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Life Cycle Assessment
Green Computing – CS 290N – Winter 2009 – January 7
“Apple's Environmental Technologies Department is an integral part of Apple's
product teams, providing input that guides product teams toward more
environmentally-friendly product design.
The Department performs industry-leading work in
• reducing the amount of toxic substances in its products,
• increasing the energy efficiency of its products,
• and lowering the amount of greenhouse gases emitted by its products.
In support of this latter effort, the Environmental Technologies Department seeks
an engineer to support its life cycle analysis (LCA) initiative.”
20 November 2008, Jean L. Lee, Ph.D., Environmental Technologies Department, Apple Inc.
Green Computing – CS 290N – Winter 2009 – January 7
The BIG picture:
Needs & Wants
Services
Source of:
Materials
Energy
Water
Land
Products
Production
Sink for:
Wastes
&
Emissions
Anthroposphere
Ecosphere
Industrial production and consumption systems use the environment as
source of resources and sink for wastes and emissions
Green Computing – CS 290N – Winter 2009 – January 7
Note: The following case study is for teaching purposes only
Question: Which beverage container has the lowest environmental impact?
Green Computing – CS 290N – Winter 2009 – January 7
Material choice for beverage containers
Processes causing environmental impacts:
Material
production
Container
manufacturing
Use &
distribution
Recycling
or disposal
Environmental impact indicator: Primary energy requirements
Aluminum
PET
Glass
Primary energy requirements for
material production (MJ/kg)
211.5
82.7
12.0
Primary energy requirements for
container forming (MJ/kg)
10.4
15.5
2.9
Density(kg/m3)
2,700
1,370
2,460
Green Computing – CS 290N – Winter 2009 – January 7
Material choice for beverage containers
Materials can not be compared on a mass basis.
Definition of Functional Unit: Containing 1 liter of beverage
Beverage container
Content
Mass
Mass/content
12 fl. oz. aluminum can
0.473 liter
19 gram
0.0402 kg/liter
20 fl. oz. PET bottle
0.591 liter
26 gram
0.0440 kg/liter
25.4 fl. oz. glass bottle
0.750 liter
325 gram
0.4333 kg/liter
Reference flows:
• 40.2 gram of aluminum cans
• 44.0 gram of PET bottles
• 433.3 gram of glass bottles
Green Computing – CS 290N – Winter 2009 – January 7
Material choice for beverage containers
How much energy is required to produce the beverage containers?
Beverage
container
Aluminum
Material production
(MJ/liter)
Container forming
(MJ/liter)
Total
(MJ/liter)
211.5 * 0.0402 = 8.5
10.4 * 0.0402 = 0.4
8.9
PET
82.7 * 0.0440 = 3.6
15.5 * 0.0440 = 0.7
4.3
Glass
12.0 * 0.4333 = 5.3
2.9 * 0.433 = 1.3
6.6
How much energy is required to transport the beverage containers?
Beverage
container
Mass
(g/liter)
Transportation
distance (km)
Transportation energy
(MJ/tonne-km)
(MJ/liter)
Aluminum
40.2
500
2.5
0.05
PET
44.0
500
2.5
0.05
Glass
433.3
500
2.5
0.54
Green Computing – CS 290N – Winter 2009 – January 7
Material choice for beverage containers
How much energy is saved through beverage container recycling?
Beverage
container
Collection
rate
Aluminum
0.52
Metal
yield
0.95
Material Energy requirements (MJ/kg)
recycling Primary
Secondary
rate
production
production
0.49
Energy Energy
yield
recovery
rate
PET
0.20
0.80
Glass
yield
Glass
0.23
1.0
0.16
211.5
25.8
Energy
savings
(MJ/liter)
3.6
Feedstock
Energy (MJ/kg)
39.8
0.3
Material Energy requirements (MJ/kg)
recycling Primary
Secondary
rate
production
production
0.23
12.0
7.2
Green Computing – CS 290N – Winter 2009 – January 7
0.5
Material choice for beverage containers
Results:
Beverage
container
Material
Container
Use &
Container Total
production manufacturing distribution 1) recycling 2) energy
Aluminum
8.5
0.4
0.1
-3.6
5.4
PET
3.6
0.7
0.1
-0.3
4.1
Glass
5.3
1.3
0.5
-0.5
6.6
1) Based on 500 km transportation
2) Based on current recycling rates
Green Computing – CS 290N – Winter 2009 – January 7
Material choice for beverage containers
Conclusion:
Products create environmental impacts at all stages of their life cycles
→ It is important to consider the entire life cycle of products
Green Computing – CS 290N – Winter 2009 – January 7
Material choice for beverage containers
Question: How do we know that primary energy requirements
is the right environmental impact indicator?
Results from a more comprehensive life cycle assessment:
Primary Energy
Requirements
(MJ NCV)
Global Warming
Potential
(kg CO2eq)
Terrestrial Eco-toxicity
Potential
(g DCBeq)
Aluminum
4.66
0.354
1.073
PET
3.94
0.205
0.553
Glass
6.88
0.426
0.430
Conclusion:
Products create different types of environmental impacts
→ It is important to consider a wide range of environmental impacts
Green Computing – CS 290N – Winter 2009 – January 7
Life cycle assessment aims at quantifying the environmental impacts across
all relevant environmental concerns and all relevant life cycle stages.
Environmental impact categories
Life cycle stages
Climate EcoPhoto-chemical Ozone
Change toxicity Smog
depletion
Production of
materials
Manufacturing
of product
Use &
Distribution
End-of-life
management
Total life cycle
Green Computing – CS 290N – Winter 2009 – January 7
Etc.
History and definition of Life Cycle Assessment
• Late 1960s, first Resource and Environmental Profile Analyses (REPAs)
(e.g. in 1969 Coca Cola funds study on beverage containers)
• Early 1970s, first LCAs (Sundström,1973,Sweden, Boustead,1972, UK, Basler &
Hofmann,1974,Switzerland, Hunt et al.,1974 USA)
• 1980s, numerous studies without common methodology with contradicting results
• 1993, SETAC publishes Guidelines for Life-Cycle Assessment: A ‘Code of Practice’,
(Consoli et al.)
• 1997-2000, ISO publishes Standards 14040-43, defining the different LCA stages
• 1998-2001, ISO publishes Standards and Technical Reports 14047-49
• 2000, UNEP and SETAC create Life Cycle Initiative
• 2006 ISO publishes Standards 14040 & 14044, which update and replace 14040-43
Definition of LCA according to ISO 14040:
LCA is a technique […] compiling an inventory
of relevant inputs and outputs of a product system;
evaluating the potential environmental impacts
associated with those inputs and outputs;
and interpreting the results of the inventory and
impact phases in relation to the objectives of the study.
Green Computing – CS 290N – Winter 2009 – January 7
Life cycle assessment terminology (ISO 14040:2006)
Elementary flows (e.g. resource extractions) – input flows
Functional unit
Economy-environment system boundary
economic
process
Intermediate
flow
economic
process
Intermediate
flow
economic
process
Intermediate
flow
Product system
Elementary flows (e.g. emissions to air) – output flows
Green Computing – CS 290N – Winter 2009 – January 7
economic
process
Life Cycle Assessment Framework
Four different phases of LCA are distinguished:
Goal and scope
definition
Inventory
analysis
Interpretation
Direct application:
• product development
and improvement
• Strategic planning
• Public policy making
• Marketing
• Other
Impact
assessment
Source: ISO 14040
Green Computing – CS 290N – Winter 2009 – January 7
Life Cycle Assessment
Goal and scope
definition
Inventory
analysis
Interpretation
Impact
assessment
Green Computing – CS 290N – Winter 2009 – January 7
Goal and Scope Definition
Functional unit and reference flows
Procedure:
1. Identify the function of the product system studied
3. Specify the function in SI units
4. Determine an appropriate amount of the function
5. Determine and identify the alternative systems studied in terms of reference flows
Previous example:
Functional Unit: Containing 1 liter of beverage
Reference flows: 40.2 g of alu cans, 44.0 g of PET bottles, 433.3 g of glass bottles
What are functional units for the comparison of
Various paints?
20m2 of wall covering with a coloured surface of 98% opacity and a lifetime of 5 years
Paper versus plastic bags in supermarkets?
Comfortable carrying of X kg and Y m3 of groceries (what about durability?)
What are the resulting reference flows?
Green Computing – CS 290N – Winter 2009 – January 7
Inventory analysis
In the inventory analysis the elementary flows of a product life cycle are quantified.
These are all natural resource inputs and waste & emission outputs of all economic
processes within the system boundaries.
Functional unit (Reference flows)
Process flow diagram
Unit processes
Inventory table for each unit processes
Aggregate inventory table for product system
Green Computing – CS 290N – Winter 2009 – January 7
Inventory Analysis
Process flow diagram
Definition:
The process flow diagram is an illustration of all the unit processes to be modeled,
including their interrelationships, which are intermediate product flows.
trees
logs
wood chips
Wood
yard
Harvesting
paper cup
Digester,
washing,
bleaching
Forming
Cup
use
Landfill,
recycling
Cup
use
Landfill,
recycling
adhesive,
coating, heat
steam,
chlorine (?)
oil
pulp
gas
oil, gas
Drilling
catalyst
gas, naphta
Refinery
catalyst
styrene
Styrene
production
PS cup
Polymerization,
blowing
solvent, blowing agent
Green Computing – CS 290N – Winter 2009 – January 7
Information contained in a process inventory
Unit
Process
INPUTS
Intermediate
flows
Elementary
flows
Materials
Energy
Biotic resources
Abiotic resources
OUTPUTS
Materials
Energy
Intermediate
flows
Emissions to air
Emissions to water
Emissions to soil
Green Computing – CS 290N – Winter 2009 – January 7
Elementary
flows
Main challenges of inventory analysis
Even though the methodology of inventory analysis seems relatively
straightforward, it is – in fact – complicated by two important issues:
• Defining boundaries for the system under analysis:
Which processes to include and which to exclude (cut-off problem in LCA)
• Allocation of elementary flows if process has more than one economic output:
Which output gets which burdens (Allocation problem in LCA)
materials
energy
unit
process
product A
wastes
emissions
product B
Green Computing – CS 290N – Winter 2009 – January 7
Allocation
There are 3 types of processes where allocation is necessary:
co-production, waste treatment, recycling and reuse in an open loop.
The 3 are treated on the basis of the same allocation rules.
materials
energy
unit
process
product A
wastes
emissions
product B
closed loop
open loop
Life
Cycle
A
Life
Cycle
B
waste A waste B
materials
energy
unit
process
wastes
emissions
A hierarchy of preferred approaches has been defined in ISO14044, Section 4.3.4:
1. Avoiding allocation by dividing the unit process
2. Avoiding allocation by system expansion
3. Allocation on the basis of physical relationship
4. Allocation on the basis of other relationship, i.e. economic value
Green Computing – CS 290N – Winter 2009 – January 7
Mass-based allocation
Example:
Emissions 1 kg
unit
process
allocated
process
Emissions 0.2 kg
20 kg product A
20 kg product A
80 kg product B
allocated
process
Emissions 0.8 kg
80 kg product B
On a mass basis, product A is allocated 20% of the emissions.
Green Computing – CS 290N – Winter 2009 – January 7
Economic allocation
Example:
Emissions 1 kg
unit
process
20 kg product A
$900
80 kg product B
$100
allocated
process
Emissions 0.9 kg
20 kg product A
$900
allocated
process
Emissions 0.1 kg
80 kg product B
$100
On an economic basis, product A is allocated 90% of the emissions.
Green Computing – CS 290N – Winter 2009 – January 7
Goal and scope
definition
Inventory
analysis
Interpretation
Impact
assessment
Green Computing – CS 290N – Winter 2009 – January 7
Life Cycle Impact Assessment
Life Cycle Inventories (LCIs) by themselves do not characterize the environmental
performance of a product system.
Impact Assessment (IA) aims at connecting the emissions and extractions listed in LCIs
on the basis of impact pathways to their potential environmental damages.
Life Cycle Inventory results
Classification
Impact categories
Characterization
Category indicator results
Normalization
Environmental profile
Valuation
One-dimensional environmental score
Green Computing – CS 290N – Winter 2009 – January 7
Elements of LCIA according to ISO 14044
Mandatory elements
Selection of impact categories, category indicators and characterization models
Classification: Assignment of LCI results to impact categories
Characterization: Calculation of category indicator results
Category indicator results (LCIA profile)
Optional elements:
Normalization of category indicator results relative to reference information
Grouping
Weighting
Data quality analysis
Green Computing – CS 290N – Winter 2009 – January 7
Classification
LCI
20kg CO2
2kg Methane
5g CFC-11
2kg NO2
1kg SO2
Impact Categories
Climate change
Stratospheric ozone depletion
Photochemical oxidant formation
Acidification
Green Computing – CS 290N – Winter 2009 – January 7
Classification
LCI
Characterization
Impact Categories
20kg CO2
2kg Methane
5g CFC-11
2kg NO2
1kg SO2
Characterization factors
Climate change
GWP (global warming potential)
Stratospheric ozone depletion
ODP (ozone depletion potential)
POCP (photochemical ozone
creation potential)
AP (acidification potential)
Photochemical oxidant formation
Acidification
Substance
Amount
(kg)
GWP100
(kg CO2 eq/kg)
CO2
20
1
Methane
2
21
CFC-11
0.005
4000
NO2
2
SO2
1
ODP∞
(kg CFC-11 eq/kg)
POCP
(kg ethylene eq/kg)
AP
(kg SO2 eq/kg)
0.006
1
0.028
0.70
1.00
Green Computing – CS 290N – Winter 2009 – January 7
Classification
LCI
Characterization
Impact Categories
20kg CO2
2kg Methane
5g CFC-11
2kg NO2
1kg SO2
Characterization factors
Climate change
GWP
Stratospheric ozone depletion
ODP
Photochemical oxidant formation
POCP
Acidification
AP
Substance
Amount
(kg)
GWP100
(kg CO2 eq/kg)
CO2
20
1
Methane
2
21
CFC-11
0.005
4000
NO2
2
SO2
1
ODP∞
(kg CFC-11 eq/kg)
POCP
(kg ethylene eq/kg)
AP
(kg SO2 eq/kg)
0.006
1
0.028
0.70
1.00
20·1 = 20 kg CO2eq
2·21 = 42 kg CO2eq
0.005·4000 = 20 kg CO2eq
(20 + 42 + 20) kg CO2eq = 82 kg CO2eq
Indicator Result
Green Computing – CS 290N – Winter 2009 – January 7
Classification
LCI
Characterization
Impact Categories
20kg CO2
2kg Methane
5g CFC-11
2kg NO2
1kg SO2
Characterization factors
Indicator results
Climate change
GWP
82kg CO2 eq
Stratospheric ozone depletion
ODP
0.005kg CFC-11 eq
Photochemical oxidant formation
POCP
Acidification
AP
Substance
Amount
(kg)
GWP100
(kg CO2 eq/kg)
CO2
20
1
Methane
2
21
CFC-11
0.005
4000
NO2
2
SO2
1
ODP∞
(kg CFC-11 eq/kg)
0.068kg ethylene eq
POCP
(kg ethylene eq/kg)
2.4kg SO2 eq
AP
(kg SO2 eq/kg)
0.006
1
0.028
0.70
1.00
Indicator
kg CO2 eq
kg CFC-11 eq
kg ethylene eq
kg SO2 eq
Results
82
0.005
0.068
2.4
Green Computing – CS 290N – Winter 2009 – January 7
Impact Assessment
The environmental impact pathway
Impact pathways consist of linked environmental processes, and they express the causal
chain of subsequent effects originating from an emission or extraction (environmental
intervention).
Examples:
Increase in effectiveness of communication of results (generally)
SO2
emissions
Acid
rain
Source
CFC
emissions
Acidified
lake
Dead
fish
Loss of
biodiversity
Endpoint
Midpoint
Tropospheric
OD
Stratospheric
OD
UVB
exposure
Human
health
Increase in uncertainty for predicting the environmental impact from the initial interventions
Green Computing – CS 290N – Winter 2009 – January 7
Impact Assessment
Impact Categories
According to ISO14044, LCI results are first classified into impact categories that are
relevant and appropriate for the scope and goal of the LCA study.
Example:
Carbon dioxide
Climate change
Methane
CFCs
Nitrogen oxides
Sulphur dioxide
Stratospheric ozone depletion
Photochemical oxidant formation
Acidification
A category indicator, representing the amount of impact potential, can be located at any
place between the LCI results and the category endpoints. There are currently two main
Impact Assessment methods:
• Problem oriented IA methods stop quantitative modeling before the end of the impact
pathway and link LCI results to so-defined midpoint categories (or environmental
problems), like acidification and ozone depletion.
• Damage oriented IA methods, which model the cause-effect chain up to the endpoints
or environmental damages, link LCI results to endpoint categories.
Green Computing – CS 290N – Winter 2009 – January 7
Impact Assessment
Classification and characterization – Example 1
Impact category
Climate change
LCI results
Emissions of greenhouse gases to the air (in kg)
Characterization model
the model developed by the IPCC defining the global
warming potential of different gases
Category indicator
Infrared radiative forcing (W/m2)
Characterization factor
Global warming potential for a 100-year time horizon
(GWP100) for each GHG emission to the air
(in kg CO2 equivalents/kg emission)
Unit of indicator result
kg (CO2 eq)
Substance
Carbon dioxide
Methane
CFC-11
CFC-13
HCFC-123
HCFC-142b
Perfluoroethane
Perfluoromethane
Sulphur hexafluoride
GWP100 (in kg CO2 equivalents/kg emission)
1
21
4000
11700
93
2000
9200
6500
23900
Source: (Guinée et al., 2002)
Green Computing – CS 290N – Winter 2009 – January 7
Impact Assessment
Classification and characterization – Example 2
Impact category
LCI results
Characterization model
Category indicator
Characterization factor
Unit of indicator result
Substance
ammonia
hydrogen chloride
hydrogen fluoride
hydrogen sulfide
nitric acid
Nitrogen dioxide
Nitrogen monoxide
Sulfur dioxide
Sulphuric acid
Acidification
Emissions of acidifying substances to the air (in kg)
RAINS10 model, developed by IIASA, describing the fate
and deposition of acidifying substances, adapted to LCA
Deposition/acidification critical load
Acidification potential (AP) for each acidifying emission to
the air (in kg SO2 equivalents/kg emission)
kg (SO2 eq)
AP (in kg SO2 equivalents/kg emission)
1.88
0.88
1.60
1.88
0.51
0.70
1.07
1.00
0.65
Source: (Guinée et al., 2002)
Green Computing – CS 290N – Winter 2009 – January 7
Outlook and future developments for LCA
Issues to be solved:
• Money and time required to do LCAs (especially important of SMEs)
• Data availability (public databases, e. g. ELCD and U.S. LCI)
• Impact assessment methodology not fully mature (especially toxicity indicators)
• Multidimensionality (multi criteria decision making)
• Relationship with Environmental Management Systems
• Product perspective is not whole system perspective
(Most important example: economic relationships)
Technical developments:
• Consequential LCA
(to resolve allocation issues)
• Hybrid LCA (Process+I/O LCA)
(to resolve cut-off issues)
• Modeling economic relationships in and between product systems
• Modeling non-linear and dynamic relationships in and between product systems
• Modeling spatial aspects of LCI and LCIA
Green Computing – CS 290N – Winter 2009 – January 7
Environmental Product Design – Example: Cell Phones
Green Computing – CS 290N – Winter 2009 – January 7
Material Composition of Cell Phones
Plastics
40-50%
Glass and Ceramics
15-20%
Ferrous metals
~ 3%
Non ferrous metals
22-37%
Other
5-10%
Green Computing – CS 290N – Winter 2009 – January 7
Cell Phone Evolution
Green Computing – CS 290N – Winter 2009 – January 7
Cell Phone Components
• Plastic housing and keypad
• Liquid crystal display (LCD)
• Printed wiring board (PWB)
• Connectors
• Active electronic components
(e.g. integrated circuits)
• Passive electronic components
(e.g. capacitors and resistors)
• Microphones and speakers
Green Computing – CS 290N – Winter 2009 – January 7
Global Cell Phone Market
Green Computing – CS 290N – Winter 2009 – January 7
Life Cycle of
a Cell Phone
Integrated Product Policy (IPP) Pilot Project (http://ec.europa.eu/environment/ipp/mobile.htm)
Green Computing – CS 290N – Winter 2009 – January 7
Environmental Assessments of Cell Phones at Nokia
Wright 1999: Life cycle energy analysis
• Scope: ‘92-’94 (160 gr) and ‘95-’96 (130 gr) cell phones, production, use, eol management,
exclude battery, charger, network infrastructure
• Functional unit: Use of the cell phone for 2.5 years
• Impact categories:
Primary energy consumption (PEC)
Frey 2002: Environmental footprint analysis
• Scope: ‘92-’94 (160 gr) and ‘95-’96 (130 gr) cell phones, production, use, eol management,
exclude battery, charger, network infrastructure
• Functional unit: Use of the cell phone for 2.5 years
• Indicator: Total area required to produce required resources and assimilate generated wastes
McLaren & Piukkula 2003: Life cycle assessment (using GaBi3)
• Scope: 2000 cell phone (90 gr), production and use, no eol management
include battery and charger, exclude network infrastructure
• Functional unit: Use of the cell phone for 2 years
• Impact categories:
Primary energy consumption (PEC), global warming potential (GWP), Ozone depletion
potential (ODP), acidification potential (AP), human toxicity potential (HTP), photochemical
oxidant creation potential (POCP)
Green Computing – CS 290N – Winter 2009 – January 7
Summary of environmental hotspots of a cell phone
• Life cycle stages: Component manufacture, use phase, end of life
• Environmental concern: energy consumption, hazardous wastes & emissions
• Use phase: Stand-by power consumption of the charger
• Component manufacture: Energy consumption of manufacturing processes
• Components with highest environmental impacts: PWB, ICs, LCD
• Transportation: Airfreight accounts for almost all of environmental impacts
• End-of-life: Hazardous substances in products (e.g. Pb, Cr, Ni, Cu, Sb)
• Beyond the handset: Energy consumption of radio base station
Green Computing – CS 290N – Winter 2009 – January 7
Cell Phone Life Cycle: Primary Energy Requirements (PER)
Life cycle stage
PER (in MJ)
PER (in % of total)
Materials production 1)
25
9
Component manufacture 1)
100
36
Product assembly 1)
25
9
Transportation
25
9
Use
100
36
0
0
275
100
End-of-life disposal 1)
Total
1) 2003 Nokia study gives only 150 MJ for product manufacture. Breakdown
is from an earlier Nokia study from 1999, as is the end-of-life assessment.
Perspective:
275 MJ is the gross calorific value of 7.9 liters of gasoline,
or 52 km in a Lincoln Navigator,
or 185 km in a Toyota Prius.
Green Computing – CS 290N – Winter 2009 – January 7
Options for improving life cycle environmental performance of cell phones
• Improvement in cell phone design
• Optimizing the in-use life-span of cell phone
• Less energy and problematic chemicals during component manufacture
• Change buying, usage and disposal behavior of consumers
• Improve eol management of cell phones
• Reduce energy consumption of network infrastructure
• Develop environmental assessment methods/tools
• Need for policies to support environmental performance improvements
Green Computing – CS 290N – Winter 2009 – January 7
Cell phone end-of-life management options
Primary
materials
production
Components
manufacture
Final
phone
assembly
Phone
demand
& use
End-of-life
phone
disposal
Inspection
&
sorting
End-of-life
phone
collection
Phone
refurbishment
Component
market
Metals
market
Component
reuse
Phone
recycling
Green Computing – CS 290N – Winter 2009 – January 7
Economics of cell phone end-of-life management
16
14
12
Revenues
Refurbishment
Recycling
Inspection
Postage
Incentive
10
8
6
4
2
0
Cost Revenue Cost Revenue Cost Revenue
£
Recycling
Component reuse Refurbishment
Green Computing – CS 290N – Winter 2009 – January 7
Handset mass and gold content have been declining over the past ten years
250
230
210
190
170
150
130
110
90
70
50
0.05
0.045
0.04
0.035
0.03
0.025
0.02
1992
gr
handset
mass
gold
content
1994
1996
1998
2000
2002
Year of manufacture
Gold contains:
60% - 80% of the economic value of the materials
(depending on the palladium content)
65% - 75% of the energy embodied in the materials
Green Computing – CS 290N – Winter 2009 – January 7
%
Therefore economic and environmental benefits
due to gold recycling has been declining as well
45
40
35
30
25
20
15
10
5
0
1992
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
MJ
1994
1996
1998
2000
2002
Year of manufacture
Green Computing – CS 290N – Winter 2009 – January 7
embodied
energy in
gold /
phone
gold
value /
phone
£