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Ã describes the average share of building fires from 2007-2010 of a certain type and size, in relation to all building fires in the same four years period. ÃÃÃÃÃÃÃÃÃÉÃ Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÆÃ Ã Ã Ã Ã Ã Ã Ã Ã It is assumed that the average percentages provided by the years 2007-2010 shown in Table 7.15 are compliable for the years 1980-2006. Hereby, similar activity data for building fires can be estimated back to 1980. By applying the damage rates of 100 %, 75 %, 30 % and 5 % corresponding to the damage sizes full, large, medium and small, a full scale equivalent can be determined. Table 7.16 shows the calculated full scale equivalents (FSE). The full time series is shown in Annex 2D-8.
Ã ÃÃÃÃÃÃÃÃÃÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã ÃÃÃ Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã The numbers of FSE of the different building categories are lower in this year’s submission compared to last year’s. This is due to two different changes that were implemented this year. Firstly, the introduction of the additional buildings category means that buildings like e.g. garages and sheds have been moved from detached houses to additional buildings. Secondly, the damage rates have been changed from large, medium and small of respectively 100 %, 50 % and 5 % to full, large, medium and small of respectively 100 %, 75 %, 30 % and 5 % The amount of detailed activity data is still limited due to the few years of reported data in the ODIN system, during the next years more data will become available providing a better basis for extrapolating back in time. &NJTTJPO GBDUPST For building fires, emissions are calculated by multiplying the number of full scale equivalent fires with the emission factors. The estimation of emissions is based on emission factors from literature. The estimation is based on the measurements and estimations performed in countries that are comparable to Denmark. By comparable is meant countries that have similar building traditions, in relation to the material used in building structure and interior. In the process of selecting the best reliable emission factors for the calculation of the emissions from Danish accidental building fires, a range of different sources have been studied. Unfortunately it is difficult to do an interrelated comparison of the different sources because they all establish emission factors on different assumptions and many of these assumptions are not fully accounted for. Table 7.17 lists the emission factors that were chosen for 2010 as the best reliable and their respective references.
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ANNUAL DANISH INFORMATIVE INVENTORY
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AU ANNUAL DANISH INFORMATIVE INVENT
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Wood combustion in residential plan
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to an error F28 was previously used
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eduction in emission of about 50 %
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elative bidrag for SO2, NOx og NH3
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holdningsanlæg (78 % i 2010). Emis
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tige syn i 2008. Opdaterede oplysni
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QA/QC plan (Chapter 1.5), the data
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of round trips per ferry, engine si
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sion. Simple mass balances for calc
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Ã *OEVTUSJBM QSPDFTTFT Categories
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Nielsen, O.-K., Mikkelsen, M.H., Ho
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42 Figure 2.1 Emissions of NH3, NOX
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44 Figure 2.4 NH3 emissions. Distri
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46 Figure 2.8 PM2.5 emissions. Dist
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48 Figure 2.11 Pb emissions. Time s
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Table 3.2 SO2, NOx, NMVOC, CO and P
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Ã ÃÃÃÃ 1A1c Manufacture of sol
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Fuel consumption, PJ Fuel consumpti
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creased 6 % since 2009. The biomass
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&NJTTJPOT 40 Stationary combustion
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emission from electricity and heat
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NMVOC, Gg 25 20 15 10 5 0 1985 1986
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accounting for 94 % of the PM2.5 em
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PM, Gg PM 2.5, Gg 30 25 20 15 10 5
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ÃÃÃÃÃÃÃÃÃÃ Ã ÃÃÃÆÃ
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Ã ÃÃÃÃÃÃÃÃÃÃ Ã ÃÃ Ã
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200 180 Ã 160 140 120 100 80 60
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Ã 0.025 0.020 Ã 0.015 Ã 0.010
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Ã Ã 25 20 Ã Ã 15 10 Ã
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The total fuel consumption in indus
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0.4 Ã 0.3 Ã 0.2 0.1 Ã Ã
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0.035 0.030 0.025 Ã 0.020 Ã 0.0
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Ã 0.30 Ã Ã 0.25 0.20
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120 Ã 100 80 60 Ã 40
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16 Ã 14 12 10 8 Ã 6
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• Emission data reported from ind
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Due to the scarce data available an
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• Research carried out by TNO (Be
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Ã ÃÃÃÃÃÃÃÃÃÃÃ Ã Ã Ã
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Christiansen, B.H., Evald, A., Baad
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Danish Environmental Protection Age
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Ã 160 140 120 100 80 60 40 20 0
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3- 5 4,5 4 3,5 3 2,5 2 1,5 1 0,5 0
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Ã Ã Ã Ã ment in emission factor
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ÃÉÃ ÃÉÃ Passenger cars 69% 2-
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Ã 1200 1000 Ã 800 Ã 600 Ã
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For all vehicle categories/technolo
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(EMEP/EEA, 2009) for air traffic, o
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Ã
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total emissions (in grams) from the
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Ã Further, the Marine Environment
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European measurement programmes; se
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For gasoline, the DEA residential s
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ANNUAL DANISH INFORMATIVE INVENTORY
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