1.A.3.c - Railways

Last updated on 29 Aug 2019 09:29 (cf. Authors)

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.

NFR-Code	Name of Category	Method	AD	EF	Key Category 1
1.A.3.c	Railways	T1, T2	NS, M	CS, D, M	L: TSP, PM2.5 | L & T: PM10, PM2.5 | L: TSP

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¹ T = key source by Trend / L = key source by Level

Methods
D	Default
RA	Reference Approach
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/CORINAIR Emission Inventory Guidebook - 2007, 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, surveys

EF - Emission Factors
D	Default (EMEP Guidebook)
C	Confidential
CS	Country Specific
PS	Plant Specific data

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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.

Method

Activity Data

Basically, total inland deliveries of diesel oil are available from the National Energy Balances (NEBs) (AGEB, 2018) [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, a study was carried out in 2012 by Hedel, R., and Kunze, J. (2012) [3]. During this study, 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.
A follow-up study to gain original cosumption data for 2015 was carried out in 2016 by Illichmann, S. (2016) [4].

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	1999	2000	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017
Diesel Oil	38,458	31,054	25,016	25,410	18,142	17,101	16,730	16,389	14,336	14,626	14,730	13,514	13,771	12,283	13,321	13,775	13,690
Biodiesel	0	0	0	0	397	498	747	810	987	949	966	882	798	745	720	724	726
Liquids TOTAL	38,458	31,054	25,016	25,410	18,539	17,599	17,477	17,199	15,324	15,575	15,696	14,396	14,569	13,028	14,041	14,499	14,416
Lignite Briquettes	0	0	541	431	0	0	0	0	0	0	0	0	0	0	0	0	0
Raw Lignite	0	0	11	0	0	0	0	0	0	0	0	0	0	0	0	0	0
Hard Coal	576	250	250	250	255	262	255	300	321	314	345	357	352	341	339	340	340
Hard Coal Coke	0	86	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1
Solids TOTAL	576	336	803	682	256	263	256	301	322	315	346	357	353	342	340	341	341
Ʃ 1.A.3.c	39,034	31,390	25,819	26,092	18,795	17,862	17,733	17,500	15,646	15,890	16,041	14,754	14,921	13,370	14,381	14,839	14,757

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	1999	2000	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017
Electric Traction	361,515	337,853	354,702	361,633	356,605	375,707	379,554	377,767	336,581	344,546	342,701	350,085	335,298	331,235	323,387	295,798	296,280
Diesel Traction	98,812	58,805	40,431	37,237	26,540	25,570	22,664	31,750	27,734	26,702	27,403	26,791	23,768	23,734	21,397	21,484	21,365
Ʃ 1.A.3.c	460,326	396,658	395,133	398,870	383,145	401,277	402,217	409,516	364,314	371,248	370,104	376,876	359,065	354,970	344,785	317,282	317,645

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. (2018a) [5] 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 [4].
On the other hand, constant default values from (EMEP/EEA, 2016) [6] are used for all reported PAHs and heavy metals and from Rentz et al. (2008) [8] 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(PM₁₀) were calculated from the emission estimates extrapolated backwards from 2013 to 1990 and the transport performance data available from TREMOD.
Regarding PM_2.5, and TSP, due to leck of better information, a fractional distribution of 0.5 : 1 : 1 (PM_2.5 : 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	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017
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	62.1	57.8	56.7	53.8	55.7	59.2	46.9	43.5	43.1	41.4	40.9	39.3
NOx	1,170	1,207	1,225	1,111	1,058	1,029	1,011	1,001	986	1,010	921	882	897	851	836	814
SOx	191	60.5	14.1	0.32	0.32	0.32	0.32	0.32	0.32	0.32	0.32	0.32	0.33	0.32	0.33	0.33
PM2	44.4	43.6	36.6	23.4	22.5	21.1	19.9	18.2	18.6	19.8	16.6	14.8	15.4	14.7	14.6	13.7
BC3	28.8	28.3	23.8	15.2	14.6	13.7	12.9	11.9	12.1	12.9	10.8	9.64	10.0	9.54	9.51	8.92
CO	287	292	255	162	153	142	136	129	129	129	109	104	104	101	98.1	94.8

¹ due to lack of better information: similar EF are applied for fossil diesel oil and biodiesel
² EF(PM_2.5) also applied for PM₁₀ and TSP (assumption: >99% of TSP consists of PM_2.5)
³ EFs calculated via f-BCs as provided in [6]: 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: Country-specific emission factors 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 4: 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

NOTE: 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.

Discussion of emission trends

NFR 1.A.3.c is no key source.

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.

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 [5], black carbon emissions follow the corresponding emissions of PM_2.5.

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.

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).

Recalculations

Activity data

Given the revised NEB 2016, both the activity data fo diesel oil and the annual amounts of blended biodiesel were revised accordingly.

Table 5: Revised 2016 fuel consumption, in terajoule

	Diesel Oil	Biodiesel
Submission 2019	13,775	724
Submission 2018	12,381	650
absolute change	1,394	74
relative change	11.26%	11.38%

Emission factors

Due to the routine revision of the TREMOD model [5], tier2 emission factors changed for recent years.
Here, the revision results mainly from the consideration of revised NCvs for diesel oil as provided by the AGEB.

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

	2012	2013	2014	2015	2016
Nitrogen oxides - NOx
Submission 2019	921	882	897	851	836
Submission 2018	921	882	890	846	830
absolute change	0.00	0.00	6.49	5.27	6.07
relative change	0.00%	0.00%	0.73%	0.62%	0.73%
Non-methane volatile organic compounds - NMVOC
Submission 2019	47	44	43	41	41
Submission 2018	47	44	43	41	41
absolute change	0.00	0.00	0.31	0.26	0.30
relative change	0.00%	0.00%	0.73%	0.62%	0.73%
Ammonia - NH3
Submission 2019	0.535	0.535	0.539	0.539	0.539
Submission 2018	0.535	0.535	0.535	0.535	0.535
absolute change	0.000	0.000	0.004	0.003	0.004
relative change	0.00%	0.00%	0.73%	0.62%	0.73%
Sulphur dioxide - SO2
Submission 2019	0.323	0.323	0.325	0.325	0.325
Submission 2018	0.323	0.323	0.323	0.323	0.323
absolute change	0.000	0.000	0.002	0.002	0.002
relative change	0.00%	0.00%	0.73%	0.62%	0.73%
Particulate matter - PM
Submission 2019	16.56	14.83	15.41	14.67	14.63
Submission 2018	16.56	14.83	15.29	14.58	14.53
absolute change	0.00	0.00	0.11	0.09	0.11
relative change	0.00%	0.00%	0.73%	0.62%	0.73%
Black carbon - BC
Submission 2019	10.8	9.6	10.0	9.5	9.5
Submission 2018	10.8	9.6	9.9	9.5	9.4
absolute change	0.00	0.00	0.07	0.06	0.07
relative change	0.00%	0.00%	0.73%	0.62%	0.73%
Carbon monoxide - CO
Submission 2019	109	104	104	101	98
Submission 2018	109	104	103	100	97
absolute change	0.00	0.00	0.75	0.62	0.71
relative change	0.00%	0.00%	0.73%	0.62%	0.73%

Furthermore, the tier1 EF (derived from tier1 default values for diesel oil from [6]) for HMs and POPs from biodiesel have been revised to take into account the this fuel's specific NCV and presumably lower HM content:

Table 7: Revised tier1 emission factors for biodiesel

	Pb	Cd	Hg	As	Cr	Cu	Ni	Se	Zn	PCDD/F	B[a]P	B[b]F	B[k]F	I[…]P	PAHs 1-4
Submission 2019	0.013	0.001	0.142	0.003	0.228	0.153	0.005	0.003	0.483	2.41	806	1,343	924	212	3,284
Submission 2018	1.213	0.233	0.123	0.002	1.164	39.572	1.629	0.233	23.277	2.09	698	1,164	801	184	2,847
absolute change	-1.20	-0.23	0.02	0.00	-0.94	-39.42	-1.62	-0.23	-22.79	0.32	107	179	123	28	437
relative change	-98.9%	-99.4%	15.4%	15.4%	-80.4%	-99.6%	-99.7%	-98.8%	-97.9%	15.4%	15.4%	15.4%	15.4%	15.4%	15.4%

For more information on recalculated emission estimates for Base Year and 2016, please see the pollutant specific 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) [8].

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 [5] 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.

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Bibliography

1. AGEB (2018): Working Group on Energy Balances (Arbeitsgemeinschaft Energiebilanzen (Hrsg.), AGEB): Energiebilanz für die Bundesrepublik Deutschland; URL: https://ag-energiebilanzen.de/7-0-Bilanzen-1990-2016.html, Köln & Berlin, 2018.

2. MWV (2018): Association of the German Petroleum Industry (Mineralölwirtschaftsverband, MWV): Annual Report 2018, page 65, Table 'Sektoraler Verbrauch von Dieselkraftstoff 2012-2016'; URL: https://www.mwv.de/wp-content/uploads/2016/06/180830_MWV_Jahresbericht-2018_RZ_Web_es_small.pdf, Berlin, 2018.

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. Knörr et al. (2018a): Knörr, W., Heidt, C., Gores, S., & Bergk, F.: ifeu Institute for Energy and Environmental Research (Institut für Energie- und Umweltforschung Heidelberg gGmbH, ifeu): Fortschreibung des Daten- und Rechenmodells: Energieverbrauch und Schadstoffemissionen des motorisierten Verkehrs in Deutschland 1960-2035, sowie TREMOD 5.81, im Auftrag des Umweltbundesamtes, Heidelberg & Berlin, 2018.

6. EMEP/EEA (2016): EMEP/EEA air pollutant emission inventory guidebook 2016, URL: https://www.eea.europa.eu/publications/emep-eea-guidebook-2016; Copenhagen, July 2017.

7. 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

8. 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.

Footnotes

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.