Analysis of station classification and network design INERIS (Laure Malherbe, Anthony Ung), NILU (Philipp Schneider), RIVM (Frank de Leeuw, Benno Jimmink) 18th EIONET meeting -Dublin- 25th October 2013

Context  An increasing amount of available data on air quality in Europe  Extension of data coverage for all pollutants both in time and space  Much effort dedicated to data QA/QC (e.g. JRC-AQUILA quality programmes)  Information on siting requested in current and future reporting obligations 18th EIONET meeting, Dublin, 25th October 2013 O 3 and PM 10 monitoring stations for which data have been reported to AirBase AirBase v7, (JRC- AQUILA Position Paper on siting criteria and station classification)

Context ...but still limited information  on the monitoring strategies underlying site selection;  on the fitness for purpose of the selected measurement locations.  An encouragement  to refine existing station classification schemes or develop supplementary ones,  to develop meta-information describing the station surroundings (land use, population density,...) 18th EIONET meeting, Dublin, 25th October 2013 (JRC- AQUILA Position Paper on siting criteria and station classification)

Objectives of the study  First part : evaluation of the network design from several angles:  evolution from 1996  fulfilment of the EUROAIRNET criteria  compliance with the AQD  Second part: a supplementary classification scheme (presented by L. Rouïl at the17 th EIONET meeting, 2012) :  update the classification according to Joly and Peuch (2012) methodology and check its robustness  analyse the results on the European scale  investigate specific situations NB: study mainly focused on NO 2, O 3 and PM 18th EIONET meeting, Dublin, 25th October 2013

Evaluation of the network 18th EIONET meeting, Dublin, 25th October 2013

Evolution of the network  Selected years:  1996: state before the implementation of the Framework AQ Directive (information for the majority of EU15 Members)  2004: from EU15 to EU 25  2007: from EU25 to EU27  2011: the most recent year available in AirBase 18th EIONET meeting, Dublin, 25th October 2013 classtype of areatype of station (sub)urban background (U) urbanbackground suburbanbackground traffic (T) urbantraffic suburbantraffic ruraltraffic unknowntraffic regional background (R)ruralbackground industrial (I) urbanindustrial suburbanindustrial ruralindustrial unknownindustrial  Considered station categories:

18th EIONET meeting, Dublin, 25th October PM 10

Monitoring criteria 18th EIONET meeting, Dublin, 25th October 2013  EURO-AIRNET (Larssen et al., 1999):  number of cities to be included in a European representative network: all large cities (>500,000) 25% of medium cities (250, ,000) 10% of small cities (50, ,000) Agg/zone>UATL-UAT more157 Minimum requirements for PM (PM 10 + PM 2.5 )  AQ Directive  The number of stations in an agglomeration/zone depends on population and current AQ status NB: Countries may also use modelling as a supplementary assessment tool ; in that case these numbers may be reduced by up to 50% under the conditions set in Dir. 2008/50/CE, Art. 7

Monitoring criteria 18th EIONET meeting, Dublin, 25th October 2013  Application of EUROAIRNET criteria: Minimum monitoring coverage Actual PM 10 monitoring coverage Actual NO 2 monitoring coverage all large cities (>500,000)72 of 73 (99%)59 of 73 (81%) 25% of medium cities (250, ,000)93 of 116 (80%)92 of 116 (79%) 10% of small cities (50, ,000)555 of 750 (74%)528 of 750 (70%)

Monitoring criteria 18th EIONET meeting, Dublin, 25th October 2013  Application of AQD criteria: Ex: PM monitoring, 702 zones/agglomerations common to 1996, 2004, 2007 and Compliance with AQD considering the assessment regimes applicable in 2011: Results for NO 2 monitoring: Number of zones for which: N stations = N min N stations > N min N stations < N min Number of zones for which: N stations = N min N stations > N min N stations < N min

Supplementary classification according to Joly & Peuch (2012) methodology 18th EIONET meeting, Dublin, 25th October 2013

Brief recall of the methodology  Methodology developed in the framework of GMES/MACC program  Objective: establishing a pollutant-specific objective classification of stations based on the temporal variability of the observation data  For each considered pollutant, time series are summarized by eight indicators characterizing the diurnal cycle, the weekend effect and the high frequency variations.  The classification is performed in two stages: 1) Definition of the classes, from class1 to 10, with a selected set of stations. A linear discriminant analysis is performed so as to best discriminate between rural stations and stations most influenced by human activities (“urban + traffic” sites). 2) Classification a posteriori of the other stations.  ETC/ACM Technical Paper 2012/17 (2013) 18th EIONET meeting, Dublin, 25th October 2013

Update and analysis with AirBase v7 18th EIONET meeting, Dublin, 25th October 2013 Spatial distribution of the classes O3O3 PM 10 NO 2  In some countries, all station classes are present.  For some pollutants, other countries only have low or high station classes.  Classification is missing for some stations (criteria not filled, missing data, only daily values reported)

 More stations have been classified: 18th EIONET meeting, Dublin, 25th October 2013 Number of stations classified in ETC/ACM (2013) study (AirBase v6, ) Number of stations classified in this study (AirBase v7, ) NO PM O3O Monitoring stations not classified last year but classified in this study Update and analysis with AirBase v7 PM 10 O3O3 NO 2

 As in 2012, the classification has been analysed in relation with EoI classification and auxiliary variables (population density, land use) This analysis confirms the robustness of the methodology. 18th EIONET meeting, Dublin, 25th October 2013 Distribution of PM 10 classes as a function of EoI classification Mean and median population density around PM 10 measurement stations for each class Update and analysis with AirBase v7

 Different types of specific situations have been identified :  stations for which the classification (according to Joly & Peuch, 2012) does not well match the types of area and site provided in AirBase;  stations in specific environments (e.g.: high population density);  stations displaying very different classes according to the measured pollutant. 18th EIONET meeting, Dublin, 25th October 2013 Interesting cases

18th EIONET meeting, Dublin, 25th October 2013 Distribution of population density in each PM 10 class  Three stations have a population density higher than inhab./km 2  They are located in the same area: Paris  They are all urban background but do not have the same class. Interesting cases: example

18th EIONET meeting, Dublin, 25th October 2013 PM 10 classes in Berlin  Berlin agglomeration contains all EoI types of area/station.  It also contains almost all the class numbers, with growing numbers from rural background to traffic sites.  As in Paris, two urban background stations are interesting for study. Interesting cases: example

General conclusions  Station classification and detailed description of the station surroundings provide helpful support:  to interpret air quality data  to have a better idea of the station representativeness  to select the most relevant sets of stations for trend analysis, model evaluation, data assimilation, air quality mapping, impact studies...  This can be achieved by the joint use of  different classification schemes such as EoI (type of area/type of site) and Joly & Peuch (2012) methodology  auxiliary data such as population density, land cover, emissions...  It is proposed to compile and make such information available to data users. 18th EIONET meeting, Dublin, 25th October 2013

Proposed content of the spreadsheet  Station code  Coordinates  Ozone classification (if applicable)  EoI Classification:  Type of area  Type of station  Characteristics of zone (if available)  Classification according to Joly & Peuch methodology (2012):  Class number for O 3, NO 2 and PM 10  Dominant emission sector(s) (if available)  LAU and NUTS codes (EBM)  Population density within 1 km radius (JRC database and ORNL)  Proportion of each main land cover class within 1 km radius (CORINE)  Other remarks 18th EIONET meeting, Dublin, 25th October 2013 A premilinary Excel file is available => link