Annual Danish informative inventory report to UNECE. Emission ...

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328 the localisation of the Danish road network and the large residential areas with single family houses. As already mentioned the total SO2 emission for Denmark has decreased significantly since 1990. The total emission of SO2 in 2005 corresponds to approx. 12 % of the total SO2 emission in 1990. The spatially distributed pattern of SO2 in 1990 is illustrated in Figure 8.2. For making comparisons between the two reporting years – see also Figure 8.1. Figure 8.2 Spatial pattern of the total annual SO2 emission in Denmark in 1990. 5HIHUHQFHV Jensen, M.T., Nielsen, O-K., Mikkelsen, M.H., Winther, M., Gyldenkærne, S., Viuf, P.Ø. & Illerup J.B., 2008: Rapportering af Luftemissioner på Grid – Metoder og Principper. Danmarks Miljøundersøgelser, Århus Universitet. 58 s. – Faglig rapport fra DMU nr. 654. (report in Danish). Available at: http://www2.dmu.dk/Pub/FR654.pdf (11-01-2010). Mikkelsen M.H., Gyldenkærne, S., Poulsen, H.D., Olesen, J.E. & Sommer, S.G., 2006: Emission of ammonia, nitrous oxide and methane from Danish Agriculture 1985 – 2002. Methodology and Estimates. National Environmental Research Institute, Denmark. 90 pp –Research Notes from NERI No. 231. Available at: http://www2.dmu.dk/Pub/AR231.pdf (11-01-2010). UN, 2003: Guidelines for Estimating and Reporting Emission Data under the Convention on Long-range Transboundary Air Pollution. Air Pollution Studies No. 15. Economic Commission for Europe. United Nations. Available at: http://www.unece.org/env/documents/2003/eb/air/ece.eb.air.80.E.p df (11-01-2010).
5HFDOFXODWLRQV DQG ,PSURYHPHQWV In general, considerable work is being carried out to improve the inventories. Investigations and research carried out in Denmark and abroad produce new results and findings which are given consideration and, to the extent which is possible, are included as the basis for emission estimates and as data in the inventory databases. Furthermore, the updates of the EMEP/CORINAIR guidebook (Now the EMEP/EEA Guidebook), and the work of the Task Force on Emission Inventories and its expert panels are followed closely in order to be able to incorporate the best scientific information as the basis for the inventories. The further important references in this regard are the IPCC guidelines and IPCC good practice guidance. The implementation of new results in inventories is made in a way so that improvements, as far as possible, better reflect Danish conditions and circumstances. This is in accordance with good practice. Furthermore, efforts are made to involve as many experts as possible in the reasoning, justification and feasibility of implementation of improvements. In improving the inventories, care is taken to consider implementation of improvements for the whole time-series of inventories to make it consistent. Such efforts lead to recalculation of previously submitted inventories. This submission includes recalculated inventories for the whole time-series. The reasoning for the recalculations performed is to be found in the sectoral chapters of this report. The text below focuses on recalculations, in general, and further serves as an overview and summary of the relevant text in the sectoral chapters. For sector specific planned improvements please also refer to the relevant sectoral chapters. (QHUJ\ Improvements and updates of the Danish energy statistics are made regularly by the producer of the statistics, the Danish Energy Agency. In close cooperation with the DEA, these improvements and updates are reflected in the emission inventory for the energy sector. The Danish energy statistics have, for the most part, been aggregated to the SNAP categorisation. This, however, does not include energy statistics for fuel consumption data for specific industries. The inventories are still being improved through work to increase the number of large point sources, e.g. power plants, included in the databases as individual point sources. Such an inclusion makes it possible to use plant-specific data for emissions, etc, available e.g. in annual environmental reports from the plants in question. 6WDWLRQDU\ &RPEXVWLRQ Improvements and recalculations since the 2010 emission inventory submission include: 329
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ANNUAL DANISH INfORMATIVE INVENTORY
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AU ANNUAL DANISH INfORMATIVE INVENT
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&RQWHQWV 6XPPDU\ , %DFNJURXQG LQIRU
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Annex 2A-11 QA/QC for stationary co
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8 ,, 7UHQGV LQ HPLVVLRQV $FLGLI\LQJ
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10 reduced emissions is mainly incr
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12 Danish energy statistics have, f
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14 ,QGXVWULDO SURFHVVHV Recalculati
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16 ,, 8GYLNOLQJHQ L HPLVVLRQHU )RUV
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18 kilde til emission af kobber er
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20 6¡IDUW Brændselsforbrug for sk
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22 en stigning i NH3 emissionen for
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24 UNECE-LRTAP Convention of the An
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26 Table 1.1 List of current data s
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28 A list of all subsectors at the
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30 )XJLWLYH HPLVVLRQV IURP QDWXUDO
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32 Please refer to Chapter 5 for fu
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34 Table 1.2 Danish uncertainty est
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36 NR is used for pollutants prior
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38 ��Ã�� Acid-
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40 ��Ã��
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42 ��Ã��
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44 �� Industrial Processes 1% N
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46 �Ã�� Non-industrial
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48 Table 3.1 NFR source categories
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50 (PLVVLRQ VRXUFH FDWHJRULHV In th
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52 Fuel consumption, PJ Fuel consum
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54 sumption in ,QGXVWU\ in 2009 add
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56 (PLVVLRQV 62� Stationary combu
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58 the reduced emission from electr
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60 NMVOC, Gg 25 20 15 10 5 0 1990 1
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62 The primary sources of PM emissi
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64 PM, Gg PM 2.5, Gg 30 25 20 15 10
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66 Table 3.11 Decrease in heavy met
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68 3$+ Stationary combustion plants
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70 Benzo(a)pyrene Benzo(a)pyrene, M
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72 plants has increased due to incr
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74 Fuel consumption, PJ SO2, Gg____
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As, Mg_____ Cd, Mg_____ Cr, Mg_____
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78 SO2, Gg____ NOx, Gg_____ Fuel co
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82 Fuel consumption, PJ 90 80 70 60
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84 As, Mg_____ 0.00 0.05 0.10 0.15
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86 Fuel consumption, PJ 1A4 Other S
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88 As, Mg Cd, Mg Cr, Mg Cu, Mg Hg,
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94 software for inventories. The me
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96 Both traded and non-traded fuels
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98 ƒ Christiansen et al. (1997).
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100 The emission factors for decent
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102 Table 3.19 Danish uncertainty e
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104 Danish Energy Agency (DEA), 201
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106 Miljøstyrelsen (MST), 2010: An
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108 Table 3.20 SNAP - NFR correspon
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110 sumption development is due to
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112 these types of machinery, the D
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114 � � 5 4,5 4 3,5 3 2,5 2 1,5
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116 Table 3.22 Emissions of SO2, NO
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118 7RQQHV 600000 500000 400000 300
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120 7RQQHV 8000 7000 6000 5000 4000
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122 The TSP emission development fo
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124 Residential (1A4b) 0% Agr./for.
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126 Table 3.24 Heavy metal emission
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128 Navigation (1A3d) 79% Navigatio
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130 Table 3.25 Dioxin and PAH emiss
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132 Residential (1A4b) 2% Railways
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134 0HWKRGRORJLFDO LVVXHV The descr
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136 1200 1000 � � Ã � 800 Ã
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138 2000 � 1600 � Ã� Ã� 1
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140 Table 3.28 Overview of the exis
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142 8') 8 ⋅ 07& + 8 = , MTC < UMA
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144 (YDSRUDWLYH HPLVVLRQV IURP JDVR
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146 The final fuel use and emission
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148 Figure 3.87 Most frequent domes
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150 No. No. 30000 25000 20000 15000
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152 [No] 4500 4000 3500 3000 2500 2
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154 ��
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156 Table 3.30 Domestic ferry route
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158 national sea transport in the D
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160 Table 3.32 Overview of the EU E
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Table 3.35 Current certification li
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164 Table 3.37 Current legislation
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166 Table 3.38 Fuel based emission
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168 1RQ URDG ZRUNLQJ PDFKLQHU\ DQG
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170 ( = )& ⋅ () (27) where E = em
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172 tions, transport to Greenland a
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174 5RDG WUDQVSRUW The total mileag
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176 Delvig, P. 2010: Unpublished da
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178 Winther, M. 2005: Kyoto notat -
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180 Table 3.41 Summary of the Danis
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182 2IIVKRUH DFWLYLWLHV Fugitive em
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184 Coal import, Gg . 16000 14000 1
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186 gasoline sales show an increase
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188 Venting in gas treatment and st
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190 and Kilde (1994) for the years
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192 Table 3.48 Emission factors for
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194 Table 3.54 Emissions of NMVOC f
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196 and initialisation of new facil
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198 Table 3.59 Estimated emission u
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200 Extraction of oil and gas: fugi
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202 OleQGU\ QVNL � ' EVNL % 6NR V
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204 Table 4.1 Survey of industrial
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206 Table 4.2 Time-series for pollu
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208 financial crises. During the sa
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210 1 1 1 1 1 0 0 0 0 0 &KHPLFDO LQ
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212 they have not been subject to t
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214 Denmark. The emission of TSP an
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218 2WKHU SURGXFWLRQ FRQVXPSWLRQ VW
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220 Nielsen, O.-K., Lyck, E., Mikke
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222 products is derived from Table
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224 kt NMVOC/year 60 50 40 30 20 10
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226 tained from the respective comp
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228 over several years so there wil
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230 8QFHUWDLQWLHV DQG WLPH VHULHV F
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232 powder consists of about 75 % o
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234 Passant et al. (2003) and Fyrve
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236 Table 5.9 Emission from firewor
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238 sumentfyrverkerier, Miljö Göt
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240 $JULFXOWXUH 1)5 VHFWRU 2YHUYLHZ
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242 Another important cause of the
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244 The emissions from agricultural
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246 Table 6.3 Livestock categories
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248 Table 6.4 Livestock production
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250 creasing. This is due to measur
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252 Table 6.7 Activity data used to
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254 Table 6.10 Activity data used t
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256 Table 6.13 Livestock categories
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258 Table 6.16 PM emission from hou
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260 swine production, etc to optimi
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262 ning, as given in the CLRTAP Em
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264 implemented NH3 reduction techn
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266 :DVWH 1)5 VHFWRU The waste sect
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268 0HWKRGRORJ\ +XPDQ FUHPDWLRQ The
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270 Even though the total number of
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272 statistic data show an increase
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274 an emission factor of 28 µg pr
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Page 280 and 281: 278 Table 7.9b Total national emiss
Page 282 and 283: 280 Table 7.10a Total national emis
Page 284 and 285: 282 Table 7.11 Estimated uncertaint
Page 286 and 287: 284 Table 7.13 Overview of yearly s
Page 288 and 289: 286 Data Processing level 1 1. Accu
Page 290 and 291: 288 Data Storage level 2 The full d
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Page 294 and 295: 292 Amount composted, Gg 1200 1000
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Page 300 and 301: 298 and 5 % of a large fire respect
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Page 304 and 305: 302 Table 7.21 Different types of n
Page 306 and 307: 304 Table 7.22 Average vehicle mass
Page 308 and 309: 306 Table 7.23 Emission factors bui
Page 310 and 311: 308 material estimated in Persson e
Page 312 and 313: 310 Table 7.26 Emission factors veh
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Page 316 and 317: 314 Table 7.28b National emissions
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Page 334 and 335: 332 the Energy Statistics for 2009
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378 Ã ÃÃ ÃÃ ÃÃ ÃÃ Benzo(a)
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Table 2A-4.9a PAH emission factors
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Table 2A-4.9b PAH emission factors
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Table 2A-4.10 Dioxin and HCB emissi
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Table 2A-4.11a Dioxin and HCB emiss
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Table 2A-4.12 NH3 emission factors
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02 MUNICIP. WASTES 44 STRAW 25 Hade
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396 national emissions in year t du
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400 ��Ã S
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402 ��Ã S
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406 • Monthly reporting by e-mail
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408 ��Ã��Ã �
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410 ��Ã��Ã �
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412 $QQH[ $ 7LPH VHULHV Fuel consum
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Table 6.1 List of external data sou
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416 however, included in the refere
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418 Data Processing level 1 3.Compl
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420 Some automated checks have been
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Stock data for small boats and plea
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Uncertainty estimation, Lead. 582 G
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Uncertainty estimation, Flouranthen
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588 Table 2C.1a Nitrogen excretion
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590 (PLVVLRQ RI 1+ � +RXVLQJ The
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592 $QQH[ & %DFNJURXQG LQIRUPDWLRQ
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598 Emissions from clinical, indust
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