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Progress of HM & POP modelling from global to country scale

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Presentation on theme: "Progress of HM & POP modelling from global to country scale"— Presentation transcript:

1 Progress of HM & POP modelling from global to country scale
Ilya Ilyin, Oleg Travnikov, Victor Shatalov, Alexey Gusev Meteorological Synthesizing Centre - East

2 Outline Overview of the GLEMOS (Global EMEP Multi-media Modelling System) model Multi-model study of Hg processes and pollution levels Research activities related to global POP transport Country-scale modelling: HM case study for Belarus

3 Global EMEP Multi-media Modelling System (GLEMOS)
Model development GLEMOS general scheme GLEMOS – new generation EMEP model for HMs and POPs aimed at replacement of previously used MSCE-HM and MSCE-POP models Anthropogenic emissions Atmosphere Land Ocean Human & environment exposure (CCE) Meteorology, ocean data Geophysics Atmospheric deposition Concentration in media Main features: Multi-pollutant (heavy metals, POPs, aerosol, …) Multi-media formulation Multi-scale consistent approach (from global to local) Based on parameterisations of previous MSC-E models

4 Multi-model study of mercury
GLEMOS model development Multi-model study of mercury EU GMOS Mercury Modelling Task Force Objectives: Multi-model evaluation of Hg atmospheric processes Assessment of Hg intercontinental transport and future scenarios Hg processes in the atmosphere Model ensemble: GLEMOS EMEP/MSC-E ICHMERIT CNR-IIA (Italy) GRAHM Environment Canada GEOS-Chem MIT (USA) CMAQ-Hg-Hem Lamar University (USA) WRF-Chem CMAQ-Hg HZG (Germany)

5 Multi-model study of mercury
GLEMOS model development Multi-model study of mercury Evaluation of Hg atmospheric processes Ground-based sites Hg0 + O3 Hg0 + OH Hg0 + Br Observations Effect of different Hg oxidation processes on Hg(II)gas concentration at Waldhof (DE2) Aircraft measurements Frankfurt - Vancouver (23 Jul 2009) Stratosphere Troposphere Effect of Hg0 depletion in the stratosphere during CARIBIC flights Marine cruises RV Urania

6 Multi-model study of mercury
GLEMOS model development Multi-model study of mercury Hg deposition from different emission sectors (2013) (UNEP/AMAP expert estimates) Speciation of global Hg emissions Stationary combustion Stationary combustion Hg0 HgIIgas HgIIpart Industrial sources Intentional use & product waste 300 600 900 Hg emissions, t/y Industrial sources Intentional use and product waste

7 Multi-model study of mercury
GLEMOS model development Multi-model study of mercury Assessment of future emission scenarios (2035) 2035 Current policy Simulated Hg deposition in 2010 and 2035 2010 New policy Maximum feasible reduction Emission data source: GMOS/AMAP estimates

8 Investigation of global POP transport using GLEMOS
GLEMOS model development Investigation of global POP transport using GLEMOS Research activities: Investigation POP long-range transport and role of secondary sources Assessment of intercontinental transport and source-receptor relationships (TF HTAP) Multi-model study of global POP pollution Verification of modelling results against UNEP SC GMP measurement data Models: GLEMOS (EMEP/MSC-E) BETR-Research (ETH, Switzerland and SU, Sweden) Substances: PCBs, PCDD/Fs, HCB, … 8

9 Long-range transport of POPs
GLEMOS model development Investigation POP long-range transport and role of air-surface exchange EMEP region Long-range transport of POPs Single-hop Multi-hop Continent A Continent B Air concentrations due to single-hop and multi-hop transport from non-EMEP emissions sources (one-year model run) Annual mean concentrations of PCB-153 for 2012 (one-year model run)

10 Intercontinental POP transport: Influence of secondary sources
GLEMOS model development Intercontinental POP transport: Influence of secondary sources 0.0 0.2 0.4 0.6 0.8 1.0 1.2 PCB-153 concentration, pg/m 3 Anthropogenic Secondary sources Modeled annual mean PCB-153 air concentrations for 2012 EMEP Source/receptor regions Source-Receptor modeling experiments using new HTAP division sources/receptor (HTAP2)

11 Investigation of global transport and fate of PCDD/Fs
GLEMOS model development Investigation of global transport and fate of PCDD/Fs Modelling with experimental emission scenario based on UNEP SC dioxins inventory 0.1 1 10 100 Observed, fg TEQ/m 3 Modelled, fg TEQ/m North America 0.1 1 10 100 Observed, fg TEQ/m 3 Modelled, fg TEQ/m Eastern Asia 0.1 1 10 100 Observed, fg TEQ/m 3 Modelled, fg TEQ/m Europe Outcome of POP research activities will be presented to UNEP SC (SC conference, Geneva, May 2015) South America Modelled vs. observed PCDD/F air concentrations Comparison of modelled PCDD/F air concentrations against UNEP GMP measurements in South America in 2012 (Schuster et al., EST, 2015)

12 From global to regional scale
GLEMOS model development From global to regional scale Nested simulations on the new EMEP grid Hg total deposition over the globe (1°×1°) Hg deposition over the new EMEP grid (0.2°×0.2°) To test the model performance in the new EMEP domain we performed pilot simulations of mercury transport with spatial resolution 0.2x0.2 degrees. Boundary conditions for the new domain were calculated with the global version of the model. As you can see the model provides high enough resolution to reproduce spatial variation on national scale. Belarus National scale Case Studies

13 Country-scale pollution assessment
EMEP HM case study Country-scale pollution assessment Case studies of HM pollution in selected EMEP countries Approach: Evaluation of pollution levels in a country with fine spatial resolution involving variety of national data Czech Republic Croatia Requirements: Detailed emissions data (fine resolution, source categories, LPS) Additional measurements from national monitoring networks Participation of national experts in joint analysis of the results Netherlands Countries involved: Country Czech Rep Croatia Netherlands Belarus Poland Status complete in progress planned

14 Major steps of HM case study for Belarus (Pb, 2012)
EMEP HM case study Major steps of HM case study for Belarus (Pb, 2012) Preparation of input data emissions measurements meteorology concentrations in soils boundary concentrations ….. 50x50 km2 10x10 km2 Data sources: - EMEP countries: CEIP - Belarus: national experts

15 Major steps of HM case study for Belarus (Pb, 2012)
EMEP HM case study Major steps of HM case study for Belarus (Pb, 2012) Preparation of input data emissions measurements meteorology concentrations in soils boundary concentrations ….. BY urban stations (national experts) Berezinskiy reserve (national experts) EMEP station (CCC) PL stations (AirBase)

16 Major steps of HM case study for Belarus (Pb, 2012)
EMEP HM case study Major steps of HM case study for Belarus (Pb, 2012) Preparation of input data emissions measurements meteorology concentrations in soils boundary concentrations ….. BY urban stations (national experts) Berezinskiy reserve (national experts) EMEP station (CCC) PL stations (AirBase) Modelling over for selected domain with fine (10x10 km) resolution Analysis of the results (together with national experts)

17 Major steps of HM case study for Belarus (Pb, 2012)
EMEP HM case study Major steps of HM case study for Belarus (Pb, 2012) Preparation of input data emissions measurements meteorology concentrations in soils boundary concentrations ….. BY urban stations (national experts) Berezinskiy reserve (national experts) EMEP station (CCC) PL stations (AirBase) Modelling over for selected domain with fine (10x10 km) resolution Analysis of the results (together with national experts)

18 Modelling of pollution levels in the EMEP domain
EMEP HM case study Modelling of pollution levels in the EMEP domain Purpose: to generate boundary concentrations for country-scale modelling domain Bias = 7.9 % Rcorr = 0.9 NRMSE = 0.57 F2 = 69% F3 = 89% Pb in air Pb in air, 2012 EMEP domain ~ 40 stations Boundary conditions Agreed domain ng/m3 10x10 km2 50x50 km2 - obs. sites The model reasonably well reproduces Pb pollution in the EMEP region, keeping in mind existing uncertainties (EMEP/MSC-E status report 2014)

19 Country-scale modelling (Pb, 2012)
EMEP HM case study Country-scale modelling (Pb, 2012) Background station Belarus (non-EMEP) EMEP station PL5, Poland PL0538 Brz PL5 PL0531 PL0148 PL0507 PL0214 Background urban stations, Poland (AirBase) kg/m3/y ng/m3 Total deposition Air concentration 10x10 km2 10x10 km2

20 EMEP HM case study Modelled vs. observed air concentrations at station Berezinskiy reserve (non-EMEP station) PL0538 Brz PL5 PL0531 PL0148 PL0507 PL0214 ng/m3 Obs. mean: 2.3 ng/m3 Mod. mean: 0.8 ng/m3 Modelled concentrations in air in 2012 with 10x10 km2 resolution Uncertainly of measurements can be estimated through participation of BY in intercalibration tests (is to be discussed with CCC)

21 Analysis of back trajectories (Berezinskiy reserve)
EMEP HM case study Analysis of back trajectories (Berezinskiy reserve) Mar. 2012 27 – 29 Apr. 2012 Future work: application of inverse modelling approach and develop emission scenarios

22 Modelled vs. observed air concentrations at Polish stations
EMEP HM case study Modelled vs. observed air concentrations at Polish stations EMEP station Reasonable agreement in warm period; underestimation in cold period No seasonal variability is officially reported in emission data National experts from PL need to be involved into analysis

23 Observed Pb air concentrations at urban stations
EMEP HM case study Observed Pb air concentrations at urban stations Observed conc. PM2.5 emission flux Observed air conc. in BY and other countries are comparable Pb emission flux Discussion on emission and measurement issues with national experts (BY, RU…) and with EMEP centres (CEIP, CCC) is needed

24 Further steps on Case Study activity with Belarus
EMEP HM case study Further steps on Case Study activity with Belarus 1. Case study for Belarus can be used to test approach of pollution level assessment in other countries of the EECCA region. 2. Application of inverse modelling approach. Construct emission scenarios. 3. Cooperation with national experts from other neighboring countries (PL, RU, UA…) and EMEP centres (CCC, CEIP) is needed. Possible extension of modeling domain to include neighboring countries. 4. Pay attention to other pollutants. Compare results for Pb with traditional pollutants (S, N, PM), involving MSC-W. 5. Prepare detailed country-specific information for Belarus with fine spatial resolution: Maps of pollution levels Contributions of foreign and secondary sources Pollution levels in individual regions Contribution of emission source categories Background levels for cities

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