Supporting the improvement of air quality management practices: The "FAIRMODE pilot" activity.

This paper presents the first outcomes of the "FAIRMODE pilot" activity, aiming at improving the way in which air quality models are used in the frame of the European "Air Quality Directive". Member States may use modelling, combined with measurements, to "assess" current levels of air quality and estimate future air quality under different scenarios. In case of current and potential exceedances of the Directive limit values, it is also requested that they "plan" and implement emission reductions measures to avoid future exceedances. In both "assessment" and "planning", air quality models can and should be used; but to do so, the used modelling chain has to be fit-for-purpose and properly checked and verified. FAIRMODE has developed in the recent years a suite of methodologies and tools to check if emission inventories, model performance, source apportionment techniques and planning activities are fit-for-purpose. Within the "FAIRMODE pilot", these tools are used and tested by regional/local authorities, with the two-fold objective of improving management practices at regional/local scale, and providing valuable feedback to the FAIRMODE community. Results and lessons learnt from this activity are presented in this paper, as a showcase that can potentially benefit other authorities in charge of air quality assessment and planning.

Annual variation of source contributions to PM10 and oxidative potential in a mountainous area with traffic, biomass burning, cement-plant and biogenic influences.

Toxicity of particulate matter (PM) depends on its sources, size and composition. We identified PM10 sources and determined their contribution to oxidative potential (OP) as a health proxy for PM exposure in an Alpine valley influenced by cement industry. PM10 filter sample chemical analysis and equivalent black carbon (eBC) were measured at an urban background site from November 2020 to November 2021. Using an optimized Positive Matrix Factorization (PMF) model, the source chemical fingerprints and contributions to PM10 were determined. The OP assessed through two assays, ascorbic acid (AA) and dithiothreitol (DTT), was attributed to the PM sources from the PMF model with a multiple linear regression (MLR) model. Ten factors were found at the site, including biomass burning (34, 40 and 38% contribution to annual PM10, OPAA and OPDDT, respectively), traffic (14, 19 and 7%), nitrate- and sulphate-rich (together: 16, 5 and 8%), aged sea salt (2, 2 and 0%) and mineral dust (10, 12 and 17%). The introduction of innovative organic tracers allowed the quantification of the PM primary and secondary biogenic fractions (together: 13, 8 and 21%). In addition, two unusual factors due to local features, a chloride-rich factor and a second mineral dust-rich factor (named the cement dust factor) were found, contributing together 10, 14 and 8%. We associate these two factors to different processes in the cement plant. Despite their rather low contribution to PM10 mass, these sources have one of the highest OPs per µg of source. The results of the study provide vital information about the influence of particular sources on PM10 and OP in complex environments and are thus useful for PM control strategies and actions.