Workshop on the use of GAINS model for the revision of the Gothenburg Protocol
Focus on key measures to improve air quality in Europe and the role of EECCA and Balkan countries in that improvement
20-21 June 2011
IIASA, Laxenbrg

Janusz Cofala (IIASA), Stefan Åström (IVL)

• Background
• Method
• Some illustrative results

• The GAINS model is an updated version of the RAINS model
• Originally, the RAINS model was developed to support the
UNECE CLRTAP
• GAINS makes it possible to propose effect-oriented international policies to reduce transboundary air pollution
• These policies are cheaper than 'uniform cap' policies.
• The GAINS model is today also including greenhouse gas calculations
• The GAINS model provides support to the work with air pollution in the EU and CLRTAP, as well as EU efforts to reduce emissions of Greenhouse gases in the EU.

• The model calculates cost efficiency from a 'technoeconomical' perspective (macro-economic feedbacks are not included)
• The model does not put an economic value on health and environmental impacts from air pollution. Cost-benefit analysis can be done as a separate task by other research team (AEA Technology)
• The model exists in several versions:
– The abatement cost minimizing offline version run by IIASA
– The Greenhouse Gases Mitigation Efforts Calculator (for Annex I countries)
– online scenario analysis tools for:
• Europé (within EMEP), East Asia (with China), South-Asia, Rest of the World
• Ireland, Italy, The Netherlands, Sweden, Russia (national implementations)

A model provides a simplified version of reality which can be used to show complex interactions

The scenario technique
A scenario is the description of a possible, consistent future development of a system (e.g. the energy, transport and agricultural system)
The purposes of scenarios are
• the presentation and quantification of different pathways of future development of technical systems and analysis of the consequences of these pathways (costs, environmental impacts)
• the analysis of changes in the system caused by changed exogenous parameters
Friedrich, 2010

Health impacts
- ambient particulate matter
- ground-level ozone
Vegetation and ecosystems damage
- ground-level ozone
- acidification
- eutrophication
Climate impacts
- long-term forcing
(GWP100)
- near-term forcing
●
●
PM
(BC/
OC)
●
●
●
●
SO
2
NO x
VOC NH
3
CO
2
CH
4
N
2
O HFCs
PFCs
SF
6
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Building blocks of GAINS
Energy/agricultural projections
Emission control options
Emissions Costs
Atmospheric dispersion
Air pollution impacts,
GWP of GHG emissions
PRIMES, POLES, CAPRI,
IEA, nat. projections

The GAINS optimization mode
Energy/agricultural projections
Emission control options
Emissions Costs
Atmospheric dispersion
Air pollution impacts,
GWP of GHG emissions
PRIMES, POLES, CAPRI,
IEA, national projections
OPTIMIZATION
Environmental targets

Decision makers
Decide about:
•Ambition level
(environmental targets)
•Level of acceptable risk
•Willingness to pay
Models
Identify cost-effective and robust measures:
• Balance controls over different countries, sectors and pollutants
• Regional differences in Europe
• Side-effects of present policies
• Maximize synergism with other air quality problems
• Search for robust strategies
Amann, 2009

Fuel categories:
• Coal
• Oil
• Gas
• Biomass
• Renewables
• Nuclear
• Electricity
• Heat
• Different types and grades included
Primary sectors:
• Power plants
• Other energy production and conversion
• Industry
• Domestic
• Transport
• Non-energy use
• Further divided into secondary sectors

Aggregation of transport sources
• Road transport
– Cars, light-duty trucks
– Heavy-duty trucks, buses
– Motorcycles and mopeds (2-stroke, 4-stroke)
• Non-road mobile sources
– Rail, Air, Inland waterways
– National sea traffic and national fishing
– Mobile machines – construction and industry, agriculture
– Other (households, gardening, forestry, military)
• For each source vehicle numbers and fuel consumption assessed. For road transport – also vehicle-kilometers

Production of raw materials:
• Steel
• Aluminum
• Other metals
• Cement
• Glass
• Oil and natural gas
• Oil refining
• Fertilizers…
Storage and handling of bulk products:
• Coal
• Agricultural products
• Metal ores
• Fertilizers
• Other…
Construction activities
Waste treatment and disposal

Stationary sources:
• SO2:
– Use of low sulfur fuels
– In-furnace control
– Flue gases desulphurization
– Process emissions controls
• NOx:
– Combustion modification
– Catalytic and non-catalytic reduction
• NH3:
– Dietary changes
– Animal housing adaptation and air purification
– Manure storage and application techniques
– Urea substitution
• VOC:
– Basic management techniques
– Solvent substitution
– End-of-pipe measures
• PM
– Cyclones, ESP, other Filters
– Cleaner industrial processes
– Improved boilers and stoves
– Good practices
Mobile sources:
• EURO standards
• Non-road EURO equivalents

SO
2
:
NO x
:
PM:
NH
3
:
VOC:
GHG:
180 options
400 options
850 options (same as NOx for transport sector sources)
110 options
500 options
300 (ca), incl structural measures for CO
2
, options for CH
4
, N
2
O, F-gases
Wagner, Klimont, 2009

• By using a data base containing information on:
– Emission factors for unabated emissions
– Dispersion of air pollution over Europe
– Ecosystem sensitivity, Population distribution
– Technologies and options for reducing emissions, specified with respect to:
• emission removal efficiency
• cost of implementation
• And by using scenario specific estimates (projections regarding:
– Activities causing pollution
– Implementation of emission reducing technologies

• The GAINS model can calculate the following results:
– Emissions in a country
– The impact on the environment and human health caused by the emissions
– The costs for reducing emissions in countries
• With respect to that:
– Some technologies used to reduce pollutants might increase emissions of other pollutants
– Emissions in some countries have a larger impact on human health and the environment than other countries’ emissions

E i
 j
 m , k ,
E i , j , k , m
 j ,
 m k ,
A i , j , k ef i , j , k
( 1
 eff m
)X i,j,k,m i,j,k,m
E i
A
Ef eff m
X
Country, sector, fuel, abatement technology
Emissions in country i
Activity in a given sector
“Raw gas” emission factor
Reduction efficiency of the abatement option m
Implementation rate of the considered abatement measure
Klimont, 2009

• All costs in constant Euro 2005
• Net of taxes
• Annual costs method
• Costs based on international investment and operating experience
• For developing countries – local components in investment costs included
• Three levels of discount rate
– 4% (social)
– 10% (business)
– 20% (private)

•Common (the same for all countries)
- unit investment costs,
- fixed O+M costs,
-extra demand for labor, energy, and materials
• Country-specific
- size of installation,
- plant factors,
- prices for labor, electricity, fuel and other materials,
- cost of waste disposal

Cost components:
•common (the same for all countries)
- annualized unit investment costs, I ann
- fixed O+M costs, OM fix
- extra demand for labor, energy, and materials, OM var
• country-specific, OM var
- size of installation,
- plant factors,
- prices for labor, electricity, fuel and other materials,
- cost of waste disposal
C = I ann
+ OM fix
+ OM var
Cofala, 2009

(Source-receptor relationships for PM2.5 - from the EMEP Eulerian model)

PM
0 .
5
2 .
5
* j
  i

I

(
 i

I
 ij
S
*
A ij a i
*
 p i

  i

I ij
 i

I
S
*
 n ij
A i
)
*
 s i


0 .
5 * min(max( 0 ,
 i

I c 1 *
 ij
W
* a i
  i

I c 1 *
14
32
*
 ij
W
* s i
 k 1 j
),
 i

I c 2 *
 ij
W
* n i
 k 2 j
)
PM2.5
j
I
Annual mean concentration of PM2.5 at receptor point j
Set of emission sources (countries)
J Set of receptors (grid cells) p i s i
Primary emissions of PM2.5 in country i n i a i
SO
2
NO x emissions in country i emissions in country i
NH
3 emissions in country i
α S,W ij
, ν S,W,A ij
, σ W,A ij
, π A ij
Linear transfer matrices for reduced and oxidized nitrogen, sulfur and primary PM2.5, for winter, summer and annual

Damage to human health:
• loss in life expectancy from PM2.5
• mortality from ground-level ozone
Damage to vegetation:
• effects of acidification and eutrophication for
• forests, semi-natural ecosystems, Natura 2000 areas
Emissions of greenhouse gases

Results- examples

Current and future (2020) emissions of air pollutants in Europe, kilotons
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
SO2 NOx PM 2.5
NH3 VOC
2000 Baseline Max. Reductions

2
Cost curves describe how pollution control costs increase with increasing levels of emission reductions.
3000
0.01 % S diesel oil
2500
2000
FGD small industrial boilers
0.6 % S heavy fuel oil
1500
1000
FGD large industrial boilers
0.2 % S diesel oil
FGD oil fired
power plants FGD - baseload power plants 1 % S heavy fuel oil
Low sulfur
coal
500
Remaining measures
Present legislation
0
0 50 100 150
Remaining emissions (kt SO
2
)
200 250 300

attributable to fine particles [months]
2000 2020 2020
CAFE baseline Maximum technical
Current legislation emission reductions
Loss in average statistical life expectancy due to identified anthropogenic PM2.5
Calculations for 1997 meteorology

2000 2020 2020
CAFE baseline Maximum technical
Current legislation emission reductions
Percentage of forest area with acid deposition above critical loads,
Calculation for 1997 meteorology

Documentation http://www.iiasa.ac.at/rains/gains-methodology.html?sb=10
Presentations http://www.iiasa.ac.at/rains/meetings/GAINS-tutorial/presentations.html