Assessment of POP pollution in EMEP region: current progress and further activities MSC-E: Alexey Gusev, Victor Shatalov, Olga Rozovskaya, Nadejda Vulykh CCC: Wenche Aas, Knut Breivik INERIS: Florian Couvidat CIEMAT: Marta Garcia Vivanco 1

Outcome of activities on POPs in 2018 Main topics: POP monitoring in the EMEP region: peculiarities and available data Model assessment of POP pollution: main results and problems Progress in the case study on B(a)P pollution in Spain and France Exceedances of B(a)P air quality limits in the EMEP countries Co-operation with subsidiary bodies, international organizations and national experts Detailed results are available in internet: www.msceast.org www.nilu.no/projects/ccc/

Monitoring of POPs EMEP monitoring network provides information on background levels of POPs New EMEP priorities imply inclusion of complementary national /regional monitoring data: B(a)P: EU AIRBASE (870 sites, 2005-2016) PCDD/F: Spanish monitoring network (12 sites, 2008-2015) TOMPS (UK) monitoring network (6 sites, 1991-2016) Involvement of additional measurements (e.g. national data, passive sampling results) needs more active participation of CCC PCDD/F, Spain PCDD/F, TOMPS EMEP POP network AIRBASE sites for B(a)P

Peculiarities of PAH and PCB monitoring PCB-153 in air (2016) B(a)P in air (2016) ng m-3 pg m-3 EMEP EMEP AIRBASE Analysis of monitoring data highlights: Need of information on observed gas-particle partitioning of POPs Importance to sustain long-time series and continued monitoring (PCBs) Importance of fine spatial and temporal resolution in PAH emissions and modelling due to high spatial variability in observed concentrations

Model assessment of POP pollution POP modelling is based on emissions with fine spatial resolution (0.1°x0.1°) Higher spatial resolution generally improves agreement with measurements PCDD/Fs HCB PCB-153 B(a)P Modelled and observed POP air concentrations (2016)

Model assessment of B(a)P pollution Modelled B(a)P concentrations vs EMEP+AIRBASE measurements for 2016 x3 x2 Low correlation: FR, ES, DE Underestimation: FR, PL Overestimation: DE Inclusion of more detailed measurements of AIRBASE indicated low correlation and underprediction of observed concentrations

Case study on B(a)P pollution: scenario modelling Aim: Explore possibility to improve B(a)P pollution assessment using experimental emission scenario Selected countries Emission scenario approach: Official emissions of selected countries were scaled according to possible uncertainties in national inventories Difference between TNO inventory and official emissions (2005) Underestimation of emission (Residential combustion sector) Overestimation of emission (Agriculture sector)

Case study on B(a)P pollution: scenario modelling Aim: Explore possibility to improve B(a)P pollution assessment using experimental emission scenario Selected countries Main features: Sectors considered: Residential combustion (PL, FR, DE, BE, NL) and Agriculture (ES, PT) Scaling coefficients were agreed with national experts (FR, ES) Annual B(a)P emissions (2015) SCENARIO 138 t BASE CASE Annual B(a)P emissions (2015)

Case study on B(a)P pollution: scenario modelling GLEMOS and CHIMERE (France) model simulations for scenario model runs GLEMOS CHIMERE GLEMOS and CHIMERE (France) model simulations for base case model runs GLEMOS CHIMERE Both models similarly showed underestimation of measurements and low correlation Both models similarly showed improvements of agreement with measurements Rough emission scenario indicates the need of further analysis of national emission inventories of selected countries To further improve accuracy of model predictions refinement of parameterizations of B(a)P degradation and gas-particle partitioning in GLEMOS and CHIMERE is planned

Case study on B(a)P pollution: Spain Over-prediction of observed B(a)P pollution - high emissions from agricultural sources Analysis of methodology for evaluation of PAH emissions revealed some inconsistencies* GLEMOS and CHIMERE (Spain) test modelling showed better agreement with measurements Further refinement of PAH emissions from the Agriculture sector (3F) CHIMERE GLEMOS Modelled and observed B(a)P air concentrations Modelled vs observed B(a)P air concentrations (GLEMOS) * performed by experts from CIEMAT (Spain)

Contribution to evaluation of exposure Measured and modelled B(a)P concentrations show exceedances of EU and WHO air quality limits in the EMEP countries According to model results ~9% of population were exposed to B(a)P concentrations above EU target level, and ~75% - above WHO reference level Highest B(a)P concentrations were observed at urban background sites Model assessment needs to consider hybrid approaches for evaluation of pollution of urban areas Modelled (5x5 km2) B(a)P air concentrations (Czech Republic) AIRBASE data (2016)

Co-operation and exchange of information on POPs Evaluation of PAH pollution and exposure requires co-operation with Working Group on PAHs of the Task Force on Health Co-operation and exchange of information with EU REACH on PAH emissions and content in various products Co-operation with HELCOM: data on POP deposition included into the Baltic Sea Pollution Load Compilation report (PLC-6) Co-operation with the Stockholm Convention: national POP emission inventories (PCDD/Fs, PCBs, HCB), monitoring data - Update of global PCDD/F emission scenario (2012-2014)

Main directions of work in 2019 Country-scale assessment of POP pollution: - Continue assessment of B(a)P pollution for Spain and France - Evaluation of pollution levels in high-emission and high-impact areas - Analysis of factors affecting quality of POP pollution modelling Evaluation of multi-compartment intercontinental transport of POPs: - Assessment of PCDD/Fs and PCB pollution from regional and global sources - Analysis of the key factors affecting POP accumulation in and exchange between the environmental media - Evaluation of secondary emissions of selected POPs 3. Contribution to the analysis of effectiveness of implementation of Protocol on POPs (co-operation with TF TEI): - Analysis of long-term trends of B(a)P pollution levels - Assessment of B(a)P pollution levels with focus on urban areas - Evaluation of the key source categories contribution to B(a)P pollution - Projections of future B(a)P pollution levels