life cycle assessment of an lte base station based on primary data
TRANSCRIPT
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 1
Life cycle assessment of an LTE base station BASED ON Primary data
Pernilla Bergmark Master Researcher, Sustainability Ericsson AB Third ETSI Workshop on ICT Energy Efficiency and Environmental Sustainability 3-5 June 2015, Sophia Antipolis
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 2
Life Cycle assessment (LCA)
Production
Use
Raw material acquisition
End-of-life
Total impact on:
Global warming potential: CO2
Acidification
Eutrophication
Ozone depletion / creation
Toxicities (human, land, water)
Abiotic depletion
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 3
› Scope: Cradle-to-grave LCA of an LTE base station Main focus on raw materials & production RBS building block for network studies Only GHG presented here
› Functional unit:
Data presented: per RBS AND per year AND per
subscriber*year (subyear) As per defined configuration and use scenario
ASSESSMENT BOUNDARIES
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 4
Data Collected
Secondary data › RBS energy use › Electricity mixes / emission factors › Complementing production process
data › Materials acquisition process data › Production process data for simple
components
Primary data: › RBS configuration and hardware data › RBS material content › RBS parts production data › Assembly data › Transportation data › Electricity mixes / emission factors
Reused primary data: › Support activities (vendor and operator) › Site data › End of life treatment › ICT network data (adopted for 2014)
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 5
Pr
od
uc
tio
n p
ro
ce
ss
es
RBS LCA Data overview
Cable sets
Cabinet
Digital units
Power modules
Other modules
Radio units
Fan module
Mechanics
Electronics
Mechanics
Electronics
Mechanics
Electronics
RBS
Mechanics:
Electronics:
Climate module
Mechanics
Electronics
Primary data
Secondary data
Generic production process data
E/// Assembly
Cable production Process data
Cabinet production Process data
Climate production
Process data
Climate production
Process data
PCB, Memories, IC, ASICS production
Processes data
Power supply production
Processes data
PCB, Memories, IC, ASICS production
processes
Ericsson mechanics Production
process data
Generic production process data
Generic production process data
PCB, Memories, IC, ASICS production
processes
Power supply production
Processes data
Ericsson assembly process data
Mechanics:
Electronics:
Mechanics:
Electronics:
Ericsson mechanics Production
process data
Die casting Process data
Mechanics:
Electronics:
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 6
Parts production Raw material acquisition (incl extraction and processing)
Part cradle-to-gate
Primary data
Secondary data
RAW MATERIALS ACQUISITION & PARTS PRoDUCTION
Unspecified
Raw material processing
Raw material acquisition
Transport -Outbound
Electricity Other energy Fuels
Parts production (of e.g. IC, PBA, cables etc.)
Unspecified
Waste
Support activities Transport -Waste
Transport -Outbound
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 7
Data collection complexity Raw materials Acquisition
› Collection of primary materials content data very time consuming
› Use of secondary process data from LCA tool database
Data age Virgin / recycled ratios Yield information Meta data
Raw Materials in RBS
Known weight
Unknown weight
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 8
From Materials data to Process Models
› Mapping between materials data and models non-trivial task › Choices: One material – many processes
› Proxy data: One material – no processes
FE
cast iron part, DE, PE-GaBi, 2012-2015 mine, iron GLO, Ecoinvent 2000 Sinter, iron, at plant, GLO, Ecoinvent 1999-2002 turning, cast iron, conventional, average, RER, 2006-2007 milling, cast iron, average, RER, Ecoinvent, 2006-2007 drilling, conventional, cast iron, RER, Ecoinvent, 2006-2007
COPPER (METALLIC)
Copper sheet mix, EU-27, PE-GaBi, 12-15 copper product manufacturing, average metal working, RER, Ecoinvent, 06-07 copper, at regional storage, RER, Ecoinvent, 94-03 copper, primary , at refinery, GLO, Ecoinvent, 94-03
ZINC
zinc, primary, at regional storage, RER, Ecoinvent, 1994-2003 zinc, from combined metal production, at refinery, SE,Ecoinvent, 2004-2006 smelting,primary zinc production, GLO, Ecoinvent, 94-03, (p-agg)
PA 46 Nylon 6 granulate (PA 6), RER, PE-GaBi, 96-06 polyamid 46. is a semi-crystalline thermoplastic with very high thermal dimensional stability. Count as PA6
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 9
56%
44%
suppliers provided data
suppliers have not provideddata
› Primary data for production processes collection very time consuming!
› Below 60% answering rate
› Suppliers not used to LCA data requests
› Yield information often confidential
Data collection complexity Production processes
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 10
Supplier Data quality Production processes
› Supplier data combined for best part level quality › Secondary data from LCA tool used to fill data gaps
0
10
20
30
40
50
60
70
80
90
100
0 1 2 3 4 5
% S
uppl
iers
scale 0-5 (0:no data, 1: invalid data, 2: unreliable data, 3:aceptable data, 4: good data, 5: excellent data)
Supplier General Data Quality
0
10
20
30
40
50
60
70
80
90
100
0 1 2 3 4 5
% S
uppl
iers
scale 0:5 (0:no data, 1: invalid data, 2: unreliable data, 3:aceptable data, 4: good data, 5: excellent data)
Supplier Energy Data Quality
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 11 *A case study on estimating future radio network energy consumption and CO2 emissions
RBS configuration, use and EoLT scenarios › Configuration
40 W RF power/ sector (2 TX, 20 W/antenna), 3 sectors/site 10 MHz bandwidth
› Materials based on Macro Indoor RBS 6201 HW
› Energy consumption according to (Frenger et al, 2013)*RF load 20%
+10% for site cooling
› Use stage emission factor for word average electricity
– energy supply chain and losses included
› EoLT Full recycling (best case) Recycling data reused
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 12
0
2
4
6
8
10
12
Manufacturing and EoLT
0
2
4
6
8
10
0
20
40
60
80
100to
nne
CO
2e p
er s
ite a
nd li
fe ti
me
(10
yrs)
tonn
e C
O2e
per
site
and
yea
r
kg C
O2e
per
sub
scrip
tion
and
year
(8
00 s
ubsc
riptio
ns p
er s
ite)
Operation (Global average electricity)
RBS cabinet
RBS cabinet operation
Site equipment
Site equipment operation
Special scenario, high cooling requirements
(add-on)
Results for RBS site (life cycle)
Life time /year /subyear
Total RBS site
Total
Note! These results are only valid under the conditions applicable for the study
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 13
Manufacturing and EoLT
0
20
40
60
80
100
120to
nne
CO
2e p
er s
ite a
nd li
fe ti
me
(10
yrs)
Operation (Global average electricity)
RBS cabinet
RBS cabinet operation
Site equipment
Site equipment operation
Tower, housing and road
Top lights operation
Special scenario, high cooling requirements
(add-on)
Special scenario, individual large tower (add-on)
Results for RBS site WITH TOWER
Life time
Total RBS site
Total
Note! These results are only valid under the conditions applicable for the study
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 14
0
0,1
0,2
0,3
0,4
0,5
0,6
Manufacturing
0
0,1
0,2
0,3
0,4
0,5
0
1
2
3
4
5to
nne
CO
2e p
er s
ite a
nd li
fe ti
me
(10
yrs)
tonn
e C
O2e
per
site
and
yea
r
kg C
O2e
per
sub
scrip
tion
and
year
(8
00 s
ubsc
riptio
ns p
er s
ite)
Total RBS cabinet
Raw materials
Mechanical and electro- mech. parts
PCBs and components,
excl. ICs
Ericsson own activities*
EoLT ICs
Transport related emissions
0
20
40
60
80
100
Total
RBS cabinet cradle-to-gate raw materials acquisition, production
RBS cabinet
Life time /year /subyear
Results based on average material production in EcoInvent/GaBi
Results based on only virgin material production
Results based on ”50/50 method”
Average customer transports
Additional emissions for 10 000 km by air
Note! These results are only valid under the conditions applicable for the study
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 15
0
10
20
30
40
50
Manufacturing (including EoLT)
0
10
20
30
40
0
100
200
300
400to
nne
CO
2e p
er s
ite a
nd li
fe ti
me
(10
yrs)
tonn
e C
O2e
per
site
and
yea
r
kg C
O2e
per
sub
scrip
tion
and
year
(8
00 s
ubsc
riptio
ns p
er s
ite)
Operation (Global average electricity) Operation (other energy, e.g. travel)
Smartphone(s) RBS site Core nodes Operator activities
Data transm. IP core network
Data centers
Overall mobile broadband service Global average electricity scenario
RBS life time /year /subyear
3 year life time assumed
Based on TeliaSonera study (2010) scaled to 2014 traffic
Also including RBS site transmission
Note! These results are only valid under the conditions applicable for the study
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 16
Summary › Assessment procedure:
LCA based on primary data is resource intensive Assumptions and choices inevitable Suppliers have limited experience in providing LCA information. LCA tool databases have insufficient metadata
› Results for assessed scenario: RBS site life cycle impact 70 tonnes CO2e
› 7 tonnes CO2e/year › 9 kg CO2e/subyear › About 80% operation, 20% embodied
Mobile broadband service equals 39 kg CO2e/subyear
› Future studies: more impact categories, broader use and EoL scenarios more sensitivity analysis
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 17
ETSI EE WS 2015, Sophia Antipolis | © Ericsson AB 2015 | 2015-05-29 | Page 18
› Identification of opportunities to improve environmental performance
› Information to decisions-makers to assist their policy choices
› Selection of relevant indicators of environmental performance for monitoring
› Understanding of the potential impact of new services and solutions
› Understanding of improvements between product generations
LCA methodology primarily to be used for