Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS)-Model
The Greenhouse gas - Air pollution Interactions and Synergies (GAINS) model developed by the International Institute for Applied Systems Analysis (IIASA), describes the pathways of atmospheric pollution from its anthropogenic origin to the most relevant environmental impacts (Amann et al. 2011). It brings together information on future economic, energy and agricultural development, emission control potentials and costs, atmospheric dispersion and environmental sensitivities towards air pollution. The model addresses threats to human health posed by fine particulates and ground-level ozone, risk of ecosystems damage from acidification, excess nitrogen deposition (eutrophication) and exposure to elevated levels of ozone, as well as various global and regional climate metrics to calculate warming potential or temperature change. The assessed impacts are considered in a multi-pollutant context, quantifying the contributions of sulphur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3), non-methane volatile organic compounds (VOCs), primary emissions of particulate matter (PM2.5, PM10 and black and organic carbon -BC, OC), carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), fluorinated gases (HFCs, PFCs and SF6), and mercury (Hg).
The GAINS model can explore cost-effective strategies to reduce emissions of air pollutants and greenhouse gases in order to meet specified environmental targets. It also assesses how specific control measures simultaneously influence different pollutants, permitting a combined analysis of air pollution and climate change mitigation strategies, which can reveal important synergies and trade-offs between these policy areas. The optimization mode of the GAINS model balances emission control measures across countries, pollutants and economic sectors such that user-defined target levels on various environmental impacts are met at least costs.
The GAINS model framework has global coverage with a geographic representation of 180 countries/regions and spanning the period 1990 to 2050 in five-year intervals with extension to 2070 for the European region. The estimation of emissions is combining activity data with emission factors describing alternative sets of pollutant reduction technologies. The emphasis lies on a rich representation of more than a thousand emission source sectors with associated alternative sets of abatement technologies. This allows for identification and quantification of emission sources, exposure levels, and mitigation potentials at a policy relevant level, e.g., by region (EU, country, sub-national, city level), by sector (industry, residential, transport, agriculture), by farm size, by urban/rural contribution. Atmospheric dispersion processes are modeled using a source-receptor methodology that linearly approximates results of full chemical transport models. Critical load information (characterizing ecosystem sensitivities) are often compiled exogenously and incorporated 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. The current version of the model can be used for viewing activity levels and emission control strategies, as well as calculating emissions and control costs for those strategies.
GAINS is frequently used to provide model input for air pollution and climate policy formulation. For example, GAINS has been used for policy analyses by the European Commission for the EU Reference Scenario (Energy, transport and GHG emissions: trends to 2070) and for the EU Thematic Strategy on Air Pollution and the air policy review (e.g., Amann et al., 2016, 2018; EC, 2019).
- Licence type
- Non-Free Software licence
GAINS uses externally produced activity scenarios for the macroeconomic, energy sector and agricultural sector developments. These are imported through links to partial equilibrium models, e.g., PRIMES for energy sector developments in Europe, CAPRI for developments in agricultural activity (livestock numbers and fertilizer use) in Europe, and the IEA-WEO and FAO for global energy and agricultural sector scenarios, respectively. In consistency with respective macroeconomic developments, GAINS generates internally projections for waste generation, relevant industry production, and consumption of F-gases. Technology-specific emission factors and cost parameters are developed internally in GAINS through information from literature and from direct dialogues and iterative consultations with stakeholders.
GAINS estimates emissions, mitigation potentials and costs for the major air pollutants (SO2, NOx, PM, NH3, VOC, BC/OC) and for the six greenhouse gases included in the Kyoto Protocol.
Outputs include emissions, impacts and costs of alternative policy configurations, prescribed or identified as cost-effective.
model spatial-temporal resolution and extent
|Spatial Extent/Country Coverage
EU Member states 27ALL countries of the WORLD
GAINS has global coverage, distinguishing 182 regions including 48 European countries, 32 provinces in China and 23 in India, further subnational regions in larger Asian countries and also some aggregated regions, e.g. Central America.
Regular Grid 1km - 10kmRegular Grid 10km - 50km
Depends on the indicator. Grid resolution for calculating ambient PM2.5 in Europe: 0.125⁰ (longitude) x 0.0625⁰ (latitude), approx. 7x7km. Different resolution in the global domain outside Europe.
Long-term (more than 15 years)
1990 to 2050 in 5-year intervals with extension to 2070 for the European region
Five years intervals