Alexey Gusev, Victor Shatalov, Olga Rozovskaya, Nadejda Vulyh

Slides:



Advertisements
Similar presentations
1 st Chimere workshop March 2005Stortini,Bonafe,Deserti,Minguzzi,Jongen Operational implementation of NINFA in Northern Italy ARPA Servizio IdroMeteorologico.
Advertisements

Title EMEP Unified model Importance of observations for model evaluation Svetlana Tsyro MSC-W / EMEP TFMM workshop, Lillestrøm, 19 October 2010.
Simulation of European emissions impacts on particulate matter concentrations in 2010 using Models-3 Rob Lennard, Steve Griffiths and Paul Sutton (RWE.
Alexey Gusev, Victor Shatalov, Olga Rozovskaya
Modelled results vs. emission estimates S.Dutchak, I.Ilyin, O.Travnikov, O.Rozovskaya, M.Varygina EMEP/MSC-East Modelled results vs. emission estimates.
MODELS3 – IMPROVE – PM/FRM: Comparison of Time-Averaged Concentrations R. B. Husar S. R. Falke 1 and B. S. Schichtel 2 Center for Air Pollution Impact.
1 Using Hemispheric-CMAQ to Provide Initial and Boundary Conditions for Regional Modeling Joshua S. Fu 1, Xinyi Dong 1, Kan Huang 1, and Carey Jang 2 1.
Reporting and use of air pollutant emission data under the ECE CONVENTION ON LONG-RANGE TRANBOUNDARY AIR POLLUTION Krzysztof Olendrzynski ECE/Air Secretariat.
12 th ICMGP, Jeju, Korea, 2015 Multi-model assessment of mercury cycling in the atmosphere Oleg Travnikov, Johannes Bieser, Ashu Dastoor, Carey Friedman,
Monitoring/modelling activities on POPs in 2015 and future work Victor Shatalov on behalf of MSC-E and CCC.
Icfi.com April 30, 2009 icfi.com © 2006 ICF International. All rights reserved. AIR TOXICS IN MOBILE COUNTY, ALABAMA: A MONITORING AND MODELING STUDY WEBINAR:
Trend analysis of HMs and POPs on the basis of measurements and modelling data Victor Shatalov and Oleg Travnikov, MSC-E.
EMEP Steering Body, Geneva, 2014 Activities on monitoring and modelling of POPs in 2014 and future work Victor Shatalov on behalf of MSC-E and CCC.
Progress of HM & POP modelling from global to country scale Ilya Ilyin, Oleg Travnikov, Victor Shatalov, Alexey Gusev Meteorological Synthesizing Centre.
Joint EMEP/WGE meeting, Geneva, 2015 Heavy metal pollution assessment within EMEP Oleg Travnikov on behalf of MSC-E and CCC.
TFEIP Workshop, Istanbul, May 2013 Emissions data for of heavy metal and POP modelling Oleg Travnikov, Alexey Gusev, Ilia Ilyin, Olga Rozovskaya, Victor.
20 th EIONET Workshop on Air Quality Assessment and Management Mapping BaP concentrations and estimation of population exposure and health impacts Cristina.
Air Quality trend analyses under EMEP/TFMM and link to EEA work Augustin COLETTE (INERIS), Chair of the TFMM/CLRTAP TFMM National Experts, CCC, MSC-E,
EMEP/WGE Bureaux, March 2015 MSC-E work plan, 2015 TaskItem Calculations of HMs/POPs for b Testing of HM/POP models in the new EMEP grid1.3.4.
29 th TF meeting of the ICP-Vegetation, March, 2016, Dubna, Russia ANALYSIS OF LONG-TERM TRENDS OF ATMOSPHERIC HEAVY METAL POLLUTION IN THE EMEP COUNTRIES.
EMEP/WGE Bureau, Geneva, March 2016 Main results of Long-term trends of HMs and POPs on the basis of modeling results and measurements.
TF HTAP Workshop, Potsdam, 2016 GMOS: Multi-model assessment of mercury pollution and processes Environment Canada Oleg Travnikov, Johannes Bieser, Ashu.
17 th TFMM Meeting, May, 2016 EMEP Case study: Assessment of HM pollution levels with fine spatial resolution in Belarus, Poland and UK Ilia Ilyin,
17 th TFMM Meeting, 17 – 20 May, 2016 Progress of HM and POP modelling: main activities and results Alexey Gusev, Ilia Ilyin, Olga Rozovskaya, Victor Shatalov,
Evaluation of pollution levels in urban areas of selected EMEP countries Alexey Gusev, Victor Shatalov Meteorological Synthesizing Centre - East.
Air Quality in EEA and EECCA Europe’s Environment assessment report, th Europe’s Environment assessment report, 2007 (‘the Belgrade report’) Hans.
Impact of various emission inventories on modelling results; impact on the use of the GMES products Laurence Rouïl
Joint EMEP/WGE meeting, Geneva, 2016 Evaluation of B[a]P pollution in the EMEP region: temporal trends and spatial variability Alexey Gusev, Olga Rozovskaya,
Assessment of POP pollution in EMEP region
Progress in 2017 Work-plan elements
Heavy metal pollution assessment within EMEP
Joint thematic session on B(a)P pollution: main activities and results
The CAMS Policy products
SHERPA for e-reporting
Advisor: Michael McElroy
Progress in assessment of POP pollution in EMEP region.
Overview of country-specific studies of heavy metal and POP pollution
Emissions data for of heavy metal and POP modelling
Heavy metal pollution assessment within EMEP
Second Stakeholder Expert Group meeting 19-20/01/2012
Progress of HM & POP modelling from global to country scale
Steve Griffiths, Rob Lennard and Paul Sutton* (*RWE npower)
EMEP case study on heavy metal pollution assessment:
POPs and HMs Summary , EMEP TFMM.
A. Aulinger, V. Matthias, M. Quante, Institute for Coastal Research
10th TFMM meeting, June, 2009, France, Paris
MSC-E: Alexey Gusev, Victor Shatalov, Olga Rozovskaya, Nadejda Vulykh
ENEA, National Agency for New Technologies, Energy and Sustainable
EMEP Case study: Assessment of HM pollution levels with fine spatial resolution in Belarus, Poland and UK Ilia Ilyin, Olga Rozovskaya, Oleg Travnikov.
CMAQ model as a tool for generating input data for HM and POP modeling
EURODELTA Preliminary results
U.S. Perspective on Particulate Matter and Ozone
MSC-E contribution concerning heavy metals
Update of MSC-E research activities on POPs.
PM observations in Europe a review of AirBase information
Progress and problems of POP modelling
EMEP case studies on HMs: State of the art
The EuroDelta inter-comparison, Phase I Variability of model responses
Title Why do we underestimate Elemental Carbon in PM?
Model uncertainties because of inconsistencies of emissions
Trend analysis of contamination in the EMEP region by HMs & POPs
Research of heavy metal pollution on regional (EMEP) and national (Germany) scales Ilyin I, Travnikov O. EMEP/MSC-E.
Multi-scale approach to HM and POP modelling
Trend analysis for HMs and POPs
Ilyin I., Travnikov O., Varygina M.
Persistent Organic Pollutants (POPs)
Model assessment of HM and POP pollution of the EECCA region
Comparison of model results with measurements
Modelling of BaP concentrations over France.
Presentation transcript:

Model assessment of B(a)P pollution: results for new EMEP grid and preliminary analysis for Spain Alexey Gusev, Victor Shatalov, Olga Rozovskaya, Nadejda Vulyh Meteorological Synthesizing Centre - East

Introduction Special session of Steering Body to EMEP (2016) on B(a)P and Wood burning - uncertainties of emissions factors, - PAH pollution levels and trends, - contribution of residential wood combustion and biomass burning (AIRUSE project) Spatial and temporal trends of B(a)P pollution - updated information on emissions and observed concentrations Progress in evaluation of B(a)P pollution - transition of modelling to the New EMEP grid Case study on B(a)P pollution in Spain - preliminary results

Observed B(a)P concentrations in EMEP region (2005-2014) Observed B(a)P concentrations indicate stabilization of pollution levels in recent decade In 2014 at 33% of stations annual mean B(a)P air concentrations were above the EU target level 1 ng/m3 2.5 -3 2.0 1.5 BaP in air, ng m 1.0 EU target level EU target level 0.5 0.0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Mean levels of B(a)P in air measured at background, suburban, and urban sites EEA AirBase measurements of B(a)P for 2014

PAH emissions in the EMEP countries (2005-2015) PAH emissions by sectors Largest contribution from Residential combustion Most of sectors show decrease (9% - 36%) Emission from Residential combustion is almost stable % change from 2005 to 2015 Italy 56 % Hungary 32 % Germany 9 % Romania 5 % Poland -18 % Five countries with largest emissions from Residential combustion sector

Progress in model assessment of B(a)P pollution: transition to the New EMEP grid New EMEP grid (0.2°x0.2°) Modelled vs measured BaP concentrations at background EMEP sites (2014) Old EMEP grid (50x50km) Old grid New grid Bias -20 % -5 % Correlation 0.73

Model assessment of B(a)P pollution in Spain: comparison with national measurements New EMEP grid (0.2°x0.2°) Modelled B(a)P concentrations vs. data of national and EMEP sites in Spain (2014) Overprediction EMEP sites National sites EMEP sites For some of the sites in Spain the model overestimate observed B(a)P concentrations

Case study on B(a)P pollution in Spain Case study for B(a)P was recommended by the recent Steering Body to EMEP Objective: Analysis of B(a)P pollution levels in Spain using EMEP fine resolution modelling and national data (measurements and modelling results) Country-specific study activities Modelling using national emissions and scenarios Verification of modelling results with EMEP and national measurements Analysis of pollution levels using GLEMOS and CHIMERE modelling results Sector-specific and source-receptor modelling using national emissions Data for the analysis National emissions with 0.1x0.1 resolution (2013, 2014) National measurements of B(a)P, EBAS, AirBase Modelling results of EMEP GLEMOS and CHIMERE models

PAH emissions in Spain: recent inventories National inventories of 2015, 2016, and 2017 Sectoral distribution (GNFR) Temporal coverage: 1990-2015 No speciation PAH emissions B(a)P emissions: fraction B(a)P/4PAHs is based on emissions of other EMEP countries Spatial distribution of annual B(a)P emission fluxes (0.1°x0.1°), g/km2/y Sectoral PAH emissions in Spain: sector L ~ 70%

Residential combustion (C) Spatial distribution of B(a)P emissions of Spain (2014): key source categories Agriculture (L) Industry (B) Emissions from field burning of agricultural residues dominate in southern areas Residential combustion (C) Road Transport (F)

Monitoring of PAH pollution levels in Spain Monitoring network for B(a)P: about 150 sites for period 2005-2016 Type of sites: background, suburban, urban, traffic, industrial Measured B(a)P concentrations do not indicate elevated levels in southern areas Locations of B(a)P monitoring sites (2014) Spatial distribution of annual B(a)P emission fluxes (0.1°x0.1°), g/km2/yr background rural background suburban background urban industrial traffic

PAH emission data versus measured air concentrations Annual PAH emission flux Spatial distribution of annual B(a)P emission fluxes in EMEP region, g/km2/y (2014) Measured B(a)P concentrations (2013, EEA AirBase) Average emission flux is among highest Observed B(a)P concentrations are among lowest

Model runs with varying contribution of emissions from agriculture Scenarios of B(a)P emissions for model simulations Base case: official emission data for 2014 Scenario 1: sector L decreased 2-fold (lower value of em. factor, EEA GuideBook) Scenario 2: sector L decreased 20-fold (average % in emissions of other EMEP countries) Base case Scenario 1 Scenario 2

Model evaluation of B(a)P pollution in Spain (2014) Setup of model simulations Meteorological data for modelling: generated using WRF for 2014 PAH emissions (incl B(a)P): for 2014 (spatial distribution based on 2013) Two nested domains: EMEP region, fine resolution domain over Spain (0.1°x0.1°) Boundary conditions: generated using modelling over EMEP region Modelled B(a)P air concentrations in the EMEP region and in Spain for 2014, base case model run

Model runs with varying contribution of emissions from agriculture Base case Scenario 1 Scenario 2 Assumption of lower emissions from agriculture (L) results in lower bias and higher correlation with measurements

Modelling results against measurements of background monitoring sites Results of model run with decreased emission from agriculture (Scenario 2) Modelled and observed B(a)P air concentrations (2014) Months Seasonal variations of B(a)P concentrations

Modelling results against measurements of background monitoring sites Results of model run with decreased emission from agriculture (Scenario 2) Modelled and observed B(a)P air concentrations (2014) Months Seasonal variations of B(a)P concentrations

Modelling results against measurements of background monitoring sites Area with significant disagreement between observed and modelled B(a)P air concentrations in North-eastern part of Spain Modelled and observed B(a)P air concentrations for 2014, (Scenario 2)

Modelling results against measurements of background monitoring sites Area with significant disagreement between observed and modelled B(a)P air concentrations in North-eastern part of Spain Overestimation in Barcelona Underestimation in mountainous areas Modelled and observed B(a)P air concentrations for 2014, (Scenario 2)

Emission from Residential Combustion vs observed B(a)P concentrations B(a)P pollution levels in North-eastern Spain: possible reasons of disagreement 1. Uncertainties in spatial distribution of emissions Negative correlation between measurements and total emissions as well as emissions from Residential Combustion Larger emissions from Res. Combustion are likely occurred in rural areas rather than in Barcelona urban area (Viana et al., 2016; EEA Report) Emission from Residential Combustion vs observed B(a)P concentrations

Original and modified spatial allocation of B(a)P emission fluxes B(a)P pollution levels in North-eastern Spain: possible reasons of disagreement 1. Uncertainties in spatial distribution of emissions Larger emissions from Res. Combustion are likely occurred in rural areas rather than in Barcelona urban area (Viana et al., 2016; EEA Report) Experimental scenario with modified spatial allocation for sector C (Res.Comb.) Original and modified spatial allocation of B(a)P emission fluxes

Modelled and observed B(a)P air concentrations, 2014 B(a)P pollution levels in North-eastern Spain: possible reasons of disagreement 1. Uncertainties in spatial distribution of emissions Larger emissions from Res. Combustion are likely occurred in rural areas rather than in Barcelona urban area (Viana et al., 2016; EEA Report) Experimental scenario with modified spatial allocation for sector C (Res.Comb.) Model simulations with altered spatial distribution of sector C (Res.Comb.) result in better agreement with measurements in Barcelona Modelled and observed B(a)P air concentrations, 2014

Modelled and observed B(a)P air concentrations, 2014 B(a)P pollution levels in North-eastern Spain: possible reasons of disagreement 2. Uncertainties due to modelling approach Insufficient spatial resolution Effects of specific meteorological and complex terrain conditions (inversions) may not were captured well Modelled and observed B(a)P air concentrations, 2014 Further analysis using refined emissions and finer spatial resolution is needed

Concluding remarks and further activity Modelling with emission scenarios indicated possible uncertainties in PAH emission data of Spain Refinement of PAH/BaP emissions of Spain is appreciated in co-operation with national experts and CEIP/TFEIP It is planned to perform analysis of factors affecting modelling results on B(a)P: parameters of degradation and deposition processes Evaluation of pollution using GLEMOS and CHIMERE modelling results Analysis of modelling results using measurements of B(a)P air concentrations for episodes, concentrations in vegetation, source apportionment studies, etc. Model evaluation of source-receptor relationships and contributions of individual sectors to B(a)P pollution Preparation of final report in co-operation with national experts and publication of results in peer-reviewed journal