Ponente
Descripción
Black carbon (BC) is a particulate matter component associated with adverse health impacts and contribution to global warming. Therefore, it is one of the priority air pollutants. Emissions of BC are however still subject to large uncertainties, in particular for residential wood combustion. In order to come to a reliable emission inventory, it is essential to verify the emissions through their use in models and consequent evaluation with observed BC concentrations. Here, we present results from a study aimed at the improvement of BC emissions for air quality modeling, focusing on Germany.
Several emission inventories exist for black carbon and a large range of PM emissions factors and BC fractions can be found in literature. Based on literature review, a new estimate for BC emissions of wood combustion and traffic country totals was derived for Germany. These were used in scenario simulations with LOTOS-EUROS using a labeling approach. Updated emission factors led to a better performance of the model. In addition, several emission distribution scenarios were explored to improve the spatial and temporal distribution of residential combustion, agricultural machinery and road traffic.
Model evaluation for BC is non-trivial. It was done based on available aethalometer and EC observations, and dedicated observations with harmonized aethalometer data in Berlin, including separation of biomass burning and fossil fuel contributions. Using location-dependent factors is key to derive BC from optical measurements and to separate fossil fuel/biomass burning contributions, and the lack of harmonized data for the rest of Germany limited the evaluation of the spatial distribution of emissions.
Using the approach with dedicated observations, final model simulations with new emission distributions showed good consistency with the observations for Berlin.
