Impacts of deep decarbonization pathways on the Italian energy intensive industries

1. Impacts of deep decarbonization pathways
on the Italian energy intensive industries
Maria Gaeta, Cristina Tommasino, Chiara Martini, Maria Rosa Virdis
ETSAP Workshop
CMA MINES ParisTech, Sophia Antipolis,
October 22-23, 2015

2. Background and objectives
• Work carried out in the framework of the DDPP project (led by IDDRI and the UN
SDSN).
• Objective: to explore the impacts of different decarbonization pathways to 2050 for
Italy. Scenarios consider 80% CO2 emissions reduction by 2050 w.r. to 1990.
• Focus on the role of CCS, renewables and energy efficiency in CO2 emissions reductions,
assuming different levels of penetration of CCS and Renewables and different effort in
energy efficiency.
• Special attention paid to energy intensive industries.
• The response strategies of the system analyzed with a linear optimization model
(TIMES-Italy) under different technological hypotheses.
• Two alternative economic assumptions: exogenous energy service demand and
price elastic energy service demand.
• The second case explicitly considers output reduction in energy intensive industries
as a response strategy in a scenario where industrial CCS options are limited.
• The same scenarios are assessed from a macroeconomic perspective using a CGE
model (GDyn-E).

3. Methodological approach
-
EU
Roadm
ap
2050
IPCC
(2°C)
EU &
ITA
policy
context
Uncertainties and challenges
• RES availability
• Technology options &
improvement
• Resource potential
• Social acceptability
•…..
Italy DD CO2 target
DD Pathways definition
CGE model analysis
ES model analysis
• Impacts on national energy
system and main indicators
• Sectorial emission
• Efficiency
• Electrification
• Technology choice &
investment
• Impacts on national
macroeconomic indicator
• Employment
• Global Trade
CO2 emissions
Energy demand
Fuel mix
GDPprojection
Fuelprice
Populationprojection
• Stage 1: Analysis of the Italian
energy system to identify key
uncertainties, challenges & build
consistent storylines.
• Stage 2: Definition of reference
macroeconomic drivers and CO2
emissions for the REF and DDP
scenarios in both models.
• Stage 3: Quantification of the main
energy trends for the chosen
scenarios using TIMES-Italy;
• Harmonization of drivers defined in
Stage 2 with the output produced
by TIMES Italy in Stage 3 (primary
energy supply by source, emission
reduction targets etc.) in the CGE
model GDyn-E
• Stage 4: Top-down, macroeconomic
evaluation of the decarbonization
scenarios with GDyn-E

4. 4
Key Challenges and uncertainties
UC-Studi
No Nuclear
- The nuclear option excluded (referendum in 2011). This could result in an increase in the
generation costs for greater use of other options.
RES
- Intermittent renewables require suitable network infrastructure (smart grid, storage etc ...)
-> investment and O&M costs increase.
- Resource availability (in particular for bioenergy)
CCS
- R&D and commercialization
- CO2 storage sites and social acceptability
ELECTRIFICATION
- It is promoted by low electricity prices.
- Lack of one or more decarbonisation factors of the electricity system reduces the
role of electrification in the end-use sectors
- EV and heat pumps deployment.
RES in end-use sectors
- Resource availability (in particular for bioenergy).
- Air quality (for biomass).
TRANSPORT
- Infrastructure costs for modal shift and attitudes towards public transport.
- R&D and costs of hydrogen and electrical storage.
Energy efficiency - High buildings retrofitting costs and availability of financing.
Industry
- CCS R&D and commercialization
- CO2 storage sites and social acceptability
- High energy prices could influence the shift towards a less energy intensive
industry

5. 5
Scenario overview
UC-Studi
The three scenarios are characterized as follows:
The CCS scenario (CCS):
• High public acceptance of key low carbon generation technologies.
• Abundant renewable sources, capture technology and CO2 storage sites allow to decarbonize
the electricity system high electrification of heating and transport ;
• Large amount of electricity from renewables and fossil fuel technologies coupled with CCS.
• The EFF scenario (EFF):
• Lower availability of options to decarbonize the electricity system, results in relatively higher
costs and a reduction of the electricity consumed in end-use sectors.
• This is compensated by an increased reliance on advanced energy efficiency technologies and
a greater renewable energy use for heat and transportation.
• A lower sectoral discount rate stimulates a higher penetration of new and advanced energy
efficiency technologies
• The DMD_RED scenario (DMD_RED)
• Limited availability of CCS (especially in the industrial sector) and high cost of decarbonization.
• Low public acceptance of CCS, in part due to insufficient policy effort.
• Simulated using the TIMES-Italy model in the version with price elastic demand:
• the demand drivers of end-use sectors are influenced by high fuel and energy carrier prices.

6. 6
Scenario overview
CCS EFF DMD_RED
Generation decarbonization
Nuclear - - -
RES +++ ++ ++
CCS +++ ++ +
Electrification
Heat pumps, EV and PHEV +++ ++ ++
Fuel switch to electricity +++ + +
End-use sectors
Building retrofit ++ +++ +++
Advanced eff. technologies ++ +++ +++
RES for heat and transportation +++ +++ ++
Fuel switch in final sectors ++ +++ +++
CCS in Industrial sector +++ ++ +
Service demand in final sectors
Transport modal shift + + ++
Reduction in Industry production - - ++

7. 7
Results
Energy-related and process CO2 emissions in Reference Scenario and Deep
Decarbonization Pathways – MtCO2.
Emissions (combustion related + process) go down to 84-92.5 Mt CO2 in DDP vs 320 in REF

8. 8
Results
Total Primary Energy Supply by energy source in three scenarios – Mtoe
Primary energy in DDPs
By 2050 is 107 - 125.5 Mtoe
vs 170 Mtoe in REF
Energy dependence down
from 70% to below 35%

9. 9
Results
Energy intensity of GDP – MJ/$2005
In DDPs energy intensity is
27% to 38% lower than in REF

10. 10
Results
Electrification of final energy consumption
Electricity emissions
intensity, g CO2/kWh
Emissions are less than 3%
of the 2010 value

11. 11
Results
Power generation
Generation from fossil fuels is 10 to 15% of the
REF value in DDP scenarios

12. 12
Results
Final Energy consumption
goes down to 70.2-85.3Mtoe in DDP vs 144.1 in REF
25% 33%
29%

13. 13
Results
Energy mix in industry sector

14. 14
Results
Industry Final Energy Use by sectors
0
10
20
30
40
50
60
2010 CCS EFF DMD_RED CCS EFF DMD_RED
2030 2050
MtonsCO2
Energy-related CO2 emissions by sector
• Final energy use highest in the CCS
scenario
• In DEM-RED scenario, iron and steel,
non ferrous metals, chemicals and non
metallic minerals reduce consumption
more visibly

15. Results
25,8
34,5
34,5
27,2
9,0
13,5
13,5
13,2
1,4
1,6
1,6
1,3
56,5
79,3
79,3
60,2
0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 80,0 90,0
CCS
EFF
DMD_RED
20102050
Non-metallicminerals Non-ferrous Paper Iron&Steel
Output levels for selected energy intensive products, Mt
Output grows least in the DMD-RED scenario, especially cement, iron and steel
and non ferrous metals

16. Macroeconomic analysis: Results
GDP change relative to Reference in 2050 - %
-14,0
-12,0
-10,0
-8,0
-6,0
-4,0
-2,0
0,0
2010 2015 2020 2025 2030 2035 2040 2045 2050
CCS
EEF
DMD-RED
Significant lowering of GDP
trajectory vs Ref after 2030,
but within the range seen in
the CGE literature (Knopf et
al. 2014)
Such dramatic impact due to
assumptions and model
characteristics:
• By construction, in this
scenario Italy does -80%
while rest of EU does
-65% CO2 emissions
• CGE perform poorly in
long run projections;
• Renewables and zero
carbon technologies not
explicitly represented in
this model version;

17. Macroeconomic analysis: Results
Output change with respect to Reference in 2050 - %
-70
-60
-50
-40
-30
-20
-10
0
10
20
CCS EEF DMD-RED

18. Macroeconomic analysis: Results
Change in value added with respect to Reference in 2050 - %
-80
-60
-40
-20
0
20
40
60
80
CCS EEF DMD-RED

19. Macroeconomic analysis: Results
Change in employment with respect to Reference in 2050 - %
-100
-50
0
50
100
150
200
250
CCS EEF DMD-RED

20. Macroeconomic analysis: Results
-500,0
-400,0
-300,0
-200,0
-100,0
0,0
100,0
200,0
300,0
400,0
500,0
CCS
EFF
DEM_RED
Trade balance with respect to Reference in 2050 - %

21. Conclusions 1/2
• RES, EE and CCS are key components of any Italian decarbonization scenario
• Energy dependence in DDPs decreases significantly: to 30-35% vs 70% in the REF case.
• The power sector is about 93% decarbonized;
• Final energy use is highest in the CCS scenario
• In DDPs electricity will be 47-49% of the final energy mix in industry by 2050.
• In DEM-RED scenario, iron and steel, non ferrous metals, chemicals and non metallic
minerals contract energy consumption more visibly
• Biggest output drop in the DMD-RED scenario. More mitigated impacts in the Energy
efficiency scenario.
• Energy system costs structure moves away from variable (fuel) costs and towards
fixed (investment) costs.

22. Conclusions 2
• Macroanalysis shows a significant GDP drop w.r. to Reference in all decarbonization
scenarios after 2030, but within the range seen in the CGE literature.
• In decarbonization scenarios the biggest output and value added contraction occurs in
extractive activities (oil&gas, other mining), oil refining, non-ferrous metals and non-
metallic minerals. Employment impacts for the same sectors are also negative
• Positive impacts in less energy intensive industries
• Trade impacts are mostly positive (large reduction in oil and gas imports,
improvement of energy dependence) except for the oil refining sector.
• If CCS is not a viable option and other enabling technologies are unable to reduce
signicantly energy demand and CO2 emissions in energy intensive industries, the result
could be delocalization and further downsizing. This calls for immediate policy
intervention especially in R&D, but may require social programs to alleviate labor
displacement.
• The GDyn-E model currently used at ENEA needs to be improved to adequately
represent low carbon technologies.
Thanks for the attention!