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Uncertainties in Emissions, Measurement & Modelling Workshop Feedback

This feedback provides insights from the Dublin workshop on uncertainties in emissions, measurements, and modeling, focusing on ozone, PM, and heavy metals.

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Uncertainties in Emissions, Measurement & Modelling Workshop Feedback

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  1. 9th TFMM, Bordeaux, France, 23-25 April 2008 Feedback of the joint TFMM/TFEIP workshop (Dublin, October 2007) on uncertainties in emissions, measurement and modelling Peter Builtjes, TNO and Free Univ. Berlin John van Aardenne, EC, DG JRC

  2. I) Aim of the Dublin workshopII) OverviewIII) Results and Conclusions Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  3. I) Aim of the Dublin workshop Science : To determine/discuss the uncertainties in emissions, measurements and modelling (Policy : How to act appropriate, knowing that our knowledge is uncertain) Aim : Bringing together experience on uncertainty in emission inventories, air quality observations and modelling (= meteorology + CTM) Focus on three Case Studies: Ozone, PM and Heavy Metals Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  4. II) Overview General Aspects: • Uncertainty in emissions: aims to determine where improvements should be made • Uncertainty in observations: data quality objectives and spatial representativeness (more important) • Uncertainty in modelling: both in meteorology (like vertical exchange, stable boundary layers, clouds) and in processes in the CTM’s Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  5. Case Study Ozone (Influence hemispherical background on Ozone over Europe ?) • The large uncertainty in the NOx/VOC emissions of sources like domestic combustion, open waste burning and soil NOx-emissions become more important with decreasing NOx and VOC emissions from the main anthropogenic sources • NOx and VOC-emission trends are in line with observed changes in Ozone-concentrations • Monte Carlo and Ensemble as methods to determine model uncertainty Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  6. Case Study PM (Underestimation model results due to lacking emissions?) • Residential biomass burning and agricultural emissions underestimated • Fugitive sources (industrial/agricultural) are problematic • EC/OC speciation in PM-emissions is needed • Problem of non-reported emissions/emissions that do not have to be reported: they do exist nevertheless (windblow dust, resuspension, agricultural area treatment) Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  7. Comparibility of PM-emission measurements and PM-concentration measurements is a problem • Compare modelled and observed PM-components, not just PM as a total • Modelling indicates emissions by woodburning: Underestimation in Central/Southern Europe and overestimation in Northern Europe • Modelling indicates emissions by traffic: Underestimation in Central/Southern Europe (resuspension?) Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  8. Case Study HM-Pd, Cd, Hg (Models indicate HM-emissions underestimated, is that correct?) • Uncertainties in emissions due to missing sources like resuspension • Uncertainties in fugitive emissions • Model-measurement show underestimation Pb by 20-30% Cd by 30-50% Hg OK • Inverse modelling would require one HM-station per country Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  9. III) Results and Conclusions • Reported emissions should contain speciation for VOC and PM (EC/OC) • Meteorological data needed for specific sources like NH3, Windblowndust • Non-inventory emission sources are important for the overal assessment and policy Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  10. Finer spatial and temporal emission data are needed for local air pollution studies • For HM-emissions more detailed activity data and emission factors are essential Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  11. Given: • Model uncertainty about 30-40 % • Overall measurement uncertainty about 30-40 % Leads to the hypothesis: • Discrepancy between model and observations of larger than 50 % might well be due to emissions Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

  12. General feeling of the participants • Usefull workshop • Repeat in about 2 year Feedback of the joint TFMM/TFEIP workshop on uncertainties in emissions, measurement and modelling

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