SIXTH FRAMEWORK PROGRAMME
Project no: 502687
NEEDS
New Energy Externalities Developments for Sustainability
INTEGRATED PROJECT
Priority 6.1: Sustainable Energy Systems and, more specifically,
Sub-priority 6.1.3.2.5: Socio-economic tools and concepts for energy strategy.
RS 1d - Deliverable n. T3.1
“Datasets on reference environment and technology”
Due date of deliverable: 30 April 2007
Actual submission date:1 August 2008
Start date of project: 1 September 2004Duration: 48 months
Organisation name for this deliverable: AEKI, CDER, CUEC, LEGI-EPT, MEERI, NREA, OME, PROFING, SEI, UNWE
Project co-funded by the European Commission within the Sixth Framework Programme (2002-2006)Dissemination Level
PU / Public / X
PP / Restricted to other programme participants (including the Commission Services)
RE / Restricted to a group specified by the consortium (including the Commission Services)
CO / Confidential, only for members of the consortium (including the Commission Services)
Table of Contents
Summary
1Reference environment database
1.1Population
1.1.1Hungary
1.1.2Czech Republic
1.1.3Estonia
1.1.4Slovakia
1.1.5Bulgaria
1.1.6Poland
1.1.7Tunisia
1.1.8Morocco
1.1.9Egypt
1.1.10Neigbouring countries
1.2Risk group fractions
1.3Crops
1.3.1Hungary
1.3.2Czech Republic
1.3.3Estonia
1.3.4Slovakia
1.3.5Bulgaria
1.3.6Poland
1.3.7Tunisia
1.3.8Morocco
1.3.9Egypt
1.3.10Neighbouring countries
1.4Materials
2Reference technology database
2.1Data requirements
2.2Tool for emission calculation based on fuel type and technology
2.2.1Model description
2.3Country-specific technological data
2.4Allocation of external costs of heat and electricity generation
2.4.1Emission allocation in CHP with back preasure turbine
2.4.2Emission allocation in CHP with extraction turbine
2.4.3Conclusion
Summary
In order to extend the geographical coverage of the EcoSense model, the databases on the receptors (population, crops, materials), emission sources (technological data of the energy generation utilities) as well as monetary values had to be extended and updated. Data collection was performed by each partner for their respective countries, which had to be performed in accordance with the data requirement of the EcoSense model (presented to the partners by USTUTT.TFU at Workshop 1).
The collection of country-specific data needed for the extension of the geographical coverage of the EcoSense model is divided to three tasks:
1. Reference environment database, which includes receptor data such as population, crops and materials data.
2. Reference technology database, which contains data of energy generation technologies selected for evaluation.
1Reference environment database
Data werecollected for respective countries and if relatively easily available, for the neighbour countries (which aren’t partners in NEEDS) as well.As a priority,data were collected for the selected base year 2005, but in case of unavailability of detailed data for 2005, the last year with detailed data with the highest possible spatial resolution was selected for data collection.
1.1Population
Since damages in human health were found to be one of the most important drivers of external costs, damages should be calculated in a relevant way not only for regional scale, but also for local scale. For this reason population data were collected at the highest possible spatial resolution.
The reference environmental database of the EcoSense model is built on the EMEP grid[1] that is based on a polar-stereographic projection. The USTUTT.TFU group generated a grid with the resolution 10×10 km² (5×5 km²). The population data could be provided in a table with the geographical position referred as the EMEP10_X and EMEP10_Y coordinates. The grid definitions (grid_definitions.zip) were provided by the USTUTT.TFU group.
Another possibility was to provide the population data on the basis of administrative units, Nomenclature of Territorial Units for Statistics (NUTS) for European countries.[2],[3] NUTS Level 4 is now called LAU level 1 and NUTS Level 5 is now the LAU level 2.[4] In the latter case, the USTUTT.TFU group had to convert the data based on the administrative units to data based on the EMEP grid. As digital maps (i.e. GIS-maps) of the contours of the NUTS Level 3 administrative units of all European countries were not available for the USTUTT.TFU group, population data based on administrative units had to be collected with a digital map (in shape format) of the contours of the respective administrative units. The absolute population (not population density) data were collected at the LAU2 administrative level (where available), as well as the GIS map of the contours of the administrative units (preferably) in the WGS84 coordinate system.
In order to harmonize of the data collection performed by the different partners, an EXCEL template was prepared and filled with the respective data provided by each partners. The description of the data headers is the following:
Country – two-letter country code, e.g. HU for Hungary
EMEP10_Xa– X coordinate in the 10×10 km² EMEP grid
EMEP10_Ya– Y coordinate in the 10×10 km² EMEP grid
Regionb–codeof the region at the administration level of the data
Year – year of data
Population – absolute number of population in the respective region
Quality – indicator of data quality (A: best, e.g. official data; E: worst, e.g. estimation)
Commentb – label of the region at the administration level of the data
Source – source of the data
a for data collection based on the EMEP grid cells
b for data collection based on administrative units
In the next subsections the collected data are described in more details for each country.
1.1.1Hungary
Population data were collected for every settlement in Hungary (LAU2 administrative level). Although the base year of the study was agreed as 2005, the most detailed population data were available only for the year of the last national census carried out in 2001. The data were obtained from the Hungarian Central Statistical Office.[5] In order to prepare the data utilizable for the USTUTT.TFU group developing the EcoSenseWeb software utility, the raw data for the statistical units were combined with a digital map of the administrative units of Hungary that was available at AEKI. The map was in the special Hungarian projection EOV that had to be converted to the geographical coordinate system WGS84. Although the collected database includes absolute number of population for 3096 settlements, the illustrative map below shows population density map for Hungary (absolute number of population divided by the area of the administrative unit).Part of the summary table of the collected population data is included in Table 1.
Fig. 1. Population density map of Hungary at the LAU2 administrative level
Table 1. Part of the population dataset for Hungary at the LAU2 administrative level (first and last 10 lines)
Country / Region / Year / Population / Quality / Comment / SourceHU / 1357 / 2001 / 1777921 / A / Budapest / Hungarian Central Statistical Office
HU / 330 / 2001 / 2135 / A / Iklad / Hungarian Central Statistical Office
HU / 480 / 2001 / 1958 / A / Domony / Hungarian Central Statistical Office
HU / 913 / 2001 / 3969 / A / Bag / Hungarian Central Statistical Office
HU / 959 / 2001 / 8043 / A / Tura / Hungarian Central Statistical Office
HU / 1394 / 2001 / 2975 / A / Hévízgyörk / Hungarian Central Statistical Office
HU / 1618 / 2001 / 6428 / A / Aszód / Hungarian Central Statistical Office
HU / 1950 / 2001 / 2527 / A / Galgahévíz / Hungarian Central Statistical Office
HU / 2248 / 2001 / 1428 / A / Verseg / Hungarian Central Statistical Office
HU / 3069 / 2001 / 5711 / A / Kartal / Hungarian Central Statistical Office
...
HU / 3170 / 2001 / 7803 / A / Sándorfalva / Hungarian Central Statistical Office
HU / 3336 / 2001 / 174135 / A / Szeged / Hungarian Central Statistical Office
HU / 783 / 2001 / 1791 / A / Derekegyház / Hungarian Central Statistical Office
HU / 1445 / 2001 / 31638 / A / Szentes / Hungarian Central Statistical Office
HU / 1723 / 2001 / 3435 / A / Nagymágocs / Hungarian Central Statistical Office
HU / 1906 / 2001 / 609 / A / Árpádhalom / Hungarian Central Statistical Office
HU / 1997 / 2001 / 2278 / A / Fábiánsebestyén / Hungarian Central Statistical Office
HU / 2299 / 2001 / 665 / A / Eperjes / Hungarian Central Statistical Office
HU / 2917 / 2001 / 521 / A / Nagytoke / Hungarian Central Statistical Office
HU / 3248 / 2001 / 4913 / A / Szegvár / Hungarian Central Statistical Office
1.1.2Czech Republic
Population data were collected by CUEC for every settlement in CzechRepublic (LAU2 administrative level). Data were bought from the Czech Statistical Office for year 2005. In order to prepare the data utilizable for the USTUTT.TFU group developing the EcoSenseWeb software utility, the data for the statistical units were collected together with a digital map of the administrative units of CzechRepublic. Although the collected database includes absolute number of population for 6352 settlements, the illustrative map below shows population density map for CzechRepublic. Part of the summary table of the collected population data is included in Table 2.
Fig. 2. Population density map of CzechRepublic at the LAU2 administrative level
Table 2. Part of the population dataset for CzechRepublic at the LAU2 administrative level (first and last 10 lines)
Country / Region / Year / Population / Quality / Comment / SourceCZ / 500259 / 2005 / 1931 / A / Veřovice / Czech Central Statistical Office
CZ / 500291 / 2005 / 2468 / A / Vřesina / Czech Central Statistical Office
CZ / 500496 / 2005 / 100381 / A / Olomouc / Czech Central Statistical Office
CZ / 500526 / 2005 / 1974 / A / Bělkovice-Lašťany / Czech Central Statistical Office
CZ / 500623 / 2005 / 1088 / A / Bílá Lhota / Czech Central Statistical Office
CZ / 500801 / 2005 / 577 / A / Blatec / Czech Central Statistical Office
CZ / 500852 / 2005 / 2462 / A / Bohuňovice / Czech Central Statistical Office
CZ / 500861 / 2005 / 1463 / A / Bouzov / Czech Central Statistical Office
CZ / 500879 / 2005 / 603 / A / Bystročice / Czech Central Statistical Office
CZ / 501476 / 2005 / 1803 / A / Dlouhá Loučka / Czech Central Statistical Office
...
CZ / 536008 / 2005 / 807 / A / Katusice / Czech Central Statistical Office
CZ / 565971 / 2005 / 18841 / A / Louny / Czech Central Statistical Office
CZ / 566624 / 2005 / 5002 / A / Postoloprty / Czech Central Statistical Office
CZ / 574252 / 2005 / 2778 / A / Meziměstí / Czech Central Statistical Office
CZ / 535443 / 2005 / 4910 / A / Bělá pod Bezdězem / Czech Central Statistical Office
CZ / 563340 / 2005 / 1048 / A / Spořice / Czech Central Statistical Office
CZ / 565768 / 2005 / 1700 / A / Třebenice / Czech Central Statistical Office
CZ / 561495 / 2005 / 5103 / A / Doksy / Czech Central Statistical Office
CZ / 568201 / 2005 / 1200 / A / Řehlovice / Czech Central Statistical Office
CZ / 568015 / 2005 / 4235 / A / Chlumec / Czech Central Statistical Office
1.1.3Estonia
Population data were collected for every settlement in Estonia (LAU2 administrative level), for 2005 from the land Board of Estonia. A very detailed table of 241 LAU2 units was provided by SEI, but unfortunately without a digital map of the contours of the administrative units. Digital map in shape format could be obtained only at the LAU1 level (from GADM[6]), therefore the illustrative map below shows population density map for Estonia at the LAU1 level only. Part of the summary table of the collected population data is included in Table 3.
Fig. 3. Population density map of Estonia at the LAU1 administrative level
Table 3. Part of the population dataset for Estonia at the LAU2 administrative level (first and last 10 lines)
Country / Region / Year / Population / Quality / Comment / SourceEE / 0296 / 2005 / 9386 / A / Keila / Land Board of Estonia
EE / 0424 / 2005 / 3469 / A / Loksa / Land Board of Estonia
EE / 0446 / 2005 / 16570 / A / Maardu / Land Board of Estonia
EE / 0580 / 2005 / 4190 / A / Paldiski / Land Board of Estonia
EE / 0728 / 2005 / 5067 / A / Saue / Land Board of Estonia
EE / 0784 / 2005 / 396193 / A / Tallinn / Land Board of Estonia
EE / 0112 / 2005 / 905 / A / Aegviidu / Land Board of Estonia
EE / 0140 / 2005 / 6244 / A / Anija / Land Board of Estonia
EE / 0198 / 2005 / 6786 / A / Harku / Land Board of Estonia
EE / 0245 / 2005 / 5197 / A / Jõelähtme / Land Board of Estonia
...
EE / 0389 / 2005 / 1773 / A / Lasva / Land Board of Estonia
EE / 0460 / 2005 / 1195 / A / Meremäe / Land Board of Estonia
EE / 0468 / 2005 / 811 / A / Misso / Land Board of Estonia
EE / 0493 / 2005 / 1031 / A / Mõniste / Land Board of Estonia
EE / 0697 / 2005 / 2045 / A / Rõuge / Land Board of Estonia
EE / 0767 / 2005 / 1914 / A / Sõmerpalu / Land Board of Estonia
EE / 0843 / 2005 / 1433 / A / Urvaste / Land Board of Estonia
EE / 0865 / 2005 / 1294 / A / Varstu / Land Board of Estonia
EE / 0874 / 2005 / 2141 / A / Vastseliina / Land Board of Estonia
EE / 0918 / 2005 / 4807 / A / Võru / Land Board of Estonia
1.1.4Slovakia
Population data were collected by PROFING for every community in Slovakia (LAU2 administrative level). The data obtained from the Staistical Office of SlovakRepublic[7] for year 2005 were reorganized to the required format. In order to prepare the data utilizable for the USTUTT.TFU group developing the EcoSenseWeb software utility, a digital map of the administrative units of Slovakia was also obtained. Unfortunately the shapefile contains only the contours of the LAU1 administrative units. Although the collected database includes absolute number of population for 2929communities, the illustrative map below shows population density map for Slovakia. Part of the summary table of the collected population data is included in Table 4.
Fig. 4. Population density map of Slovakia at the LAU1 administrative level
Table 4. Part of the population dataset for Slovakia at the LAU2 administrative level (first and last 10 lines)
Country / Region / Year / Population / Quality / Comment / SourceSK / 528595 / 2005 / 42241 / A / Bratislava - Staré Mesto / Statistical Office SR
SK / 529311 / 2005 / 19977 / A / Bratislava - Podunajské Biskupice / Statistical Office SR
SK / 529320 / 2005 / 69674 / A / Bratislava - Ružinov / Statistical Office SR
SK / 529338 / 2005 / 18996 / A / Bratislava - Vrakuňa / Statistical Office SR
SK / 529346 / 2005 / 37040 / A / Bratislava - Nové Mesto / Statistical Office SR
SK / 529354 / 2005 / 20357 / A / Bratislava - Rača / Statistical Office SR
SK / 529362 / 2005 / 4331 / A / Bratislava - Vajnory / Statistical Office SR
SK / 529401 / 2005 / 1005 / A / Bratislava - Devín / Statistical Office SR
SK / 529371 / 2005 / 15629 / A / Bratislava - Devínska Nová Ves / Statistical Office SR
SK / 529389 / 2005 / 34540 / A / Bratislava - Dúbravka / Statistical Office SR
...
SK / 543951 / 2005 / 2097 / A / Vojčice / Statistical Office SR
SK / 543969 / 2005 / 516 / A / Vojka / Statistical Office SR
SK / 543977 / 2005 / 777 / A / Zatín / Statistical Office SR
SK / 543985 / 2005 / 291 / A / Zbehňov / Statistical Office SR
SK / 543993 / 2005 / 404 / A / Zemplín / Statistical Office SR
SK / 544001 / 2005 / 964 / A / Zemplínska Nová Ves / Statistical Office SR
SK / 544019 / 2005 / 1487 / A / Zemplínska Teplica / Statistical Office SR
SK / 544027 / 2005 / 1138 / A / Zemplínske Hradište / Statistical Office SR
SK / 544035 / 2005 / 629 / A / Zemplínske Jastrabie / Statistical Office SR
SK / 544043 / 2005 / 489 / A / Zemplínsky Branč / Statistical Office SR
1.1.5Bulgaria
Population data were collected for every sub-region in Bulgaria (LAU1 administrative level), for 2005 from the Bulgarian National Statistical Office. A very detailed table containing data for 264 sub-regions was provided by UNWE, but unfortunately without a digital map of the contours of the administrative units. Digital map in shape format could be obtained only at the NUTS3 level (from GADM6), therefore the illustrative map below shows population map for Bulgaria at the NUTS3 level only. Part of the summary table of the collected population data is included in Table 5.
Fig. 5. Population map of Bulgaria at the NUTS3 administrative level
Table 5. Part of the population dataset for Bulgaria at the LAU1 administrative level (first and last 10 lines)
Country / Region / Year / Population / Quality / Comment / SourceBG / BLG01 / 2005 / 13114 / A / Bansko / Bulgarian National Statistical Institute
BG / BLG02 / 2005 / 9518 / A / Belitza / Bulgarian National Statistical Institute
BG / BLG03 / 2005 / 77462 / A / Blagoevgrad / Bulgarian National Statistical Institute
BG / BLG11 / 2005 / 32022 / A / Gotze Delchev / Bulgarian National Statistical Institute
BG / BLG13 / 2005 / 14593 / A / Gurmen / Bulgarian National Statistical Institute
BG / BLG28 / 2005 / 5852 / A / Kresna / Bulgarian National Statistical Institute
BG / BLG33 / 2005 / 57102 / A / Petritch / Bulgarian National Statistical Institute
BG / BLG37 / 2005 / 21591 / A / Razlog / Bulgarian National Statistical Institute
BG / BLG40 / 2005 / 42299 / A / Sandanski / Bulgarian National Statistical Institute
BG / BLG42 / 2005 / 17428 / A / Satovcha / Bulgarian National Statistical Institute
...
BG / SHU21 / 2005 / 6796 / A / Nikola Kozlevo / Bulgarian National Statistical Institute
BG / SHU22 / 2005 / 19141 / A / Novi Pazar / Bulgarian National Statistical Institute
BG / SHU23 / 2005 / 15855 / A / Veliki Preslav / Bulgarian National Statistical Institute
BG / SHU25 / 2005 / 7818 / A / Smjadovo / Bulgarian National Statistical Institute
BG / SHU30 / 2005 / 101515 / A / Shumen / Bulgarian National Statistical Institute
BG / JAM03 / 2005 / 4856 / A / Boljarovo / Bulgarian National Statistical Institute
BG / JAM07 / 2005 / 18303 / A / Elhovo / Bulgarian National Statistical Institute
BG / JAM22 / 2005 / 14538 / A / Straldja / Bulgarian National Statistical Institute
BG / JAM25 / 2005 / 29083 / A / Tundja / Bulgarian National Statistical Institute
BG / JAM26 / 2005 / 79314 / A / Yambol / Bulgarian National Statistical Institute
1.1.6Poland
Population data were collected by MEERI for every settlement in Poland (LAU2 administrative level), for year 2004 from the Central Statistical Office of Poland. In order to prepare the data utilizable for the USTUTT.TFU group developing the EcoSenseWeb software utility, the data for the statistical units were converted directly to the 50×50, 10×10 and 5×5 km2 grids at the EMEP projection compatible with the database incorporated in the EcoSenseWeb utility. An illustrative map below shows population distribution ofPoland in the 5×5 km2 EMEP grid.
Fig. 6. Population map of Poland in the 5×5 km2 EMEP grid.
1.1.7Tunisia
Population data were collected by LEGI-EPT for administrative units “Gouvernorat” equivalent to the NUTS3 level in Europe. Data were obtained from the Institut National de la Statistique (INS), for year 2005. Digital map including the contours of the same administrative units in the WGS84 coordinate system was also provided. An illustrative map below shows population map for Tunisia. The collected population data are tabulated in Table 6.
Fig. 7. Population map of Tunisia based on administrative units “Gouvernorat” equivalent to NUTS3 in Europe.
Table 6. Population dataset for Tunisia based on andministrative units “Gouvernorat”
Country / Region / Year / Population / Quality / Comment / SourceTN / TN.AN / 2005 / 435900 / A / Ariana / Institut National de la Statistique (INS)
TN / TN.BJ / 2005 / 304000 / A / Béja / Institut National de la Statistique (INS)
TN / TN.BA / 2005 / 520200 / A / Ben Arous / Institut National de la Statistique (INS)
TN / TN.BZ / 2005 / 529300 / A / Bizerte / Institut National de la Statistique (INS)
TN / TN.GB / 2005 / 345900 / A / Gabés / Institut National de la Statistique (INS)
TN / TN.GF / 2005 / 326000 / A / Gafsa / Institut National de la Statistique (INS)
TN / TN.JE / 2005 / 418100 / A / Jendouba / Institut National de la Statistique (INS)
TN / TN.KR / 2005 / 548200 / A / Kairouan / Institut National de la Statistique (INS)
TN / TN.KS / 2005 / 415700 / A / Kasserine / Institut National de la Statistique (INS)
TN / TN.KB / 2005 / 144400 / A / Kébili / Institut National de la Statistique (INS)
TN / TN.KF / 2005 / 258500 / A / Le Kef / Institut National de la Statistique (INS)
TN / TN.MH / 2005 / 381900 / A / Mahdia / Institut National de la Statistique (INS)
TN / TN.MN / 2005 / 341800 / A / Manubah / Institut National de la Statistique (INS)
TN / TN.ME / 2005 / 436700 / A / Médenine / Institut National de la Statistique (INS)
TN / TN.MS / 2005 / 466300 / A / Monastir / Institut National de la Statistique (INS)
TN / TN.NB / 2005 / 705000 / A / Nabeul / Institut National de la Statistique (INS)
TN / TN.SF / 2005 / 869400 / A / Sfax / Institut National de la Statistique (INS)
TN / TN.SZ / 2005 / 398400 / A / Sidi Bou Zid / Institut National de la Statistique (INS)
TN / TN.SL / 2005 / 233900 / A / Siliana / Institut National de la Statistique (INS)
TN / TN.SS / 2005 / 557100 / A / Sousse / Institut National de la Statistique (INS)
TN / TN.TA / 2005 / 143900 / A / Tataouine / Institut National de la Statistique (INS)
TN / TN.TO / 2005 / 98500 / A / Tozeur / Institut National de la Statistique (INS)
TN / TN.TU / 2005 / 986700 / A / Tunis / Institut National de la Statistique (INS)
TN / TN.ZA / 2005 / 163300 / A / Zaghouan / Institut National de la Statistique (INS)
1.1.8Morocco
Population data were collected by CDER for every province in Morocco (equivalent to LAU1 administrative level in Europe). Data were obtained from the Direction de la Statistique, for year 2004.The dataset includes population data for 61 provinces. Digital map including the contours of the same administrative units was also provided. An illustrative map below shows population map for Morocco. Parts of the summary table of the collected population data are included in Table 7.
Fig. 8. Population map of Morocco based on administrative units provinces, equivalent to LAU1 in Europe.
Table 7. Part of population dataset for Morocco based on administrative units provinces.
Country / Region / Year / Population / Quality / Comment / SourceMA / 01.066 / 2004 / 20513 / A / Aousserd / Direction de la Statistique
MA / 01.391 / 2004 / 78854 / A / Oued Ed-Dahab / Direction de la Statistique
MA / 02.121 / 2004 / 46129 / A / Boujdour / Direction de la Statistique
MA / 02.321 / 2004 / 210023 / A / Laâyoune / Direction de la Statistique
MA / 03.071 / 2004 / 43535 / A / Assa-Zag / Direction de la Statistique
MA / 03.221 / 2004 / 60426 / A / Es-Semara / Direction de la Statistique
MA / 03.261 / 2004 / 166685 / A / Guelmim / Direction de la Statistique
MA / 03.521 / 2004 / 70146 / A / Tan-Tan / Direction de la Statistique
MA / 03.551 / 2004 / 121618 / A / Tata / Direction de la Statistique
MA / 04.001 / 2004 / 487954 / A / Agadir-Ida ou Tanane / Direction de la Statistique
...
MA / 14.451 / 2004 / 259577 / A / Sefrou / Direction de la Statistique
MA / 14.591 / 2004 / 150422 / A / Moulay Yacoub / Direction de la Statistique
MA / 15.051 / 2004 / 395644 / A / Al Hoceïma / Direction de la Statistique
MA / 15.531 / 2004 / 668232 / A / Taounate / Direction de la Statistique
MA / 15.561 / 2004 / 743237 / A / Taza / Direction de la Statistique
MA / 16.151 / 2004 / 524602 / A / Chefchaouen / Direction de la Statistique
MA / 16.227 / 2004 / 97295 / A / Fahs Anjra / Direction de la Statistique
MA / 16.331 / 2004 / 472386 / A / Larache / Direction de la Statistique
MA / 16.511 / 2004 / 762583 / A / Tanger-Assilah / Direction de la Statistique
MA / 16.571 / 2004 / 613506 / A / Tétouan / Direction de la Statistique
1.1.9Egypt
No data received so far from Egypt.
1.1.10Neigbouring countries
Gridded population density data are available at the SEDAC website[8], with a spatial resolution of 2.5 minutes. The source and year of the raw data are well documented at the website. The average input resolution shows different levels of resolution for different countries. According to the USTUTT.TFU group, this data source is sufficient if the RS1d partners don’t have easily available data with higher resolution. The figure below shows screenshot for Latvia.
Fig. 9. Screenshot of the population density map of Latvia based on the SEDAC data (green: low density, blue: high density).
1.2Risk group fractions
In order to assess morbidity based on diseases connected to different age/symptom groups, information regarding the so called “Risk-Group-Fraction” (RGF), i.e.percentage of population in the country for each age/symptom groups were collected for several partner countries. The data collection results are summarized in Table 8. Default values for RGF available in EcoSense are average values for EU15 countries.
Table 8. Summary of risk group fractions in the RS1d countries (sources of data are commented)
Name / Age group / [%] default / [%] BG / [%] CZ / [%] HU / [%] MA / [%] SK / [%] TNInfants / 0-11 months / 0.9 / 0.95b / 1.0d / 1.85g / 1.00h
Children / 0 – 14 years / 17 / 14.94b / 16.6d / 31.2g / 16.59h / 24.00i
5 – 14 years / 11.2 / 10.38b / 11.8d / 21.3g / 11.77h / 10.51i,j
asthmatics / 2.24 / 2.34a / 2.53c / 1.5e;
4–6f
Adults / „adults“ / 81.7 / 81.25b
15 – 64 years / 67.2 / 71.02b / 68.2d / 63.2g / 71.67h / 66.39i
18 – 64 years / 64 / 67.21b / 64.4d / 56.8g / 67.22h / 55.66i,k
27 years and above / 70 / 68.33b / 65.4d / 44.7g / 64.04h / 45.58i,l
asthmatics / use defaultc
20 years and above with chronic respiratory symptoms / 24.5 / use defaultc
Asthmatics / asthmatics of total popul. / 4.5 / use defaultc / 1.58d
Elderly / 65 years and above / 15.8 / 15.05b / 15.2d / 5.6g / 11.74h / 6.89i
Baseline mortality / 0.0099 / 0.0105b / 0.0108d / 0.01h / 0.0059i
a National Health Information Center, Bulgaria, 2005