Methodology and models
In the MACEB project several emission pathways is studied to mitigate the warming of Arctic climate by black carbon. The main modeling tool box in the project consisted of the combination of the global Greenhouse Gas and Air Pollution Interactions and Synergies model (GAINS) of International Institute for Applied Systems Analysis (IIASA) and aerosol-climate model ECHAM5-HAM2, developed at the Max Planck Institute for Meteorology.
GAINS model
The GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies) model (http://gains.iiasa.ac.at/) simultaneously addresses health and ecosystem impacts of particulate pollution, acidification, eutrophication and tropospheric ozone, as well as considers greenhouse gas emission (GHG) rates and the associated value per ton of CO2 equivalence. GAINS allows for the analysis of synergies in the air pollution and climate policies.
Historic emissions of air pollutants and GHGs are estimated for each country based on information collected by available international emission inventories and on national information supplied by individual countries. The GAINS model assesses emissions on a medium-term time horizon, emission projections are specified in five year intervals through the year 2050.
Options and costs for controlling emissions are represented by several emission reduction technologies. Atmospheric dispersion processes, critical load data, and critical level data are often modeled/collected exogenously and integrated into the GAINS model framework. The model can be operated in the 'scenario analysis' mode, i.e., following the pathways of the emissions from their sources to their impacts. In this case the model provides estimates of regional costs and environmental benefits of alternative emission control strategies. The model can also operate in the 'optimization mode' which identifies cost-optimal allocations of emission reductions in order to achieve specified deposition levels, concentration targets, or GHG emissions ceilings.
Although GAINS includes global coverage, the spatial resolution varies between regions. For Europe, other Northern Hemisphere countries, and most of Asia the calculation is done on a national level while for Russia and several large Asian countries (China, India, Japan, Indonesia, etc.) provincial/administrative state units are also distinguished. For the rest of the World approach varies from national data (e.g., Australia, New Zealand, Egypt, and South Africa) to aggregated regions consistent with the IPCC SRES regions.
ECHAM model
The ECHAM5-HAM2 aerosol-climate model was developed at the Max Planck Institute for Meteorology (Stier et al., 2005, Zhang et al., 2012 ). The model is one of the most sophisticated global aerosol-climate models available. It includes all the major aerosol processes and takes into account the direct and indirect aerosol effects (cloud modifications). In terms of aerosol species it has black carbon, organic aerosols, sulphate aerosols, dust and sea salt. ECHAM is a widely used climate model, for example it is one of the Intergovernmental Panel on Climate Change (IPCC) ensemble models.
Methodology and model configuration
The ECHAM5-HAM2 model simulates 5 years long time period and the final monthly results are obtained by averaging or summing multi-year data. In this way it is possible to reduce the internal variability known to exist models overall. For all different simulation, a so called nudging mode is used. In the nudged mode, the model meteorology (divergence, vorticity, surface pressure and temperature) are forced to follow ERA-interim reanalysis data (Dee et al., 2011). This means that for the 5 years time period (from 2003 to 2007), the model's climate is nudged to follow reanalysis data, but the different emissions pathways are changed. With this approach, it is possible to see how the scenario pathways would effect, for example, the Arctic in today's climatological conditions.
Model modification and new emissions
In the MACEB project the model ECHAM5-HAM2 is used with an updated emission module. The module includes new ship and wildfire emissions for black carbon, organic carbon and sulfur dioxide, new aviation emissions for black carbon, and updated anthropogenic emissions from the GAINS model.
The ship emissions are from two different sources: global proxy data by Wang et al. (2007) and Arctic shipping emission dataset by Corbett et al. (2010). For the global proxy, the RCP 8.5 (Representative Concentration Pathways) values for the years 2005, 2020 and 2030 are used (Riahi et al., 2007; Riahi et al., 2011). For all overlapping grid point, Arctic shipping values are used. For the aviation emissions, QUANTIFY project emission data for the year 2000 is used (http://www.pa.op.dlr.de/quantify/). To scale these values for the years 2005, 2020 and 2030, scaling factors obtained from the Fig. 6 in Lee et al. (2010) are used.
FRES model
Finnish Regional Emission Scenario (FRES) model is a national air pollution emission modeling tool (Karvosenoja 2008). Compared with the GAINS model, FRES calculates emissions of air pollutants specifically for Finland, with more detailed description of point sources and nationally important source sectors, such as residential wood combustion. The emission outputs can be gridded to have a 1km x 1km geographical resolution. FRES model acts as a Finnish reference tool in national expert consultations with IIASA, i.e. the parameters of activity projections and emission factors are well harmonized between the two models. The calculation for aerosol emissions, including black carbon and organic carbon in the FRES model was developed in close collaboration with respective GAINS model development. The FRES model calculates aerosol emissions in four particle size classes (PM10-2.5-1.0-0.1). Emission uncertainty analysis has been carried out for the different parts of the FRES model (Karvosenoja et al. 2008, Tainio et al. 2010).
