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sector:ippu:bulk_products:handling_of_bulk_products:start [2021/04/14 06:43] – kotzulla | sector:ippu:bulk_products:handling_of_bulk_products:start [2022/02/24 09:42] – Unified citation EUROSTAT a/b gniffke | ||
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Official statistics are of limited use in determining handling of bulk products. There are only transport statistics available providing the amounts of several transported materials. | Official statistics are of limited use in determining handling of bulk products. There are only transport statistics available providing the amounts of several transported materials. | ||
- | During a research project carried out by (Müller-BBM) [((bibcite 1))], activity data was derived from primary statistical data from the Federal Statistical Office for Germany (Satistisches Bundesamt, Destatis) and the Federal Motor Transport Authority (Kraftfahrt-Bundesamt, | + | During a research project carried out by (Müller-BBM) [(MUELLERBBM2011)], activity data was derived from primary statistical data from the Federal Statistical Office for Germany (Satistisches Bundesamt, Destatis) and the Federal Motor Transport Authority (Kraftfahrt-Bundesamt, |
- | Here, for all years until 2009, the collection of data for transported goods followed the official **NST/R** (1968) **nomenclature and regulation** (Eurostat, | + | Here, for all years until 2009, the collection of data for transported goods followed the official **NST/R** (1968) **nomenclature and regulation** (Eurostat, |
- | As of 2010, statistical data following the newly implemented **NST-2007** [((bibcite 3))], [((bibcite 4))] **nomenclature and regulation** from Destatis and KBA is applied instead. | + | As of 2010, statistical data following the newly implemented **NST-2007** [(EUROSTAT2015b)], [(DESTATIS2013)] **nomenclature and regulation** from Destatis and KBA is applied instead. |
__Table 1: Overview of primary activity data sources over time__ | __Table 1: Overview of primary activity data sources over time__ | ||
- | ||= **1990-1996** || simplified estimates without differentiation of handled materials || | + | ^ |
- | ||= **1997-2009** || statistical data following NST/R nomenclature || | + | ^ |
- | ||= **as of 2010** || statistical data following NST-2007 nomenclature || | + | ^ |
Here, NST/R allowed the distribution of a broad variety of goods and materials (e.g. barley, corn, oats, rice, rye, and wheat), whereas NST-2007 provides only a very condensed list of classes of goods (e.g. ' | Here, NST/R allowed the distribution of a broad variety of goods and materials (e.g. barley, corn, oats, rice, rye, and wheat), whereas NST-2007 provides only a very condensed list of classes of goods (e.g. ' | ||
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For estimating the amount of moved bulk materials as well as emissions from the loading and unloading of bulk materials, these primary activity data (PAD, including the amounts of imported and exported goods as well as goods transported within Germany) have to be calculated from the amounts of transported goods: | For estimating the amount of moved bulk materials as well as emissions from the loading and unloading of bulk materials, these primary activity data (PAD, including the amounts of imported and exported goods as well as goods transported within Germany) have to be calculated from the amounts of transported goods: | ||
- | PAD< | + | <WRAP center round info 60%> |
+ | PAD< | ||
+ | </ | ||
with | with | ||
- | - PAD< | + | - PAD< |
- | - PAD< | + | - PAD< |
- | - PAD< | + | - PAD< |
As the basic statistics provide only total amounts of imported, exported and domestically transported dry goods without any distinction into bulk and packed goods, the shares of bulk goods had to be estimated via expert judgement during the workshop mentioned above. | As the basic statistics provide only total amounts of imported, exported and domestically transported dry goods without any distinction into bulk and packed goods, the shares of bulk goods had to be estimated via expert judgement during the workshop mentioned above. | ||
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So the activity data finally used for estimating specific particulate matter emissions for every bulk material is calculated as a specific share //s// of the amount of this material //i// loaded and/or unloaded within Germany: | So the activity data finally used for estimating specific particulate matter emissions for every bulk material is calculated as a specific share //s// of the amount of this material //i// loaded and/or unloaded within Germany: | ||
- | [[math]] | + | <WRAP center round info 60%> |
- | \begin{gather} | + | AD< |
- | AD_\text{ | + | </WRAP> |
- | \end{gather} | + | |
- | [[/math]] | + | |
- | __Table 2: Amounts of dry, dusty bulk goods handled in Germany 2010-2018, in tonnes__ | + | __Table 2: Amounts of dry, dusty bulk goods handled in Germany 2010-2019, in tonnes__ |
- | ||= **Product / Good / Material** ||= **Mode of transport** ||= **2010** ||= **2011** ||= **2012** ||= **2013** ||= **2014** ||= **2015** ||= **2016** ||= **2017** ||= **2018** ||= | + | | |
- | ||~ other herbal products ||< inland vessel ||> 5,523,633 ||> | + | ^ other herbal products |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ raw mineral chemicals ||< inland vessel ||> 6,794,922 ||> | + | ^ raw mineral chemicals |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ raw organic chemicals ||< inland vessel ||> 6,299,350 ||> | + | ^ raw organic chemicals |
- | ||< | + | | ::: |
- | ||< ||< heavy-duty vehicle ||> 11,345,600 ||> | + | | ::: |
- | ||< | + | | ::: |
- | ||~ iron ore ||< inland vessel ||> 25,728,177 ||> | + | ^ iron ore |
- | ||< ||< railways ||> 38,565,334 ||> | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ crops ||< inland vessel ||> 9,816,233 ||> | + | ^ crops | inland vessel |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ potatoes ||< inland vessel ||> 1,383 ||> | + | ^ potatoes |
- | ||< ||< railways ||> 17,135 ||> | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ coal products ||< inland vessel ||> 2,409,311 ||> | + | ^ coal products |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ proiducts | + | ^ products |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< ||< sea-going vessel ||> 3,104,125 ||> | + | | ::: |
- | ||~ mineral fertilisers ||< inland vessel ||> 760,174 ||> | + | ^ mineral fertilisers |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ natural sands, gravel and stones ||< inland vessel ||> 40,518,020 ||> | + | ^ natural sands, gravel and stones |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ non-iron ores ||< inland vessel ||> 1,512,246 ||> | + | ^ non-iron ores | inland vessel |
- | ||< ||< railways ||> 29,742 ||> | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ raw coals ||< inland vessel ||> 36,652,759 ||> | + | ^ raw coals | inland vessel |
- | ||< | + | | ::: |
- | ||< ||< heavy-duty vehicle ||> 10,561,400 ||> | + | | ::: |
- | ||< ||< sea-going vessel ||> 13,299,295 ||> | + | | ::: |
- | ||~ secondary raw materials ||< inland vessel ||> 15,691,876 ||> | + | ^ secondary raw materials |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< ||< sea-going vessel ||> 5,047,097 ||> | + | | ::: |
- | ||~ rock & saline salt ||< inland vessel ||> 2,769,356 ||> | + | ^ rock & saline salt |
- | ||< ||< railways ||> 3,067,187 ||> | + | | ::: |
- | ||< ||< heavy-duty vehicle ||> 21,579,000 ||> | + | | ::: |
- | ||< ||< sea-going vessel ||> 567,059 ||> | + | | ::: |
- | ||~ noítrogen | + | ^ nitrogen |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ white cement, lime, cement ||< inland vessel ||> 3,273,975 ||> | + | ^ white cement, lime, cement |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||~ sugar beet ||< inland vessel ||> 0 ||> | + | ^ sugar beet |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
- | ||< | + | | ::: |
sources: annual data deliveries DESTATIS & KBA (for heavy-duty vehicles) to the inventory compiler | sources: annual data deliveries DESTATIS & KBA (for heavy-duty vehicles) to the inventory compiler | ||
=== Emission factors === | === Emission factors === | ||
- | Emission factors are based on the methodology according VDI guidelines 3790. The values used here originate from a research project by (Müller-BBM, | + | Emission factors are based on the methodology according VDI guidelines 3790. The values used here originate from a research project by (Müller-BBM, |
Within the study, PM emission factors are estimated for each material or good that might be transported as dry and unpacked bulk. These very specific EF are than assigned to the classes of materials/ | Within the study, PM emission factors are estimated for each material or good that might be transported as dry and unpacked bulk. These very specific EF are than assigned to the classes of materials/ | ||
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__Table 2: specific EF for PM emissions from NST/R crop products, in [kg/t], as used for 2009 estimates__ | __Table 2: specific EF for PM emissions from NST/R crop products, in [kg/t], as used for 2009 estimates__ | ||
- | ||= **vehicle type** ||= **TSP** ||= **PM,, | + | |
- | ||||||||= **for barley** || | + | | |
- | ||< inland ship ||> 0.038 ||> 0.019 ||> 0.004 ||> | + | | for barley |
- | ||< railway ||> 0.038 ||> 0.019 ||> 0.004 ||> | + | ^ inland ship | 0.038 | 0.019 | 0.004 | |
- | ||< maritime ship ||> 0.038 ||> 0.019 ||> 0.0038 ||> | + | ^ railway |
- | ||< heavy-duty vehicle ||> 0.038 ||> 0.019 ||> 0.004 ||> | + | ^ maritime ship | 0.038 | 0.019 | |
- | ||||||||= **for oats** || | + | ^ heavy-duty vehicle |
- | ||< inland ship ||> 0.018 ||> 0.009 ||> 0.002 ||> | + | | for oats |||| |
- | ||< railway ||> 0.018 ||> 0.009 ||> 0.002 ||> | + | ^ inland ship | 0.018 | 0.009 | 0.002 | |
- | ||< maritime ship ||> 0.018 ||> 0.009 ||> 0.00179 ||> | + | ^ railway |
- | ||< heavy-duty vehicle ||> 0.018 ||> 0.009 ||> 0.002 ||> | + | ^ maritime ship | 0.018 | 0.009 | 0.00179 | |
- | ||||||||= **for corn** || | + | ^ heavy-duty vehicle |
- | ||< inland ship ||> 0.029 ||> 0.014 ||> 0.003 ||> | + | | for corn |||| |
- | ||< railway ||> 0.029 ||> 0.014 ||> 0.003 ||> | + | ^ inland ship | 0.029 | 0.014 | 0.003 | |
- | ||< maritime ship ||> 0.029 ||> 0.014 ||> 0.00287 ||> | + | ^ railway |
- | ||< heavy-duty vehicle ||> 0.029 ||> 0.014 ||> 0.003 ||> | + | ^ maritime ship | 0.029 | 0.014 | 0.00287 | |
- | ||||||||= **for rice** || | + | ^ heavy-duty vehicle |
- | ||< inland ship ||> 0.015 ||> 0.008 ||> 0.002 ||> | + | | for rice |||| |
- | ||< railway ||> 0.015 ||> 0.008 ||> 0.002 ||> | + | ^ inland ship | 0.015 | 0.008 | 0.002 | |
- | ||< maritime ship ||> 0.015 ||> 0.008 ||> 0.00151 ||> | + | ^ railway |
- | ||< heavy-duty vehicle ||> 0.015 ||> 0.008 ||> 0.002 ||> | + | ^ maritime ship | 0.015 | 0.008 | 0.00151 | |
- | ||||||||= **for rye** || | + | ^ heavy-duty vehicle |
- | ||< inland ship ||> 0.038 ||> 0.019 ||> 0.004 ||> | + | | for rye |
- | ||< railway ||> 0.038 ||> 0.019 ||> 0.004 ||> | + | ^ inland ship | 0.038 | 0.019 | 0.004 | |
- | ||< maritime ship ||> 0.038 ||> 0.019 ||> 0.0038 ||> | + | ^ railway |
- | ||< heavy-duty vehicle ||> 0.038 ||> 0.019 ||> 0.004 ||> | + | ^ maritime ship | 0.038 | 0.019 | |
- | ||||||||= **for wheat** || | + | ^ heavy-duty vehicle |
- | ||< inland ship ||> 0.038 ||> 0.019 ||> 0.004 ||> | + | | for wheat |
- | ||< railway ||> 0.038 ||> 0.019 ||> 0.004 ||> | + | ^ inland ship | 0.038 | 0.019 | 0.004 | |
- | ||< maritime ship ||> 0.038 ||> 0.019 ||> 0.0038 ||> | + | ^ railway |
- | ||< heavy-duty vehicle ||> 0.038 ||> 0.019 ||> 0.004 ||> | + | ^ maritime ship | 0.038 | 0.019 | |
+ | ^ heavy-duty vehicle | ||
Here, in order to match the new NST-2007 classes for goods and materials, the very specific emission factors used in fomer submissions were converted to aggregated implied emission factors. | Here, in order to match the new NST-2007 classes for goods and materials, the very specific emission factors used in fomer submissions were converted to aggregated implied emission factors. | ||
__Table 3: IEFs used for emission estimates as of 2010, in [kg/t]__ | __Table 3: IEFs used for emission estimates as of 2010, in [kg/t]__ | ||
- | ||= **Product / Good / Material** ||||||= **Heavy-duty vehicles** ||||||= **Railways** ||||||= **Inland vessels** ||||||= **Sea-going | + | | ^ |
- | ||= ||= TSP ||= PM,,10,, ||= PM,,2.5,, ||= TSP ||= PM,,10,, ||= PM,,2.5,, ||= TSP ||= PM,,10,, ||= PM,,2.5,, ||= TSP ||= PM,,10,, ||= PM,,2.5,, ||= | + | | | TSP | PM<sub>10</ |
- | ||~ Other herbal products ||> 0.032000 ||> 0.016000 ||> 0.003200 ||> 0.024000 ||> 0.012000 ||> 0.002400 ||> 0.022000 ||> 0.011000 ||> 0.002200 ||> 0.028000 ||> 0.014000 ||> 0.002800 ||> | + | ^ Other herbal products |
- | ||~ Chemische Grundstoffe. mineralisch ||> 0.041000 ||> 0.020500 ||> 0.004100 ||> 0.031000 ||> 0.015500 ||> 0.003100 ||> 0.029000 ||> 0.014500 ||> 0.002900 ||> 0.036000 ||> 0.018000 ||> 0.003600 ||> | + | ^ Chemische Grundstoffe. mineralisch |
- | ||~ Raw organic chemicals ||> 0.024000 ||> 0.012000 ||> 0.002400 ||> 0.018000 ||> 0.009000 ||> 0.001800 ||> 0.017000 ||> 0.008500 ||> 0.001700 ||> 0.021000 ||> 0.010500 ||> 0.002100 ||> | + | ^ Raw organic chemicals |
- | ||~ Iron ore ||> 0.057000 ||> 0.028500 ||> 0.005700 ||> 0.042000 ||> 0.021000 ||> 0.004200 ||> 0.040000 ||> 0.020000 ||> 0.004000 ||> 0.050000 ||> 0.025000 ||> 0.005000 ||> | + | ^ Iron ore | 0.057000 |
- | ||~ Crops ||> 0.045000 ||> 0.022500 ||> 0.004500 ||> 0.034000 ||> 0.017000 ||> 0.003400 ||> 0.031000 ||> 0.015500 ||> 0.003100 ||> 0.039000 ||> 0.019500 ||> 0.003900 ||> | + | ^ Crops |
- | ||~ Potatoes ||> 0.007000 ||> 0.003500 ||> 0.000700 ||> 0.005000 ||> 0.002500 ||> 0.000500 ||> 0.005000 ||> 0.002500 ||> 0.000500 ||> 0.006000 ||> 0.003000 ||> 0.000600 ||> | + | ^ Potatoes |
- | ||~ Coal products ||> 0.019000 ||> 0.009500 ||> 0.001900 ||> 0.014000 ||> 0.007000 ||> 0.001400 ||> 0.013000 ||> 0.006500 ||> 0.001300 ||> 0.017000 ||> 0.008500 ||> 0.001700 ||> | + | ^ Coal products |
- | ||~ Products from grinding and shelling mills ||> 0.003000 ||> 0.001500 ||> 0.000300 ||> 0.003000 ||> 0.001500 ||> 0.000300 ||> 0.003000 ||> 0.001500 ||> 0.000300 ||> 0.003000 ||> 0.001500 ||> 0.000300 ||> | + | ^ Products from grinding and shelling mills |
- | ||~ Mineral fertilisers ||> 0.024000 ||> 0.012000 ||> 0.002400 ||> 0.018000 ||> 0.009000 ||> 0.001800 ||> 0.017000 ||> 0.008500 ||> 0.001700 ||> 0.021000 ||> 0.010500 ||> 0.002100 ||> | + | ^ Mineral fertilisers |
- | ||~ Natural sands. gravel. and stones ||> 0.027000 ||> 0.013500 ||> 0.002700 ||> 0.020000 ||> 0.010000 ||> 0.002000 ||> 0.019000 ||> 0.009500 ||> 0.001900 ||> 0.023000 ||> 0.011500 ||> 0.002300 ||> | + | ^ Natural sands. gravel. and stones |
- | ||~ Non-iron ores ||> 0.066000 ||> 0.033000 ||> 0.006600 ||> 0.049000 ||> 0.024500 ||> 0.004900 ||> 0.046000 ||> 0.023000 ||> 0.004600 ||> 0.058000 ||> 0.029000 ||> 0.005800 ||> | + | ^ Non-iron ores |
- | ||~ Raw coals ||> 0.016000 ||> 0.008000 ||> 0.001600 ||> 0.016000 ||> 0.008000 ||> 0.001600 ||> 0.020000 ||> 0.010000 ||> 0.002000 ||> 0.028000 ||> 0.014000 ||> 0.002800 ||> | + | ^ Raw coals |
- | ||~ Secondary raw materials ||> 0.027000 ||> 0.013500 ||> 0.002700 ||> 0.020000 ||> 0.010000 ||> 0.002000 ||> 0.019000 ||> 0.009500 ||> 0.001900 ||> 0.023000 ||> 0.011500 ||> 0.002300 ||> | + | ^ Secondary raw materials |
- | ||~ Rock & saline salt ||> 0.068000 ||> 0.034000 ||> 0.006800 ||> 0.051000 ||> 0.025500 ||> 0.005100 ||> 0.047000 ||> 0.023500 ||> 0.004700 ||> 0.059000 ||> 0.029500 ||> 0.005900 ||> | + | ^ Rock & saline salt | 0.068000 |
- | ||~ Nitrogen fertilisers ||> 0.024000 ||> 0.012000 ||> 0.002400 ||> 0.018000 ||> 0.009000 ||> 0.001800 ||> 0.017000 ||> 0.008500 ||> 0.001700 ||> 0.021000 ||> 0.010500 ||> 0.002100 ||> | + | ^ Nitrogen fertilisers |
- | ||~ White cement. lime. cement ||> 0.005000 ||> 0.002500 ||> 0.000500 ||> 0.004000 ||> 0.002000 ||> 0.000400 ||> 0.003000 ||> 0.001500 ||> 0.000300 ||> 0.004000 ||> 0.002000 ||> 0.000400 ||> | + | ^ White cement. lime. cement |
- | ||~ Sugar beet ||> 0.000240 ||> 0.000120 ||> 0.000024 ||> 0.000180 ||> 0.000090 ||> 0.000018 ||> 0.000170 ||> 0.000085 ||> 0.000017 ||> 0.000210 ||> 0.000105 ||> 0.000021 ||> | + | ^ Sugar beet | 0.000240 |
- | +++ Ratio TSP : PM,,10,, : PM,,2.5,, | ||
- | The shares of | + | ** Ratio TSP : PM<sub>10</ |
- | Assumptions: | + | The shares |
- | * TSP = 100%, | + | |
- | * 50% of TSP are =< 10 µm. Therefore, the EF(PM,, | + | |
- | * 10% of TSP are =< 2.5 µm. Therefore, the EF(PM,, | + | |
- | [[image | + | Assumptions: |
+ | - TSP = 100%, | ||
+ | - 50% of TSP are =< 10 µm. Therefore, the EF(PM< | ||
+ | | ||
- | The ratios of TSP, PM,,10,,, and PM,,2.5,, were also discussed in the research project mentioned above, but without generating any new data. Nonetheless, | + | The ratios of TSP, PM<sub>10</ |
+ | ===== Recalculations ===== | ||
- | ===== Discussion | + | As for submission 2021 activity data for 2019 could not be derived from national statistics, amounts |
+ | With the current submission, these data are replaced with original 2019 activity data, resulting in correspondingly revised | ||
- | > **NFR 2.L(a)** is key category for **PM,,2.5,,**, **PM,,10,,**, and **TSP**. | + | __table: Revised amounts of bulk goods transported in 2019, in tonnes__ |
+ | | ^ Submission 2021 ^ Submission 2022 ^ absolute change | ||
+ | ^ other herbal products | ||
+ | | ::: | 445,547 | 613,000 | 167,453 | 38% | | ||
+ | | ::: | | ||
+ | | ::: | 6,614,999 | 6,067,598 | | ||
+ | ^ raw mineral chemicals | ||
+ | | ::: | | ||
+ | | ::: | | ||
+ | | ::: | 7,386,700 | 4,839,421 | -2,547,279 | -34% | | ||
+ | ^ raw organic chemicals | ||
+ | | ::: | 0 | | ||
+ | | ::: | | ||
+ | | ::: | 2,463,615 | 2,623,994 | 160,379 | 7% | | ||
+ | ^ iron ore | ||
+ | | ::: | | ||
+ | | ::: | 1,680,885 | 731,400 | | ||
+ | | ::: | | ||
+ | ^ crops | 7,715,977 | 8,128,252 | 412,275 | 5% | | ||
+ | | ::: | 2,985,786 | 3,169,000 | 183,214 | 6% | | ||
+ | | ::: | 58,957,570 | 56,315,100 | | ||
+ | | ::: | 7,672,262 | 7,985,888 | 313,626 | 4% | | ||
+ | ^ potatoes | ||
+ | | ::: | 4,896,748 | 0 | | ||
+ | | ::: | 9,621,800 | 4,789,300 | | ||
+ | | ::: | | ||
+ | ^ coal products | ||
+ | | ::: | 8,421,754 | 6,743,000 | | ||
+ | | ::: | | ||
+ | | ::: | | ||
+ | ^ products from grinding | ||
+ | | ::: | 349,419 | 645,000 | 295,581 | 85% | | ||
+ | | ::: | | ||
+ | | ::: | 3,788,108 | 4,001,310 | 213,202 | 6% | | ||
+ | ^ mineral fertilisers | ||
+ | | ::: | 3,224,654 | 2,756,000 | | ||
+ | | ::: | 1,814,964 | 1,423,800 | | ||
+ | | ::: | 311,822 | 392,516 | | ||
+ | ^ natural sands, gravel and stones | ||
+ | | ::: | | ||
+ | | ::: | 1, | ||
+ | | ::: | | ||
+ | ^ non-iron ores | 3,043,062 | 2,749,584 | | ||
+ | | ::: | | ||
+ | | ::: | 512,051 | 0 | | ||
+ | | ::: | 4,621,799 | 3,488,596 | | ||
+ | ^ raw coals | | ||
+ | | ::: | | ||
+ | | ::: | | ||
+ | | ::: | | ||
+ | ^ secondary raw materials | ||
+ | | ::: | | ||
+ | | ::: | 502,448,809 | 175,973,100 | | ||
+ | | ::: | 3,427,249 | 3,502,952 | | ||
+ | ^ rock & saline salt | ||
+ | | ::: | 3,017,352 | 2,673,000 | | ||
+ | | ::: | | ||
+ | | ::: | 1,116,411 | 961,803 | | ||
+ | ^ nitrogen fertilisers | ||
+ | | ::: | | ||
+ | | ::: | | ||
+ | | ::: | 7,239,705 | 7,385,920 | 146,215 | 2% | | ||
+ | ^ white cement, lime, cement | ||
+ | | ::: | | ||
+ | | ::: | | ||
+ | | ::: | 2,172,344 | 1,972,384 | | ||
+ | ^ sugar beet | ||
+ | | ::: | 0 | 2,000 | 2,000 | | | ||
+ | | ::: | | ||
+ | | ::: | 3,277 | 0 | | ||
- | In general, diffuse particulate matter emissions depend strongly on the amounts of dry bulk goods handled and transported. In addition, due to efforts to prevent such particle emissions, the time series of the emission factors applied for all three fractions of particulate matter show a falling trend. | ||
- | ===== Recalculations ===== | + | __table: Revised particulate matter emissions from of bulk goods transported in 2019, in kilotonnes__ |
+ | | ^ PM< | ||
+ | ^ current submission | ||
+ | ^ previous submission | ||
+ | ^ absolute change | ||
+ | ^ relative change | ||
- | With both **activity data** and **emission factors** remaining unrevised, no recalculations have been carried out. | ||
===== Planned improvements ===== | ===== Planned improvements ===== | ||
Line 217: | Line 290: | ||
Although no specific improvement is planned, additional effort will be necessary to further minimise the inconsistencies in the activity data time series resulting from the different approaches applied. | Although no specific improvement is planned, additional effort will be necessary to further minimise the inconsistencies in the activity data time series resulting from the different approaches applied. | ||
- | ------ | ||
- | [[bibliography]] | + | |
- | : 1 : Müller-BBM, | + | [(MUELLERBBM2011> |
- | : 2 : Eurostat, 2015a: Standard Goods Classification for Transport Statistics/ | + | [(EUROSTAT2015a> |
- | : 3 : Eurostat, 2015b: Standard | + | [(EUROSTAT2015b> |
- | : 4 : Destatis, 2013: Statistisches Bundesamt, Verkehr, NST-2007: Einheitliches Güterverzeichnis für die Verkehrsstatistik – 2007 - URL: https:// | + | [(DESTATIS2013> |
- | [[/ | + |