Pollutants and non-GHG forcing agents - MESSAGE-GLOBIOM

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Model Documentation - MESSAGE-GLOBIOM

Corresponding documentation
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Model information
Model link
Institution International Institute for Applied Systems Analysis (IIASA), Austria, http://data.ene.iiasa.ac.at.
Solution concept General equilibrium (closed economy)
Solution method Optimization

Air pollution implications are derived with the help of the GAINS (Greenhouse gas–Air pollution INteractions and Synergies) model. GAINS allows for the development of cost-effective emission control strategies to meet environmental objectives on climate, human health and ecosystem impacts until 2030 (Amann et al., 2011 1). These impacts are considered in a multi-pollutant context, quantifying the contributions of sulfur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3), non-methane volatile organic compounds (VOC), and primary emissions of particulate matter (PM), including fine and coarse PM as well as carbonaceous particles (BC, OC). As a stand-alone model, it also tracks emissions of six greenhouse gases of the Kyoto basket with exception of NF3. The GAINS model has global coverage and holds essential information about key sources of emissions, environmental policies, and further mitigation opportunities for about 170 country-regions. The model relies on exogenous projections of energy use, industrial production, and agricultural activity for which it distinguishes all key emission sources and several hundred control measures. GAINS can develop finely resolved mid-term air pollutant emission trajectories with different levels of mitigation ambition (Cofala et al., 2007 2; Amann et al., 2013 3). The results of such scenarios are used as input to global IAM frameworks to characterize air pollution trajectories associated with various long-term energy developments (see further for example Riahi et al., 2012 4; Rao et al., 2013 5; Fricko et al., 2016 6).


  1. ^  |   (). Cost-effective control of air quality and greenhouse gases in {Europe}: {Modeling} and policy applications. '.
  2. ^  |  Janusz Cofala, Markus Amann, Zbigniew Klimont, Kaarle Kupiainen, Lena Höglund-Isaksson (2007). Scenarios of global anthropogenic emissions of air pollutants and methane until 2030. Atmospheric Environment, 41 (38), 8486--8499.
  3. ^  |  Markus Amann, Zbigniew Klimont, Fabian Wagner (2013). Regional and global emissions of air pollutants: {Recent} trends and future scenarios. Annual Review of Environment and Resources, 38 (), 31--55.
  4. ^  |  Keywan Riahi, Frank Dentener, Dolf Gielen, Arnulf Grubler, Jessica Jewell, Zbigniew Klimont, Volker Krey, David McCollum, Shonali Pachauri, Shilpa Rao, Bas van Ruijven, Detlef P van Vuuren, Charlie Wilson (2012). Chapter 17 - Energy Pathways for Sustainable Development. In Global Energy Assessment - Toward a Sustainable Future(pp. 1203--1306). Cambridge University Press, Cambridge, UK and New York, NY, USA and the International Institute for Applied Systems Analysis, Laxenburg, Austria: .
  5. ^  |  Shilpa Rao, Shonali Pachauri, Frank Dentener, Patrick Kinney, Zbigniew Klimont, Keywan Riahi, Wolfgang Schoepp (2013). Better air for better health: {Forging} synergies in policies for energy access, climate change and air pollution. Global environmental change, 23 (5), 1122--1130.
  6. ^  |  Oliver Fricko, Petr Havlik, Joeri Rogelj, Zbigniew Klimont, Mykola Gusti, Nils Johnson, Peter Kolp, Manfred Strubegger, Hugo Valin, Markus Amann, Tatiana Ermolieva, Nicklas Forsell, Mario Herrero, Chris Heyes, Georg Kindermann, Volker Krey, David L McCollum, Michael Obersteiner, Shonali Pachauri, Shilpa Rao, Erwin Schmid, Wolfgang Schoepp, Keywan Riahi (2016). The marker quantification of the shared socioeconomic pathway 2: a middle-of-the-road scenario for the 21st century. Global Environmental Change, In press ().