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Progress in the development of HM/POP modelling

Progress in the development of HM/POP modelling. Victor Shatalov , Alexey Gusev, Ilia Ilyin, Valeriy Sokovykh, Oleg Travnikov. Meteorological Synthesizing Centre East. 14 th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb. Policy-relevant questions.

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Progress in the development of HM/POP modelling

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  1. Progress in the development of HM/POP modelling Victor Shatalov, Alexey Gusev, Ilia Ilyin, Valeriy Sokovykh, Oleg Travnikov Meteorological Synthesizing Centre East 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  2. Policy-relevant questions • What are the priorities (and gaps to be filled in) for future model development and the time scale for achievement? • What is the added value of inverse modelling to improve emission inventories and air quality monitoring? Are those techniques really operational? • How to build up operational framework to “integrate” global and regional models? Is the idea relevant? • Is there an optimum for model resolution according to objectives, accuracy of input data, state of the art? What are the costs (human and computational resources, expertize, ...) induced by improved resolution? • Is it possible to discriminate various contributions to current and future air pollution (local emissions, hemispheric transport, climate penalty …)? • What are the most sensitive parameters in emissions to improve model results (chemical species, spatio-temporal resolution, activities and emission factors)? Is it possible to quantify their effects? 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  3. Data pre-processing (WRF, ECMWF, …) Main directions of research and development GLEMOS general scheme • Refinement of atmospheric processes • Atmospheric speciation and chemistry (Hg) • Interaction with atmospheric aerosols (PAHs) • Secondary sources and multi-media modelling • Refinement of wind re-suspension and other secondary sources (Pb, Cd, Hg, PAHs, HCB) • Analysis of emissions to the media other than atmosphere (PCDD/Fs) • Further development and application of inverse modelling • Analysis and refinement of spatial distribution and temporal variation of anthropogenic emissions (Cd, PCDD/Fs, PAHs) • Transition to lat-lon grid and modelling with fine resolution (EB Decision 2012/13) Atmosphere Ocean Terrestrial Heavy metals (Hg, Pb, Cd, …) POPs (HCB, PCDD/Fs, PAH, …) Atmospheric aerosol, EC Global Regional National 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  4. Model studies of Hg atmospheric processes Motivation: Large gaps in knowledge on major Hg oxidation mechanisms in the atmosphere Method:Model sensitivity runswith individual chemical mechanisms and evaluation vs. field campaign measurements • Processes studied: • Speciation of Hg anthropogenic emissions • Hg oxidation by O3, OH, Br • Oxidation products (gaseous or particulate) • Gas-particle partitioning of Hg(II) 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  5. RV Urania Waldhof (Germany) Model studies of Hg atmospheric processes Measurements from intensive field campaigns • Continental boundary layer • Waldhof site, EMEP monitoring network (Germany, 2009) • Free troposphere and lower stratosphere • CARIBICproject (Lufthansa international flights, 2009) • WAMO project (North America, C-130 aircraft, 2010) • Marine boundary layer • MEDOCEANOR cruise (Mediterranean Sea, RV Urania, August 2012) 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  6. Hg0 + O3 → Hg(II)gas Hg0 + OH → Hg(II)gas Hg0 + Br → Hg(II)gas Hg in boundary layer (DE2, Germany) Model sensitivity runs with different chemical mechanisms • Preliminary conclusions: • All oxidation mechanisms reproduce diurnal variation but lead to overestimation of measurements • Hg(II)gas concentration in is more affected by atmospheric chemistry, whereas Hg(II)part by direct anthropogenic emissions 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  7. Selected CARIBIC flights Frankfurt - Vancouver (23Jul 2009) Frankfurt - Osaka (27May 2009) Osaka Vancouver Caracas Cape Town Evaluation of model results vs. observations of TGM Br Obs Base O3 OH Hg in upper troposphere (CARIBIC) • Preliminary conclusions: • Model successfully reproduce spatio-temporal variation of Hg in the upper troposphere • The highest correlation was for the runs governed by the O3 chemistry; the lowest for the OH chemistry 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  8. BaP air concentration (1990-2010) Problem: Underestimation of B[a]P air concentrations in winter Overestimation in summer Refinement of model parameterization of POP processes • Improvements needed: • Model parameterization of • sorption on aerosols • degradation on aerosol surface (heterogenic chemistry) • Seasonal variations of emissions 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  9. Aerosol composition (according to Lohman and Lammel, 2004) Sorption scheme currently used in the model aerosol OC fraction Distribution of particle-bound B[a]P POPs in the atmosphere rest of aerosol Parameterization of sorption POPs on aerosols • Processes affected by sorption: • Gas-particle partitioning • Degradation • Deposition 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  10. aerosol OC fraction Aerosol EC fraction POPs in the atmosphere Rest of aerosol Parameterization of sorption POPs on aerosols • Processes affected by sorption: • Gas-particle partitioning • Degradation • Deposition Aerosol composition (according to Lohman and Lammel, 2004) Modification of sorption scheme for refinement of degradation process Distribution of particle-bound B[a]P B[a]P:Sorption on EC is ~ 10 times more intensive than on OC 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  11. Parameterization of PAH degradation Currently used in the model: Degradation of gaseous form reaction with OH radical Degradation of particle-bound form degradation rate constants obtained for atmospheric aerosol (Chen et al., 2001) Half-lives due to degradation of particle-bound B[a]P (O3 = 75 ppb). Data from Zhou et al., 2011, Kwamena et al., 2004, Calvert et al., 2002 POPs sorbed at EC are highly stable in air Refinement of degradation and sorption processes taking into account EC fraction of atmospheric aerosol can improve the description of POPs contamination 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  12. Data on atmospheric aerosol EC • Possible sources of the data on atmospheric aerosol composition: • Usage of external models • Calculations by CMAQ • Calculations by MOZART • Calculations by MSC-W • Inclusion of aerosol module to the GLEMOS system OC EC and OC concentrations for 2010 (CMAQ) 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  13. Refinement of secondary source contributions Secondary sources: re-suspension / re-volatilization from environmental media to the atmosphere Contributions of secondary sources to contamination of the EMEP region are essential for most of HMs and POPs Relation between anthropogenic and secondary sources Processes affecting secondary source contributions: Emissions to environmental media (air, soil, seawater) Accumulation in media other than the atmosphere due to deposition process Degradation in the environmental media (POPs) 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  14. Ways to overcome: • Collection and analysis of measurement data from national campaigns • Analysis of emission uncertainties and construction of emission scenarios • Collecting of the data on emissions to other media (EU Projects) • UNEP Toolkit for identification of realizes of D&F, 2013 Evaluation of PCDD/F contamination of EMEP region • Challenges: • Absence of regular measurements under EMEP • Uncertainties in official emission data • Emissions to other media 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  15. Underestimation ~ 5 times Comparison of PCDD/F simulations with measurements For the analysis 315 measurements of air concentrations for various years at various locations in Europe found in literature were used • Possible reasons: • model uncertainties in description of POP behaviour in soil and exchange processes • uncertainties in emissions to air and other media • Model validation: • model performance is tested on other pollutants (PAHs, PCBs) • model took part in a number of model intercomparison studies • the MSCE-POP model represents the state-of-the-science (EMEP/TFMM Workshop on model review) Comparison of air concentrations calculated with official emission data against measurements 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  16. Relation between emissions to air and soil in 1994 (MSC-E estimates) Trend of total emissions (to air and to soil) from 1930 to 2010 used in calculations. Evaluated on the basis of the trend of emissions to the atmosphere. Extrapolation POPCYCLING-Baltic Project Official data Scenario of PCDD/F emissions to soil Emissions to soil areevaluated on the basis of the data from 17 EU countries in 1994 (EU Project “Releases of Dioxins and Furans to Land and Water in Europe”) Sector-specific data on emissions to soil in 1994 for 17 EU countries (EU Project) 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  17. Agreement: Factor of 3 – 60% Among them factor of 2 – 37% Underestimation still takes place. Poor correlation between calculations and measurements Modelling with emissions to air and soil (constructed scenario) Calculation results Calculations of PCDD/F transport and accumulation for the period from 1930 to 2010 were performed taking into account emissions to both air and soil Comparison with measurements Modelling with emissions to air only (official EMEP data) 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  18. Further activities on PCDD/Fs • Further refinement of parameterization of model description of soil processes (particularly, degradation in soil) • Construction of emission scenarios for emissions to waters • Refinement of emission totals for emissions to the atmosphere and to soil • Refinement of spatial distribution of emissions (particularly to soil) • Collection the data on PCDD/F emissions to the atmosphere from forest fires 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  19. One-year model simulations with HCB anthropogenic emissions only HCB air concentrations for 2009, ng m-3 Comparison with EMEP measurements Evaluation of HCB pollution levels HCB contamination of the EMEP domain is in a great extent formed due to secondary sources • Contemporary levels of HCB in air are mostly controlled by secondary emissions (re-volatilization) [Barber et al., SciTotEnv, 2005] • Re-volatilization of HCB from soils essentially exceeds contemporary anthropogenic emissions (Germany: anthropogenic emission – 0.2 t y-1, re-volatilization – 10-50 t y-1 [Franke et al., 1996]) Underestimation is about a factor of 17 (7 – 30) 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  20. Multicompartment modelling within the period is needed for evaluating contemporary contamination levels • Scenario for HCB historic emissions should be constructed Peculiarities of HCB modelling • Hexachlorobenzene (HCB) is industrial by-product. From ~1945 to 1980 was actively used in agriculture as a fungicide • HCB is extremely persistent in the environment (half-life in air ~3 y, half-life in soil ~6 y) • HCB tends to accumulate in soils and sediments binding to organic matter. • The processes governing accumulation are: phase partitioning, sorption to SOM, and degradation in soil 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  21. Spatial distribution 1978 2010 Development of scenario of global historical HCB emissions for 1945-2010 Temporal variations Banning of agricultural use, ~ 1980 Compiled on the basis of FAO data and expert estimates by [Bailey et al., 2001] 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  22. Anthropogenic emissions,2010 Re-volatilization from soil,2010 Modelling of long-term cycling and accumulation of HCB in media using GLEMOS model (1945 – 2010) Model estimates of HCB relative content in media (1945 – 2010) Contribution of primary and secondary emission sources to the contamination of the EMEP domain 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  23. EMEP Model still somewhat underestimates observed HCB air concentrations for the period 1990-2010 Comparison of HCB calculated air concentrations with measurements Comparison with measurements HCB in air in 2010 (calculated by GLEMOS model), ng m-3 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  24. Refinement of emission data: • Refine estimates of HCB global historical and contemporary anthropogenic emissions • Further work is required to improve completeness and quality of official HCB emissions in the EMEP region Evaluation of HCB pollution: further activities Improvement of modelling approach: • Refine parameterization of processes governing HCB accumulation in soils: partitioning between different phases; degradation and its temperature dependence; sorption to soil organic matter. • Refine information on organic matter content in soil. • Evaluate model simulation of HCB soil content dynamics against available measurements. 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  25. Tool: adjoint model • At present the following versions of adjoint model are developed: • Adjoint model for heavy metals • Simplified adjoint model for B[a]P (not taking into account media exchange) Inverse modelling approach • The method is used to analyze: • Emission data spatial and temporal variations and their effect on modelled concentrations and deposition fluxes • Discrepancies between measurements and modelling results In future it is supposed to work out full version of adjoint model for pollutants with considerable fraction of gaseous form 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  26. eij cij = eij · fij ei’j’ ci’j’ = ei’j’ · fi’j’ Contributions (cij) of emission eij to the value of cav: cij = eij · fij cav = Σij cij = Σij fij · eij Adjoint model Target parameter (TP) (e. g., annual/monthly average cav of concentraitons at a given location) Influence function (fij) sensitivity of TP to emissions eij – adjoint model (for given meteorological data) TP (cav) If the influence function for the given TP is once calculated, the value of target parameter (cav) can be evaluated for any emission data without running the direct model 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  27. Influence functions (IFs) were calculated for all sites and all months of 2010 IF for B[a]P average at DE9 over January 2010 Maximum values of IFs for all sites and months Analysis of B[a]P emissions using adjoint modelling Measurement sites: FI96, SE12, SE14, NO2, DE1, DE9, NL9, NL91, BE13 and PL5 Target parameters: B[a]P monthly concentrations in 2010 for all months and sites Variational optimization of emission fields was applied to analyze model-measurement discrepancies at selected EMEP sites for 2010. 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  28. Comparison of measured and calculated concentrations at three EMEP sites • Application of optimized emission scenario diminished overall Root Mean Square Error (RMSE) more than twice (from 0.25 to 0.1) • Calculation results are most sensitive to emissions from Residential heating Analysis of B[a]P emissions using adjoint modelling Effect of application of optimization procedure Industry Residential heating Road transport Source category-specific optimization coefficients 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  29. Global (1°×1°) Regional (0.2°×0.2°) Local (0.05°×0.05°) Fine resolution modelling EB Decision 2012/13: Change the EMEP_ grid to latitude-longitude projection Increase spatial grid resolution to 0.1º × 0.1º Ongoing activity: adaptation of GLEMOS to simulations with fine resolution in lat-lon projection Multi-scale simulations are needed to consider contributions of non-EMEP sources to contamination of the EMEP region One-way nesting is sufficient for evaluation of EMEP contamination 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  30. Transition period: Fine resolution modelling in particular regions where necessary information is available Evaluation of improvement due to usage meteorology, emissions and land use with fine spatial resolution (presentation on Case study) 5 x 5 km Emission data for the Netherlands in 2007 Fine resolution modelling • Required information: • Emission data with fine spatial resolution Countries, CEIP • Additional measurements for model validation Countries, CCC • Geophysical data (land cover, soil properties, …) • Meteorology (generating and testing) • Adaptation of model parameterization Modelling centres 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  31. Evaluation of computational resources Computational resources needed for calculation with various resolution (Document prepared by EMEP Centres at February 2012, last revised at September 2012) 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

  32. Topics of further research • Update and evaluate GLEMOS for EMEP operational calculations on the lat.-long. projection • Improve description of Hg atmospheric loads to aquatic ecosystems through application of the multi-media modeling approach • Further evaluation of secondary sources of heavy metals and POPs (wind re-suspension, re-volatilization), their contribution to pollution levels in the EMEP domain and interaction with climate change • Improved parameterizations of processes related to interaction of Hg and POPs with atmospheric aerosols including sorption to EC/BC and OC fractions and heterogeneous chemistry • Further develop inverse modeling approach and its applications for analysis of uncertainties of heavy metal and POP emissions and modelling results for the EMEP domain 14th TF on measurements and modelling meeting, 6 – 8 May 2013, Zagreb

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