Regions Bordering Ukraine |
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Geoinformation Technologies and Spatial Analysis of GHG Emissions in Polish Regions Bordering Ukraine |
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geoinformation technologies and spatial analysis of ghg emissions in polish regions bordering ukraine |
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Інститут проблем штучного інтелекту МОН України та НАН України |
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Интеллектуальные системы планирования, управления, моделирования и принятия решений |
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| citation_txt |
Geoinformation Technologies and Spatial Analysis of GHG Emissions in Polish Regions Bordering Ukraine / M. Lesiv, R. Bun // Штучний інтелект. — 2011. — № 4. — С. 244-252. — Бібліогр.: 11 назв. — англ. |
| series |
Штучний інтелект |
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AT lesivm geoinformationtechnologiesandspatialanalysisofghgemissionsinpolishregionsborderingukraine AT bunr geoinformationtechnologiesandspatialanalysisofghgemissionsinpolishregionsborderingukraine |
| first_indexed |
2025-07-05T11:31:54Z |
| last_indexed |
2025-07-05T11:31:54Z |
| _version_ |
1836806428746055680 |
| fulltext |
«Искусственный интеллект» 4’2011 244
5L
UDC 004.942:519.876.5
M. Lesiv, R. Bun
Lviv Polytechnic National University, Lviv
myroslava.lesiv@gmail.com
Geoinformation Technologies and Spatial
Analysis of GHG Emissions in Polish Regions
Bordering Ukraine
The specificity of territorial distribution of the GHG emission sources has been analyzed for polish regions
bordering Ukraine. Mathematical models and geoinformation technology for spatial analysis of GHG
emissions in the Energy sector that consider the territorial distribution of GHG emission sources and the
structure of statistical data for Polish regions Lublin and Subcapathian are developed. The results of spatial
analysis for the Lublin and Subcapathian voivodeships are presented.
Introduction
Climate change is one of the main global problems that we face nowadays. Scientists
assert that the increase in concentration of anthropogenic green house gases (GHGs) in the
atmosphere is the main reason of the global warming. That’s why an agreement in the
reductions of GHG emissions is the primary issue of international negotiations. It is very
important to accurately assess GHG emissions and produce relevant reports in order to
verify the fulfilment of international obligations.
To estimate the effectiveness of GHG emission reduction measures one must have
information on GHG sources and sinks at the level of individual regions, not only at the
national (country) level. Therefore, countries are encouraged to develop their own
mathematical models to assess the processes of GHG emission/absorption. Ukrainian
scientists such as Bun R., Hamal H., Yaremchyshyn O. have made a large contribution to
the creation of mathematical models and carrying out the spatial analysis of greenhouse gas
emissions in different sectors of human activity. From abroad Costa M., Winiwarter W.,
Webber P. H., Gregg J. S., Lindley S. J., Oda T., Olivier J. G. J., Friedrich R., Bachman
W., Brandmeyer J should be denoted.
In the border regions of Ukraine the spatial GHG inventory that would fully
encompass a certain sector of human activity has not been conducted. For example, in the
Polish voivodeships of Lublin and Subcarpathian the spatial GHG inventory has been done
only in the category of households of the energy sector [7], [11]. So, there is a need to
modify the mathematical models for spatial GHG inventory taking into account regional
characteristics and structure of statistical data on economic activities in these border areas.
Administrative division in Poland
The territory of Poland is divided into the following administrative units:
voivodeships (in Polish it is województwo), powiats (in Polish it is powiat) and gminas (in
Polish it gmina). Voivodeship is the largest territorial and administrative unit in Poland.
Geoinformation technologies and spatial analysis of GHG emissions in Polish regions...
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Powiat is a unit with local government. Gmina is the smallest administrative unit in Poland,
for an example a city, a village or a group of villages and towns. In total Poland has 16
voivodeships, which are divided into 308 powiats, and the last one into 2469 gminas.
The two polish voivodeships Lublin and Subcarpathian (Lubelskie and Podkarpackie)
border western part of Ukraine. The spatial inventory of GHGs only in the category of
households has already been made for these regions [7], [11].
Voivodeship of Lublin
The voivodeship of Lublin is characterized with the low level of urbanization.
Administratively the region is divided into twenty powiats, four cities with powiat status
and 213 gminas. Lublin is a center of voivodeship [4], [9].
Good soil and climatic conditions are favourable to the development of agriculture.
Therefore, voivodeship of Lublin is one of the main centers of agricultural production.
Chemical and machine-building enterprises are developed as well. Geographically the
voivodeship is located on the polish border with Ukraine and Belarus. Therefore important
international highways: from Brussels, Berlin, Warsaw to Lviv, Kyiv, Minsk, Odessa and
Moscow are crossing its territory. Almost half of the border passenger and half of all traffic
flow through the eastern border of Poland. One of the most modern cargo terminals in
Europe operates in Koroschyn and there is the largest in this part of the continent dump
railway in Malaszewicze.
The long-term evaluation of air pollution in the voivodeship of Lublin shows that air
pollution (including GHGs) is negligible in comparison with other regions, except urban
areas, where GHG emissions and other pollutants are significant.
Subcarpathian voivoideship
Subcarpathian voivodeship is divided administratively into 21 powiats and four
cities with powiat status, and 159 gminas [5]. The capital of the vovodeship – Rzeszów.
Almost half of the territory is covered with forests, national parks. For example,
Bieszczady and Mahurskyy national parks, 70 nature reserves, many mineral springs and
health resorts.
Subcarpathian voivodeship is characterized by the lowest level of industrialization to
compared with other voivodeships. The area is in good ecological condition. The main
sources of greenhouse gases and pollutants are households, industry and transport. Almost
67% of GHG emissions are caused by surface sources, including households, 21% is
industry, 12% is road transport [10].
GHG inventory in Energy sector
Most of the estimates of carbon dioxide emissions in the energy sector are based on
the data concerning fossil fuel consumption. Emissions are calculated as the product of
amount of fuel burned, the carbon content in fuel consumption efficiency (example, the
proportion of fuel that is not oxidized). The fuel fraction which is not oxidized is quite
small in modern systems of fuel consumption. The IPCC recommends assume that 100%
of carbon in fuel is oxidized. Amount of consumed fuel could be measured, but it is really
difficult to measure carbon content. There is a good correlation between the share of
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carbon in the fuel and the amount of energy released from burning, so the transfer of
consumed fuel per unit of mass or volume to energy units enables to take into account the
carbon content in it [1], [3]. Required inventory data on fuel consumption is not always
available. In some cases emissions of carbon dioxide can be estimated using mathematical
models that reflect the basic processes of consumption, such as the amount of released gas
by motor vehicle when passing a certain distance. At the national level it is sometimes
appropriate to assess the amount of fuel consumed on the basis of available information on
the amount of produced fuel, its imports and exports. However, fuel is not always
consumed where it has been purchased. For example, purchased fuel for the ships, aircraft
and other vehicles may be burned in different countries.
Quantity of consumed biomass is reported according to the UNFCCC, but the
corresponding emission of carbon dioxide isn’t reported in such a way. In the process of
growing biomass absorbs CO2 from the atmosphere, but when it is burned the gas again is
emitted to the atmosphere. Therefore, the resulting emissions are considered to be “zero”.
However, emissions from consumed fossil fuel during processes of production, harvesting
and transporting biomass are reported in the appropriate categories. When biomass is
combined with another type of fuel or waste, the emissions caused by the burning part of
the other fuels are only reported. When, for example, pure ethanol is combined with
gasoline as fuel, the emissions are reported only those that are caused by the gasoline
consumption [1], [6].
Carbon dioxide emissions are estimating by the next steps [1]:
analysis of the energy sources in the region;
calculation of carbon in conventional units;
assessment of contained carbon in products that are made from fossil fuels;
calculation of the share of burning carbon;
calculation of CO2 emissions for all fuels.
CO2 emissions are calculated as the product of quantity of consumed fuel, the
calorific value and the rate of oxidation. The general formula for calculating CO2
emissions [1]:
CCenstat FKKDE (1)
where E is emission, Gg; statD is activity data in physical units, t; enK is amount of energy
released during combustion of 1 ton of material, J / t; CK is emissions of carbon dioxide
per unit of obtained energy, Gg / J; CF is carbon oxidation factor (in numerical
experiments realized it was thought that CF = 1).
The IPCC recommends using an amount of fossil fuel, emission factors and carbon
oxidation factors. However, for different categories of human activities and properties of
different fuel types these parameters have different values. For better estimation of GHG
emissions it is recommended to use emissions factors that were estimated for a certain
region and category. Table 1 and Table 2 present the examples of these parameters that
were estimated for Polish regions.
For other greenhouse gases (CH4, N2O) the emission estimates are based on the
statistical data for various sectors of human activity. The amount of emissions depends on
the fuel type, processes, conditions of production, type of equipment and methods of
monitoring.
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Table 1 – CO2 emission factors for coal [8]
Category of human
activity
Calorification enK
[MJ/kg]
CO2 emission factor CK
[kg/GJ]
Power plants 21,10 94,42
Industrial power plantsі 21,51 94,86
Boiler houses 21,65 94,82
Manufacturing and
construction
23,87 94,31
Agriculture/forestry/
fisheries and others
25,17 94,05
Average values 22,34 94,65
Table 2 – CO2 emission factors for other fuel types [8]
Fossil fuel Calorification [MJ/kg]
CO2
emission[kg/GJ]
Natural gas 48,0 55,82
Wood 15,6 109,76
Liquid gas 47,31 62,44
Gasoline 44,80 68,61
Diesel 43,33 73,33
Masout 40,19 76,59
Emissions N2O, CH4 and other gases are estimated by the next steps:
estimating an amount of consumed fuel per year for the certain human activity;
estimating the basic factors for each type of activity;
calculating emissions.
The structure of statistical information on consumption of fossil fuels by category in
the Polish regions is [2]:
heat and power plants (according to IPCC sector classification - 1.A.1);
industrial boilers and other heating units (1.A.1);
non-industrial boiler-houses (1.A.1);
industry and manufacturing (1.A.2);
transport (road, rail, etc.) (1.A.3);
other sectors including: agriculture and forestry, households, and other (1.A.5).
To carry out spatial analysis of GHG emissions geographic information system (GIS)
has been used. GIS allows forming a database on GHG emission sources as geographic
features that are characterized by spatial coordinates and results of simulation on digital maps.
As input data for spatial inventory we used digital maps with information on
administrative division with population and statistical data on consumption of fossil fuels
obtained from special yearbook prepared by Department of Statistics in each polish region.
Based on these data the spatial distributed database has been formed. The process of spatial
distributed analysis is divided into the following steps:
Lesiv M., Bun R.
«Искусственный интеллект» 4’2011 248
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1) collecting statistical data and forming input databases (for example, Excel, Oracle
or Access);
2) splitting the digital maps of investigated areas into elementary objects using grids
(for example, grid with resolution of 2 km x 2 km) and disaggregating data on population
proportionally to the area of newly created objects;
3) running modules that simulate the processes of GHG emissions in different sectors
of human activity for each elementary object;
4) forming thematic maps that illustrate the spatial distribution of GHG.
After splitting regional maps into elementary objects the programmed modules that
are based on the developed mathematical models calculate emissions from stationary and
mobile sources. The final step is a spatial analysis of the achieved thematic maps with
information on the GHG emissions at the level of elementary objects.
Mathematical background
In consistence with the structure of national statistics on the consumption of fuels in
Poland stationary sources include:
heat and power plants;
boiler and heating installation of industrial facilities;
non-industrial boilers;
fuel combustion in industry and construction;
fuel combustion in agriculture, forestry and fisheries;
households.
Heat and power plants, industrial and non-industrial boiler-houses have specific
locations more often in settlements. As the statistical data is only available concerning total
amounts of consumed fuels by category in each voivodeship [2], [8], so this amount should
be disaggregated by the number of emission sources. The emissions of a elementary object
(area) for a particular voivodeship could be calculated by the formulas:
emissions from consumption of fossil fuels by heat and power plants:
F TEC
RTEC
Nj jR
iRemGFTECenFTECFTEC
iRGTEC N
N
P
PKKD
E
R
,
,
,,,,,,,
,,, , (2)
where iRGTECE ,,, is emissions of gas G from burning fuels by heat and power plants for
elementary object i that is located in gmina R ; FTECD , is an amount of burned fuel F by
heat and power plants; emGFTECenFTEC KK ,,,,, , is a calorification and an emission factor of gas
G for burned fuel F by heat and power plants; RTECN , is account of heat and power plants
in gmina R (or other parameter that characterised energy and heat production ); TECN is
total account of heat and power plants in voivodeship; R is a set of the elementary
objects in gmina R ; iRP , is population in the elementary object i from gmina R ; is a set
of all types of fossil fuels;
emissions from consumption of fossil fuels by industrial boiler-houses:
KZ
RKZ
F Nj jR
iRemGFKZenFKZFKZ
iRGKZ N
N
P
PKKD
E
R
,
,
,,,,,,,
,,,
, (3)
Geoinformation technologies and spatial analysis of GHG emissions in Polish regions...
«Штучний інтелект» 4’2011 249
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where iRGKZE ,,, is emissions of gas G from burning fuels by industrial boiler-houses for
elementary object i that is located in gmina R ; FKZD , is amount of burned fuel F by
industrial boiler-houses; emGKZFenFKZ KK ,,,,, , is the calorification and emission factor of gas
G for burned fuel F by industrial boiler-houses; RKZN , is the account of industrial boiler-
houses in gmina R ; KZN is total account of industrial boiler-houses in the voivodeship;
emissions from consumption of fossil fuels by non-industrial boiler-houses:
KZ
RKnZ
F Nj jR
iRemGFKnZenGFKnZFKnZ
iRGKnZ N
N
P
PKKD
E
R
,
,
,,,,,,,,
,,,
, (4)
where iRGKnZE ,,, is emissions of gas G from burning fuels by non-industrial boiler-houses
for elementary object i that is located in gmina R ; FKnZD , is amount of burned fuel F by
non-industrial boiler-houses; emGKnZFenFKnZ KK ,,,,, , is the calorification and emission factor
of gas G for burned fuel F by non-industrial boiler-houses; RKnZN , is the account of non-
industrial boiler-houses in gmina R ; KnZN is total account of non-industrial boiler-houses in
voivodeship.
Emissions from combustion of fossil fuels in the category of manufacturing and
construction should be disaggregated by a gross value of real assets (in million PLN).
Gross value of assets - is the cost of acquisition or production of real assets involved in
production (excluding depreciation). The emissions of an elementary object (area) for a
particular voivodeship could be calculated by the formula:
Ind
RInd
F Nj jR
iRemGFIndenGFIndFInd
iRGInd V
V
P
PKKD
E
R
,
,
,,,,,,,,
,,,
, (5)
where iRGIndE ,,, is emissions of gas G from the consumed fuels in manufacturing industries
and construction for elementary object i that is located in gmina R ; FIndD , is amount of
burned fuel F in manufacturing and construction; emGFIndenGFInd KK ,,,,,, , is the calorification
and emission factor of gas G for burned fuel F in manufacturing industries and
construction; RindV , is a gross value of real assets for gmina R ; IndV is total gross value of
real assets for the voivodeship.
The emissions sources of consumed fuels in agriculture, fisheries, and forestry are
mainly located in the countryside. So, the GHG emissions in this category could be
estimated by the formula:
F Nj jRs
iRsemGFAgrenGFAgrFAgr
iRsGAgr
sR
P
PKKD
E
,
,,,,,,,,
,,, , (6)
where iRsGAgrE ,,, is emissions of gas G from consumed fuels in agriculture, fisheries, and
forestry for elementary object i that is located in gmina R ; FAgrD , is amount of burned
fuel F in agriculture, fisheries, and forestry; emGFAgrenGFAgr KK ,,,,,, , is the calorification and
emission factor of gas G for burned fuel F in agriculture, fisheries, and forestry; iRsP , is
Lesiv M., Bun R.
«Искусственный интеллект» 4’2011 250
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population of elementary object i for the village-gmina Rs ; Rs is a set of elementary objects
that are located in the gmina Rs .
The emission sources of consumed fuels in the households or other small activities
are difficult to detect, so it is assumed that burned fuels in these category are disaggregated
by population in each elementary area in the voivodeship:
F j j
iemGFOtherenGFOtherFOther
iGOther P
PKKD
E ,,,,,,,
,, , (7)
where iGFOtherE ,,, is emissions of gas G from consumed fuels in households or other small
activities for elementary object i that is located in gmina R ; FOtherD , is amount of burned
fuel F in households or other small activities; enFOtherK ,, and emGFOtherK ,,, are the
calorification and emission factor of gas G for burned fuel F in households or other small
activities; iP is population of the elementary object i ; is a set of elementary objects,
R R , where is a set of all gminas in the voivodeship.
Total emissions from the stationary sources are calculated by the formula:
R i
iRGFIndiRGFKnZiRGFKZiRGFTEC
stac
GF
R
EEEEE ,,,,,,,,,,,,,,,,,
i
iGFOther
Rs i
iRsGFAgr EE
s Rs
,,,,,,, , (8)
where stac
GFE , is emissions of gas G from consumed fuel F -th by the stationary sources;
s is a set of the village-gminas.
Emissions from mobile sources (line type), for an example a road transport, are
calculated by the formula:
F
j
jroad
iroadFGemFroad
iGroad K
KKD
E
,
,,,,
,, , (9)
where iGroadE ,, is emissions of gas G from consumed fossil fuels in elementary object i ;
FroadD , is amount of consumed fuel F ; GFemK ,, is gas G emission factor for fuel F ; iroadK , is
a traffic factor on the elementary part of the road i ; is a set of the elementary objects of the
roads in the voivodeship.
Emissions from other mobile sources, i.e. railways, are calculated by the formula:
j
jrail
irailGemrail
iGrail K
KKD
E
,
,,
,, , (10)
where i,G,railE is emissions of gas G from the consumed diesel in the elementary object i ;
railD is amount of diesel ; GFemK ,, is gas G emission factor for diesel; is a set of
elementary objects of railways in the voivodeship; irailK , is a traffic factor on the elementary
part of railway i .
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Numerical modeling
Geoinformation technology based on the developed mathematical models has been
created using tools of MapInfo and MapBasic. With its help the spatial analysis of CO2,
N2O, CH4 emissions in the energy sector for Lublin and Subcarpathian voivodeships has
been done. The results are presented in the form of digital maps. For an example, figure 1
shows the total GHG emission in the energy.
Total GHG emissions in the voivodeship of Lublin are higher than in the
Subcarpathian voivodeship. This is due to the fact that the voivodeship of Lublin is
characterized by a higher level of urbanization and industrialization. The significant
emission sources are located mainly in Pulawy, Lublin, Holm. In contrast the
Subcarpathian voivodeship is an important agricultural center, the emission sources are
located more or less evenly, depending on population density.
Figure 1. Spatial distribution of CO2, CH4, N2O emissions in the energy sector for Lublin
and Subcarpathian voivodeships (in CO2 equivalent, grid 2 km x 2 km, 2008)
Conclusions
The distribution of GHG emission sources in Lublin and Subcarpathian voivodeships
is analyzed. The largest emissions sources are located in Lublin voivodeship. For exapmle,
powerful nitrate enterprises in Pulawy, two powerful power plants in Lublin, the cement
factory in Holm. The subcarpathian voivodeship is characterized by lots of farmland and
forested areas, national parks. For the Subcarpathian voivodeship the GHG emissions are
mainly disaggregated by population density. The mathematical model for the spatial GHG
inventory and corresponding geoinformatonal technology have been developed concerning
the structure of statistical information and specificity of sources. The developed models
reflect processes of GHG emissions from stationary and mobile sources and for various
categories. Based on the presented mathematical models of emission processes modules
were programmed in the MapBasic language using the tools of GIS MapInfo. The spatial
Rzeszów
Lublin Holm
Lesiv M., Bun R.
«Искусственный интеллект» 4’2011 252
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analysis of CO2, N2O, CH4 emissions in the energy sector has been carried for Lublin and
Subcarpathian voivodeships. Results are presented in the form of digital maps.
References
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М.Ю. Лесив, Р.А. Бунь
Геоинформационные технологии и пространственный анализ эмиссии парниковых газов
в польских регионах, граничащих с Украиной
Проанализирована специфика территориального размещения источников эмиссии парниковых газов в
польских регионах, граничащих с Украиной. Разработаны математические модели эмиссии парниковых
газов в энергетическом секторе с учетом структуры статистической информации и соответствующие
геоинформационные технологии для осуществления пространственной инвентаризации в польских
воеводствах: Люблинском и Подкарпатском. Представлены результаты пространственного анализа для
этих двух воеводств.
М.Ю. Лесів, Р.А. Бунь
Геоінформаційні технології та просторовий аналіз емісії парникових газів в польських регіонах,
що межують з Україною
Проаналізовано специфіку територіального розміщення джерел емісії парникових газів в польських регіонах,
що межують з Україною. Розроблено математичні моделі емісії парникових газів в енергетичному секторі з
врахуванням структури статистичної інформації та відповідні геоінформаційні технології для здійснення
просторової інвентаризації в польських воєводствах: Люблінському та Підкарпатському. Представлено
результати просторового аналізу для цих двох воєводств.
Статья поступила в редакцию 16.06.2011.
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