1.A.4.a ii - Commercial / Institutional: Mobile

In NFR 1.A.4.a ii - Commercial/institutional: Mobile fuel combustion activities and emissions from non-road diesel and LPG-driven (forklifters) vehicles used in the commercial and institutional sector are taken into account.

Sector-specific diesel consumption data are included in the primary fuel-delivery data available from NEB line 67: 'Commercial, trade, services and other consumers' (AGEB, 2022) ¹⁾.

Table 1: Sources for primary fuel-deliveries data

Following the deduction of diesel oil inputs for military vehicles as provided in (BAFA, 2022) ²⁾, the remaining amounts of diesel oil are apportioned onto off-road construction vehicles (NFR 1.A.2.g vii) and off-road vehicles in commercial/institutional use (1.A.4.a ii) as well as agriculture and forestry (1.A.4.c ii) based upon annual shares derived from (Knörr et al. (2022b)) ³⁾ (cf. superordinate chapter).

Table 2: Annual contribution of NFR 1.A.4.a ii to the over-all amounts of diesel oil provided in NEB line 67

source: TREMOD MM ⁴⁾

As the NEB does not distinguish into specific biofuels, consumption data for biodiesel are calculated by applying Germany's official annual shares of biodiesel blended to fossil diesel oil.

In contrast, for LPG-driven forklifters, specific consumption data is modelled in TREMOD-MM. These amounts are then subtracted from the over-all amount available from NEB line 67 to estimate the amount of LPG used in stationary combustion.

Table 3: Annual fuel consumption, in terajoules

The emission factors used here are of rather different quality: Basically, for all main pollutants, carbon monoxide and particulate matter, annual IEF modelled within TREMOD MM are used, representing the sector's vehicle-fleet composition, the development of mitigation technologies and the effect of fuel-quality legislation.

As no such specific EF are available for biofuels, the values used for diesel oil are applied to biodiesel, too.

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

¹ due to lack of better information: similar EF are applied for fossil and biofuels
² EF(PM_2.5) also applied for PM₁₀ and TSP (assumption: > 99% of TSP consists of PM_2.5)
³ estimated via a f-BCs as provided in ⁵⁾, 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

NFR 1.A.4.a ii is no key source.

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

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. Here, emissions of sulphur oxides follow the step-by-step reduction of sulphur contents in liquid fuels, resulting in a reduction of over 99% since 1990.

Ammonia emissions are driven by the consumption of LPG with its comparably high emission factor.

Emissions oif NMVOC are again driven by the consumption of LPG with its comparably high emission factor. Here, the ongoing downward trend results from the decrease in the emission factor applied for diesel fuels.

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 the 2019 EMEP Guidebook ⁶⁾, black carbon emissions follow the corresponding emissions of PM_2.5.

Activity data have been revised according to the now finalized National Energy Balance 2020.

Table 5: Revised activity data 2019, in terajoules

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)) ⁷⁾.

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

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

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

The EF provided in ⁸⁾ 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.