Last updated on 29 Aug 2019 09:29 (cf. Authors)
Short description
Under sub-category 1.A.4.c ii - Agriculture/Forestry/Fishing: Off-road Vehicles and other Machinery fuel combustion activities and resulting emissions from off-road vehicles and machinery used in agriculture and forestry are reported seperately.
| NFR-Code | Source category | Method | AD | EF | Key Category 1 |
|---|---|---|---|---|---|
| 1.A.4.c ii | Agriculture/Forestry/Fishing: Off-Road Vehicles and Other Machinery | T1, T2 | NS, M | CS, D, M | L & T: PM10, BC | L: NOx, PM2.5 |
| including mobile sources sub-categories | |||||
| 1.A.4.c ii (a) | Off-road Vehicles and Other Machinery: Agriculture | T1, T2 | NS, M | CS, D, M | - |
| 1.A.4.c ii (b) | Off-road Vehicles and Other Machinery: Forestry | T1, T2 | NS, M | CS, D, M | - |
Method
Activity data
Sector-specific consumption data is included in the primary fuel-delivery data are available from NEB line 67: 'Commercial, trade, services and other consumers' (AGEB, 2018) [1].
Table 1: Sources for primary fuel-delivery data| through 1994 | AGEB - National Energy Balance, line 79: 'Haushalte und Kleinverbraucher insgesamt' |
| as of 1995 | AGEB - National Energy Balance, line 67: 'Gewerbe, Handel, Dienstleistungen u. übrige Verbraucher' |
Following the deduction of energy inputs for military vehicles as provided in (BAFA, 2018) [2], the remaining amounts of gasoline and diesel oil are apportioned onto off-road construction vehicles (NFR 1.A.2.g vii) and commercial/institutional used off-road vehicles (1.A.4.a ii) as well as agriculture and forestry (NFR 1.A.4.c ii) based upon annual shares derived from TREMOD MM (Knörr et al. (2018b)) [3] (cf. NFR 1.A.4 - mobile).
To provide more specific information on mobile sources in agriculture and forestry, the inventory compiler further devides NFR sector 1.A.4.c ii into 1.A.4.c ii (i) - NRMM in agriculture in and 1.A.4.c ii (ii) - NRMM in forestry.
Table 2: Annual percentual contribution of NFR 1.A.4.c ii to the primary fuel delivery data provided in NEB line 67| 1990 | 1995 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | |||
| percentual shares of diesel fuels as provided in NEB line 67 as allocated… | ||||||||||||||||||||||
| …to agriculture | 48.4% | 46.7% | 46.8% | 47.5% | 48.1% | 48.3% | 49.3% | 50.1% | 49.0% | 49.7% | 49.8% | 50.1% | 50.9% | 50.6% | 50.6% | 50.5% | 50.3% | 50.7% | 51.0% | 51.1% | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| …to forestry | 2.38% | 1.34% | 2.05% | 1.56% | 1.75% | 2.17% | 2.42% | 2.65% | 2.87% | 3.60% | 2.61% | 2.32% | 2.67% | 2.74% | 2.54% | 2.56% | 2.60% | 2.66% | 2.51% | 2.57% | ||
| percentual shares of gasoline fuels as provided in NEB line 67 as allocated… | ||||||||||||||||||||||
| …to forestry | 68.5% | 40.3% | 44.9% | 36.6% | 37.1% | 39.9% | 40.7% | 41.6% | 41.6% | 47.4% | 38.0% | 33.9% | 36.0% | 36.2% | 33.7% | 33.5% | 33.8% | 34.1% | 32.4% | 32.7% | ||
source: own estimations based on Knörr et al. (2018b) [3]
1 no gasoline used in agriculatural vehicles and mobile machinery
2 no 4-stroke gasoline vehicles and mobile machinery used in forestry
| 1990 | 1995 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | |
| Diesel Oil | 56,808 | 46,985 | 46,460 | 44,832 | 44,830 | 44,705 | 44,359 | 43,181 | 42,985 | 44,262 | 44,329 | 46,967 | 47,423 | 48,400 | 47,307 | 49,146 | 51,193 | 54,109 | 56,347 | 57,756 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Gasoline | 3,093 | 3,004 | 3,325 | 2,695 | 2,750 | 2,955 | 3,018 | 3,036 | 3,064 | 3,487 | 2,759 | 1,509 | 1,563 | 1,425 | 399 | 391 | 421 | 1,698 | 1,615 | 1,888 |
| Biodiesel | 0 | 0 | 0 | 0 | 0 | 0 | 382 | 944 | 1,252 | 1,977 | 2,191 | 3,234 | 3,076 | 3,173 | 3,089 | 2,846 | 3,104 | 2,925 | 2,960 | 3,063 |
| Bioethanol | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 21 | 44 | 47 | 53 | 43 | 60 | 58 | 18 | 17 | 18 | 74 | 70 | 82 |
| Ʃ 1.A.4.c ii | 59,900 | 49,989 | 49,784 | 47,527 | 47,579 | 47,659 | 47,762 | 47,183 | 47,345 | 49,773 | 49,332 | 51,753 | 52,123 | 53,056 | 50,813 | 52,399 | 54,736 | 58,806 | 60,992 | 62,790 |
 |
 |
Emission factors
The emission factors applied here are of rather different quality:
Basically, for all main pollutants, carbon monoxide and particulate matter, annual IEF modelled within TREMOD MM [3] are used, representing the sector's vehicle-fleet composition, the development of mitigation technologies and the effect of fuel-quality legislation.
For Information on the country-specific implied emission factors applied to mobile machinery in agriculture and forestry, please refer to the respective sub-chapters linked above.
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.4.c ii is key source for emissions of NOx, BC, PM2.5 and PM10.
Unregulated pollutants (NH3, HMs, POPs, …)
 |
For all unregulated pollutants, emission trends directly follow the trend in fuel consumption.
Regulated pollutants
Nitrogen oxides (NOx), Sulphur dioxide (SO2)
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.
 |
 |
Particulate matter (Black Carbon, PM2.5, PM10, and TSP)
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.
 |
Recalculations
Compared to the fundamental revision carried out with submission 2018, activity data and emission factors changed only slightly.
Activity data
As fuel consumption data is calculated from primary NEB data via annual sectoral shares from (Knörr et al. (2018b): TREMOD MM 2018) [3], any revisions in these shares impacts the AD estimates.
The following table gives an overview of the changes in annual shares resulting from the routine revision of TREMOD MM.
| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | |||||||||
| diesel fuels used in agricultural vehicles and mobile machinery (1.A.4.c ii (i)) | |||||||||||||||
| Submission 2019 | 0.509 | 0.506 | 0.506 | 0.505 | 0.503 | 0.507 | 0.510 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Submission 2018 | 0.509 | 0.506 | 0.506 | 0.505 | 0.503 | 0.507 | 0.510 | ||||||||
| absolute change | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||||||||
| relative change | 0.000% | -0.001% | -0.001% | -0.001% | -0.001% | -0.001% | -0.001% | ||||||||
| diesel fuels used in forestry vehicles and mobile machinery (1.A.4.c ii (ii)) | |||||||||||||||
| Submission 2019 | 0.027 | 0.027 | 0.025 | 0.026 | 0.026 | 0.027 | 0.025 | ||||||||
| Submission 2018 | 0.027 | 0.027 | 0.025 | 0.026 | 0.026 | 0.027 | 0.025 | ||||||||
| absolute change | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||||||||
| relative change | 0.000% | -0.001% | -0.001% | -0.001% | -0.001% | -0.001% | -0.001% | ||||||||
| gasoline fuels used in forestry vehicles and mobile machinery (1.A.4.c ii (ii)) | |||||||||||||||
| Submission 2019 | 0.360 | 0.362 | 0.337 | 0.335 | 0.338 | 0.341 | 0.324 | ||||||||
| Submission 2018 | 0.360 | 0.362 | 0.337 | 0.335 | 0.338 | 0.341 | 0.324 | ||||||||
| absolute change | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||||||||
| relative change | 0.000% | -0.002% | -0.002% | -0.002% | -0.002% | -0.002% | -0.002% | ||||||||
These changes in annual shares together with the updated 2016 Energy Balance result in the following changes in sub-sectoral activity data:
Table 6: Revised activity data 2010-2016, in terajoules| 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | |||||||||
| diesel fuels | |||||||||||||||
| Submission 2019 | 50,499 | 51,573 | 50,397 | 51,992 | 54,297 | 57,034 | 59,306 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Submission 2018 | 50,518 | 51,589 | 50,409 | 52,006 | 54,314 | 57,035 | 57,733 | ||||||||
| absolute change | -18.53 | -15.76 | -12.82 | -13.27 | -16.99 | -0.58 | 1,573 | ||||||||
| relative change | -0.04% | -0.03% | -0.03% | -0.03% | -0.03% | 0.00% | 2.72% | ||||||||
| gasoline fuels | |||||||||||||||
| Submission 2019 | 1,624 | 1,484 | 416 | 407 | 439 | 1,772 | 1,686 | ||||||||
| Submission 2018 | 1,624 | 1,484 | 416 | 407 | 439 | 1,772 | 1,829 | ||||||||
| absolute change | 0.00 | -0.02 | -0.02 | -0.01 | -0.01 | -0.03 | -143 | ||||||||
| relative change | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | -7.83% | ||||||||
| 1.A.4.c ii - over-all fuel consumption | |||||||||||||||
| Submission 2019 | 52,123 | 53,056 | 50,813 | 52,399 | 54,736 | 58,806 | 60,992 | ||||||||
| Submission 2018 | 52,141 | 53,072 | 50,826 | 52,413 | 54,753 | 58,807 | 59,562 | ||||||||
| absolute change | -18.53 | -15.78 | -12.84 | -13.28 | -17.00 | -0.62 | 1,430 | ||||||||
| relative change | -0.04% | -0.03% | -0.03% | -0.03% | -0.03% | 0.00% | 2.40% | ||||||||
Emission factors
For Information on the revision of the annual country-specific emission factors applied to mobile machinery in agricultur and forestry, please refer to the respective sub-chapters linked above.
For information on the impacts on 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: "Ermittlung der Unsicherheiten der mit den Modellen TREMOD und TREMOD-MM berechneten Luftschadstoffemissionen des landgebundenen Verkehrs in Deutschland" by (Knörr et al. (2009)) [6].
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 TREMOD MM, 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 [4] 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 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 and bioethanol.