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Measuring and modeling mobile phone charger
energy consumption and environmental impact
Mikko V. J. Heikkinen
School of Electrical Engineering
Aalto University, Espoo, Finland
Email: mikko.heikkinen@aalto.fi
Jukka K. Nurminen
School of Science
Aalto University, Espoo, Finland
Email: jukka.k.nurminen@aalto.fi
Abstract—This paper studies the electricity consumption of
mobile phone chargers. The charger’s electricity consumption
varies depending on its state. We measured the electricity
consumption of various phone and charger models in different
states. We also did panel studies on the recharging behavior
of smartphone users. Based on these and other sources, we are
able to estimate mobile phone recharging electricity consumption,
cost, and CO2emissions both in Europe and in the USA. Our
analysis shows that the actual recharging of batteries consumes
only 40% of the total energy; the rest is wasted mainly by
unnecessarily plugged-in chargers consuming 55% of the total
energy.
I. INTRODUCTION
The number of mobile phones in the world is rising rapidly.
Therefore the environmental impact of the mobile phones
starts to be a relevant concern. Although recharging a single
mobile phone is not consuming much electrical energy, the
extremely large user base means that the aggregate energy
consumption of mobile phones is significant.
In this paper, we analyze the electrical energy consumption
of mobile phone recharging. We want to understand how much
energy is spent on recharging the mobile phones, how large
impact the recharging behavior of consumers has on energy
consumption, and how much savings could be achieved if
the users changed their behavior. We also measure if there
are fundamental differences between the recharging energy
consumption between different mobile phone vendors.
We can divide the recharging process into a number of
states. When both phone and charger are disconnected from
the power grid, no external energy is consumed. The phone
consumes the power stored in its battery. The battery capacity,
user actions, and the energy-efficiency of the phone hardware
and software determine how fast the charge in the battery
declines. At some point the user decides to recharge the phone.
This decision can arise from alert of low battery, suitable
recharging opportunity, or regular habit [1]. While the energy
consumption of operating on battery power does not have a
direct influence on the electrical energy consumption from
the power grid, the indirect effect is important. High power
consumption leads to frequent recharging needs, and thus to
higher electrical energy consumption from the power grid.
In the recharging state, both phone and charger are con-
nected to the power grid; the user has plugged in the phone for
recharging. The energy and power management logic monitors
the battery charge and the battery is actively recharged.
When battery charge has reached full capacity, the system
enters the idle state, where it either allows some battery con-
sumption before restarting active recharging, or draws power
from the grid instead of the battery. The detailed mechanisms
governing these decisions are vendor specific.
In the no-load state, the phone is disconnected but the
charger is left plugged into the grid. The charger may still
consume some energy in the form of current leakage. Active
R&D work aims minimizing the wasted energy and is strongly
encouraged by regulators (see [2]). As an additional approach,
some phone vendors try to influence user behavior with alerts
suggesting the user to disconnect the charger when recharging
is complete.
From this analysis we can conclude that there are three
main factors that influence the recharging electrical energy
consumption of a mobile phone:
1) The usage pattern of the phone: how actively the user
uses different applications, how mobility and signal
strength variations influence power consumption, etc.
Draining the battery faster results into frequent need to
recharge and via it to increased energy consumption.
2) The recharging behavior of the phone user: when do
users typically recharge their phones, how long the
phone is connected to the charger, etc.
3) The charger power consumption in different states
(recharging, idle, and no-load).
The first two points depend a lot of the phone user’s
behavior while the last one is beyond the control of the
phone user. In this paper we study these points in detail. We
measure the electrical energy consumption in different states
with various phone and charger models and complement the
measurements with studies on users’ recharging behavior to
estimate the aggregate electricity consumption in macro scale
in Europe and in the USA.
This paper is structured as follows. In Section II we briefly
review related studies. Section III reports our measurements,
Section IV describes our model and the results, and Section
V discusses the results.
II. RE LATE D WORK
We found two studies quantifying the energy consumption
of mobile phones and networks. Etoh et al. [3] studied the total
energy consumption of the largest mobile telecommunications
operator in Japan in 2006 and estimated that an average
customer’s phone consumes 0.83 Wh per day whereas the
mobile network consumes 120 Wh per day per customer.
Schaefer et al. [4] estimated the German mobile telecommuni-
cations sector to consume 79.5 Wh per day per subscriber in
2000, phones being responsible to 36 Wh of the consumption.
The discrepancy between these two studies illustrates the
challenge of estimating the power consumption of mobile
telecommunications technologies.
Research on recharging behavior of mobile phone users
is rather limited. Ferreira et al. [5] assessed the recharging
behavior of a large sample of Android users, but reported
only limited details on their behavior. (For example, they
did not report numbers and durations of recharging periods.)
Heikkinen et al. [6] had a smaller sample but reported more
details.
Some previous work has quantified the energy efficiency
of chargers for mobile phones [7]–[9]. As mobile services are
increasingly using resources residing in the Internet, the energy
consumption of the Internet and the data centers connected to
it is becoming increasingly relevant to understand the overall
picture of the energy consumption of mobile services [10]–
[12].
III. MEASUREMENTS
We used two types of measurements for our analysis:
recharging behavior measurements with a usage logging soft-
ware in two panel studies, and exploratory recharging power
measurements of several phone and charger models.
A. Phone recharging behavior measurements
The first usage logging panel study (P07) started in Novem-
ber 2007 and ended in February 2008. The invitation to
participate was sent by SMS to ca. 13,500 customers of three
Finnish mobile network operators. The panel consisted of 253
participants with mean 50 active days in the panel. A typical
panelist was male (81.7%), employed (68.0%), and 20-39
years of age (73.3%).
The second usage logging panel study (P08) started in
October 2008 and ended in December 2008. This time the
invitation to participate was sent by SMS to ca. 10,000
customers of three Finnish mobile network operators. The
panel consisted of 105 participants with mean 31 active days
in the panel. Again, a typical panelist was male (73.3%),
employed (64.8%) with mean 35 years of age (25th percentile
28 years, and 75th percentile 40 years).
The demographics of both panels are biased compared to the
general population in Finland, but not necessarily compared to
the Finnish users of advanced phones at the time. Participation
in the panels required a phone having a Nokia Symbian S60
Third Edition operating system and installation of the usage
TABLE I
DURATIONS OF RECHARGING AND IDLE PERIODS PER PANELIST (H/DAY)
10th percentile 90th percentile Mean
Panel P07
Recharging 0.05 2.01 0.67
Idle 0.01 4.92 1.10
Panel P08
Recharging 0.08 1.67 0.60
Idle 0.02 4.22 1.14
TABLE II
EXPLORATORY RECHARGING POWER MEASUREMENTS RESULTS
Phone OS Recharging (W) Idle (W)
Apple iPhone 4 iOS 3–4 1–2
Ericsson U20i Android v2.1 4–5 0–1
Ericsson X10i Android v2.1 4–5 0–2
Motorola Milestone Android v2.2 4–5 0–1
Nokia 6020 S40 3–6 0–0
Nokia 6120c S60 v3.1 1–6 0–0
Nokia 6300 S40 1–6 0–0
Nokia E71 S60 v3.1 1–6 0–0
Samsung Omnia 7 Windows 7 2–5 0–1
ZTE Blade Android v2.1 4–5 2–3
logging software. Heikkinen et al. [6] discuss the sampling for
the panels and the results from them in detail.
For the purposes of this paper, we are interested in the
recharging behavior of the panelists. Table I reports the daily
durations of recharging and idle periods per panelist.
B. Exploratory recharging power measurements
We also did exploratory measurements to quantify the
power consumption of different phones and their chargers. We
measured the minimum and maximum power values during
recharging, idle and no-load periods with a measurement
device, which was placed between the charger and the wall
socket. The device has an accuracy of 5% ±0,5 W [13].
Table II reports minimum and maximum power consump-
tion values for different phones and corresponding charger
models. (Charger model information is omitted to save space.)
In all cases the no-load consumption was measured to be 0 W
but is likely to be higher because the accuracy of our metering
device was only 0.5W.
Our power consumption measurements should be consid-
ered exploratory for various reasons. First, we were able to
reach only a coarse-grained accuracy with our measurement
setup. Second, we report values from recharging cycles as-
sumed to be stable over time, but we did not do any systematic
analysis on the recharging cycles. Third, the batteries of
the phones were of varying condition in terms of age and
remaining capacity. Fourth, we measured a limited number
of phones and chargers (for example, we were unable to
measure any BlackBerry models). However, we consider our
measurements sufficient for the purposes of this paper, as our
intent is to estimate total energy consumption, not to conduct
definitive measurements.
Based on the measurements, it appears all phone and charger
combinations consume little power during no-load periods.
Nokia phones and the Windows phone consumed very little
power also during idle periods, whereas Android phones and
the Apple iPhone power consumption varied as a function of
user actions during idle periods. We believe the difference is
due to a design choice whether to let the phone draw power
from the battery or from the electricity grid while plugged
into the charger. Also, we believe the differences during the
recharging period are due to different recharging cycle designs.
IV. MOD EL
In this section we present our model for estimating the
energy consumption of mobile phone recharging.
We use power values in watts to estimate the energy
consumption of chargers. We make a distinction between
power consumption while recharging Precharging , while idle
on electrical grid power Pidle,g, while idle on battery power
Pidle,b, and while under no load (i.e., no phone plugged into
a charger in the grid) Pno−load.
We also need to consider the share of chargers plugged
into the grid all the time rplugged . Many people, especially in
developed economies, have a tendency of leaving the charger
plugged in all the time. It is also increasingly common that
people have multiple chargers, e.g. one at home and one in
the office. In the extreme case more than one charger for each
phone could be plugged in.
Corresponding to the power values, we estimate the daily
duration a charger is recharging trecharging , idle tidle, and has
no load but is plugged into the wall outlet tno−load:
tno−load = (tmax −trecharging −tidle)∗rplugg ed (1)
where tmax is 24 hours.
Next, we introduce the variables varying based on the
region under study. Share of advanced phones radvanced is
the market share of so-called “smartphones” (i.e., phones
with the Android, Apple iOS, BlackBerry, Symbian, Windows
Mobile, or other advanced operating system). As Android
and iOS phones are currently the most prominent class of
advanced phones consuming grid power while not recharging
but connected to a charger (i.e., idle on grid power), we use the
combined share of Android rAndroid and iOS riOS phones of
the share of advanced phones radvanced to estimate the share
of phones idle on grid power ridle,g:
ridle,g = (rAndroid +riOS )∗radvanced (2)
Then, we can calculate an estimate for power consumption
while idle connected into charger Pidle:
Pidle =ridle,g ∗Pidle,g + (rmax −ridle,g )∗Pidle,b (3)
where rmax is 1 (i.e., 100%).
Other region-dependent variables are the number of active
subscriptions nsubs, the price of electrical energy penergy, and
TABLE III
MOD EL IN PU T VALUE S
Variable Min Max Average
Precharging (W) 3.50 4.50 4.00
Pidle,g (W) 1.00 2.00 1.50
Pidle,b (W) 0.03 0.30 0.17
Pno−load (W) 0.03 0.30 0.17
trecharging (h/day) 0.06 1.84 0.63
tidle (h/day) 0.02 4.57 1.12
rplugged 0.90 0.99 0.95
Europe
radvanced 0.25 0.35 0.30
rAndroid 0.10 0.40 0.25
riOS 0.15 0.25 0.20
nsubs 520,000,000 630,000,000 575,000,000
penergy (EUR/kWh) 0.1645
rCO2−e(kg/kWh) 0.578
USA
radvanced 0.25 0.35 0.30
rAndroid 0.25 0.55 0.40
riOS 0.20 0.30 0.25
nsubs 285,646,200 302,900,000 295,000,000
penergy (USD/kWh) 0.115
rCO2−e(kg/kWh) 0.592
the ratio of carbon dioxide equivalent emissions released per
electrical energy consumed rCO2−e.
Using the above variables, calculating the total energy con-
sumption Eof chargers during a period of time is straightfor-
ward by adding up the energy consumption during recharging
Erecharging , idle Eidle and no load Eno−load phases:
E=Erecharging +Eidle +Eno−load (4)
where
Erecharging =nsubs ∗Pr echarging ∗trechar ging
Eidle =nsubs ∗Pidle ∗tidle
Eno−load =nsubs ∗Pno−load ∗tno−load
The price of the consumed energy p=E∗penergy and the
corresponding emission of carbon dioxide e=E∗rCO2−e.
A. Input values
We calculate scenarios with input values, which we consider
to be the minimum, maximum, or average values. The input
values are given in Table III. They can be classified into
region-independent and -dependent values.
The region-independent values are derived as follows:
Recharging and idle on grid power values Precharging and
Pidle,g are averaged over our power measurements, see Table
II. Idle on battery power and under no-load values Pidle,b and
Pno−load are based on a technical specification by Nokia [14].
(Other vendors do not publish detailed information about their
chargers.) The daily durations for recharging trecharging and
idle tidle are averaged over our behavior measurements, see
Table I. We did not find any source for the share of chargers
plugged in all the time rplugged , so we estimated it.
The region-dependent values are derived as follows: We
only consider Europe and the USA, because we have no
usage data generalizable to other markets. We define Europe
to consist of the EU, EFTA, and CEFTA countries (see [15]).
The shares of advanced phones radvanced and phones with the
Android and the iOS operating systems, rAndroid and riOS ,
respectively, are based on analyst estimates [16]–[20]. The
numbers of active subscriptions nsubs are based on data from
[21]–[24]. The European energy price penergy and the ratio
of carbon dioxide equivalent emissions released per electrical
energy consumed rCO2−eare based on data from EU-27
countries [25]–[27]; the US numbers are based on data from
[28], [29].
B. Results
Table IV contains the results from our model for the
minimum, maximum, and average scenarios for both Europe
and the USA. They are given annually per subscriber. For each
recharging state, the impact of consumption is quantified in
kilowatt-hours (kWh), currency (EUR or USD), and kilograms
of carbon dioxide equivalent emissions (CO2-e kg).
The average annual energy consumption of a subscriber
(2.34 kWh) approximately equals to 39 hours of operation
of a 60 W light bulb. Assuming 175 g/km CO2-e emissions
for a car, the average annual emissions of a subscriber (1.4
kg) equals to about 8 km of driving a car.
C. Comparison of results to other estimates
Table V contains estimates derived from other sources.
Our average estimate of mobile phone energy consumption
in the USA is within the same range as estimates of mobile
phone energy consumption in Germany in 2000 [4], but an
order of magnitude higher than an estimate of mobile phone
energy consumption in Japan in 2006 [3], [30]. Our average
estimate of mobile phone energy consumption in Europe
is within the same range as an estimate of mobile phone
energy consumption in the USA in 2004 [7], [21], but much
lower than the estimate on the energy consumption of mobile
networks in Japan in 2006 [3], [30]. For comparison to other
types of energy consumption, our average estimates are lower
than estimates of Google’s energy consumption in 2010 [12]
and an order of magnitude lower than estimates on the energy
consumption of data centers in Western Europe or the USA in
2005 [11] or the total standby power consumed by consumer
appliances in the USA in 1998 [31]. Finally, our average
estimates were ca. 0.02% and 0.04% of the estimates on total
net electricity generation in the USA and in Europe [32],
respectively.
D. Sensitivity analysis
We also did elementary sensitivity analysis to the model,
where we varied a single input parameter within its theoretical
minimum and maximum range, and observed its effect on
output in the average scenario. Table VI contains the range
TABLE IV
RES ULTS F ROM TH E MO DEL :AN NUA LLY PER S UB SCR IB ER
Min Max Average Unit
Europe
Recharging 0.08 3.02 0.92 kWh
Idle 0.00 1.15 0.14 kWh
No-load 0.17 2.59 1.27 kWh
Total 0.25 6.76 2.34 kWh
Recharging 0.01 0.50 0.15 EUR
Idle 0.00 0.19 0.02 EUR
No-load 0.03 0.43 0.21 EUR
Total 0.04 1.11 0.38 EUR
Recharging 0.05 1.75 0.53 CO2-e kg
Idle 0.00 0.66 0.08 CO2-e kg
No-load 0.10 1.50 0.74 CO2-e kg
Total 0.15 3.91 1.35 CO2-e kg
USA
Recharging 0.08 3.02 0.92 kWh
Idle 0.00 1.34 0.17 kWh
No-load 0.17 2.59 1.27 kWh
Total 0.25 6.96 2.37 kWh
Recharging 0.01 0.35 0.11 USD
Idle 0.00 0.15 0.02 USD
No-load 0.02 0.30 0.15 USD
Total 0.03 0.80 0.27 USD
Recharging 0.05 1.79 0.55 CO2-e kg
Idle 0.00 0.80 0.10 CO2-e kg
No-load 0.10 1.54 0.75 CO2-e kg
Total 0.15 4.12 1.40 CO2-e kg
TABLE V
COMPARISON TO OTHER ESTIMATES (1E9KWH/Y EAR )
Mobile phones Japan 2006 0.03
Mobile phones Germany 2000 0.6
Mobile networks Germany 2000 0.7
Mobile phones USA 0.7
Mobile phones USA 2004 1.3
Mobile phones Europe 1.3
Google total energy consumption 2010 2.3
Mobile networks Japan 2006 4.6
Data centers Western Europe 2005 41.3
USA standby power 1998 44.3
Data centers USA 2005 56.0
Total Electricity Net Generation Europe 2008 3,421
Total Electricity Net Generation USA 2009 3,953
of both input values and output values. The range of output is
reported as a comparison to the average scenario. Our model is
most sensitive to recharging and idle durations, and to power
consumption under no-load; moderately sensitive to the share
of chargers plugged in all the time, and to the share of phones
idle on grid power; and least sensitive to power consumption
while idle or recharging.
TABLE VI
SENSITIVITY ANALYSIS
Input range Output range
Min Max Min Max
Pidle,g (W) 1.0 2.0 -1.7% 1.7%
Pidle,b (W) 0.03 0.3 -2.0% 2.0%
Precharging (W) 3.5 4.5 -4.9% 4.9%
ridle,g 0.01 0.99 -4.3% 19.9%
rplugged 0.01 0.99 -53.9% 2.3%
Pno−load (W) 0.03 0.3 -44.6% 44.6%
tidle (h/day) 0.01 24.00 -4.6% 94.7%
trecharging (h/day) 0.01 2.00 -37.3% 82.2%
V. DISCUSSION
As with any model, the accuracy of input values to our
model defines the accuracy of the output. The uncertainty
in our input values prevents us from giving a conclusive
answer for the energy consumption and environmental impact
of mobile phone chargers, but we can characterize the possible
ranges of both input variables and resulting scenarios. We did
only exploratory measurements with different mobile phone
and charger models, but as we demonstrated in Sec. IV-D,
our model is not very sensitive to power consumption related
input values. We believe we have very reasonable behavior
estimates based on two subsequent panel studies, but we admit
the challenges of generalizing results from panel studies to
large populations.
According to our model, recharging constitutes ca. 40%
of the total mobile phone energy usage. Having chargers
unnecessarily plugged in the grid wastes ca. 55% of the energy
usage, whereas having idle phones plugged into chargers
wastes ca. 5% of the energy usage.
Our model suggests a major energy saving could be gained
by unplugging chargers after recharging a mobile phone.
However, a typical Western consumer probably considers the
cost savings and environmental benefits not worth the hassle
of unplugging the charger. Therefore, charger manufacturers
should intensify their efforts to produce chargers wasting
minimum amount of energy while under no load (see [2]).
Vendor-specific solutions trying to influence user behavior
(e.g., prompting users to unplug chargers) are likely to be
less efficient as technical improvements. However, while the
operating time with a single recharge is clearly a competing
factor improving the user experience, the electricity consump-
tion of the recharging process is not immediately relevant to
the end user and therefore of smaller importance to mobile
phone vendors.
Our exploratory analysis suggests phone vendors have two
different approaches towards maintaining charge while phone
is plugged into a charger: the phone either takes energy from
battery or from the power grid. Consuming power from the
grid may waste energy, but guarantees that the phone remains
charged if it is used for high-energy-consuming functions
(e.g., acting as a mobile modem) while plugged in. One
approach would be to make the phone intelligently decide
which approach to utilize when plugged into a charger: for
example, the phone could consume battery power while idle,
and grid power while performing energy-intensive functions.
Further work is warranted at least on the following topics:
defining the share of mobile phone chargers plugged in all
the time, and conducting more accurate measurements on the
power consumption of mobile phone chargers (including anal-
ysis of recharging cycles and batteries of various condition).
Gaining a holistic understanding including the energy usage of
mobile networks and service infrastructure is also of interest.
ACK NOW LE DG ME NT
MH’s work was supported by the MoMIE project, TEKES
and industrial partners.
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