Table of Contents

1.A.3.c - Transport: Railways

Short description

In category 1.A.3.c - Railways, emissions from fuel combustion in German railways and from the related abrasion and wear of contact line, braking systems and tyres on rails are reported.

Category Code Method AD EF
1.A.3.c T1, T2 NS, M CS, D, M
NOx NMVOC SO2 NH3 PM2.5 PM10 TSP BC CO PB Cd Hg Diox PAH HCB
Key Category: -/- -/- -/- -/- L/- L/- L/- -/- -/- -/- -/- -/- -/- -/- -/-

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T = key source by Trend L = key source by Level

Methods
D Default
T1 Tier 1 / Simple Methodology *
T2 Tier 2*
T3 Tier 3 / Detailed Methodology *
C CORINAIR
CS Country Specific
M Model
* as described in the EMEP/EEA Emission Inventory Guidebook - 2019, in the group specific chapters.
AD - Data Source for Activity Data
NS National Statistics
RS Regional Statistics
IS International Statistics
PS Plant Specific data
As Associations, business organisations
Q specific Questionnaires (or surveys)
M Model / Modelled
C Confidential
EF - Emission Factors
D Default (EMEP Guidebook)
C Confidential
CS Country Specific
PS Plant Specific data
M Model / Modelled


Germany's railway sector is undergoing a long-term modernisation process, aimed at making electricity the main energy source for rail transports. Use of electricity, instead of diesel fuel, to power locomotives has been continually increased, and electricity now provides 80% of all railway traction power. Railways' power stations for generation of traction current are allocated to the stationary component of the energy sector (1.A.1.a) and are not included in the further description that follows here. In energy input for trains of German railways, diesel fuel is the only energy source that plays a significant role apart from electric power.

Methodology

Activity Data

Basically, total inland deliveries of diesel oil are available from the National Energy Balances (NEBs) (AGEB, 2022) 1). This data is based upon sales data of the Association of the German Petroleum Industry (MWV) 2). As a recent revision of MWV data on diesel oil sales for the years 2005 to 2009 has not yet been adopted to the respective NEBs, this original MWV data has been used for this five years.

Data on the consumption of biodiesel in railways is provided in the NEBs as well, from 2004 onward. But as the NEBs do not provide a solid time series regarding most recent years, the data used for the inventory is estimated based on the prescribed shares of biodiesel to be added to diesel oil.

Small quantities of solid fuels are used for historical steam engines vehicles operated mostly for tourism and exhibition purposes. Official fuel delivery data are available for lignite, through 2002, and for hard coal, through 2000, from the NEBs. In order to complete these time series, studies were carried out in 2012 3), 2016 4) and 2021 5). During these studies, questionaires were provided to any known operator of historical steam engines in Germany. Here, due to limited data archiving, nearly complete data could only be gained for years as of 2005. For earlier years, in order to achieve a solid time series, conservative gap filling was applied.

Table 1: Overview of activity-data sources for domestic fuel sales to railway operators

Activity data source / quality of activity data
combustion of:
Diesel oil 1990-2004: NEB lines 74 and 61: 'Schienenverkehr' / 2005-2009: MWV annual report, table: 'Sektoraler Verbrauch von Dieselkraftstoff' / from 2010: NEB line 61
Biodiesel calculated from official blending rates
Hard coal 1990-1994: NEB lines 74; 1995-2004: interpolated data; from 2005: original data from studies; 2016: forward extrapolation
Hard coal coke 1990-1997: NEB lines 74 and 61; 1998-2004: interpolated data; from 2005: original data from studies; 2016: forward extrapolation
Raw lignite from 1990: NEB lines 74 and 61
Lignite briquettes from 1990: NEB lines 74 and 61
abrasion and wear of contact line, braking systems and tyres on rails:
transport performance data in Mio ptkm (performance-ton-kilometers) derived from the TREMOD model

Table 2: Annual fuel consumption in German railways, in terajoules

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Diesel Oil 38,458 31,054 25,410 18,142 14,626 14,730 13,514 13,771 12,283 13,321 13,775 11,344 9,425 10,747 10,782 11,072
Biodiesel 0 0 0 401 957 974 890 804 751 727 729 606 548 612 896 769
Liquids TOTAL 38,458 31,054 25,410 18,543 15,583 15,704 14,404 14,575 13,034 14,048 14,504 11,950 9,973 11,359 11,678 11,841
Lignite Briquettes 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Raw Lignite 200 86 1.33 0.79 0.79 0.76 0.74 0.71 0.68 0.66 0.63 0.46 0.46 0.43 0.22 0.35
Hard Coal 576 232 223 267 324 362 374 368 358 351 361 367 365 362 306 325
Hard Coal Coke 2,000 1,309 431 14.6 7.32 5.86 4.40 2.94 1.48 0.02 1.19 1.21 1.20 1.20 1.12 1.15
Solids TOTAL 2,776 1,627 655 283 332 368 379 372 360 352 363 368 367 363 308 327
Ʃ 1.A.3.c 41,234 32,681 26,065 18,826 15,915 16,073 14,783 14,947 13,395 14,400 14,867 12,318 10,340 11,722 11,985 12,168

The use of other fuels – such as vegetable oils or gas – in private narrow-gauge railway vehicles has not been included to date and may still be considered negligible.

Table 3: Annual transport performance, in Mio tkm (ton-kilometers)

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
Diesel 98,812 58,805 37,237 26,540 26,702 27,403 26,791 23,768 23,734 21,397 21,484 21,484 21,365 19,580 18,058 16,917
Electric 361,515 337,853 361,633 356,605 344,546 342,701 350,085 335,298 331,235 323,387 295,798 295,798 296,280 288,336 281,130 262,268
Ʃ 1.A.3.c 460.326 396.658 398.870 383.145 371.248 370.104 376.876 359.065 354.970 344.785 317.282 317.282 317.645 307.916 299.188 279.184

Annual energy input from liquid fuels Annual energy input from solid fuels

Regarding particulate-matter and heavy-metal emissions from abrasion and wear of contact line, braking systems, tyres on rails, annual transport performances of railway vehicles with electrical and Diesel traction derived from Knörr et al. (2022a) 6) are applied as activity data.

Emission factors

The (implied) emission factors used here for estimating emissions from diesel fuel combustion of very different quality: For main pollutants, CO and PM, annual tier2 IEF computed within the TREMOD model are used, representing the development of German railway fleet, fuel quality and mitigation technologies 7). On the other hand, constant default values from (EMEP/EEA, 2019) 8) are used for all reported PAHs and heavy metals and from Rentz et al. (2008) 9) regarding PCDD/F. As no emission factors are available for HCB and PCBs, no such emissions have been calculated yet.

Regarding emissions from solid fuels used in historic steam engines, all emission factors displayed below have been adopted from small-scale stationary combustion.

Furthermore, regarding emissions from abrasion and wear, emission factors are calculated from PM10 emission estimates directly provided by the German railroad company Deutsche Bahn AG.

As these original emissions are only available as of 2013, implied EF(PM,10) were calculated from the emission estimates extrapolated backwards from 2013 to 1990 and the transport performance data available from TREMOD.

Regarding PM2.5, and TSP, due to leck of better information, a fractional distribution of 0.5 : 1 : 1 (PM2.5 : PM10 : TSP) is assumed for now. Emission factors for emssions of copper, nickel and chrome are calculated via typical shares of the named metals in the contact line (copper) and in the braking systems (Ni and Cr). Other heavy metals contained in alloys used for the contact line (silver, magnesium, tin) are not taken into account here. Furthermore, emissions from other wear parts (e.g. the current collector) are not estimated. However, these components are not supposed to contain any of the nine heavy metals to be reported here (current collectors are made of aluminium alloys and coal).

Table 3: Annual country-specific emission factors for diesel fuels1, in kg/TJ

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
NH3 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54 0.54
NMVOC 109 100 90.2 64.8 52.0 54.1 44.7 42.2 41.6 39.2 39.0 37.8 36.8 36.3 37.7 36.8
NOx 1170 1207 1225 1111 970 989 919 899 885 826 802 776 749 707 741 744
SOx 196 60.5 14.1 0.32 0.32 0.32 0.32 0.32 0.33 0.32 0.33 0.33 0.33 0.33 0.33 0.33
BC3 28.8 28.3 23.8 15.2 11.5 12.0 10.4 9.5 9.3 8.67 8.52 8.05 7.70 7.40 7.90 7.90
PM 44.4 43.6 36.6 23.4 17.7 18.4 16.0 14.7 14.3 13.3 13.1 12.4 11.8 11.4 12.2 12.2
CO 287 292 255 162 121 121 105 101 99.6 95.8 94.6 93.6 90.9 89.8 90.3 89.6

1 due to lack of better information: similar EF are applied for fossil diesel oil and biodiesel
2 EF(PM2.5) also applied for PM10 and TSP (assumption: >99% of TSP consists of PM2.5)
3 EFs calculated via f-BCs as provided in 10): diesel fuels: 0.56 (Chapter: 1.A.3.c - Railways, Appendix A: tier1), solid fuels: 0.064 (Chapter: 1.A.4 - Small Combustion: Residential combustion (1.A.4.b): Table 3-3, Zhang et al., 2012)

Table 4: Emission factors applied for solid fuels, in kg/TJ

NH3 NMVOC NOx SOx PM2.5 PM10 TSP BC CO
Hard coal 4.00 15.0 120 650 222 250 278 14.2 500
Hard coal coke 4.00 0.50 120 500 15.0 15.0 15.0 0.96 1,000

Table 5: Country-specific emission factors for abrasive emissions, in g/km

PM2.5 PM10 TSP BC Pb Cd Hg As Cr Cu Ni Se Zn
Contact line 1 0.00016 0.00032 0.00032 NA NA NA NA NA NA 0.00033 NA NA NA
Tyres on rails 2 0.009 0.018 0.018 NA NA
Braking system 3 0.004 0.008 0.008 NA NA NA NA NA 0.00008 NA 0.00016 NA NA
Current collector 4 NE NE NE NE NA

1 assumption: 100 per cent copper
2 assumption: 100 per cent steel
3 assumption: steel alloy containing Chromium and Nickel
4 typically: aluminium alloy + coal contacts; no particulate matter emissions calculated yet

With respect to the emission factors applied for particulate matter, given the circumstances during test-bench measurements, condensables are most likely included at least partly. 1)

For information on the emission factors for heavy-metal and POP exhaust emissions, please refer to Appendix 2.3 - Heavy Metal (HM) exhaust emissions from mobile sources and Appendix 2.4 - Persistent Organic Pollutant (POP) exhaust emissions from mobile sources.

Table 6: Outcome of Key Category Analysis

for: TSP PM10 PM2.5
by: Level L/- L/-

Basically, for all unregulated pollutants, emission trends directly follow the trend in over-all fuel consumption.

Here, as emission factors for solid fuels tend to be much higher than those for diesel oil, emission trends are disproportionately effected by the amount of solid fuels used. Therefore, for the main pollutants, carbon monoxide, particulate matter and PAHs, emission trends show remarkable jumps especially after 1995 that result from the significantly higher amounts of solid fuels used.

Annual ammonia emissions Annual notrogen oxides emissions

For all fractions of particulate matter, the majority of emissions generally result from abrasion and wear and the combustion of diesel fuels. Additional jumps in the over-all trend result from the use of lignite briquettes (1996-2001). Here, as the EF(BC) for fuel combustion are estimated via fractions provided in 11), black carbon emissions follow the corresponding emissions of PM2.5.

Annual particulate matter emissions Annual PM10 emissions

Due to fuel-sulphur legislation, the trend of sulphur dioxide emissions follows not only the trend in fuel consumption but also reflects the impact of regulated fuel-qualities. For the years as of 2005, sulphur emissions from diesel combustion have decreased so strongly, that the over-all trend shows a slight increase again due to the now dominating contribution of sulphur from the use of solid fuels.

Annual sulphur oxides emissions

Regarding heavy metals, emissions from combustion of diesel oil and from abrasion and wear are estimated from tier1 default emission factors. Therefore, the emission trends reflect the development of diesel use and - for copper, chromium and nickel emissions resulting from the abrasion & wear of contact line and braking systems - the annual transport performance (see description of activity data above).

Annual copper emissions


Recalculations

Given the revised NEB 2020, both the activity data for diesel oil and the annual amounts of blended biodiesel were revised accordingly.

Table 5: Revised fuel consumption data 2020, in terajoule

DIESEL OIL BIODIESEL SOLID FUELS
current submission 10,782 896 308 11,985
previous submission 10,145 843 308 11,295
absolute change 637 52.9 0 690
relative change 6.28% 6.27% 0.00% 6.11%

Due to the routine revision of the TREMOD model 12), tier2 emission factors changed for recent years.

Table 6: Revised country-specific emission factors for diesel fuels, in kg/TJ

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Non-methane volatile organic compounds - NMVOC
current submission 109 100 90.2 64.8 52.0 54.1 44.7 42.2 41.6 39.2 39.0 37.8 36.8 36.3 37.7
previous submission 109 100 90.2 64.8 52.0 54.1 44.7 41.9 41.2 38.5 38.2 37.2 35.2 34.2 35.6
absolute change 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.34 0.49 0.68 0.78 0.58 1.55 2.11 2.15
relative change 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.82% 1.18% 1.76% 2.03% 1.56% 4.42% 6.19% 6.04%
Nitrogen oxides - NOx
current submission 1.170 1.207 1.225 1.111 970 989 919 899 885 826 802 776 749 707 741
previous submission 1.170 1.207 1.225 1.111 970 989 919 899 887 826 801 775 747 699 737
absolute change 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -0.34 -1.32 -0.12 0.99 0.60 2.82 7.51 4.15
relative change 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% -0.04% -0.15% -0.01% 0.12% 0.08% 0.38% 1.07% 0.56%
Black carbon - BC
current submission 28.8 28.3 23.8 15.2 11.5 12.0 10.4 9.5 9.3 8.67 8.52 8.05 7.70 7.40 7.90
previous submission 28.8 28.9 24.2 16.1 11.4 11.5 12.0 10.4 9.5 9.29 8.65 8.48 8.05 7.60 7.18
absolute change 0.00 -0.62 -0.44 -0.91 0.09 0.49 -1.62 -0.83 -0.20 -0.61 -0.12 -0.44 -0.35 -0.20 0.72
relative change 0.00% -2.15% -1.80% -5.65% 0.78% 4.27% -13.5% -8.04% -2.12% -6.61% -1.40% -5.13% -4.37% -2.57% 10.04%
Particulate matter - PM (PM2.5 = PM10 = TSP)
current submission 44.4 43.6 36.6 23.4 17.7 18.4 16.0 14.7 14.3 13.3 13.1 12.4 11.8 11.4 12.2
previous submission 44.4 43.6 36.6 23.4 17.7 18.4 16.0 14.6 14.3 13.3 13.1 12.4 11.7 11.0 11.8
absolute change 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.03 0.04 0.06 0.00 0.15 0.34 0.35
relative change 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.33% 0.23% 0.32% 0.46% 0.00% 1.29% 3.10% 2.96%
Carbon monoxide - CO
current submission 287 292 255 162 121 121 105 101 100 95.8 94.6 93.6 90.9 89.8 90.3
previous submission 287 292 255 162 121 121 105 101 99 94.6 93.3 92.6 88.5 87.0 87.2
absolute change 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.52 0.78 1.16 1.34 1.08 2.43 2.80 3.04
relative change 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.52% 0.79% 1.23% 1.43% 1.17% 2.75% 3.22% 3.49%

Furthermore, the transport performance data as activity data for the estimation of abrasive emissions from current line, wheels and brakes have been revised for more recent years:

Table 7: Revised transport performance data, in [Mio km]

2015 2016 2017 2018 2019 2020
current submission 344.785 317.282 317.282 317.645 307.916 299.188
previous submission 344.785 317.282 317.645 307.916 299.188 279.184
absolute change 0,00 0,00 -363 9.729 8.728 20.003
relative change 0,00% 0,00% -0,11% 3,16% 2,92% 7,16%

Abrasive particulate matter and heavy metal emissions were revised accordingly.

For pollutant-specific information on recalculated emission estimates for Base Year and 2020, please see the recalculation tables following chapter 8.1 - Recalculations.

Uncertainties

Uncertainty estimates for activity data of mobile sources derive from research project FKZ 360 16 023 (title: “Ermittlung der Unsicherheiten der mit den Modellen TREMOD und TREMOD-MM berechneten Luftschadstoffemissionen des landgebundenen Verkehrs in Deutschland”) carried out by Knörr et al. (2009) 13).

Planned improvements

Besides the scheduled routine revision of TREMOD, no further improvements are planned for the next annual submission.

FAQs

Why are similar EF applied for estimating exhaust heavy metal emissions from both fossil and biofuels?

The EF provided in the 2019 EMEP/EEA Guidebook 14) represent summatory values for (i) the fuel's and (ii) the lubricant's heavy-metal content as well as (iii) engine wear. Here, there might be no heavy metals contained in the biofuels. But since the specific shares of (i), (ii) and (iii) cannot be separated, and since the contributions of lubricant and engine wear might be dominant, the same emission factors are applied to biodiesel.


1) AGEB, 2022: Working Group on Energy Balances (Arbeitsgemeinschaft Energiebilanzen (Hrsg.), AGEB): Energiebilanz für die Bundesrepublik Deutschland; https://ag-energiebilanzen.de/daten-und-fakten/bilanzen-1990-bis-2020/?wpv-jahresbereich-bilanz=2011-2020, (Aufruf: 23.11.2022), Köln & Berlin, 2022
2) MWV (2021): Association of the German Petroleum Industry (Mineralölwirtschaftsverband, MWV): Annual Report 2018, page 65, Table 'Sektoraler Verbrauch von Dieselkraftstoff 2012-2019'; URL: https://www.mwv.de/wp-content/uploads/2020/09/MWV_Mineraloelwirtschaftsverband-e.V.-Jahresbericht-2020-Webversion.pdf, Berlin, 2021.
3) Hedel, R., & Kunze, J. (2012): Recherche des jährlichen Kohleeinsatzes in historischen Schienenfahrzeugen seit 1990. Probst & Consorten Marketing-Beratung. Dresden, 2012.
4) Illichmann, S. (2016): Recherche des Festbrennstoffeinsatzes historischer Schienenfahrzeuge in Deutschland 2015, Probst & Consorten Marketing-Beratung. Study carried out for UBA; FKZ 363 01 392; not yet published; Dresden, 2016.
5) Hasenbalg (2021): Recherche des Festbrennstoffeinsatzes historischer Schienenfahrzeuge in Deutschland 2019 & 2020, Probst & Consorten Marketing-Beratung. Study carried out for UBA; FKZ 363 01 392; not yet published; Dresden, 2021.
6), 12) Knörr et al. (2021a): Knörr, W., Heidt, C., Gores, S., & Bergk, F.: Fortschreibung des Daten- und Rechenmodells: Energieverbrauch und Schadstoffemissionen des motorisierten Verkehrs in Deutschland 1960-2035, sowie TREMOD, im Auftrag des Umweltbundesamtes, Heidelberg [u.a.]: Ifeu Institut für Energie- und Umweltforschung Heidelberg GmbH, Heidelberg & Berlin, 2022.
7) (bibcite 4)
8), 11), 14) EMEP/EEA (2019): EMEP/EEA air pollutant emission inventory guidebook 2019, https://www.eea.europa.eu/publications/emep-eea-guidebook-2019/part-b-sectoral-guidance-chapters/1-energy/1-a-combustion/1-a-3-c-railways/view; Copenhagen, 2019.
9) Rentz et al. (2008): Nationaler Durchführungsplan unter dem Stockholmer Abkommen zu persistenten organischen Schadstoffen (POPs), im Auftrag des Umweltbundesamtes, FKZ 205 67 444, UBA Texte | 01/2008, January 2008 - URL: http://www.umweltbundesamt.de/en/publikationen/nationaler-durchfuehrungsplan-unter-stockholmer
10) (bibcite 6)
13) Knörr et al. (2009): Knörr, W., Heldstab, J., & Kasser, F.: Ermittlung der Unsicherheiten der mit den Modellen TREMOD und TREMOD-MM berechneten Luftschadstoffemissionen des landgebundenen Verkehrs in Deutschland; final report; URL: https://www.umweltbundesamt.de/sites/default/files/medien/461/publikationen/3937.pdf, FKZ 360 16 023, Heidelberg & Zürich, 2009.
1)
During test-bench measurements, temperatures are likely to be significantly higher than under real-world conditions, thus reducing condensation. On the contrary, smaller dillution (higher number of primary particles acting as condensation germs) together with higher pressures increase the likeliness of condensation. So over-all condensables are very likely to occur but different to real-world conditions.