Chapter 1.7 - General Uncertainty Evaluation

Last updated on 30 Aug 2017 16:54 (cf. Authors)



As stated in the EMEP-EEA Guidebook, an important aspect of an uncertainty analysis concerns the ways on how to express the uncertainties associated with individual estimates or the total inventory. It is recommended to use the same quantity to express uncertainty in a LRTAP Convention inventory as required in a greenhouse gas inventory, namely the 95 % confidence interval.
This 95 % confidence interval is specified by the confidence limits defined by the 2.5 percentile and 97.5 percentile of the cumulative distribution function of the estimated quantity, that means that there is a 95 % probability that the actual value of the quantity estimated is within the interval defined by the confidence limits. In practical terms, the 95 % confidence interval for a normal distribution lies between ± 2 standard deviations around the mean.

In order to prioritise efforts and resources in subsequent years, expert judgments mainly made by the UBA inventory staff together with EMEP/EEA air pollutant emission inventory guidebook references on default uncertainties in activity data and emission factors and as well some uncertainty data of the PAREST project have been the basis for this IPCC Tier 1 uncertainty evaluation.

Uncertainties 2015

The uncertainties of the German emission inventory were evaluated by the inventory staff for the first time in 2016 for NEC pollutants in the categories Industrial Processes and Agriculture. They now are reported for the first time to the CLRTAP with the current submission in 2017, starting with the emissions of the NEC pollutants SO2, NOx, NMVOC and NH3 for all categories , covering the time period of 1990 to 2015.

Pollutant Uncertainty in total inventory 2015 Uncertainty introduced into the trend
NOx 29 % 7 %
SO2 10 % 1 %
NH3 17 % 9 %
NMVOC 21 % 5 %

Research Project PAREST

As a first approach for uncertainty analysis of the German inventory the results of a research project were available in 2010.
The PAREST project (“Particle Reduction Strategies” - UFOPLAN FKZ 206 43 200/01 - Strategien zur Verminderung der Feinstaubbelastung) has been a research project, in which emission scenarios until 2020 were constructed for fine particles (PM10 und PM2.5) as well as aerosol precursors SO2, NOx, NH3 and NMVOC, both for Germany and Europe. Reduction measures were assessed and finally air quality in Germany was modeled.

For PAREST, all uncertainty input variables to the German Federal Environmental Agency’s model system of emission reporting were replaced by probability distribution functions. The parameters determining the shapes and quantiles of the functions were taken over from primary and secondary literature or estimated through expert judgement.

Based on that, a Monte-Carlo simulation was carried out to analyse the uncertainties of the German nationally aggregated 2005 emissions of fine particles (PM10 und PM2.5) and of the aerosol precursors SO2, NOx, NH3 and NMVOC.

Pollutant - [%] + [%]
PM10 16 23
PM2.5 15 19
NOx 10 23
SO2 9 9
NMVOC 10 12
NH3 13 13

Looking at the results (95%-confidence interval), the inventories for PM10 (-16%/+23%), PM2.5 (-15%/+19%) and NOx (-10%/+23%) appear most uncertain, while the inventories for SO2 (-9%/+9%), NMVOC (-10%/+12%) and NH3 (-13%/+13%) show a higher reliability.

The source categories adding the most relevant contributions to overall uncertainty vary across the pollutants and comprise agriculture (NOx from fertiliser application, NMVOC from manure management, NH3 from animal husbandry and cultivation of land, PM10 from pig fattening), mobile machinery in agriculture and forestry (PM10, PM2,5 and NOx), construction sites/2.A.7.b (PM10), small businesses /carpentries (PM10 and PM2.5), cigarette smoke and fireworks (PM2.5), NOx from heavy duty vehicles and passenger cars, NMVOC and NH3 from petrol engines), solvent use (NMVOC) and stationary combustion (SO2 from coal-fired power plants and oil-fired domestic furnaces, PM10 and NMVOC from wood firing).

As an additional information the following table shows the uncertainties of the source category agriculture in our database CSE compared to the sectoral uncertainties for agriculture from the PAREST project for relevant pollutants (the higher uncertainty value of the Tier 2 results). Agriculture was the first source category with a complete uncertainty data set for NEC pollutants and PM for the current German inventory.

Pollutant Agriculture Uncertainties PAREST project Agriculture Uncertainties CSE database
NH3 14 % 10 %
NOx 420 % 402 %
PM10 58 % 65 %
PM2.5 67 % 72 %

Next section: 1.8 General Assessment of Completeness

Unless otherwise stated, the content of this page is licensed under Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License