Spatial representativeness of air quality monitoring sites: Outcomes of the FAIRMODE/AQUILA intercomparison exercise

Autor: KRACHT OLIVER, SANTIAGO JOSÉ LUÍS, MARTIN FERNANDO, PIERSANTI ANTONIO, CREMONA GIUSEPPE, RIGHINI GAIA, VITALI LINA, DELANEY KEVIN, BASU BIDROHA, GHOSH BIDISHA, SPANGL WOLFGANG, BRENDLE CHRISTINE, LATIKKA JENNI, KOUSA ANU, PÄRJÄLÄ ERKKI, MERETOJA MIIKA, MALHERBE LAURE, LETINOIS LAURENT, BEAUCHAMP MAXIME, LENARTZ FABIAN, HUTSEMEKERS VIRGINIE, NGUYEN LAN, HOOGERBRUGGE RONALD, ENEROTH KRISTINA, SILVERGREN SANNA, HOOYBERGHS HANS, VIAENE PETER, MAIHEU BINO, JANSSEN STIJN, ROET DAVID, GERBOLES MICHEL
Jazyk: angličtina
Rok vydání: 2017
Popis: We are presenting an evaluation of the outcomes of the FAIRMODE & AQUILA intercomparison exercise (IE) on spatial representativeness (SR). The assessment of the spatial representativeness (SR) of air quality monitoring stations is an important subject that is linked to several highly topical areas, including risk assessment and population exposure, the design of monitoring networks, model development, model evaluation and data assimilation. Nevertheless, European regulations lack a clear definition and provisions to determine the SR of the stations. Also in the scientific literature, there is no unified agreement to address this complex problem. In order to further explore this topic and to make progress in the harmonization of the related assessment procedures, the FAIRMODE (Forum for Air Quality Modelling in Europe) Cross-Cutting Activity group on SR organized a comprehensive intercomparison exercise (IE). The main objective of this IE was to evaluate the scattering of spatial representativeness results obtained by applying the range of different contemporary approaches to a jointly used example case study. In order to ensure a broad participation in this exercise, a collaborative effort has been established between FAIRMODE and AQUILA (the European Network of Air Quality Reference Laboratories). As a working basis, a shared dataset has been collected among a set of monitoring, emission and modelling data from the city of Antwerp. Within this IE, 11 different teams from 9 different countries provided their SR estimates for PM10 and NO2 at one traffic site, and for PM10, NO2 and O3 at two urban background sites. In order to narrow down the range of conceivable SR approaches and definitions, it was beforehand suggested to use the area of SR of the monitoring sites as a general concept to work with. During the course of the exercise, this concept of the SR area in fact turned out to be a useful indicator, and 10 of 11 teams were able to define shapes surrounding the stations under investigation, whereas one team rather worked towards a classification of the stations, as this was more common practice for SR evaluation in their member state. The resulting SR areas nevertheless revealed a considerable range of dissimilarity between the different teams - not only in terms of the extent and position of the SR perimeters, but also in the technical procedures and the extent of input data effectively used. These differences required detailed evaluations in order to identify the major factors triggering and controlling this spread, which can be found amongst (1) the basic principles of the methods, (2) the parameterization of the similarity criteria and thresholds, (3) the effective use of input data, and (4) the detailed conceptualization and definitions of SR. These outcomes do underline the need for (i) a more harmonized definition of the concept of “the area of representativeness” and (ii) consistent and transparent criteria used for its quantification. A comprehensive concluding section (chapter 10) is highlighting the challenges that the expert community working on spatial representativeness is currently facing. Recommendations are given for the directions to be focused on SR in the near to mid-term future. In this regards, we are outlining a roadmap towards a modular approach for better SR characterization. It is stressed that that for the aim of harmonization the concept of spatial representativeness will probably require a paradigm shift in its definition. Beyond the questions of harmonization, it should not be disregarded that alternative interpretations for the strong variability of the SR results might exist. The observed divergences in SR results could for example point us to some more fundamental discrepancies related to the evaluation of the air quality data. It is advised to take care, that in the endeavour for methodological harmonization such alternative explanations are not overlooked. An example could be a potential inconsistency within the input data coming from emission, monitoring and modelled data. Furthermore, the findings of this study are not only relevant with regard to the SR of a single monitoring station. It also gives evidence that questions need to be raised about what is the real representativeness of network monitoring data in general since it seems that there is no current consensus on its evaluation. Example given: Is there a need for the European Commission to check the criteria for the number and the siting of Air Quality Monitoring Stations set in the Air Quality Directive when a consensus on SR is reached?
JRC.C.5-Air and Climate
Databáze: OpenAIRE
Externí odkaz: