E-PRTR incompleteness check Irene Olivares Industrial Pollution Group Air and Climate Change Programme Eionet NRC workshop on Industrial Pollution Copenhagen 4 th March 2015

1.Introduction ‐Background ‐Main objectives 2.Methodologies already developed (presented to MS) 1.Cross pollutant checks 2.Facility checks across time series 3.Feedback from MS 4.Conclusions 3.Methodologies under development (still not presented to MS) 1.Assessment of the completeness of the E-PRTR dataset focusing on missing facilities, in particular for some rarely reported pollutants 2.Using Economic and Employment Statistics to Review EU E-PRTR Emissions Data 4.Next steps Overview of the presentation

E-PRTR in-completeness check work – Introduction 2. Main objectives  Identify non reported releases and transfers on the country, activity and facility level  Identify non reported facilities  With the aim of be able to detect the data set weaknesses and find the way to improvement the data quality 1. Background  The standard informal review can easily identify outliers  The identification of non-reported facilities/ pollutants/ activities is the biggest challenge when reviewing E-PRTR data  Provision of this type of information to the EC is considered a high priority for the next years

E-PRTR in-completness check work - Methodologies already developed (presented to MS) 1.Cross pollutant check The purpose is to list possible outliers or missing values based on the emission of another pollutant, taking the Annex I activity and in some cases the main NACE into account Accidental releases are excluded Thresholds are taken into account Expected emission ranges based on literature: EMEP/EEA Guidebook, IPCC Guidelines, BREF’s 174 relations are used Pros Fast check On EEA database and on national database Easy adjustable: Excel spreadsheet with predefined queries Cons Only releases to air Limited amount of activities and pollutants (<20%) Relations between pollutants are based on literature

2. Facility checks across time series Aim: identify facilities which do not report in particular years and/or do not report all pollutants Four different methodologies: 1.Cross pollutant completeness checks across the time series: to verify whether the reporting of two selected pollutants reported by an E-PRTR facility is consistent over the full time series 2.Sector completeness checks: to verify whether E-PRTR facilities of a typical size with specific main activities and/or NACE codes (specific technology) have reported the expected pollutants for the different years 3.Time series consistency checks: to detect inconsistencies in the time series of a release/transfer of any pollutant into a defined medium. 4.Cross pollutant ratio check: to check whether the calculated quantity ratio of two defined pollutants exceeds a predefined threshold for the different years. E-PRTR in-completness check work - Methodologies already developed (presented to MS)

Pros Proved to be reliable for the identification of non-reporting if the facility has reported at least once since 2008 The tests can be further elaborated (pollutants, activities, media) For the main pollutants (CO2, SOx, NOx) seems to be quite complete Cons For PM10, HMs and POPs more gaps The test results can only flag potential non-reporting To identify facilities which did not reported under E-PRTR in any year, other methods have to be used, in particular the comparison with other data in combination with expert judgement.

3.- Feedback from MS So far 9 countries has send feedback Acknowledgement from all of them of the work done by ETC/ACM as a useful tool for improvement the E-PRTR data quality Many of the countries have provided detailed feedback about the reasons behind the potential problems E-PRTR in-completness check work - Methodologies already developed (presented to MS) 4.- Conclusions The exercise seems to be a useful tool for MS to facilitate the improvement of data quality Further analysis will be done by ETC/ACM in order to incorporate the feedback received from MS Further work is still needed in order to have a broader overview about the weaknesses of the data set Note: all methodology documents, reports, feedback material provided to the countries across the years in the context of the E-PRTR informal review is available at:

1.- Assessment of the completeness of the E-PRTR dataset focusing on missing facilities, in particular for some rarely reported pollutants Based on a comparison of: Production statistics (Prodcom) per NACE Rev.2 sector per country for the year 2011 from Eurostat Number of facilities in E-PRTR per NACE sector per country for the year 2011 Comparison is performed based on the 3 and 4 digit NACE Rev.2 codes and focus on the sectors which are most relevant for the rarely reported pollutants Previously a check has been performed to assess whether Member States have implemented the correct NACE codes for each of the E-PRTR activities. This check is done for the sectoral level and is not a facility specific test E-PRTR in-completness check work - Methodologies under development (still not presented to MS)

Preliminary results E-PRTR coverage differs a lot between countries. There are several cases where Prodcom data show that production exists, but no emission reports are included in E-PRTR E-PRTR in-completness check work - Methodologies under development (still not presented to MS)

2.- Using Economic and Employment Statistics to Review EU E-PRTR Emissions Data Basic premise of this work is that the emissions for a given pollutant from a given E- PRTR activity do not vary substantially per unit of economic activity, or per employee between countries. This methodology is based in some assuptions: First, it is assumed that all industrial activities within each E-PRTR activity are similar. Secondly, it is assumed that the distribution of plant size or capacity within an E- PRTR activity is similar between different countries It is also assumed that the efficiencies of the industrial activities are generally similar across different countries. The E-PRTR emissions data (2012 data) were combined with activity data (2012 data from Eurostat website) E-PRTR in-completness check work - Methodologies under development (still not presented to MS)

Preliminary results After processing the data it is possible to identify outliers according to one of three different criteria: Upper outlier Lower outlier Zero emission There may be valid reasons for the emissions at the E-PRTR activity level to be lower than that of the lower confidence interval The activity data from Eurostat proved to be far from complete, and this had a significant impact on data capture E-PRTR in-completness check work - Methodologies under development (still not presented to MS)

ETC/ACM is looking at the feedback we have received The comments will be incorporated The two “new” methodologies will be share also with MS in order to get feedback Some work will be done in order to developed some checks for water E-PRTR in-completness check work - Next steps

E-PRTR dataflow management Incompleteness checks introduced/tested in 2014 Irene Olivares Bendicho Industrial Pollution Group Air and Climate Change Programme Eionet NRC workshop on Industrial Pollution Copenhagen 4 th March 2015