GAINS (Greenhouse Gas and Air Pollution
INteractions and Synergies) model
Z. Klimont
Pollution Management Group; Energy, Climate and Environment program

IPCC Expert Meeting on Short-lived Climate Forcers, 11 October 2021, virtual

GAINS: A tool for a systematic assessment of thecost-effectiveness of emission control strategies
https://gains.iiasa.ac.at/models/index.html• GAINS quantifies sectoral emission control potentials and costs,• for exogenous (governmental, international agencies) activity projections.

• Search for least-cost mix of mitigation measures to meet air quality and/or GHG targets• GAINS has global coverage - about 180 regions (several model implementations exist):• Europe*, Asia (public free access) and• for several countries/regions, e.g., Italy, Sweden, Netherlands, Ireland, Vietnam, South Africa, Hanoi, Beijing, Guateng(SA) (access for projects partners), and• global (access for projects partners; sharing results with global/regional modelling community; also CEDS)* In early 2022, the domain will be extended to include all EECCA countries

GAINS model has been also applied and further developed at thenational levelGAINS also applied in several regional and global research activities: e.g., EU funded(ACCENT, CityZen, ECLIPSE), IEA, UNEP/CCAC, GEA, RCP8.5, EMF, SSPs; CEDS

The GAINS multi-pollutant/multi-effect framework(Greenhouse gas and Air pollution INteractions and Synergies)
PM*(BC, SO2OC)
Health impacts:
PM (Loss in life expectancy)O3 (Premature mortality)
Vegetation damage:O3

Acidification
EutrophicationNOx

VOC NH3CO-+/- +N2O++

++/-CH4

Climate impacts:Long-term

Near-term forcing

CO2HFCs
PFCs
SF6-++* Includes PM2.5, PM10 as well as PM1, TSP; particle number calculation and Hg will be revised in 2023

GAINS model and emission inventories• GAINS is not an emission inventory model• We are not reviewing the inventories but use them(and other sources) to validate GAINS estimates;
this might also lead to questioning assumptions
behind inventories• We try to understand and reproduce the inventory(within GAINS source and regional resolution)• More and more effort to compare the results of GAINS
with ambient measurements to ‘validate’ theresults/assumptions• GAINS requires often more data than Tier1/2
inventories;* ‘Official reporting’ is referring to the high level Tier1/2 submitted/reported inventories

Calculating emissions
Over a 1000 ‘fuel-technology-emission reduction technology’ options
when accounting for all pollutants

Ei =  Ei , j ,k ,m =  Ai , j ,k ef i , j ,k ( 1 − effm )X i,j,k,mj ,k ,mj ,k ,mi,j,k,mCountry, sector, fuel, abatement technology

EiEmissions in country iAActivity in a given sector

Ef“Raw gas” emission factor

effmReduction efficiency of the abatement option mXm

Implementation rate of the considered abatement measure mKey elements of the emission calculation•Activity data [A] – originates from international (e.g., IEA, FAO, Eurostat, IRF, USGS,etc.), national statistics, local studies, modelling work•

Emission factors [ef] (region-specific) originate from peer-reviewed studies,measurement campaigns (some are calculated within the model dependent of
data/assumptions about e.g., sulfur, ash content, retention of S in ash, productivity,climatic conditions, etc.)•Control measures efficiency [eff] – real-life performance assessment included
where possible, multipollutant aspects (including trade-offs) considered explicitly.

•Technology application rates [X] – own interpretation of policy, regional and localassessments, stakeholder consultations, etc.

Source structure (simplified key categories)•

Several fuels/activities – coal (5), oil (2), gas, biomass, renewables, electricity, nuclear, steel,aluminum, non-ferrous metals, cement, glass, refining, fertilizers, livestock (>10), waste (>5),
paints, etc.

•Sectors – power plants (7), industry (boilers and furnaces but also >25 solvent use sectors),
fossil fuel production and distribution, residential combustion (several categories for cooking andheating), brick production (several production processes), transport (several categories for roadand non-road; high emitters treated explicitly), enteric fermentation, rice production, waste
treatment (solid waste and waste water), refrigeration, air conditioning, etc.

•Control measures – various desulphurization measures, combustion modification, catalyticand non-catalytic controls, cyclones, ESP and fabric filters, improved stoves, pellet
stoves/boilers, EURO stages, solvent substitution, manure storage options, efficient manure
application, improved waste management and recycling, etc.

Source structure (simplified key categories)•Several fuels/activities – coal (5), oil (2), gas, biomass, renewables, electricity, nuclear, steel,aluminum, non-ferrous metals, cement, glass, refining, fertilizers, livestock (>10), waste (>5),
paints, etc.

•Sectors – power plants (7), industry (boilers and furnaces but also >25 solvent use sectors),
fossil fuel production and distribution, residential combustion (several categories for cooking andheating), brick production (several production processes), transport (several categories for roadand non-road; high emitters treated explicitly), enteric fermentation, rice production, wastetreatment (solid waste and waste water), refrigeration, air conditioning, etc.

•Control measures – various desulphurization measures, combustion modification, catalytic
and non-catalytic controls, cyclones, ESP and fabric filters, improved stoves, pellet
stoves/boilers, EURO stages, solvent substitution, manure storage options, efficient manure
application, improved waste management and recycling, etc.

GAINS is a collaborative effort
Data needs

Initial IIASA version(international data)

Improved with input from national
experts

Base year & projections of
economic activities

Data already implemented in
GAINS (IEA, FAO, UN, IPCC,etc.)

National data and projections

Emission factors

Current GAINS database (peerreviewed and grey literature)

Refinements based on local
measurements

Emission controls;
efficiencies, costs

Current GAINS database (peerreviewed and grey literature)

Refinement based on national
information

Current/maximum
application of emission
controls

Current GAINS databases,
including published info about
legislation

Local information

Atmospheric dispersion

GAINS modelling based on global& regional atmospheric dispersion
model

Local fine scale model utilizing local
monitoring campaigns; updated withfindings from monitoring and source
apportionment studies (if available)

Health impacts

Global WHO methodology

Local health statistics

Current status (1) https://gains.iiasa.ac.at/models/index.html• Current release 4.01
• Modelling periodo 1990 – 2015 (historical data in five-year intervals)
o 2008, 2009, 2014, 2016 developed available globally and 2018 for some regionso 2020 – 2050 (projections in five-year intervals)• More detailed info and publications can be found at
o https://gains.iiasa.ac.at/models/gains_resources.html• Selected documentation papers• Amann et al (2011) https://doi.org/10.1016/j.envsoft.2011.07.012• Klimont et al (2017) https://www.atmos-chem-phys.net/17/8681/2017/acp-17-8681-2017.html• Gomez-Sanabria et al (2018) https://adgeo.copernicus.org/articles/45/105/2018/• Hoglund-Isaksson et al (2020) https://iopscience.iop.org/article/10.1088/2515-7620/ab7457

Current status (2) https://gains.iiasa.ac.at/models/index.html• Uncertainty in model parameters is not explicitly included in the model• Few assessments in the past for European model application• Dedicated studies jointly with atmospheric modelling and remote sensing community evaluating results• Gaps, ongoing and potential extensions• Condensables• Further improvements for solid waste management – electronic waste• NMVOC speciation• Temporal distribution (currently annual with few sectors (e.g. residential heating) where regional (grid)
specific patterns developed)• Second-hand vehicles trade and performance• Focus on some regions that have had less data or difficult access to data
(Central Asia, Africa, parts of Latin America)• Spatial gridding – moving to 0.1 x 0.1 degree globally for all species• …