1.A.4.b ii - Residential: Household and Gardening: Mobile

Short description

Under sub-category 1.A.4.b ii - Residential: Mobile Sources in Households and Gardening fuel combustion activities and resulting emissions from combustion engine driven devices such as motor saws and lawn mowers are being reported.

Method AD EF Key Category Analysis
T1, T2 NS, M CS, M, D L/T: CO

image Lawnmower.PNG size="small"

Methodology

Activity data

Activity data are taken from annual fuel delieveries data provided in line 66: 'Households' of the National Energy Balances (NEB) for Germany (AGEB, 2020) 1).

Table 1: Sources for consumption data in 1.A.4.b ii

Relevant years Data Source
through 1994 AGEB - National Energy Balance, line 79: Households
since 1995 AGEB - National Energy Balance, line 66: Households

Here, given the rare statistics on sold machinery, these activity data is of limited quality only (no annual but cascaded trend).

As the NEB only provides primary activity data for total biomass used in 'households', but does not distinguish into specific biofuels, consumption data for bioethanol used in NFR 1.A.4.b ii are calculated by applying Germany's official annual shares of biogasoline blended to fossil gasoline.

Please note: Data on gasoline used in households as provided in the National Energy Balances represents a “residual item” following the allocation of the majority of this fuel to road and military vehicles. Here, fuel sales to road vehicles might also include gasoline acquired on filling stations but used for household equipment.

Due to these reasons, activity data for gasoline consumption in households machinery and, hence, several emission estimates show no realistic trend but a stepwise development with significant jumps.

Table 2: Annual over-all fuel deliveries to residential mobile sources, in terajoules

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Gasoline 2.177 2.395 2.395 2.395 3.379 4.069 3.995 3.720 3.946 4.228 4.228 4.228 4.070 4.046
Biogasoline 0 0 0 16 131 167 177 159 172 183 184 178 183 175
Ʃ 1.A.4.b ii 2.177 2.395 2.395 2.411 3.510 4.236 4.172 3.879 4.118 4.411 4.412 4.406 4.253 4.221

source: AGEB, 2020 2) and TREMOD MM 3)

These primary activity data can be distributed onto 2- and 4-stroke engines used in households via annual shares from Knörr et al. (2020b) 4).

Table 3: Annual shares of 2- and 4-stroke engines

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
2-Stroke 28,2 % 49,7 % 66,5 % 69,6 % 73,9 % 74,5 % 75,7 % 76,4 % 76,6 % 76,8 % 77,1 % 77,2 % 77,4 % 77,5 %
4-Stroke 71,8 % 50,3 % 33,5 % 30,4 % 26,1 % 25,5 % 24,3 % 23,6 % 23,4 % 23,2 % 22,9 % 22,8 % 22,6 % 22,5 %

source: TREMOD MM 5)

Table 4: Resulting estimates for fuel consumption in 2- and 4-stroke engines, in terajoules

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
2-stroke engines
Gasoline 614 1.191 1.592 1.667 2.498 3.033 3.023 2.841 3.023 3.249 3.258 3.266 3.150 3.137
Biogasoline 0 0 0 11 97 124 134 122 131 141 142 138 142 135
4-stroke engines
Gasoline 1.563 1.204 803 728 881 1.036 972 879 923 979 970 962 920 909
Biogasoline 0 0 0 5 34 42 43 38 40 42 42 41 41 39
Ʃ 1.A.4.b ii 2.177 2.395 2.395 2.411 3.510 4.236 4.172 3.879 4.118 4.411 4.412 4.406 4.253 4.221

Emission factors

The emission factors used here are of rather different quality: For all main pollutants, carbon monoxide and particulate matter, annually changing values computed within TREMOD-MM (Knörr et al. (2020b)) 6) are used, representing the development of mitigation technologies and the effect of fuel-quality legislation.

Here, as no such specific EF are available for biofuels, the values used for gasoline are applied to bioethanol, too.

For lead (Pb) from leaded gasoline and corresponding TSP emissions, additional emissions are are calculated from 1990 to 1997 based upon contry-specific emission factors from 7).)

Table 4: Annual country-specific emission factors from TREMOD MM1, in kg/TJ

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
4-stroke machinery
NH3 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09
NMVOC2 475 1.289 1.604 1.651 1.647 1.646 1.645 1.643 1.641 1.638 1.635 1.632 1.628 1.624
NMVOC3 727 819 809 783 774 771 769 767 765 763 762 761 760 756
NOx 51,0 85,3 103 108 122 124 126 129 131 132 133 134 135 133
SOx 10,1 8,27 3,22 0,37 0,37 0,37 0,37 0,37 0,37 0,37 0,37 0,37 0,37 0,37
BC5 0,31 0,27 0,24 0,23 0,24 0,25 0,25 0,25 0,26 0,26 0,26 0,26 0,26 0,26
PM4 6,29 5,46 4,85 4,62 4,87 4,94 5,00 5,06 5,11 5,15 5,19 5,22 5,24 5,25
CO 39.998 32.154 28.346 27.161 27.992 28.278 28.555 28.813 29.047 29.249 29.418 29.548 29.647 29.614
2-stroke machinery
NH3 0,07 0,07 0,07 0,07 0,07 0,08 0,08 0,08 0,09 0,09 0,09 0,09 0,09 0,09
NMVOC2 6.126 5.914 5.879 5.816 5.835 5.372 4.327 3.635 3.473 3.315 3.164 3.024 2.900 2.796
NMVOC3 1.387 1.129 510 392 280 288 305 317 321 325 328 331 334 335
NOx 19,8 25,7 36,3 53,4 63,8 61,9 57,1 55,0 55,9 56,8 57,5 58,2 58,7 59,2
SOx 10,10 8,27 3,22 0,37 0,37 0,37 0,37 0,37 0,37 0,37 0,37 0,37 0,37 0,37
BC5 6,91 6,14 5,13 4,93 4,79 4,93 5,22 5,41 5,49 5,55 5,61 5,67 5,71 5,75
PM4 138 123 103 99 96 99 104 108 110 111 112 113 114 115
CO 20.270 18.743 16.255 15.483 14.699 15.068 15.891 16.438 16.618 16.797 16.967 17.125 17.266 17.385
2- and 4-stroke machinery
TSP6 2,35 0,82
Pb 1,47 0,52

1 due to lack of better information: similar EF are applied for fossil and biofuels
2 from fuel combustion
3 from gasoline evaporation
4 EF(PM2.5) also applied for PM10 and TSP (assumption: > 99% of TSP consists of PM2.5)
5 estimated via a f-BCs as provided in 8), Chapter 1.A.2.g vii, 1.A.4.a ii, b ii, c ii, 1.A.5.b i - Non-road, note to Table 3-1: Tier 1 emission factors for off-road machinery
6 from leaded gasoline (until 1997)

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. 9)

For lead (Pb) from leaded gasoline and corresponding TSP emissions, additional emissions are are calculated from 1990 to 1997 based upon contry-specific emission factors from 10).

NOTE: For the country-specific emission factors applied for particulate matter, no clear indication is available, whether or not condensables are included.

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: Outcome of Key Category Analysis

for: CO
by: Level & Trend

Given the limited quality of gasoline-deliveries data from NEB line 66, the following emission trends are of limited significance only.

Unregulated pollutants (Ammonia, HMs, POPs, ...)

For all unregulated pollutants, emission trends directly follow the trend in fuel consumption.

Here, as the emission factors for heavy metals (and POPs) are derived from tier1 default values, the emission's trend is stronlgy influenced by the share of 2-stroke gasoline fuel (containing lube oil with presumably higher HM content) consumed.

Regulated pollutants

For all regulated pollutants, emission trends follow not only the trend in fuel consumption but also reflect the impact of fuel-quality and exhaust-emission legislation. However, especially for CO and NOx, trends are strongly influenced by the changes in annual fuel deliveries as provided in NEB line 66.

Particulate matter

Over-all PM emissions are by far dominated by emissions from diesel oil combustion with the falling trend basically following the decline in fuel consumption between 2000 and 2005. Nonetheless, the decrease of the over-all emission trend was and still is amplified by the expanding use of particle filters especially to eliminate soot emissions.

Additional contributors such as the impact of TSP emissions from the use of leaded gasoline (until 1997) have no significant effect onto over-all emission estimates.

Here, as the EF(BC) are estimated via fractions provided in 11), black carbon emissions follow the corresponding emissions of PM2.5.

Recalculations

Primary activity data fro NEB line 66 remains unrevised. However, the percental shares of 2- and 4-stroke engines have been revised according to TREMOD MM.

Table 5: Revised annual shares of 2- and 4-stroke engines

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018
2-stroke machinery
Submission 2021 0,282 0,497 0,665 0,696 0,739 0,745 0,757 0,764 0,766 0,768 0,771 0,772 0,774
Submission 2020 0,282 0,497 0,665 0,687 0,728 0,734 0,745 0,752 0,755 0,757 0,759 0,761 0,763
absolute change 0,000 0,000 0,000 0,009 0,011 0,012 0,012 0,012 0,012 0,011 0,011 0,011 0,011
relative change 0,00% 0,00% 0,00% 1,28% 1,57% 1,61% 1,58% 1,55% 1,54% 1,52% 1,49% 1,49% 1,48%
4-stroke machinery
Submission 2021 0,718 0,503 0,335 0,304 0,261 0,255 0,243 0,236 0,234 0,232 0,229 0,228 0,226
Submission 2020 0,718 0,503 0,335 0,313 0,272 0,266 0,255 0,248 0,245 0,243 0,241 0,239 0,237
absolute change 0,000 0,000 0,000 -0,009 -0,011 -0,012 -0,012 -0,012 -0,012 -0,011 -0,011 -0,011 -0,011
relative change 0,00% 0,00% 0,00% -2,81% -4,19% -4,44% -4,62% -4,70% -4,73% -4,72% -4,70% -4,76% -4,77%

Table 5: Resulting revised annual fuel consumptions of 2- and 4-stroke engines

1990 1995 2000 2005 2010 2011 2012 2013 2014 2015 2016 2017 2018
2-stroke machinery
Submission 2021 1.563 1.204 803 733 915 1.078 1.015 917 963 1.021 1.012 1.003 961
Submission 2020 1.563 1.204 803 754 955 1.128 1.065 962 1.010 1.072 1.062 1.053 1.009
absolute change 0,00 0,00 0,00 -21,2 -40,0 -50,1 -49,1 -45,3 -47,7 -50,6 -49,9 -50,1 -48,1
relative change 0,00% 0,00% 0,00% -2,81% -4,19% -4,44% -4,62% -4,70% -4,73% -4,72% -4,70% -4,76% -4,77%
4-stroke machinery
Submission 2021 614 1.191 1.592 1.679 2.594 3.158 3.157 2.963 3.155 3.390 3.399 3.404 3.292
Submission 2020 614 1.191 1.592 1.658 2.554 3.108 3.108 2.917 3.107 3.340 3.349 3.354 3.244
absolute change 0,00 0,00 0,00 21,20 40,03 50,09 49,13 45,26 47,74 50,63 49,89 50,11 48,11
relative change 0,00% 0,00% 0,00% 1,28% 1,57% 1,61% 1,58% 1,55% 1,54% 1,52% 1,49% 1,49% 1,48%

In addition, several annual country-specific emission factors have been revised accoring to changes within TREMOD but cannot be displayed here in a comprehendible way.

For pollutant-specific information on recalculated emission estimates for Base Year and 2018, 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 (Knörr et al. (2009)) 12): “Ermittlung der Unsicherheiten der mit den Modellen TREMOD und TREMOD-MM berechneten Luftschadstoffemissionen des landgebundenen Verkehrs in Deutschland”.

Uncertainty estimates for emission factors were compiled during the PAREST research project. Here, the final report has not yet been published.

Planned improvements

Besides a routine revision of the TREMOD MM model, no specific improvements are planned.

FAQs

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

The EF provided in 13) 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 metal contained in 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 and bioethanol.


1), 2) AGEB, 2020: Working Group on Energy Balances (Arbeitsgemeinschaft Energiebilanzen (Hrsg.), AGEB): Energiebilanz für die Bundesrepublik Deutschland; URL: http://www.ag-energiebilanzen.de/7-0-Bilanzen-1990-2018.html, (Aufruf: 29.11.2020), Köln & Berlin, 2020
3), 4), 5), 6), 7) Knörr et al. (2020b): Knörr, W., Heidt, C., Gores, S., & Bergk, F.: ifeu Institute for Energy and Environmental Research (Institut für Energie- und Umweltforschung Heidelberg gGmbH, ifeu): Aktualisierung des Modells TREMOD-Mobile Machinery (TREMOD MM) 2020, Heidelberg, 2020.
8), 10), 11) EMEP/EEA, 2019: EMEP/EEA air pollutant emission inventory guidebook – 2019, Copenhagen, 2019.
9) 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.
12) 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.
13) 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