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SENCO
Including Non-Technical Measures for reducing air pollution
in Integrated Assessment Modelling
Workshop Goteborg 7-8 December 2005
Mark Barrett
SENCO Sustainable Environment Consultants
www.sencouk.co.uk
SENCONon-Technical Measures
• Define NTMs
• Illustrate certain NTMs
• Modelled results of NTMs
• Modelling issues
Some references:Report on consumption and NTMshttp://www.sencouk.co.uk/Consumption/Consumption.htm
Work in progress energy scenario including NTMshttp://www.sencouk.co.uk/Energy/Energy.htm
For comment and discussion only
SENCOThe need for Non-Technical Measures
• Assuming emission equity, global population of ten billion, GHG emission reductions of over90% required in rich countries to stabilise climate.
• Conservation, energy efficiency and renewable energy sources are vital options, but thesemeasures run into increasing marginal economic and environmental cost, and technical limits.This makes it difficult to reach reductions of over 90% with these means, at least with knowntechnologies.
• Cost-effective limits to some emission control technologies being approached
• Some NTMs can reduce multi pollutants, penetrate quickly and have low cost
SENCONon-Technical Measures: definition and examples
Non-technical measures (NTMs) may be defined as measures where the behaviour of people changes such as to reduce a givenenvironmental impact. This does not include the instruments for achieving behavioural change, such as fiscal orregulatory instruments.
NTMs may be put into four classes, as follows (with examples):
Reduce consumption• change expenditure patterns to purchase commodities with less impact, e.g. buy a hi-fi rather than an air ticket• reduce travel needs by living close to work or teleworking• holiday locally rather than abroad
Substitution• use telecommunications for business rather than air travel• modal shift from car to bus, or truck to train• wear warmer clothes to reduce thermostat setting
Technology choice• purchase of small car rather than a large one
Technology use• Transport
– reduce vehicle speeds on motorways– increase vehicle load factor
• Buildings– control of lights and appliances
SENCOComfort temperature, clothing and activity
Appropriate clothing reduces energy demand and emissions
Activity & Metabolic Rate (W/m2)
5
10
15
20
25
30
0.0 Naked
.3 Light
.5 Light
.8 Typical
1. Typical
1.3 Warm
1.5 Warm
1.8 Special
2. Special
Clothing level
SENCOBuilding use
Control of building energy systems reduces energy demand and emissions
3
8
13
18
23
28
Amb. Temp
Tt :Sitting
Tt :Kitchen
Tt :Bedrooms
Tr :Sitting
Tr :Kitchen
Tr :Bedrooms
SENCOTransport NTMs
In general energy use and carbon emissions resulting from transport depend on:• Demand: the load distance and timing of travel
– employment patterns– land use patterns– production patterns
• Substitution– trips shifted from cars to other modes;
• primary change - vehicle performance• secondary system change - congestion
• Choice of technology– car size/power– technology type (liquid, electric fuelled)
• Use of technology– speed and acceleration– the proportion of vehicle load capacity utilised
SENCOPassenger transport: distance and carbon emission by purpose
Ed ucatio n2 %Sho p p ing
10 %
Med ical (p ers)1%
Other p erso nal5%
Eat/d rink2 %
To friend s15%
So cial2 %
Entertain4 %
Sp o rt (d o )2 %
Ho lid ay 4 %
Day trip4 %
Other0 %
Esco rt6 %
Carbon emissionby purpose
To work 30%
In work 13%
• Commuting and travel in workaccount for large fraction ofemissions
SENCOPassenger transport use by trip length
St age Lengt h (km )
Car
bon
Em
issi
on (M
t)
0
5
10
15
20
25
0 50 100 150 200 250 300 350 400 450 500
Car/van T ax i M ot orcycle Bus
Coach Underground T rain Ot her public
SENCOPassenger transport: carbon emission purpose and by trip length
Stage length (km)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
0 20 40 60 80 100 120 140 160 180 200
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Non-work
In workTo and from work
Carbon dioxide emission (MtC)
% to work
Cumulative proportion
% Non work
% in work
SENCOPassenger transport : potential effect of teleworking
Minimum stage length of te leworking substitution (mile s)
Red
uctio
n in
car
bon
emis
sion
0%
1%
2%
3%
4%
5%
0 5 10 15 20 25
Reduct ion on total carbon emissionfrom UK passenger t ransport
Reduct ion on emissionof commuting
Reduct ion on emissionof in work t ravel
SENCOPassenger transport: carbon emission by mode of travel
Load factor
Roa
d &
Rai
l GW
E (g
Ceq
/p.k
m)
0
10
20
30
40
50
60
70
80
10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0
50
100
150
200
250
Air
craf
t GW
E (g
Ceq
/p.k
m)
M/cycle
Moped
Car
Bus
T rain
Aircraft
Car average
Aircraft
Charter
Scheduled
SENCOPassenger transport: mode of travel by distance
S ta g e Le n g th (M i l e s )
Prop
ortio
n of
Dis
tanc
e by
Mod
e
0 %
2 0 %
4 0 %
6 0 %
8 0 %
1 0 0 %
1 2 3 5 10 15 25 35 50 75 100
150
200
ove
r
W alk Bicy cle Car /v an T ax i M o t o rcy c le
Bus Co ach U n dergro un d BR O t h e r p ublic1 98 5 /6
SENCOPassenger transport: carbon emission by car performance
grammes Carbon per km
0
5
10
15
20
25
25 35 45 55 65 75 85
0
50
100
150
200
250
300
Acceleration
Fuel
Speed
UKspeedlimit
Petrol
DieselMicrocars
SENCOPassenger transport: car load factor by journey distance
Journey distance (miles)
1.0
1.5
2.0
2.5
3.0
3.5
1 2 3 5 10 15 25 35 50
To work
Working
Shopping
To friends
Holiday
Day trip
All purposes
SENCOTransport: road speed and CO2 emission
Note: Only applicable tocurrent internalcombustion vehicles.Curves for otherpollutants generallysimilar, because emissionstrongly related to fuelconsumption.
Characteristics of futurevehicles (e.g. urbaninternal combustion andelectric powered) wouldbe different. Minimumemission would probablybe at a lower speed, andthe fuel consumption andemissions at low speedswould not show the sameincrease. 0%
100%
200%
300%
400%
500%
600%
5 25 45 65 85 105 125 145
kph
Car (D,> 2.0 l, EURO IV) Car (P,< 1.4 l, EURO IV)Car (P,1.4 - 2.0 l, EURO IV) Car (P,> 2.0 l, EURO IV)HGV (D,Rigid, EURO IV) HGV (D,Artic, EURO IV)Bus (D,0, EURO IV) Van (D,medium, EURO IV)Van (D,large, EURO IV) Mcycle (P,250-750cc 4-s, pre)Mcycle (P,>750cc 4-s, pre)
Motorway
Fraction of minimum CO2 g/km
Low speed emission
Average concealsstart/ stop congestion
And car designdependent
SENCOTransport: road speed and PM emission
0%
100%
200%
300%
400%
500%
600%
700%
800%
900%
1000%
5 25 45 65 85 105 125 145
kph
Car (D,< 2.0 l, EURO IV) Car (P,> 2.0 l, EURO III)Car (P,< 1.4 l, EURO IV) Car (P,1.4 - 2.0 l, EURO IV)HGV (D,Artic, EURO III) HGV (D,Rigid, EURO IV)Bus (D,0, EURO III) Van (D,small, EURO IV)Van (D,medium, EURO IV) Mcycle (P,<250cc 4-s, pre)Mcycle (P,250-750cc 4-s, pre)
Motorway
Fraction of minimum PM g/km
SENCOTransport: road speed and NOx emission
0%
100%
200%
300%
400%
500%
600%
5 25 45 65 85 105 125 145
kph
Car (D,< 2.0 l, 83/351) Car (P,< 1.4 l, 91/441)Car (P,1.4 - 2.0 l, 91/441) Car (P,> 2.0 l, 91/441)Car (P,> 2.0 l, EURO IV) HGV (D,Rigid, 88/77)HGV (D,Artic, 91/542 II) Van (D,medium, 93/59)Van (D,large, 93/59) Van (P,large, EURO III)Van (P,small, EURO IV)
Motorway
Fraction of minimum NOx g/km
SENCOUK passenger transport: carbon emission saving with NTM
Car
bon
Em
issi
on (M
tC)
0
5
10
15
20
2519
90
Car
pur
chas
e
Mod
al sh
ift
Use
of c
ars
Dem
and
AL
L0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Carbon
% Foot /cycle
% Car
% P ublic/other
Vehicle distance (%1990)
Emission reduct ion (cf1990)
SENCOSEEScen: Society, Energy, Environment Scenario model
Applicable to any largecountry having IEAenergy statistics
Method• Simulates system over
years, or hours• Optimisation under
development
Scenarios• Base/Kyoto• Carbon15• LifeStyle• Tech High• Tech Lifestyle
HISTORY
FUTURE
COSTS
INPUTS / ASSUMPTIONS
IMPACTSENERGY
IEA dataEnergyPopulation, GDP
Other dataClimate, insulation...
Delivered fuel
End use fuel mix
End use efficiency
Delivered fuel by end use
Useful energy
Socioeconomic
Useful energy
Delivered energy
Lifestyle change
Demand
End use fuel mix
End use efficiency
Conversion
Primary energy
Supply efficiency
Emissions
Capital
Running Distribution losses
Supply mix
Trade
Conversion
SENCOConsumption: SEEScen : Energy services and demand drivers
• Demand for energy services determined by humanneeds, both basic and cultural
– food– comfort, hygiene, health– culture
• Population increases• Households increase faster because of smaller
households
• Wealth increases, but energy consumption andimpacts depend on choices of expenditure on goodsand services somewhat arbitrary
0
10
20
30
40
50
60
70
80
1990
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
M
GBR: TechLifestyle: Population
SHHPop_M
0
5
10
15
20
25
30
35
1990
1995
2000
2005
2010
2015
2020
2025
2030
2035
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2045
2050
M
GBR: TechLifestyle: Households
SENCOConsumption: SEEScen : Demand growth
• Growth assumed in all sectors assumed to follow from drivers• Fastest growth in international aviation
0
2
4
6
8
10
12
1419
90
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
Inde
x199
0
Ind:Iron and steel
Ind:Chem/petrochem(inc feed)Ind:Heavy
Ind:Light
Agr:
Oth:
Ser:
Res:
Tra:Nat passenger
Tra:Nat freight
Tra:Int passenger
Tra:Int freight
GBR: TechHigh: Activity
SENCOTransport, national: passenger mode
Shift from car to fuel efficient bus and train for commuting and longer journeys.
0
0.2
0.4
0.6
0.8
1
1.219
90
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
%
Nat:Pas:Ship
Nat:Pas:Plane
Nat:Pas:Rail
Nat:Pas:Bus
Nat:Pas:Car
Nat:Pas:MCycle
Nat:Pas:Bike
GBR: TechBeh: National : Passenger : Mode
SENCOTransport: national : freight mode
Shift from truck to rail. Currently, no assumed shift to inland and coastal shipping.
0
0.2
0.4
0.6
0.8
1
1.219
90
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
%
Nat:Fre:Plane
Nat:Fre:Ship
Nat:Fre:Pipe
Nat:Fre:Rail
Nat:Fre:LDV
Nat:Fre:Truck
GBR: TechBeh: National : Freight : Mode
SENCOTransport: passenger vehicle distance
A large reduction in road traffic reduces congestion which gives benefits of less energy, pollution andtravel time.
0
50
100
150
200
250
300
350
400
450
1990
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
Gv.
km
Int:Pas:Plane_LB
Int:Pas:Plane_K
Int:Pas:Ship_D
Nat:Pas:Ship_D
Nat:Pas:Plane_K
Nat:Pas:Rail_E
Nat:Pas:Rail_LB
Nat:Pas:Rail_D
Nat:Pas:Bus_E
Nat:Pas:Bus_H2
Nat:Pas:Bus_CNG
Nat:Pas:Bus_LB
Nat:Pas:Bus_D
Nat:Pas:Car_E
Nat:Pas:Car_H2
Nat:Pas:Car_LB
Nat:Pas:Car_LPG
Nat:Pas:Car_D
Nat:Pas:Car_G
Nat:Pas:MCyc_G
Nat:Pas:Bike_S
GBR: TechBeh: Passenger : Vehicle distance
SENCOConsumption: carbon and energy intensity of commodities
0
200
400
600
800
1000
1200
1400
Watc
hes an
d clock
s
Printin
g, pub
lishing o
f new
spap
ers et
c.
Furnitu
re & up
holstery
Footwea
r
Radio, T
V and h
i-fi e
quipmen
tCompute
rs
Overalls
/men
's shirt
s/unde
rwea
r
Toys/gam
es/sp
orts eq
uipmen
t
Electri
c applia
nces
Carpets
Meta
l furn
iture
Plastic
s pro
ducts
Air tra
vel (2
000 km)
Car
bon
inte
nsity
0
5
10
15
20
25
30
35
Ener
gy in
tens
ity
Carbon intensity (kgC/k£)
Energy intenisty (GJ/k£)
SENCOUK: Carbon reductions through NTMs
Carbon Emiss ion (MtC)
0 5 10 15 20 25 30 35 40 45
Space heat
W at er
P rocess
Ligh t ing
App liances
M ot ive P ower
T ranspo rt
1990
Lifestyle
Total UK Carbon Emission 1990 : 155 MtCAfter lifes tyle changes : 117 MtC
SENCO
Demand management
Freight
Passenger
Business
Leisure
Technology
AirframeEngine
Aircraft size
Operation Traffic control
Load factor
Altitude
Speed
Route length
CONTROL MEASURES
Aviation: control measures
SENCOAviation: effects of technical and operational measures
30%
40%
50%
60%
70%
80%
90%
100%
600 650 700 750 800 850 900 950 1000
C ruis e s pe e d (k ph)
Fuel
use
per
pas
seng
er k
ilom
etre
C urre ntD e c re a s e d de s ig n c ruis e s pe e d
Turboprop /p rop fan rep laces turbo fan
Im p ro ve airfram e
In crea se loa d fa ctor
Improve existingturbo fan engine
P ropfan
Te c hno lo g ic a lim pro v e m e nt
O pe ra tio na lc ha ng e
SENCOAviation scenarios
0
100
200
300
400
500
600
1991 1996 2001 2006 2011 2016 2021 2026 2031 2036 2041
Demand
Business as usual
Operational
Technology
All except demand
All measures
Load factor
Carbon emission (MtC)
SENCOEnvironment: CO2 emission by scenario
0
100
200
300
400
500
600
700
1990
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
Mt
Base/Kyoto
LifeStyle
Carbon15
TechHigh
TechLifestyle
GBR: Scenarios: Environment : Air : CO2
SENCONon-Technical Measures: summary of use as policy options
NTMs have these advantages, they:• can have a significant and rapid effect on emissions• do not assume speculative technological development• often do not have negative environmental side effects• can have low or net negative direct costs
NTMs have disadvantages, they:• require visible changes in behaviour that will generally be resisted by consumers, whereas
most technical emission control measures (catalytic converters, loft insulation) are virtuallyinvisible to the consumer
• TMs, if based on standards, have a fairly predictable easily calculated effect on futureemissions. NTMs are more uncertain.
• have indirect costs that are difficult to quantify
SENCOModelling approach, conceptual and practical problems: costing NTMs
Indirect cost calculation• Net direct costs (capital and running) of NTMs often negative
– small cars cost less than big ones– driving more slowly saves money
• Why don’t people realise these savings?– they don’t realise cost savings and therefore make economically sub-optimal
choices?– they attach a value to car size and speed?
• How can this value be imputed?– from cost savings foregone– with willingness-to-pay (WTP)
SENCOModelling approach: conceptual and practical problems: effects of NTMs
Energy, emission and cost calculationChanges to energy demand, whether by TM or NTM, cause multiple, interdependent
changes to the energy supply system, so it is problematic to assign energy, cost andemission saving to any single measure.
• Non-additive.– E.g : choosing smaller cars reduces emission by x, and, independently, lowering
motorway speed reduces emission by y, then the combined effect will be less thanx+y.
• Multiple effect.– E.g : switching from petrol cars to diesel bus and train
• reduces petrol car emissions and increases diesel bus and train emissions• reduces road congestion, and therefore emissions from all road vehicles• reducing liquid fuel consumption will reduce refinery emissions
• Wider system impacts.– Congestion of transport infrastructure– Electricity demand patter and generation mix
SENCOModelling approach, conceptual and practical problems: model integration
These interconnected aspects of NTMs have implications for modelling approaches.
• To integrate NTMs into a model depends on the structure of the model, the processesand linkages it incorporates, and its databases.
• No general model (RAINS/GAINS, PRIMES, SEEScen, ...) captures all of the detailrequired to assess NTMs; they have to be supported by sectoral models and otherexogenous analysis.
• An approach:– Which sectors are most problematic for future emission control?– Estimate the potential of each NTM individually in terms of emission reduction,
cost, political feasibility, etc.– Analyse multiple effects and interactions of NTMs.– Estimate the indirect costs (e.g. with WTP) and add to direct costs.– Fit the most promising NTMs into models so as to approximate the results of
detailed analysis. Consistency must be ensured if there are multiple effects.
• In SEEScen, TMs and NTMs are assumed (mode, speed, load factor, etc.) and then theinterdependent consequences are simulated with an interconnected system model. Thedirect costs of technologies, fuels and operation and maintenance are then calculated.
SENCOModelling approach, conceptual and practical problems: country and time dependency
The effects of NTMs will depend on scenario context and country.
SENCOUK Energy flow chart: 1990SENCO GBR : TechBeh : Y1990
Trade Extraction Fuel processing Electricity and heat Delivered Sectors Useful energyEnvironment
Waste energy
Trd_E
Trd_N
Ext_G
Ext_S
Ext_L
Solid
Nuclear
Refinery Liq
Solid
Nuclear
L_FueOil
ElOnly
Gas
Solid
Elec
Liq
Biomass Food
Res_G_
Res_S_Res_E_Res_L_
Ser_G_Ser_S_Ser_E_Ser_L_
Ind_G_
Ind_S_Ind_E_
Ind_L_
Oth_G_Oth_L_
Tra(nat) E
Tra(nat) L
Tra(int) L
Mot W
Proc W
H>120C
H<12-C
Water H
Space H
Space ACCool
CO2 CO2
SENCOUK Energy flow chart: 2050SENCO GBR : TechBeh : Y2050
Trade Extraction Fuel processing Electricity and heat Delivered Sectors Useful energyEnvironment
Waste energy
Trd_G
Trd_E
Trd_L
Ext_G
Ext_S
Biomass
Solid
Wind
TideWave
Solar
Biowaste
BiomassBiomass
proc
Refinery
S_BioL_Bio
Liq
Wind
TideWaveSolar
Waste
CHPDHFuI
ElOnly
Auto
CHPDH_H
Auto_H
Gas
G_CHP
H_Solar
Solid
Elec
Liq
Biomass Food
Res_G_CHPRes_H_Solar
Res_E_
Ser_G_CHPSer_H_SolarSer_E_
Ind_G_Ind_G_CHP
Ind_H_SolarInd_S_Ind_E_
Ind_L_Ind_L_CHP
Oth_G_
Tra(nat) ETra(nat) L
Tra(int) L
Mot W
El equipProc W
Light
H>120C
H<12-C
Cooking
Water H
Space H
Space AC
Cool
CO2
SENCOSweden: energy flow chart: 2000 (approximate data)SENCO SWE : TechBeh : Y2000
Trade Extraction Fuel processing Electricity and heat Delivered Sectors Useful energyEnvironment
Waste energy
Trd_G
Trd_S
Trd_E
Trd_N
Trd_L
Biomass
Solid
Nuclear
Hydro
BiomassBiomass
proc
Refinery
S_Bio
Liq
Nuclear
Hydro
CHPDHFuICHPDHFuICHPDHFuI
ElOnly
CHPDH_H
HeaDHout
Gas
Solid
Elec
Heat
Liq
Biomass Food
Res_S_Res_E_Res_H_Pipe
Res_L_
Ser_E_Ser_H_Pipe
Ser_L_
Ind_G_Ind_S_
Ind_E_
Ind_H_PipeInd_L_
Tra(nat) ETra(nat) L
Tra(int) L
Mot W
El equipProc W
H>120C
H<12-C
Water H
Space H
Space ACCool
CO2
SENCOEnvironment: nitrogen oxides
0
200
400
600
800
1000
1200
1400
1600
180019
90
1995
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2005
2010
2015
2020
2025
2030
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2050
kt
Fue:Ext
Fue:ProEle:Gen
Ele:Pum
Ele:TraHea:Pub
Hea:Aut
Tra(int):Sea:IntTra(int):Air: In
Tra(nat):Other i
Tra(nat):Air: DoTra(nat):Rail
Tra(nat):Road: F
Tra(nat):Road: P
Res:ResSer:Ser
Oth:oth
Ind:AgrInd:Lig
Ind:Met
Ind:CheInd:Iro
GBR: TechBeh: Air : NOx
SENCOEnvironment: particulate matter
0
20
40
60
80
100
120
140
160
18019
90
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
kt
Fue:Ext
Fue:ProEle:Gen
Ele:Pum
Ele:TraHea:Pub
Hea:Aut
Tra(int):Sea:IntTra(int):Air: In
Tra(nat):Other i
Tra(nat):Air: DoTra(nat):Rail
Tra(nat):Road: F
Tra(nat):Road: P
Res:ResSer:Ser
Oth:oth
Ind:AgrInd:Lig
Ind:Met
Ind:CheInd:Iro
GBR: TechBeh: Air : PM10
SENCOEconomics: TechBeh scenario annual costs of fuel, conversion and demand management
The annuitised costs of each fuel, technology and demand management option are calculated for each ofthe end use and supply sectors. In the low demand scenario, the fraction of total cost due toconverters (boilers, power stations, etc.) and demand management increases as compared to fuels.
0
20000
40000
60000
80000
100000
120000
14000019
90
1995
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
M€/
a
Fuel
Conversion
Dem Manage
GBR: TechBeh: Economics : Country
SENCOUK energy, space and time illustrated with EST
SENCOElectricity trade
• An extensive continentalgrid already exists
• Diversity of demand andsupply variations acrossgeographical regions
• What is the best balancebetween local and remotesupply?
InterEnergy model• Trade of energy over links
of finite capacity• Time varying demands and
supply• Minimise avoidable
marginal cost• Marginal cost curves for
supply generated by modelsuch as EleServe
SENCOEurope and western Asia – large point sources
The environmental impact of energy is a global issue: what is the best strategy for reducingemissions within a larger region?
