This web site provides access to documentations of model methodology.

Emissions of SO2

  • Cofala et al. (1998): Sulfur Emissions, Abatement Technologies and Related Costs for Europe in the RAINS Model Database

  • Emissions of CH4

    Methodology for bottom-up inventory of CH4 1990-2020 & projections to 2050:

    Methodology for European CH4 with technical mitigation potentials and costs:

    Methodology for CH4 emission factors for the oil and gas sector:

    Other selected publications with GAINS estimates of CH4 emissions:

    Emissions of CO2

    Methodology of calculating CO2 emissions is described in Klaassen G., Berglund C., Wagner F. (2005) The GAINS Model for Greenhouse Gases - Version 1.0: Carbon Dioxide (CO2).

    Emissions of N2O

    Methodology of calculating N2O emissions has been initially described in Winiwarter W. (2005) The GAINS Model for Greenhouse Gases - Version 1.0: Nitrous Oxide (N2O).

    Subsequent imprvements have been documented by Winiwarter et al. (2018), ERL , specifically with the Supplementary Material.

    Emissions of NH3

    The methodology for calculating NH3 emissions is described in Klimont Z. and Winiwarter W. (2011): Integrated Ammonia Abatement - Modelling of Emission Control Potentials and Costs in GAINS.

    Emissions of NOx

    Methodology of calculating NOx emissions is described in Cofala J., Syri S. (1998) Nitrogen Oxides Emissions, Abatement Technologies and Related Costs for Europe in the RAINS Model Database.

    Emissions of PM

    Since the introduction of the particulate matter component in the GAINS model, there have been a number of reports and papers documenting the different elements of the model and ongoing updates.

    The most recent paper, addressing also global perspective, documents PM estimation methods and emission factors, including black carbon (BC) and organic carbon (OC), as well as development of emissions in the period 1990-2010:Klimont et al.(2017) Global anthropogenic emissions of particulate matter including black carbon.

    The original methodology of calculating PM emissions, including also cost estimation methods, is described in the IIASA report:Klimont et al. (2002) Modelling Particulate Emissions in Europe A Framework to Estimate Reduction Potential and Control Costs.

    Furthermore, the original methodology of calculating primary black carbon (BC) and organic carbon (OC) emissions, including extensive documentation of available measurement data and emission factors available at the time, is described in the IIASA report Kupiainen K. and Klimont Z.(2004) Primary Emissions of Submicron and Carbonaceous Particles in Europe and the Potential for their Control.. This work lead to a publication of a paper where on of the first assessment of European BC emissions was presented: Kupiainen K. and Klimont Z.(2007).

    Note that emission factor values given in the above reports might not be the same as actually used in the current version of the model owing to the continuous development of the model.

    Emissions of VOC

    The methodology for calculating VOC emissions is described in Klimont, Z., Cofala J., Amann M. (2000) Estimating Costs for Controlling Emissions of Volatile Organic Compounds (VOC) from Stationary Sources in Europe. Furthermore, recent information on emission controls in sectors regulated within the EU Solvent Directive has been incorporated into GAINS in collaboration with the Expert Group on Techno-Economic Issues (EGTEI).

    Impacts

    Europe

    The GAINS-Europe transfer coefficients are used (see Kiesewetter et al., 2015), which have a native resolution of 0.5° x 0.25° (roughly 28 x 28 km). Optionally, an urban increment based on a simulation with the CHIMERE CTM at 0.125° x 0.0625° (roughly 7 x 7km) is included. For the map display, a population-weighted average of the 7km grid resolution concentrations is calculated within each 28km grid.

    The menu allows to display either:

    • Anthropogenic PM2.5, 28km resolution,
    • Anthropogenic PM2.5 including an urban increment (population-weighted average within the 28km grid),
    • Anthropogenic PM2.5 including an urban increment (maximum concentrations within the 28km grid),
    • Total PM2.5, including natural PM, 28km resolution,
    • Total PM2.5, including natural PM and an urban increment (population-weighted average within the 28km grid).
    • Total PM2.5, including natural PM and an urban increment (maximum concentrations within the 28km grid).

    Asia

    This option shows ambient PM2.5 concentrations for a given scenario and year on a 0.1° grid following the methodology described in Amann et al. (2020) (see SI). Atmospheric transfer coefficients are based on perturbation simulations with the global EMEP Chemistry Transport Model run at 0.5° x 0.5° resolution for the full meteorological year 2015, with separate reduction simulations for urban low-level sources done at 0.1° x 0.1° resolution.

    Health

    This option calculates, for a given scenario and year, the number of annual deaths attributable to long-term exposure to ambient PM2.5 from five diseases: Ischemic heart disease, stroke, COPD, lung cancer, and acute lower respiratory infections (ALRI).

    Ambient PM2.5 concentrations are calculated for a given scenario and year on a 0.1° grid following the methodology described in Amann et al. (2020) (see SI). Atmospheric transfer coefficients are based on perturbation simulations with the global EMEP Chemistry Transport Model run at 0.5° x 0.5° resolution for the full meteorological year 2015, with separate reduction simulations for urban low-level sources done at 0.1° x 0.1° resolution. Population exposure is calculated by overlaying ambient PM2.5 with projected population on the same grid, based on fine resolution gridded population from the University of Southampton's WorldPop data set, projected to scenario years applying the trends in urban and rural population changes from UN World Urbanization Prospects (2018 revision).

    Attributable deaths are estimated by applying disease and age specific attributable fractions to total disease/age specific deaths. The PAF calculation makes use of the integrated exposure-response functions of the WHO (2016) Burden of Ambient Air Pollution assessment. Disease-specific baseline mortality is estimated from disease and age specific shares of total deaths as reported in the Global Burden of Disease 2013 Study, applied to total deaths as reported/projected in the UN World Population Prospects (2017 revision) (medium variant) for the scenario year.