Electronic Supplementary Materials
Impacts of different diffusion scenarios for
mitigation technology options and of model
representations regarding renewables intermittency
on evaluations of CO2 emissions reductions
Fuminori Sano1, Keigo Akimoto1, 2, Kenichi Wada1
Systems Analysis Group, Research Institute of Innovative Technology for the
Earth (RITE), 9-2 Kizugawadai, Kizugawa-shi, Kyoto 619-0292, Japan
2
Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba,
Meguro-ku, Tokyo 153-8902, Japan
Phone: +81-774-75-2304
Fax: +81-774-75-2317
E-mail: sanofumi@rite.or.jp (F. Sano)
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1
S1 Overview of the DNE21+ model
The DNE21+ model (Akimoto et al. 2010) is an inter-temporal linear
programming model for assessing global energy systems and global warming
mitigation. In this model, the sum of the discounted world total energy systems
costs is minimized. The model covers the first half of the 21st century as a time
range, with 2000, 2005, 2010, 2015, 2020, 2025 2030, 2040, and 2050 as
representative time points.
The energy supply sectors are connected to the energy end-use sectors, so that
assessments are made while maintaining complete consistency across energy
supply and demand levels. For the energy supply sectors and several groups of the
energy end-use sectors (energy intensive industries, road transportation, and
several kinds of appliances in residential and commercial sector), various
technology options are explicitly modeled with assumptions of costs, energy
efficiencies, and life times of facilities. Activity amounts of the energy end-use
sectors (e.g., crude steel production in iron and steel sector, passenger or freight
transport service in road transportation) are exogenously assumed as a scenario.
Other sectors in the energy end-use sectors are modeled in a top-down fashion;
final energy demands are exogenously assumed as a scenario by energy carrier.
Energy-saving effects in these sectors are evaluated using long-term price
elasticity. The model specifies energy systems whose costs are minimized and
which meet the assumed scenarios and other requirements (e.g, carbon taxes).
The world is divided into 54 regions. To take into consideration the
transportation of energy and CO2, large countries such as the United States,
Canada, Australia, China, India, and Russia are further disaggregated into several
regions. This detailed regional segregation enables us to perform our analysis
while taking regional differences into consideration.
About 300 specific technologies, including carbon dioxide capture and storage
(CCS) technologies and CO2 fixation by afforestation, are explicitly modeled as
the technology options. This enables us to assess CO2 emission reduction
measures in detail.
A model has been developed based on the study by Hyman et al. (2003), and
with some modifications considering new insights for non-CO2 GHGs, it is used
for assessment of non-CO2 GHGs emissions and reductions. The non-CO2 GHGs
assessment model calibrates the recent historical emissions of non-CO2 GHGs
(Akimoto et al. 2010).
2
S2 Methodology for evaluation of CO2 emission
reduction effect by sector and by technology
CO2 emission reduction effect by sector and by technology is evaluated using
following equation.
ENBaseline  ENER


 S ER  S Baseline
Baseline
ER
EGBaseline
 EI Fossil

EI Fossil
, Elec
ER
 Baseline 

 EI
Baseline 
ER 
EI Fossil  EI
EI

Baseline
ER
ER
 EG , Elec
EG , Elec 
EI


 EI ER Fossil

Baseline
ER

EI ER  EI Fossil
EI Fossil

 EO Baseline

EGBaseline
 EI Baseline EI ER 
, Elec



EI Baseline  EO Baseline EO ER 
EGBaseline
EI ER
, Elec
EI Baseline EO ER
…(1)
…(2)
…(3)
…(4)

 



Baseline

ED Baseline    EO ER 
ED ER 
 EO



End use sec tors
End use sec tors
 



…(5)


 EGBaseline

EI ER
 Baseline

, Elec
Baseline




E

E

ED Baseline  ED ER 
 N , Fossil

N , Fossil
Baseline
ER
 EI

EO
End use sec tors 



…(6)

E: CO2 emission, S: CO2 sequestration in electricity generation sector, EI: Energy
input for electricity generation, EO: Electricity output, ED: Electricity demand in
end-use sectors, Baseline: Baseline scenario (EMF27G1 in this paper), ER:
Emission reduction scenario, G: Gross, N: Net, Elec: Electricity generation sector,
Fossil: Fossil fuels.
The CO2 emission reduction by CCS in electricity generation sector is evaluated
based on (1), with subtracting CO2 increase effect by electricity consumption for
carbon capture.
The CO2 emission reductions by nuclear and renewables are evaluated by (2).
Energy conversion efficiency of renewables excluding biomass is assumed to be
100%. For nuclear, the efficiency is assumed to be 33%. The CO2 emission
reduction by (2) is disaggregated into the CO2 emission reduction by each energy
source based on primary energy share in nuclear and renewables.
The CO2 emission reductions by fuel switching among fossil fuels in electricity
generation sector, by efficiency improvements in electricity generation sector, and
by improvements in transmission loss are evaluated by (3), (4), and (5),
respectively. They are aggregated into “Others” in this paper.
The CO2 emission reductions in the energy end-use sectors are evaluated by (6),
and residual is used as the CO2 emission reductions in energy conversion sectors
excluding electricity generation sector.
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S3 Regional impact of model representations
regarding intermittency of wind power and solar PV
Standard
No consideration for
capacity credit
550 ppm CO2eq
EMF27G12
(Nuclear phase out)
EMF27G11
(Without CCS)
EMF27G9
(All technologies)
EMF27G20
(Nuclear phase out)
EMF27G19
(Without CCS)
No consideration for
grid stability
EMF27G17
(All technologies)
Share of wind power and PV in electricity grid [%]
100
90
80
70
60
50
40
30
20
10
0
No consideration for
capacity credit and
grid stability
450 ppm CO2eq
Fig. S1 Share of wind power and solar PV in electricity grid (USA)
Standard
No consideration for
capacity credit
550 ppm CO2eq
EMF27G12
(Nuclear phase out)
EMF27G11
(Without CCS)
EMF27G9
(All technologies)
EMF27G20
(Nuclear phase out)
EMF27G19
(Without CCS)
No consideration for
grid stability
EMF27G17
(All technologies)
Share of wind power and PV in electricity grid [%]
100
90
80
70
60
50
40
30
20
10
0
No consideration for
capacity credit and
grid stability
450 ppm CO2eq
Fig. S2 Share of wind power and solar PV in electricity grid (EU-27)
Standard
No consideration for
capacity credit
550 ppm CO2eq
EMF27G12
(Nuclear phase out)
EMF27G11
(Without CCS)
EMF27G9
(All technologies)
EMF27G20
(Nuclear phase out)
EMF27G19
(Without CCS)
No consideration for
grid stability
EMF27G17
(All technologies)
Share of wind power and PV in electricity grid [%]
100
90
80
70
60
50
40
30
20
10
0
No consideration for
capacity credit and
grid stability
450 ppm CO2eq
Fig. S3 Share of wind power and solar PV in electricity grid (Japan)
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Standard
No consideration for
capacity credit
550 ppm CO2eq
EMF27G12
(Nuclear phase out)
EMF27G11
(Without CCS)
EMF27G9
(All technologies)
EMF27G20
(Nuclear phase out)
EMF27G19
(Without CCS)
No consideration for
grid stability
EMF27G17
(All technologies)
Share of wind power and PV in electricity grid [%]
100
90
80
70
60
50
40
30
20
10
0
No consideration for
capacity credit and
grid stability
450 ppm CO2eq
Fig. S4 Share of wind power and solar PV in electricity grid (Australia)
Standard
No consideration for
capacity credit
550 ppm CO2eq
EMF27G12
(Nuclear phase out)
EMF27G11
(Without CCS)
EMF27G9
(All technologies)
EMF27G20
(Nuclear phase out)
EMF27G19
(Without CCS)
No consideration for
grid stability
EMF27G17
(All technologies)
Share of wind power and PV in electricity grid [%]
100
90
80
70
60
50
40
30
20
10
0
No consideration for
capacity credit and
grid stability
450 ppm CO2eq
Fig. S5 Share of wind power and solar PV in electricity grid (China)
Standard
No consideration for
capacity credit
550 ppm CO2eq
EMF27G12
(Nuclear phase out)
EMF27G11
(Without CCS)
EMF27G9
(All technologies)
EMF27G20
(Nuclear phase out)
EMF27G19
(Without CCS)
No consideration for
grid stability
EMF27G17
(All technologies)
Share of wind power and PV in electricity grid [%]
100
90
80
70
60
50
40
30
20
10
0
No consideration for
capacity credit and
grid stability
450 ppm CO2eq
Fig. S6 Share of wind power and solar PV in electricity grid (India)
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