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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 �������� Acid-
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40 ����������
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42 ����������
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44 �� Industrial Processes 1% N
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46 ����� 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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80 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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90 SO2, Gg____ NOx, Gg_____ Fuel co
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92 SO2, Gg____ NOx, Gg_____ Fuel co
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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 � � � 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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216 Table 4.3 Emission factors for
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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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276 Table 7.8 Emission factors for
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278 Table 7.9b Total national emiss
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280 Table 7.10a Total national emis
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282 Table 7.11 Estimated uncertaint
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284 Table 7.13 Overview of yearly s
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286 Data Processing level 1 1. Accu
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288 Data Storage level 2 The full d
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290 Date=06%2F30%2F2004&_sk=9994499
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292 Amount composted, Gg 1200 1000
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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
- Page 314 and 315: Table 7.27a National emissions from
- Page 316 and 317: 314 Table 7.28b National emissions
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- Page 330 and 331: 328 the localisation of the Danish
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- Page 334 and 335: 332 the Energy Statistics for 2009
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- Page 384 and 385: Table 2A-4.9b PAH emission factors
- Page 386 and 387: Table 2A-4.10 Dioxin and HCB emissi
- Page 388 and 389: Table 2A-4.11a Dioxin and HCB emiss
- Page 390 and 391: Table 2A-4.12 NH3 emission factors
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396 national emissions in year t du
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398 ���������à S
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400 ���������à S
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402 ���������à S
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406 • Monthly reporting by e-mail
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408 �������à �
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410 �������à �
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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 household and garden
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Stock data for small boats and plea
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Ferry data: Sailing time (single tr
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Uncertainty estimation, NH3. 578 Ga
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Uncertainty estimation, Chromium. 5
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Uncertainty estimation, Lead. 582 G
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Uncertainty estimation, Flouranthen
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Uncertainty estimation, Benzo(g,h,i
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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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594 $QQH[ & %DFNJURXQG LQIRUPDWLRQ
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596 $QQH[ ± &RPSOHWHQHVV DQG XVH R
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598 Emissions from clinical, indust
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