# Appendix C – Landline Telephone Usage in Barrels of Oil per Day

```Team # 5904
Page 1 of 43
Summary: Modeling the Energy Consequences of the Cell Phone Revolution
Introduction - The purpose of this study was to model the energy consequence of the wireless
phone revolution. As this technology has continued to grow, the demand for electricity to
charge cell phones has grown linearly. We decided to model the energy consumed by one cell
phone, on an average day, and extrapolate this to encompass the energy demands of the entire
U.S. population. We did this by breaking down the energy consumption of the cell phone into
the following three parts: time during which cell phone battery is replenishing from the
charger, the standby time where the phone battery is fully charged but still plugged in, and
lastly the time which the phone is removed from the charger but the charger remains plugged
into the wall. Together these times make up the typical day for the energy profile of each
wireless phone.
Model Approach - In order to be flexible, our model was created to handle various distributions
of data. For example, we partitioned people into groups according to how much time they
spend on their cell phones each day; this gave us a distribution on how much the phone battery
had been drained throughout the day. However, to solve the many problems asked, we used
several expected values to get the mean range to the solution. We also used several linear
regressions, by Least Squared Estimates, to predict population trends in the future.
Strengths and Weaknesses of the Model - The biggest strength of our model is that it
encompasses many factors to accurately predict the amount of energy required to charge a cell
phone battery. By partitioning people into subgroups of the population, and separating the
typical day into distinct charging periods, our model gives a more accurate look at the energy
consumption by cell phones. Likewise, our model has strength in its’ ability to forecast the
future by extrapolating current trends in population and subscriptions to wireless phone
service. The main weakness out our model is that it tends to predict average energy
consumption and may not fully estimate the total energy consumption. Likewise, our models’
Achilles Heel is likely the research we found. Our research came from a large amount of
resources, and some of it may not be as accurate as we hoped.
Team # 5904
Page 2 of 43
 Modeling the Energy Consequences of the Cell Phone Revolution.....................................4
 Introduction...................................................................................................................4
 Preview of Model...........................................................................................................4
 Developing the Model...................................................................................................5
 Requirement One................................................................................................................6
 Synopsis.........................................................................................................................6
 Assumptions..................................................................................................................6
 Analysis..........................................................................................................................6
 Partitioning Model.........................................................................................................9
 Analysis of Both Landline and Cellular Telephone Usage and
Energy Consumption.....................................................................................................11
 Requirement Two................................................................................................................15
 Synopsis.........................................................................................................................15
 Assumptions..................................................................................................................15
 Analysis..........................................................................................................................16
 Optimal Way of Providing Phone Service.....................................................................16
 Discussion of Social and Economic Consequences of Choosing
Landlines or Cell Phones................................................................................................16
 Requirement Three..............................................................................................................17
 Synopsis..........................................................................................................................17
 Assumptions...................................................................................................................17
 Analysis...........................................................................................................................18
 Requirement Four.................................................................................................................19
 Synopsis...........................................................................................................................19
 Analysis............................................................................................................................19
 Requirement Five...................................................................................................................22
 Synopsis............................................................................................................................22
 Analysis.............................................................................................................................22
 Summary and Evaluation........................................................................................................23
 Works Cited............................................................................................................................25
 Appendices: Data and Input Calculations...............................................................................26
 Appendix A – Lithium Ion Battery Data............................................................................27
 Appendix B – Cell Phone Talk Time Data.........................................................................28
 Appendix C – Landline Telephone Usage in Barrels of Oil per Day..................................34
 Appendix D – Cellular Telephone Usage in Barrels of Oil per Day...................................36
 Appendix E – Household Phantom Energy Consumption.................................................38
Team # 5904
Page 3 of 43
 Appendix F – Calculating Projections of Percentage of
Households with Landlines............................................................................................41
Team # 5904
Page 4 of 43
Modeling the Energy Consequences of the Cell Phone Revolution:
Introduction:
The purpose of this study was to analyze the energy consequences of the cell phone
revolution. As many people are choosing to become reliant on wireless phones, and to forgo
the use of landline phones, the number of mobile phone and mobile phone chargers using
electricity has dramatically increased. However, there still remain a large percentage of U.S.
households that use landline services or a combination of landline and wireless services. Our
first goal is to model the effects on energy consumption if the U.S. were to replace landline
telephones with cellular phones. We will attempt to predict how this change will occur in order
to analyze the transitional and steady state periods of this switch. Lastly, we will estimate the
energy wasted by various household electronics in terms of barrels of oil per day.
The second goal of this study is to consider a “Pseudo U.S.” which has comparable
economic standing to the real United States, but has yet to provide any telephone service to its
citizens. Our model will attempt to find an optimal way of choosing which phone service is the
most energy efficient. Considering that populations do not remain constant, so we will also
predict future growth of Pseudo U.S. and its impact on energy consumption in terms of barrels
of oil per day. Finally, we will model how much energy is wasted by inefficient cell phone
charging techniques such as daily battery charging, battery over-charging, and leaving the
charger plugged when not charging.
Preview of Model:
Our model will attempt to estimate the costs of electricity consumption by cell phones
in terms of barrels of oil per day. To do this we must consider several variables to use in our
model. The change in population is one of the biggest factors, but we must also consider the
following:
-
-
Energy consumption of cell phones during charging period.
Energy consumption of cell phones during standby period.
Phantom energy consumption of cell phone chargers.
Average battery capacity re-charged daily, based on the expected number of
minutes people will talk on their cell phone per day and the mean talk time of their
cell phone battery as well as the amount of battery that drains during standby
periods.
Varying rates of cell phone service subscribership.
Energy conversions from mobile phone charger outputs to barrels of oil.
Team # 5904
Page 5 of 43
Developing our Model:
Assuming cell phone chargers
are always left plugged in, they
16 hours of each day.
-find phantom energy data on
cell phone chargers.
energy consumed by
cell phone charger
(cell phone not
plugged in).
Population Growth:
-calculating
changing population
of US and
consumers with cell
phones.
Finding average
battery capacity
consumed during day.
-using data on avg.
min. talked and avg.
talk time of phone.
Energy from charging cell
phone.
-based on percentage of
battery capacity used.
Total Energy
consumed per cell
phone per day
Assuming mobile phones are
plugged into their chargers for
8 hours, how long is battery
being charged when it is full?
-Consumes energy at rate of
battery drainage.
Standby energy
consumed by fully
charged cell phone
that remains plugged
into charger.
Initial Equation to
model total energy
consumed:
E = Ec + Es + Ep
-Ec = energy charging
-Es = energy standby
Total US energy
consumption by cell
phones, in terms of
barrels of oil per day.
Team # 5904
Page 6 of 43
Requirement One:
Synopsis:
The US currently has about 300 million people. These people have either chosen to
continue using their existing landlines, adopt the wireless technology of cell phones, or use a
combination of both. Our goal is to model the transition from landline usage to reliance on
wireless phones. Our model will attempt to analyze the consequences of this change in
electricity utilization by considering the amount of energy used to recharge the cell phone
batteries versus using landline phones. We will look at both the transition period and the
Assumptions:
-
On average, people will charge their cell phones for 8 hours each night.
The cell phone charger will be left plugged in for remaining 16 hours.
Lithium Ion batteries are used in all cell phones and have negligible energy loss
during charging1.
Analysis of Landline Telephone Usage and Energy Consumption:
Table 1.1 - Usage Percentages by Phase2
Cordless
Corded
Standby
0.23
0.23
0.96
Charge
0.73
0.73
n/a
Active
0.04
0.04
0.04
Table 1.2 – Energy Consumption by Phase (watts)2
Cordless
Corded
Standby
2.3
3.1
1.68
Charge
3.4
4.4
n/a
Active
3.1
3.9
0.525
Using the data from Table 1.1 and Table 1.2, it is possible compute the weighted
averages of wattage usage for each type of landline telephone. This is done by taking the sum
of the products of the percent of time spent in a particular phase and the energy consumed
while in that phase for each of the applicable phases. Doing this yields the results in Table 1.3.
1&quot;Charging
2
Lithium-ion batteries&quot; by Battery University
&quot;Energy use of set-top boxes and telephony products in the U.S.&quot; by the Lawrence Berkeley National Laboratory
Team # 5904
Page 7 of 43
These weighted averages tell us how much wattage is being used by each of the phone types,
on average, at any given time.
Table 1.3 - Weighted Average of Wattage
by Phone Type
Cordless Phone
3.135
4.081
Total Energy for Corded
1.6338
Table 1.4 - Number of Phones Per
Household by Type
Corded Landline Phones
2
Cordless Phones
1
1
Using the computed weighted averages, the assumptions presented in Table 1.4,
household projections from the U.S. Bureau of the Census and the percent of households with
landline telephones from the Centers for Disease Control (see Appendix C), it’s possible to
calculate the total amount of energy consumed by landline telephones for a given year. For
instance, in 2007 there were 111,162,259 households3, 81.9% of which had landline
telephones3, which indicates that there were a total of 91,041,890 total households with
landline telephones. The total wattage consumed by landline telephones in an average
household can be computed by taking the sum of the products of the data in Table 1.3 and
Table 1.4 for corresponding telephone types. This shows that the average household in the
U.S. with landline telephones uses 10.48 watts exclusively for landline telephones, which is
equivalent to 251.6Wh (watt-hours) per day. 91,041,890 households times 251.6Wh is equal to
22,906,139,524Wh per day, which is equivalent to 13,475 barrels of oil per day4. Figure 1.1
shows how the total amount of energy consumed by landline telephones is decreasing due to
the decreasing number of households with landline telephones.
3
4
See Appendix C
Bio-energy Conversion Factors
Team # 5904
Page 8 of 43
Figure 1.1 - Total Energy Used by Landline Telephones by Year
18,000
16,000
Barrels of Oil per Day
14,000
12,000
10,000
Total Energy Used by Landline
Phones (Barrels of Oil per Day)
8,000
6,000
4,000
2,000
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
0
Figure 1.1 shows that the amount of energy consumed by landline telephones peaked around
the year 2001. This seems puzzling at first, but makes sense considering that prior to 2001 the number
of households with landline telephones was increasing as the population (and correspondingly the
number of housing units) was increasing. After 2001, some households began substituting landline
telephones in favor of cellular phones.
Analysis of Cellular Telephone Usage and Energy Consumption:
Table 1.5 - List of Figures
Average Talk Time Used Per Day5
Average Talk Time Until Battery Dies6
Average Standby Time Until Battery Dies5
Average Voltage of a Lithium Ion Battery7
Average mAh of a Lithium Ion Battery8
Average Time It Takes To Fully Charge9
Average Energy Used by Charger With No Phone10
Assumed Average Time Cell Phone Is Active (Not Charging)
Assumed Percentage of Subscriptions That Are Multiples
5
“Global Wireless Matrix 4Q07” by Merrill Lynch
See Appendix B
7 Batteries4Less.com
8 See Appendix A
9 Charging Lithium-ion batteries&quot; by Battery University
10
“Standby Power Summary Table&quot; by Lawrence Berkeley National Laboratory
6
0.5 hours
4.9 hours
222.4 hours
3.7 V
935 mAh
3 hours
0.14 W
16 hours
10
Team # 5904
Page 9 of 43
Throughout our research and analysis of data, we determined the values listed in Table
1.5 above. Using the figures from Table 1.5, population projections from the U.S. Bureau of the
Census and the number of cell phone subscriptions in the U.S. from the Global Wireless Matrix
4Q07 Report (see Appendix D), it’s possible to calculate the total amount of energy consumed
by cellular telephones for a given year. For instance, in 2007 there were 255 million cell phone
subscriptions11 and 301,279,593 people in the U.S.11, assuming 10% of subscriptions are for
people with multiple cell phones, we can calculate the total percentage of the U.S. population
with cell phones by taking 90% of the 255 million subscriptions and dividing by the number of
people in the United States, which gives us 76.2% or 22.95 million people. The total energy
consumed by cellular telephones by an average person can be computed by the Partitioning
Model below.
Partitioning Model
Methodology:
Suppose each individual, 𝑖, has an energy profile, 𝐸. That is, an individual consumes a
finite amount of power in a given day from cell phone use. Then, the energy that is consumed
by a single individual can be modeled as follows:
𝐸𝑖 = 𝑒𝑐 + 𝑒𝑠 + 𝑒𝑝
where:



𝑒𝑐 is the energy used from charging a lithium ion battery.
𝑒𝑠 is the energy used from charging the battery while the cell phone is on standby.
𝑒𝑝 is the energy used from a phantom load.
Calculating 𝑒𝑐 :
Let 𝛽 be the percentage of the battery drained. Then, for an average day,
𝑇𝑎 𝐻 − 𝑇𝑎
𝛽=( +
)
𝑇𝑡
𝑆𝑡
where:




11
𝑇𝑎 is the average talk time for an individual
𝑇𝑡 is the total talk time a cell phone battery allows (𝑇̅𝑡 = 4.9)12
𝐻 is the total time the battery is away from the charger (𝐻 = 16 in our 8-hour charging
assumption)
𝑆𝑡 is the total standby time (𝑆𝑡̅ = 222.4)13
See Appendix D
See Appendix B
13
Calculated from data provided in the “Full Specification Pages” from Cell Phone Reviews by Cnet.com
12
Team # 5904
Page 10 of 43
We constrict 𝛽 ≤ 1, since the battery cannot be more than 100% drained. This is because
𝑇𝑎
𝐻−𝑇𝑎
𝑡
𝑆𝑡
( 𝑇 ) represents the percentage of battery drained while talking and (
) represents the
percentage of battery drained while in standby. Adding these two percentages together yields
the total percentage of the battery that was drained in an average day.
Then, the energy that a cell phone consumes in an average day is equal to the energy the
battery consumes during a full recharging cycle scaled by the percentage drained:
𝑒𝑐 = 𝛽(𝑉 ∗ 𝐼)
where:
𝑉 is the voltage of the battery (typically 3.7V)14.
𝐼 is the capacity of the battery in amp-hours (our data suggests an average of
935mAh)15.
Calculating 𝑒𝑠 :
When the battery is fully charged, yet still plugged into the charger, we propose that the
rate of energy being drawn from an outlet is equal to the rate that the battery drains while in
standby. In this case, we can calculate 𝑒𝑠 as this rate scaled by the power a battery consumes
during a full charge.
24 − 𝐻 − 𝛽𝑇
𝑒𝑠 = (
) (𝑉 ∗ 𝐼)
𝑆𝑡
where 𝑇 is the time it takes for a battery to become fully charged after having no charge
(𝑇̅ = 3)15.
Calculating 𝑒𝑝 :
We are assuming an 8 hour charge time with a corresponding 16 hour period where the
charger is using energy but is not plugged in to the cell phone. This energy loss is known as a
phantom load. The phantom energy consumed by cell phone chargers has been estimated by
the University of Berkeley (0.14W)16. From this estimate, we conclude that 𝑒𝑝 can be
approximated for a 16 hour period as follows:
𝑒𝑝 ≈ 0.14W &times; 16h = 2.24Wh
Consider a full 24-hour day in which an individual has a cell phone. Assume that an
individual charges his/her cell phone for 8 hours each night. Then, cell phone energy use can be
modeled by considering the energy profile of every individual 𝑖, in the space 𝑆, the cell phone
users of the United States. If we sum over all energy profiles in the United States, we could
14
Charging Lithium-ion batteries&quot; by Battery University
See Appendix A
16
“Standby Energy Power Table” - by Lawrence Berkeley National Laboratory
15
Team # 5904
Page 11 of 43
estimate how much energy is used from cell phones in the United States each day. Namely, if
𝑇𝐸 is total energy,
𝑇𝐸 = ∑ 𝐸𝑖
𝑖∈𝑆
Estimating 𝑇𝐸:
Naturally, data on the energy profile for each cell phone user is unavailable. However, if
something is known about the proportion of people that talk on their cell phones, we can
estimate 𝑇𝐸. Partition the space 𝑆 into 𝑝 subsets. Place each individual in 𝑆 that talks a given
percent of the time on his/her cell phone into partition 𝑔𝑝 . Based on the percentage of time
each person talks on his/her cell phone, we can generate an energy profile, 𝐸𝑝 for each group.
Then, we have 𝑝 distinct energy profiles and can estimate 𝑇𝐸, as a weighted average. The
estimation equation follows:
̂ = |𝑔1 |𝐸1 + |𝑔2 |𝐸2 + ⋯ + |𝑔𝑝 |𝐸𝑝
𝑇𝐸
𝑝
= ∑|𝑔𝑖 |𝐸𝑖
𝑖=1
Where |𝑔𝑖 | denotes the cardinality of subset 𝑔𝑖 .
Note that, if |𝑆| = 𝑛, and each individual has a distinct energy profile,
𝑝
𝑇𝐸 = lim ∑|𝑔𝑘 |𝐸𝑘
𝑝→𝑛
𝑘=1
Thus, the more partitions that are available, the better the estimate can be.
Example:
According to a survey of 2,011 cell phone users from Wirefly.com:



46 percent use their cell phone 500 minutes a month or less.
32 percent use their cell phone between 500 and 1000 minutes per month.
13 percent said they use their cell phone more than 1000 minutes each month.
Convert this into a daily average:



46 percent use their cell phone 16.44 minutes per day or less.
32 percent use their cell phone between 16.44 and 32.88 minutes per day.
13 percent said they use their cell phone more than 32.88 minutes per month (We set
the upper bound to obtain at 49.32 minutes to obtain uniform intervals).
Team # 5904
Page 12 of 43
Partition the group of 2,011 people as follows, based on the percentage of time they talk on
a cell phone per day:
Group
𝑔1
𝑔2
𝑔3
|𝑔|
925/.91 = 1016
644/.91 = 708
261/.91 = 287
Energy Profile
𝐸1
𝐸2
𝐸3
Now, the energy profile can be estimated by the methodology and estimates discussed above:
Group
𝑔1
𝑔2
𝑔3
𝑒𝑐 (Wh)
0.34
0.53
0.72
𝑒𝑠 (Wh)
0.12
0.11
0.11
𝑒𝑝 (Wh)
2.24
2.24
2.24
𝐸(Wh)
2.70
2.88
3.07
̂ = 1016 ∗ 2.70 + 708 ∗ 2.88 + 287 ∗ 3.07 = 5663.33 Wh
𝑇𝐸
Now, suppose that this sample is representative of the current United States cell phone users.
Then, if we scale this number by the number of cell phones users in the United States we can get an
estimate of the total amount of energy consumed by cell phones. For instance, in 2007 there were
22.95 million17 cell phone users, which gives us
5663.33 Wh
(
) (22950000 People) = 64631240 Wh
2011 People
As the number of people surveyed and the distinctions among partitions increase, the model
would more accurately describe the overall energy usage. Also, such a large population size plays an
important role in this model; a change in even a tenth of a watt makes a tremendous difference. The
model greatly depends on the fidelity of the data.
17
See Appendix D
Team # 5904
Page 13 of 43
Figure 1.2 - Total Energy Used by Cellular Telephones by Year
16,000
Barrels of Oil per Day
14,000
12,000
10,000
8,000
Total Energy Used by Cell
Phones (Barrels of Oil per Day)
6,000
4,000
2,000
2033
2030
2027
2024
2021
2018
2015
2012
2009
2006
2003
2000
1997
1994
0
Figure 1.2 shows that the rate at which the energy consumed by cellular telephones increases
from year to year changes abruptly around 2013. This is because prior to 2013 the percentage of people
with cell phones in the U.S. was increasing along with the population. After 2013, our model indicates
that nearly 100% of people will have a cell phone, at which point the number of people with cell phones,
and correspondingly the amount of energy consumed by cell phones, will increase only as the
population increases.
Analysis and of Both Landline and Cellular Telephone Usage and Energy Consumption:
Figure 1.3 - Total Energy Used by Telephones Divided by Type by Year
70,000
60,000
50,000
Total Energy Used by Cell
Phones (Barrels of Oil per
Day)
40,000
Total Energy Used by
Landline Phones (Barrels
of Oil per Day)
30,000
20,000
10,000
2032
2029
2026
2023
2020
2017
2014
2011
2008
2005
2002
1999
1996
1993
1990
0
Team # 5904
Page 14 of 43
Figure 1.3 shows the total amount of energy used by all telephones broken up by type.
Comparing the year 1990 (all landline phones) to 2034 (projected to be all cellular phones) it is clear that
cell phones consume more energy than landline phones. The total energy consumed by all phones
appears to level off around the year 2013. This is because prior to 2013 the percentage of people with
cell phones in the U.S. was increasing along with the population. After 2013, our model indicates that
nearly 100% of people will have a cell phone, at which point the number of people with cell phones, and
correspondingly the amount of energy consumed by cell phones, will increase only as the population
increases. Coincidently the population increases at about the same rate that households with landline
phones decreases, causing the amount of energy consumed by all phones to appear to level off. After
2034, the energy consumed by all phones (at this point all cell phones) will begin to increase again as the
population, and thus the number of cell phone users, increases.
Figure 1.4 - Total Energy Used by Telephones Divided by Type by Year, Assuming
25,000
20,000
Total Energy Used by Cell Phones
(Barrels of Oil per Day)
15,000
Total Energy Used by Landline Phones
(Barrels of Oil per Day)
10,000
5,000
2032
2029
2026
2023
2020
2017
2014
2011
2008
2005
2002
1999
1996
1993
1990
0
Figure 1.4 shows the total amount of energy used by all telephones broken up by type,
assuming negligible phantom load. Comparing the year 1990 (all landline phones) to 2034 (projected to
be all cellular phones), it appears from this figure that the energy amounts consumed are roughly equal.
This figure is interesting because it indicates that the differences between Figure 1.3 and Figure 1.4 are
caused exclusively by phantom load. That is to say, phantom load is the only thing that causes cell
phones to use so much more energy than landline phones in Figure 1.4. Consider also that the
population in 1990 was 247 million and the population in 2032 is projected to be 380 million. Roughly
the same amount of energy could be used to provide telephone service to 133 million more people
using cell phones rather than landlines, provided that phantom load could be eliminated. This suggests
that if the phantom load could be eliminated (for example by removing the charger from the wall when
it’s not being used), cell phones would actually consume less energy than landline phones.
Team # 5904
Page 15 of 43
Requirement Two:
Synopsis:
“Pseudo U.S.” is a country very similar to the current US. It has approximately 300
million people and has a comparable economic standing. However, this developing country has
neither landline phones nor cell phones. We will attempt to use our model to predict the
optimal was of providing phone service to this emerging country. Although our model will
purely consider this from and energy perspective, we will also briefly discuss the social and
economic consequence of choosing landlines or cell phones.
Assumptions:
-
Underlying infrastructure for landlines or cell phones will already be in place. (No
construction costs involved, just energy costs)
People are free to choose which service they want.
-
Optimal way of providing phone service:
Case 1: Cell phone users keep their chargers plugged in while not in use
If all wireless users forgo conservative energy practices, than the sum of the energy
wasted becomes so large that landlines are by far the optimal choice for providing cell phone
service. This is so because of the phantom energy costs of leaving the phone chargers plugged
in. Our model has shown these energy costs to be quite significant, and thus wireless phone
service would cost much more in terms of energy. Therefore, we can conclude under these
circumstances that “Pseudo U.S.” would adopt landlines as their primary means of
communication.
Figure 2.1 - Total Energy Used by Telephones Divided by Type by Year
70,000
60,000
50,000
Total Energy Used by Cell
Phones (Barrels of Oil per
Day)
Total Energy Used by
Landline Phones (Barrels
of Oil per Day)
40,000
30,000
20,000
10,000
2032
2029
2026
2023
2020
2017
2014
2011
2008
2005
2002
1999
1996
1993
1990
0
Team # 5904
Page 16 of 43
Case 2: Cell phone users practice energy efficient techniques and unplug chargers when not on.
If the citizens of “Pseudo U.S.” adopted energy efficient techniques, then the optimal
phone service would be wireless. Our model shows that without the phantom energy
consumption, the amount of energy consumed by landline and wireless is nearly equal. Thus
“Pseudo U.S.” could have either of the two. It is most likely they would choose a wireless
phone service due to several factors. Such as cell phones are extremely convenient, portable,
and provide users with entertainment.
Figure 2.2 - Total Energy Used by Telephones Divided by Type by Year, Assuming
25,000
20,000
Total Energy Used by Cell Phones
(Barrels of Oil per Day)
15,000
Total Energy Used by Landline
Phones (Barrels of Oil per Day)
10,000
5,000
2032
2029
2026
2023
2020
2017
2014
2011
2008
2005
2002
1999
1996
1993
1990
0
Discussion of social and economic consequences of choosing landlines or cell phones:
Although under most conditions it is more energy efficient to use landlines, there are
many social and economic advantages that come with the use of cell phones. The main
advantage of cell phones, and a large reason they have become so popular in the current US, is
their portability. Cell phones can not only be used at home, but can be used at work or when
traveling. Studies have shown that 74% of Americans have used their cell phone in some sort of
an emergency, and received help by doing so. Also, 41% of cell phone owners admit they use
their wireless device to fill in their free time (Rainie). Clearly cell phones have transcended the
levels of landline communications; offering multimedia messaging and round the clock access
to people who carry them. These additional benefits, which could not be obtained by
phonelines, are the reasons that people have chosen to accept the higher monetary costs of
using wireless services. Yet, there still remains a small demographic in the current US that
chooses to utilize the existing landline services. Their motives are most likely based on cost. As
phone lines are already in place, and thus very cheap to use, many people still choose to use
their existing landline phones. However, as the advantages of having cell phones continue to
grow and become more appealing to Americans, we will continue to see growth in the number
of cell phone users. Thus, the convenience of using cell phones, and the entertainment we
receive from them, has trumped the cost and energy effectiveness of landlines. If current
trends hold true, landlines will soon become obsolete; and the US will we become completely
wireless.
Team # 5904
Page 17 of 43
Requirement Three:
Synopsis:
Although cell phones do not need to be recharged every day, many people choose to do
so. They may also choose to leave their chargers plugged in all day. These practices waste
energy, and add to the overall energy consumption by cell phones. Our model will be used
here to calculate the costs of this wasteful practice in terms of barrels of oil per day.
Assumptions:
-
Cell phones are charged daily, and the chargers are left in all day.
It takes 3 hours to charge the battery, and the cell phone is removed after 8 hours.
Thus leaving the charger plugged in for 16 hours.
• Charging
phone
• Battery is
partially or
fully drained.
Takes 3 hours to
charge empty
battery
Charges for
hours.
• Battery is now
fully charged.
• Standby
energy is
consumed as
phone is still
plugged in.
• Cell phone is
unplugged,
but charger is
still plugged
in.
16 hours of
phantom energy
consumption.
Figure 3.1 shows the changes in the amount of phantom energy consumed by cell phones by
year. Cell phones did not become commercially viable at the retail level until around 1996, which is
represented in the graph by the constant value of 0 barrels of oil per day being consumed by cell phones
prior to 1996. This graph shows that the rate at which the energy consumed by cellular telephones
increases from year to year changes abruptly around 2013. This is because prior to 2013 the percentage
of people with cell phones in the U.S. was increasing along with the population. After 2013, our model
indicates that nearly 100% of people will have a cell phone, at which point the number of people with
Team # 5904
Page 18 of 43
cell phones, and correspondingly the amount of energy consumed by cell phones, will increase only as
the population increases.
Figure 3.1 - Total Phantom Energy Used by Cell Phones by Year
(Barrels of Oil per Day)
60000
Barrels of Oil per Day
50000
40000
30000
Total Energy Used by Cell
Phones (Barrels of Oil per Day)
20000
10000
2032
2029
2026
2023
2020
2017
2014
2011
2008
2005
2002
1999
1996
1993
1990
0
The amount of energy consumed by cell phones that are plugged into chargers longer than
necessary to fully charge the phone is not included in the above model. This exclusion results from our
assumption that cell phones are left on 24 hours per day. This means that whether the phone is plugged
into the charger or not the battery will drain at the same rate. If the cell phone were unplugged from
the charger after fully charging, the battery would drain at the standby rate and would thus need to
charge more the next night. If the cell phone were left plugged into the wall, the battery would still
drain at the standby rate, but would instantaneously be recharged. The difference between unplugging
the phone once it is fully charged compared to leaving the phone plugged in comes down to a question
of when the battery is recharged, not how much energy it takes to do it.
Note: If we include the amount of energy consumed by cell phones that are plugged into
chargers longer than necessary to charge the phone in the above graph, the results change only slightly.
That is to say that the amount of energy “wasted” in this way is essentially negligible.
Team # 5904
Page 19 of 43
Requirement Four:
Synopsis:
Phantom loads are not only a concern while considering cell phone usage. All electrical
appliances draw power, even while switched off. With this power drain continuously occurring
in U.S. households, one might question how much energy is consumed from phantom loads
alone. In this section, we will target this question and approximate how much energy phantom
loads are responsible for in terms of barrels of oil.
Analysis:
A sample of phantom loads from common electronic devices was collected. These data
were obtained from the Lawrence Berkeley National Laboratory. From this compilation, the
authors selected a list of appliances to be a conservative estimate, representative of a typical
household:
Product (Off)
Air Conditioner, room/wall
Computer Display, LCD
Computer, Desktop
Computer, notebook
Heating, furnace central
Modem, DSL
Modem, cable
Night Light, interior
Printer, inkjet
Set-top Box, DVR
Speakers, computer
Stereo, portable
Television, rear projection
Audio Minisystem
Coffee Maker
DVD/VCR
Game Console
Microwave Oven
Surge Protector
Total:
18
“Standby Energy Power Table” - by Lawrence Berkeley National Laboratory
Mean18 (W)
0.9
1.13
2.84
8.9
4.21
1.37
3.84
0.05
1.26
36.68
1.79
1.66
6.6
8.32
1.14
5.04
1.01
3.08
1.05
90.87
Team # 5904
Page 20 of 43
Suppose that each household has one of each of the above electronic devices and has a
phantom load consumption of 90.87 Watts. We use this assumption, the same U.S. Census
Bureau household data as discussed in Requirement 1, and the appropriate conversion for a
barrel of oil into energy. We use these data to convert phantom load energy into its barrel of oil
equivalent:
𝐵(𝑡)
⏟
=
⏟
90.87
&times;
Average Watt
Per HouseHold
Number of
Barrels of Oil
Used per Day at
Time 𝑡 (years)
1W
⏟
1000kW
Conversion from
W to kW
&times;
24
⏟
&times;
Conversion from
kW to kWh (devices
are on 24 hours)
1
⏟
1700
Conversion from
kWh to Barrels of Oil
&times;
ℎ(𝑡)
⏟
Number of Households
at Time t (years)
= 𝑐 ∗ ℎ(𝑡)
Appendix E contains tabulated values for 𝐵(𝑡).
The following figure shows 𝐵(𝑡) for a number of years.
Daily Oil Usage Over Time From Phantom Loads
250000
Oil (Barrels)
200000
150000
Oil Usage
100000
50000
2070
2066
2062
2058
2054
2050
2046
2042
2038
2034
2030
2026
2022
2018
2014
2010
2006
2002
1998
1994
1990
0
According to the Energy Information Administration, the U.S. consumes 20,680,000
barrels of petroleum each day.19 Compared to this figure, daily phantom load consumption may
not appear to amount to much daily, but suppose that U.S. households consume the amount of
barrels predicted by 𝐵(𝑡) each day.
19
“Petroleum Basic Data” by the Energy Information Administration
Team # 5904
Page 21 of 43
A linear regression in Microsoft Excel provides the following function for ℎ(𝑡):
ℎ(𝑡) = 1131231𝑡 + 90835303
Let
𝑡
1
𝑔(𝑡) = 𝑐 ∗ ∑ ℎ (
𝑡)
365
𝑖=1
Where 𝑐 is the constant used to convert from watts to barrels of oil.
The sum, 𝑔(𝑡), computes the cumulative number of barrels of oil consumed by
Americans at time 𝑡, the number of days after 1990. The following plot of 𝑔(𝑡) shows the
disconcerting amount of cumulative consumption resulting from phantom loads:
Figure 4.1 - Cumulative Oil Usage Over Time From Phantom Loads
6
Barrels of Oil (Billions)
5
4
3
Oil Usage
2
1
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76
Years
since
1990
The energy withdrawal for phantom loads over time is considerable; if phantom loads
could have been prevented from 1990 up to 2070, enough energy could be conserved to meet
the oil provisions of the current United States for over 246 days.
Recall that these figures are derived from conservative estimates of a household. If each
household in the U.S. owned more than one TV, computer, sound system, etc., the phantom
load consumption would be even more substantial (see Appendix E for data).
Team # 5904
Page 22 of 43
Requirement five:
Synopsis:
Even though cell phones are a considerable part of our economy right now, they will
continue to expand and become an even larger factor for energy consumption in the future.
Our model will attempt to predict the changes in population and economic growth over the
next 50 years, and how this will impact energy consumption in terms of barrels of oil.
Figure 5.1 - Total Energy Used by Telephones Divided by Type by Year
70,000
60,000
50,000
Total Energy Used by Cell
Phones (Barrels of Oil per
Day)
Total Energy Used by
Landline Phones (Barrels
of Oil per Day)
40,000
30,000
20,000
10,000
0
1990
2000
2010
2020
2030
2040
2050
2060
Figure 5.1 shows the total energy consumed by telephones from 1990 to 2060. An abrupt shift
in the rate of change of the amount of energy consumed first appears around 1996. This is because cell
phones did not become commercially viable at the retail level until around 1996. As cell phones began
to increase in popularity, the amount of energy consumed by all phones increased as well. The next
abrupt change appears to occur around 2013. This is because, prior to 2013, the percentage of people
with cell phones in the U.S. was increasing along with the population. After 2013, our model indicates
that nearly 100% of people will have a cell phone, at which point the number of people with cell phones,
and correspondingly the amount of energy consumed by cell phones, will increase only as the
population increases. Coincidently, the population increases at about the same rate that the number of
households with landline phones decreases, causing the amount of energy consumed by all phones to
appear to level off (or slightly decrease). After 2034, the energy consumed by all phones (at this point,
all cell phones) will begin to increase again as the population, and thus the number of cell phone users,
increases.
Team # 5904
Page 23 of 43
Summary and Evaluation:
Brief Introduction:
The purpose of this study was to model the energy consequence of the wireless phone
revolution. As this technology has continued to grow, the demand for electricity to charge cell
phones has grown linearly. We decided to model the energy consumed by one cell phone, on
an average day, and extrapolate this to encompass the energy demands of the entire U.S.
population. We did this by breaking down the energy consumption of the cell phone into the
following three parts: time during which cell phone battery is replenishing from the charger,
the standby time where the phone battery is fully charged but still plugged in, and lastly the
time which the phone is removed from the charger but the charger remains plugged into the
wall. Together, these times make up the typical day for the energy profile of each wireless
phone.
Strengths:
The strength of our model comes from partitioning the population into subsets
dependent on their usage of their cell phone. This allows us to include the varying amounts of
energy needed to recharge the batteries in our model. This helped to get a more accurate
estimate of the total energy consumption by cell phone chargers in the U.S. Similarly, we
divided the energy profile of each cell phone into three time frames. First, the battery is
partially or fully drained and it is recharged. Second, the battery is full but still plugged into the
charger. Lastly, the phone is removed from the charger, but the charger remains plugged into
the wall. This has helped us to accurately model the energy consumption by cell phone
chargers.
Weaknesses:
The main weakness of our model is its’ tendency towards the average. Many of the
data inputs we use in our calculations are averages of the data we found from our resources,
and this may not fully represent the current trends in energy consumption. Our model most
likely estimates the total energy consumption on the conservative side. Another weakness of
the model is that we have assumed a perfectly efficient energy transfer from the charger to the
battery. Realistically, some energy might be lost to resistance, and the total energy used to
charge a cell phone would be higher.
Problems:
The biggest problem with our model will most likely be the accuracy and cohesiveness
of the data. As our data was taken from so many different sources, some of varying credibility,
tiny errors in their calculations could extrapolate to very large errors as we used our model to
make projections into the future. Furthermore, some of the research was very hard to find
Team # 5904
Page 24 of 43
during our short period of time we had to work on this problem. We have tried our hardest to
find the most credible and accurate sources, and we have cited them throughout our solution.
Conclusion:
We found that the total energy consumption of cell phones is far greater than the total
energy consumption of landline phones. This is partly due to the fact that people do not share
their mobile phones, as they could with landline phones. So, there are a growing number of cell
phones, and shortly in the future we expect there to be one wireless subscription for every
person in the U.S. This has created a large increase in the consumption of energy (in terms of
barrels of oil) by all phones. However, a very large part of this increase is wasted by inefficient
cell phone charging techniques. Our model shows that phantom load, energy consumed by the
charger itself plugged into the wall, plays a significant role in the overall levels of energy
consumption. Thus, if the U.S. were able to adopt more energy efficient charging techniques,
the costs of cell phones cut largely be cut.
Team # 5904
Page 25 of 43
Works Cited:
“Battery review – CNET.” Product reviews and Prices, Software downloads, and tech news –
CNET. 07 Feb. 2009 &lt;http://www.cnet.com/1770-5_1-0.html?&gt;.
Bernstein, R. Census Bureau Projects U.S. Population of 305.5 Million on New Year's Day. Rep.
no. # CB08-191. 29 Dec. 2008. U.S Census Bureau News. 5 Feb. 2009
&lt;http://www.census.gov/Press-Release/&gt;.
&quot;Bioenergy Conversion Factors.&quot; Bioenergy Feedstock Information Network (BFIN)
&lt;http://bioenergy.ornl.gov/papers/misc/energy_conv.html&gt;.
Blumberg, Ph.D, Stephen J., and Julian V. Luke. &quot;N C H S - N H I S - Wireless Substitution Tables,
July-December 2007 (Released 5/2008).&quot; Centers for Disease Control and Prevention.
Dec. 2007. National Center for Health Statistics. 06 Feb. 2009
&lt;http://www.cdc.gov/nchs/data/nhis/earlyrelease/wireless200805_tables.htm&gt;.
Buckmann, Isiodor. &quot;Charging Lithium-ion batteries.&quot; Welcome to Battery University. Mar.
2006. 08 Feb. 2009 &lt;http://www.batteryuniversity.com/&gt;.
&quot;Cell Phone Battery Guide | Cellular Battery Guide - Cellphone Battery Warehouse.&quot; Cell Phone
Battery Warehouse - Cell Phone Battery | Cell Phone Batteries | Cellular Battery |
Cellular Batteries. 07 Feb. 2009
&lt;http://www.batteries4less.com/contents/Battery_Guide/?module=static&amp;section=Batt
ery_Guide&gt;.
Edwards, Tom. Nation's Housing Stock Reaches 128 Million. Rep. no. CB08-151. 6 Oct. 2008. U.S
Census Bureau News. 5 Feb. 2009 &lt;http://www.census.gov/Press-Release/&gt;.
&quot;EIA - Petroleum Basic Data.&quot; Energy Information Administration - EIA - Official Energy Statistics
from the U.S. Government. 2007. US Government- Federal Statistics. 08 Feb. 2009
&lt;http://www.eia.doe.gov/basics/quickoil.html&gt;.
&quot;Global Wireless Matrix 4Q07.&quot; Scribd. 21 Apr. 2003. Merrill Lynch. 07 Feb. 2009
&lt;http://www.scribd.com/doc/7656611/Global-Wireless-Matrix-4Q07&gt;.
&quot;Phantom Loads Steal Energy.&quot; Alternative Technology and Renewable Energy at Home. 07 Feb.
2009 &lt;http://www.alternativetechnology.info/phantom.htm&gt;.
&quot;Population Projections - 2008 National Population Projections: Summary Tables.&quot; Census
&lt;http://www.census.gov/population/www/projections/summarytables.html&gt;.
Rainie, Lee, and Scott Keeter. &quot;Cell Phone Use.&quot; Pew Internet &amp; American Life Project. Apr.
2006. Associated Press. 07 Feb. 2009
&lt;http://www.pewinternet.org/pdfs/PIP_Cell_phone_study.pdf&gt;.
Team # 5904
Page 26 of 43
&quot;Standby Power Summary Table.&quot; Standby Power. 2009. Lawrence Berkeley National
Laboratory. 07 Feb. 2009 &lt;http://standby.lbl.gov/summary-table.html&gt;.
Dec. 2008. 05 Feb. 2009 &lt;http://www.fcc.gov/wcb/iatd/trends.html&gt;.
Appendices: Data and Input Calculations
Calculating average hours of talk time per cell phone and average cell phone battery capacity:
Appendix A: This table was taken from an online website that sells batteries. It is a sample of
143 Lithium Ion batteries that are most commonly found in typical cell phones. Most batteries
are manufacture by the largest cell phone producers such as Motorola and Samsung. The data
displays the storage capacities of the batteries.
Appendix B: This data was obtained from CBS’s CNET. The sample is 611 cell phones tested
under uniform conditions. The data measures the average talk time of each phone; where talk
time is taken to be how long the battery will last while actively being used.
Calculations for average battery capacity:
In order to eliminate outliers, a ten percent trimmed mean was taken of the 143 batter
samples. A ten percent mean being interpreted as discarding the highest 5% and the lowest 5%
of the data. Then we simply used Excel to average the remaining data to obtain the expected
battery capacity. Avg. Battery Capacity = 935.2 mAh (milliamp hours)
Calculations for average talk time:
We also chose to eliminate outliers from this data set by utilizing the ten percent trimmed
mean. Then using Excel to calculate the average from the remaining data, we obtained the expected
value of talk time per cell phone. Avg. Talk Time = 5.08h (hours)
Team # 5904
Page 27 of 43
Appendix A:
Model
LI-2600
LI-3390
LI-3390XT
LI-6100
LI-6100HC
LI-6100VB
LI-6100VBHC
LI-6100XC
LI-6100XCVB
LI-8260
LI-8290
LI-A2218Z
LI-AV8000
LI-AV8300
LI-AV8400
LI-AV8500
LI-AV8600
LI-AV8610
LI-AV8900
LI-AV9500
LI-AV9950
LI-CDM130
LI-CDM4000
LI-CDM9100
LI-i1000HC
LI-i30XT
LI-i80
LI-i85
LI-i85XT
LI-i90XT
LI-KY7135
LI-KYKE414
LI-KYKOI
LI-KYKX1
LI-KYKX440XT
LI-KYS14
LI-KYSE47
LI-LG1010
LI-LG110
LI-LG1200
mAh
1000
900
1200
1000
1300
1000
1400
3600
3600
900
900
1000
1400
900
800
850
900
850
900
550
900
1000
1150
650
1200
1400
900
900
1400
1400
1000
700
800
700
1400
700
900
1000
650
1400
LI-LG330
LI-LG4010
LI-LG4NE1
LI-LG510B
LI-LG510S
LI-LG5350XT
LI-LGC1300
LI-LGLX5400
LI-LGLX5450
LI-LGLX5550
LI-LGVX1
LI-LGVX2000
LI-LGVX3100
LI-LGVX3200
LI-LGVX4400
LI-LGVX4400XT
LI-LGVX4500
LI-LGVX6000
LIM-STACHCBK
LI-MT720
LI-MT720XT
LI-MTC331
LI-MTi530XT
LI-MTi730XT
LI-MTi830
LI-MTi830XT
LI-MTV171
LI-MTV220
LI-MTV3
LI-MTV710
LI-N200
LI-NK2270
LI-NK3220
LI-NK6015
LI-NK6102
LI-NK7210
LI-PNTX310
LI-PNTX310XT
LI-PNTX320
LI-Q2035
LI-Q2135
900
800
1300
800
800
1400
800
900
950
950
900
1000
900
800
900
1400
700
1000
1200
900
1300
700
1400
1300
900
1400
700
800
600
650
1400
900
700
950
700
650
600
1400
900
900
900
LI-Q3035
LI-R225
LI-R225XT
LI-RM7100
LI-RM7250
LI-S4500
LI-S6000
LI-S6100
LI-S800
LI-SCH210
LI-SCHA310
LI-SET300
LI-SET610
LI-SEZ500
LI-SGHN105
LI-SL3500
LI-SL411
LI-SMA55
LI-SMCF62
LI-SN4900
LI-SN5000
LI-SN5300
LI-SN5400
LI-SN6200
LI-SN7300
LI-SN8100
LI-SPHA400
LI-SPHA460XT
LI-SPHN240
LI-SPHN300
LI-SPHN400
LI-SQ105
LI-SSA310
LI-SSA460
LI-SSA500XT
LI-SSA530
LI-SSA610
LI-SSA620
LI-SSA670
LI-SSD415
LI-SSE105
900
650
900
800
950
650
1000
1000
1000
1400
1400
700
700
700
650
900
1000
700
750
1400
1300
1400
1400
1300
900
1300
1400
1300
650
900
1400
1000
900
900
1400
1400
1200
1000
900
900
650
LI-SSE315
LI-SSE715
LI-SSi500
LI-SSI600
LI-SSS105
LI-SSV205
LI-SSX105
LI-STACTP
LI-T28
LI-T60
LI-T61
LI-TP2100
LI-TP5200XT
LI-TPOINT
LI-TX220
LI-TX320
LI-V120C
LI-V3620
LI-V60XT
LI-V66
LI-V70
950
650
1400
900
700
900
900
900
1200
900
600
900
1300
900
1400
1400
900
900
850
550
450
Team # 5904
Page 28 of 43
Appendix B:
Model
Talk Time
(hours)
Audiovox CDM-8900
3
Audiovox CDM-8910
3.5
Audiovox CDM-8940
3.6
Audiovox CDM-9900
2.5
Audiovox Flasher V7
3.5
Audiovox PM-8920
4
Audiovox PPC4100
4.5
Audiovox PPC6601
4
Audiovox SMT5600
7
UTStarcom Verizon
4.6
Wireless Blitz
UTStarcom CDM-105 2.5
UTStarcom CDM-120 3
UTStarcom CDM-180 4
UTStarcom CDM3.55
8905
UTStarcom CDM4.5
8945
UTStarcom Slice
3.8
PCS1400
UTStarcom Super
4.6
Slice
UTStarcom Virgin
4.08
Mobile Arc
UTStarcom XV6700
4
2.83
(Virgin Mobile TNT)
Kyocera Tempo
3.38
E2000
Kyocera Jet
3.75
Kyocera K10 Royale
3.25
Kyocera K321P
3.06
Kyocera K323
2
Kyocera K324 Cyclops 4
Kyocera K4130 SoHo 2.75
Kyocera KX2 Koi
3
Kyocera KX444
3
Kyocera KX9D Oystr
Kyocera Marbl K127
Kyocera SE47
Kyocera Slider Sonic
Kyocera Switch Back
Kyocera Wild Card
LG A7110
LG Aloha - LX140
LG AX275
LG AX490
LG C1300
LG C1500
LG C2000
LG CE110
LG CE500
LG CG180
LG CG225
LG CG300
LG Chocolate 8550
LG VX8560 Chocolate
3
LG Chocolate KG800
LG Chocolate VX5800
LG CU320
LG CU400
LG CU500
LG CU515
LG Dare
LG Decoy
LG DM-L200
LG enV (VX9900)
LG enV(2)
LG F7200
LG F9100
LG F9200
LG Flare LX175
LG G4011
3.5
4
4
2.5
3.5
3.75
2.75
3
3
4
3.5
3
4
3.08
7.2
9.23
7
4.5
4.6
3.12
5.75
2.5
3.6
4.25
4.5
6.48
5.15
4.16
4
4.75
5.95
9
4.5
8
3.75
9.5
LG G4050
LG Glimmer
LG Incite
LG L1150
LG L1200
LG Lotus
LG LX150
LG LX160
LG LX350
LG LX400
LG LX5450
LG LX550 Fusic
LG LX5560
LG MM-535
LG Muziq 570
LG PM-225
LG PM-325
LG Rumor
LG Scoop AX260
LG Shine CU720
LG Trax CU575
LG V1-125
LG Venus VX8800
LG VI5225
LG Voyager VX10000
LG Vu CU920
LG VX3200
LG VX3400
LG VX3450
LG VX4500
LG VX4600
LG VX4700
LG VX5200
LG VX5300
LG VX5400
LG VX5500
4
3.16
6.35
4.8
5
3.43
4
3.75
3.75
4.53
3.5
4
2.25
4.75
4.3
4.25
2.5
3
3.75
4.6
3.68
3.3
4
3.26
3
3.8
3.16
3.5
3.75
3.6
3.5
3.75
4
4.5
3
5.18
4.95
Team # 5904
LG VX6100
LG VX7000
LG VX8000
LG VX8100
LG VX8300
LG VX8350
LG VX8600
LG VX8700
LG VX9800
LG Wave AX380
Motorola A630
Motorola A845
Motorola Active
W450
Motorola C139
Motorola C168i
Motorola C290
Motorola C650
Motorola E815
Motorola Hollywwod
Motorola i335
Motorola i425
Motorola i570
Motorola i860 Tattoo
Motorola i880
Motorola i885
Motorola ic502
Motorola ic902
Motorola Krave ZN4
Motorola Krzr K1
Motorola Krzr K1 (TMobile)
Motorola Krzr K1m
(Verizon)
Motorola Krzr K1m
(Sprint)
Motorola Ming
A1200
Motorola MPx220
Motorola i265
Motorola i315
Motorola i355
Page 29 of 43
3.75
4
4
3.5
3.5
4.25
3
4
5.5
3.6
3
4
8.18
11.5
8
2.6
6
4
4.5
4.5
3.03
6.13
3
5
3
3.3
5
6.1
9.25
6.25
4.25
3.5
8.5
4
3.5
4.75
5.5
Motorola i365
Motorola i530
Motorola i580
Motorola i670
Motorola i730
Motorola i736
Motorola i830
Motorola i836
Motorola i850
Motorola i860
Motorola i870
Motorola i930
Motorola Pebl
Motorola Q
Motorola Q (Amp'd
Mobile)
Motorola Q (Sprint)
Motorola Q Global
Motorola Q9c
(Sprint)
Motorola Q9c
(Verizon)
Motorola Q9h
Motorola Rapture
VU30
Motorola Razr
(Amp'd Mobile)
Motorola Razr Maxx
Ve
Motorola Razr VE20
Motorola Razr V3
Motorola Razr V3c
Motorola Razr V3i
Motorola Razr V3m
(Verizon)
Motorola Razr V3m
(Sprint)
Motorola Razr V3xx
Motorola Razr2 V8
(T-Mobile)
Motorola Razr2 V9
(AT&amp;T)
Motorola Razr2 V9m
(Alltel)
6.01
3
3
2.5
5.6
4
3
3
3.25
3.2
2.75
1.5
6.5
4
5.6
4.8
9
7.5
6
4
2.66
4
4.2
4.35
6.5
3.8
8.3
4
3.25
3.5
7.45
5
4.9
Motorola Razr2 V9m
(Sprint)
Motorola Razr2 V9m
(Verizon)
Motorola Razr2 V9x
V950
Motorola Rizr
Motorola Rizr Z6tv
Motorola Rizr Z8
Motorola Rokr E1
Motorola Rokr E8
Motorola Rokr Z6m
Motorola Slvr L2
Motorola Slvr L6
Motorola Slvr L7
Motorola Slvr L7c
(Sprint)
Motorola Slvr L7c
(Verizon)
Motorola Slvr L7e
Motorola U9
Motorola V180
Motorola V188
Motorola V195
Motorola V195s
Motorola V220
Motorola V265
Motorola V300
Motorola V325
Motorola V330
Motorola V360
Motorola V365
Motorola V400
Motorola V505
Motorola V557
Motorola V600
Motorola V710
Motorola V750
Motorola VU204
Motorola W315
5.08
5
3.13
4.56
6.5
5.62
6.5
9
10.6
3
3.83
5.5
6.5
8.5
4
5
6
7.5
9
5
4.25
8.3
5
3.5
5
4
5.5
4.75
3.3
2.75
6
5
6
3.5
4.56
5.38
4
Team # 5904
Motorola W385
Motorola W450
Motorola W490
Motorola W755
Motorola Z6c
Motorola Z9
Motorola ZN5
Nokia 1680
Nokia 2115i Shorty
Nokia 2366i
Nokia 2600
Nokia 2610
Nokia 2760
Nokia 3155i
Nokia 3200
Nokia 3205
Nokia 3220
Nokia 3300
Nokia 3555
Nokia 3620
Nokia 5140
Nokia 5300 Xpress
Music
Nokia 5310 Xpress
Music
Nokia 5610 Xpress
Music
Nokia 5700 Xpress
Music
Nokia 6030
Nokia 6061
Nokia 6061i
Nokia 6085
Nokia 6086
Nokia 6101
Nokia 6102
Nokia 6126
Nokia 6133
Nokia 6200
Nokia 6215i
Nokia 6225
Page 30 of 43
4.08
8.3
8.16
3.45
3.63
3.16
5.18
12.2
3
4.5
4.3
11.9
8
7.75
4.5
7
3
4.5
5
4.83
7
6
3
6.73
5.76
4
15
4
4
3
5
7.5
7.5
3.75
4
4.75
4
3
Nokia 6230
Nokia 6236i
Nokia 6255i
Nokia 6263
Nokia 6301
Nokia 6305i
Nokia 6315i
Nokia 6555
Nokia 6600
Nokia 6610
Nokia 6682
Nokia 6820
Nokia 7270
Nokia 7280
Nokia 7370
Nokia 7380
Nokia 7390
Nokia 7610
Nokia 8800
Nokia 9300
Nokia E61
Nokia E61
Nokia E62
Nokia E65
Nokia E70
Nokia E71
Nokia E90
Nokia Luna 8600
Nokia N73
Nokia N75
Nokia N76
Nokia N78
Nokia N80
Nokia N81
Nokia N91
Nokia N93
Nokia N95
Nokia N95 (8GB)
Nokia N95 (North
American edition)
Nokia Prism 7500
6
5
3.75
5
7.83
5.2
4
2
2.75
5
4
5
5.5
4.25
3.75
2
4
6
4
5.25
8
8
8
7
7.5
4
11.5
3.5
9.5
2
4.5
3
5
7
5.5
6.1
8
3.5
8.5
2
Palm Centro (AT&amp;T)
Palm Centro (Sprint)
Palm Centro
(Verizon)
Palm Treo 650
(Cingular)
Palm Treo 650
(Sprint)
Palm Treo 650
(Verizon)
Palm Treo 680
(AT&amp;T)
Palm Treo 700p
(Sprint)
Palm Treo 700p
(Verizon)
Palm Treo 700w
Palm Treo 700wx
Palm Treo 750
Palm Treo 755p
Palm Treo 800w
Palm Treo Pro
(unlocked)
RIM BalckBerry
7130e
RIM BalckBerry 7750
RIM BlackBerry
7100g
RIM BlackBerry 7100i
RIM BlackBerry 7100t
RIM BlackBerry 7130c
RIM BlackBerry 8700c
RIM BlackBerry
8700g
RIM BlackBerry
8703e
RIM BlackBerry 8800
RIM BlackBerry 8820
RIM BlackBerry 8820
(T-Mobile)
RIM BlackBerry 8830
(Verizon)
RIM BlackBerry 8830
(Sprint)
RIM BLackBerry Bold
5.5
4
4.5
4.5
5
5
5.2
5
5
5
5.8
3
4.2
4.5
5.5
4.5
4
4.5
5.25
4
4.5
5.6
7
5.2
7.5
7
7
4.3
4.5
7
Team # 5904
RIM BlackBerry Curve
8300 (AT&amp;T)
RIM BlackBerry Curve
8310 (AT&amp;T)
RIM BlackBerry Curve
8320 (T-Mobile)
RIM BLackBerry
Curve 8330 (US
Cellular)
RIM BlackBerry Curve
8330 (Sprint)
RIM BlackBerry Curve
8330 (Verizon)
RIM BlackBerry Pearl
(T-Mobile)
Rim BlackBerry Pearl
Flip 8820
RIM BlackBerry Pearl
8120 (AT&amp;T)
RIM BlackBerry Pearl
8120 (T-Mobile)
RIM BlackBerry Pearl
8130 (Verizon)
RIM BlackBerry Storm
(Verizon Wireless)
Samsung (Helio) Drift
Samsung (Helio) Fin
Samsung (Helio) Heat
Samsung (Helio)
Mysto
Samsung Access SGHA827
Samsung Armani
Samsung Behold
Samsung Delve SCHr800 (Alltel)
Samsung DM-S110
Samsung Epix
Samsung Eternity
Samsung FlipShot
SCH-U900
Samsung Gleam SCHU700
Samsung Glyde SCHU940
Page 31 of 43
8.5
5
5.5
5.25
5
5
5.8
7
5.5
6.5
5
7
3
3.6
3.3
4.56
4.03
9.03
4.62
4.02
3.3
4
14.3
4.42
3.3
4.83
Samsung Gravity
Samsung Highnote
SPH-M630
Samsung Hue SCHR500
Samsung Innov8
SGH-i8510
Samsung Instinct
Samsung IP-830w
Samsung Juke SCHU470
Samsung Katalyst
Samsung Knack SCHU310
Samsung MM-A700
Samsung MM-A800
Samsung MM-A880
Samsung MM-A900
Samsung MM-A920
Samsung MM-A940
Samsung Muse SCHU706
Samsung MyShot
SCH-R430
Samsung Omnia
(8GB, unlocked)
Samsung Omnia
(Verizon Wireless)
Samsung PM-A740
Samsung PM-A840
Samsung Porpel
Samsung RL-A760
Samsung Rant SPHM540
Samsung Renown
Samsung Rugby SGHA837
Samsung Saga
Samsung SCH-A610
Samsung SCH-A670
Samsung SCH-A790
Samsung SCH-A870
Samsung SCH-A890
Samsung SCH-A930
8.2
4.83
3.2
8.25
6
2.5
4.16
5.16
4.61
3.75
5
4
2.75
3.5
4.75
4.26
2.75
15
8
3
3.25
3.12
3.6
6.03
4.7
5.25
6.5
4.5
5
4.5
3
4.5
4.5
Samsung SCH-A950
Samsung SCH-A970
Samsung SCH-A990
Samsung SCH-i730
Samsung SCH-i760
Samsung SCH-i830
Samsung SCH-N330
Samsung SCH-R510
Samsung SCH-U340
Samsung SCH-U410
Samsung SCH-U410
Samsung SCH-U420
Samsung SCH-U430
Samsung SCH-U520
Samsung SCH-U540
Samsung SCH-U550
Samsung SCH-U600
Samsung SCH-U620
Samsung SCH-U740
Samsung SGH-A117
Samsung SGH-A127
Samsung SGH-A227
Samsung SGH-A237
Samsung SGH-A437
Samsung SGH-A517
Samsung SGH-A637
Samsung SGH-A717
Samsung SGH-A727
Samsung SGH-A737
Samsung SGH-A777
Samsung SGH-C417
Samsung SGH-D307
Samsung SGH-D357
Samsung SGH-D407
Samsung SGH-D415
Samsung SGH-D807
Samsung SGH-D900
Samsung SGH-E105
Samsung SGH-E316
Samsung SGH-E335
4.5
3.5
4
3.5
4
2.5
4
2.8
4.2
4.6
4.6
4.2
4.21
2
4.3
3.95
4.63
2.8
4.3
7.6
5.25
10.9
10.1
8
10.4
2
2.65
4
4
3.35
3.26
10.5
4.5
5
4
4.5
4
7
2.25
6
6
Team # 5904
Samsung SGH-E635
Samsung SGH-E715
Samsung SGH-G800
Samsung SGH-i450
Samsung SGH-i718
Samsung SGH-P107
Samsung SGH-P207
Samsung SGH-P300
Samsung SGH-P735
Samsung SGH-P777
Samsung SGH-T109
Samsung SGH-T209
Samsung SGH-T219
Samsung SGH-T229
Samsung SGH-T309
Samsung SGH-T329
Samsung SGH-T339
Samsung SGH-T409
Samsung SGH-T429
Samsung SGH-T439
Samsung SGH-T509
Samsung SGH-T519
Samsung SGH-T539
Samsung SGH-T609
Samsung SGH-T619
Samsung SGH-T629
Samsung SGH-T639
Samsung SGH-T719
Samsung SGH-T729
Samsung SGH-T809
Samsung SGH-T819
Samsung SGH-x475
Samsung SGH-x495
Samsung SGH-X497
Samsung SGH-X507
Samsung SGH-X820
Samsung SGH-ZX10
Samsung SGH-ZX20
Samsung Slash
Samsung SLM SGHA747
Page 32 of 43
6
5.6
7.75
6.7
8.3
4.5
4.75
3
5
5
3.65
4.5
5
7.9
4.25
4.25
5.18
5.18
8
6.5
4.5
6.2
6.5
3
4.2
4
5.36
5
3.88
3.5
4.92
6
4
6.5
5
5
5
4
6.3
4.82
Samsung Soul SGHU900
Samsung Spex SCHR210
Samsung SPH-A420
Samsung SPH-A560
Samsung SPH-A580
Samsung SPH-A640
Samsung SPH-M220
Samsung SPH-M300
Samsung SPH-M320
Samsung SPH-M500
Samsung SPH-M510
Samsung SPH-M520
Samsung SPH-M610
Samsung Sync SGHA707
Samsung Sway SCHU650
Samsung Upstage
SPH-M620
Samsung VI660
Samsung VI-A820
Samsung VM-A680
Samsung Z400
Sanyo RL4920
Sanyo 6600 Katana
Sanyo Katana DLX
8500
Sanyo Katana Eclipse
Sanyo Katana II 6650
Sanyo Katana LX
Sanyo M1
Sanyo MM-5600
Sanyo MM-7400
Sanyo MM-7500
Sanyo MM-8300
Sanyo MM-9000
Sanyo PM-8920
Sanyo Pro-200
Sanyo Pro-700
Sanyo RL2500
9.12
4.96
3.5
3
3
4
4.03
3.3
4.75
3.6
3.3
3.16
3.6
4
5.25
3
3.5
3
3.25
4.93
4
4
5
5.16
4.5
5.26
4.3
3.5
3.6
3.6
2.25
3.5
3.25
5.32
5.38
3.1
Sanyo RL4930
Sanyo RL7300
Sanyo S1
Sanyo SCP-200
Sanyo SCP-2400
Sanyo SCP-3100
Sanyo SCP-7000
Sanyo SCP-7050
Sanyo SCP-8400
Sanyo VI-2300
Sanyo VM4500
Sony Ericsson C902
Sony Ericsson J300a
Sony Ericsson K700i
Sony Ericsson K750i
Sony Ericsson K790a
Sony Ericsson K800i
Sony Ericsson K850i
Sony Ericsson P1i
Sony Ericsson P900
Sony Ericsson P910
Sony Ericsson P990i
Sony Ericsson S500i
Sony Ericsson S710a
Sony Ericsson T637
Sony Ericsson TM506
Sony Ericsson W200a
Sony Ericsson W300i
Sony Ericsson W350a
Sony Ericsson W380a
Sony Ericsson W580i
Sony Ericsson W600i
Sony Ericsson W710i
Sony Ericsson W760i
Sony Ericsson W800i
Sony Ericsson W810i
Sony Ericsson W850i
Sony Ericsson W880i
Sony Ericsson W980
Sony Ericsson Xperia
X1
5
3.75
3
3.3
3.5
3
3.6
4.5
4
3.25
3.3
5.91
8
4.5
5.5
6.6
6.75
8.83
9.5
10.6
9
8.5
6.75
5
3.75
7.38
8.25
8
11.7
8
8.95
8.25
10
9
7.08
7.5
6.5
11.5
7.8
8.66
9
Team # 5904
Sony Ericsson Z310a
Sony Ericsson Z500a
Sony Ericsson Z520a
Sony Ericsson Z525a
Sony Ericsson Z555i
Sony Ericsson Z600
Sony Ericsson Z710i
Sony Ericsson Z750a
Apple iPhone 3G
(with 3G on)
Apple iPhone 3G
(with 3G off)
Apple iPhone Classic
Asus P527
Bang &amp; Olufsen
Serene
Casio G'zOne Boulder
Casio G'zOne Type-S
Casio G'zOne Type-V
Curitel Identity
Enfora TicTalk
HP iPaq
HP iPaq 910c
HTC (AT&amp;T )Tilt
HTC (Cingular) 2125
HTC (Cingular) 3125
HTC (Cingular) 8125
HTC (Cingular) 8525
HTC (T-Mobile) Dash
HTC (T-Mobile) MDA
HTC (T-Mobile) SDA
HTC (T-Mobile)
HTC (T-Mobile) Wing
HTC (Verizon)
XV6900
HTC Athena
HTC Mogul
HTC SMT5800
HTC Touch
Page 33 of 43
8.5
6
8
5
10.1
8
7
8
7.5
4.95
8.75
7.3
8.5
3
4.16
3.3
3.3
3
8
7
3.5
3.5
11
8
10.6
8
11
12.5
11
8
9
4
6
6.5
4
6
HTC Touch (Sprint)
HTC Touch Diamond
(Sprint)
HTC Touch Dual
HTC Touch Pro
(Sprint)
HTC Vox S710
i-mate Jaq
i-mate Jaq3
NEC 232E
NEC 525 HDM
NEC 535 HDM
NEC L1
Neonode N2
Pantech (Helio) Hero
Pantech (Helio)
Ocean
Pantech Breeze
Pantech C120
Pantech C150
Pantech C300
Pantech C610
Pantech DM-P100
Pantech DM-P205
Pantech Duo C810
Pantech Matrix
Pantech PN-210
Pantech PN-300
Pantech PN-820
Pharos GPS Phone
600e
Sharp TM150
Siemens C61
Siemens CF62T
Siemens CT66
Siemens S66
Siemens SX1
Sierra Vog
Sonim XP1
T-Mobile G1
T-Mobile Sidekick
4.5
4.5
3.2
4.25
11
8
4.5
4.5
5
2.8
2
6.83
2.8
5.2
11.0
8
3
3.6
5.5
3.38
3.3
3.3
4.92
3.3
3.5
2
4.5
5
2.5
7.25
5.5
4.3
3
4
3.75
7.46
4
7
T-Mobile Sidekick ID
T-Mobile Sidekick II
T-Mobile Sidekick III
Velocity 103
VK Mobile (Helio)
Kickflip
VK2020
Wherfy Wherifone
ZTE C88
ZTE C79
8
5
4.5
3
3.1
5.25
4
3.03
4.05
Team # 5904
Page 34 of 43
Appendix C – Landline Telephone Usage in Barrels of Oil per Day
Year
U.S. Household
Projections
Percentage of
Households with
Landline Telephones
Number of
Households with
Landline Phones
Total Energy Used by Landline
Phones (Barrels of Oil per Day)
U.S. Bureau of the
Census
Centers for Disease
Control
Calculated
Calculated
1990
91,966,534
100.00
91,966,534
13,611
1991
93,097,766
100.00
93,097,766
13,779
1992
94,228,997
100.00
94,228,997
13,946
1993
95,360,228
100.00
95,360,228
14,114
1994
96,491,460
100.00
96,491,460
14,281
1995
97,722,883
100.00
97,722,883
14,463
1996
98,856,603
100.00
98,856,603
14,631
1997
99,965,175
100.00
99,965,175
14,795
1998
101,042,864
100.00
101,042,864
14,955
1999
102,118,600
100.00
102,118,600
15,114
2000
103,245,963
100.00
103,245,963
15,281
2001
104,344,445
100.00
104,344,445
15,443
2002
105,456,124
97.49
102,812,188
15,217
2003
106,566,127
94.41
100,613,648
14,891
2004
107,672,899
91.20
98,197,684
14,534
2005
108,818,659
88.80
96,630,969
14,302
2006
109,981,970
84.10
92,494,837
13,690
2007
111,162,259
81.90
91,041,890
13,475
2008
112,362,848
79.02
88,790,728
13,141
2009
113,567,967
75.94
86,246,759
12,765
2010
114,825,428
72.86
83,666,728
12,383
2011
115,722,392
69.79
80,757,698
11,952
2012
116,853,623
66.71
77,949,714
11,537
2013
117,984,855
63.63
75,072,078
11,111
2014
119,116,086
60.55
72,124,790
10,675
2015
120,247,317
57.47
69,107,851
10,228
2016
121,378,549
54.39
66,021,261
9,771
2017
122,509,780
51.31
62,865,019
9,304
2018
123,641,011
48.24
59,639,125
8,827
2019
124,772,243
45.16
56,343,580
8,339
2020
125,903,474
42.08
52,978,383
7,841
2021
127,034,705
39.00
49,543,535
7,333
2022
128,165,937
35.92
46,039,035
6,814
2023
129,297,168
32.84
42,464,884
6,285
2024
130,428,399
29.76
38,821,081
5,746
Team # 5904
Page 35 of 43
2025
131,559,631
26.69
35,107,627
5,196
2026
132,690,862
23.61
31,324,521
4,636
2027
133,822,093
20.53
27,471,764
4,066
2028
134,953,325
17.45
23,549,355
3,485
2029
136,084,556
14.37
19,557,295
2,895
2030
137,215,787
11.29
15,495,583
2,293
2031
138,347,019
8.21
11,364,219
1,682
2032
139,478,250
5.14
7,163,204
1,060
2033
140,609,481
2.06
2,892,538
428
2034
141,740,713
0.00
0
0
Note on “U.S. Households Projections”: The U.S. Bureau of the Census published figures of their
projections for the number of households in the United States between 1995 and 2010 (As indicated by
the boxed in region of the above chart). After determining that the data follows a linear model, we used
a linear regression to extrapolate the data beyond the date ranges presented by the U.S. Bureau of the
Census.
Note on “Percentage of Households with Landline Phones”: The Centers for Disease Control published
figures of their findings of the percentage of households with landline phones in bi-annual increments.
After determining that the data followed a linear model, we used a linear regression on their bi-annual
figures to obtain the annual figures used in our report. In order to compare the bi-annual data to other
annual data, we included only the data collected for the second half of the listed year.
Note on “Number of Households with Landline Phones”: The figures in this data set are derived by
multiplying the number of U.S. households by the percentage of households with landline phones.
Note on “Total Energy Used by Landline Phones (Barrels of Oil per Day)”: The figures in this data set are
derived by the method described in Requirement 1 using the data from Table 1.3 and Table 1.4 and
using the conversion rates found in Bio-energy Conversion Factors.
Team # 5904
Page 36 of 43
Appendix D – Cellular Telephone Usage in Barrels of Oil per Day
Number of Cell Phone
Subscriptions
(Millions)
Percent of
Population with
Cell Phones
Total Number
of People with
Cell Phones
Total Energy Used by
Cell Phones (Barrels of
Oil per Day)
Census
Wireless Matrix
Report
Calculated
Calculated
Caclulated
1990
247,459,004
0.0
0
1991
250,622,084
0.0
0
1992
253,785,164
0.0
0
1993
256,948,244
0.0
0
1994
260,111,324
0.0
0
0
0
1995
263,274,404
3.8
1.303997219
343,309,091
127
1996
266,437,484
24.3
8.192745666
2,182,854,545
806
1997
Year
U.S. Population
Projections
U.S. Bureau of the
269,600,565
44.7
14.91985006
4,022,400,000
1,485
1998
272,763,645
69.2
22.83295491
6,228,000,000
2,300
1999
275,926,725
86.0
28.0509255
7,740,000,000
2,858
2000
282,158,336
109.5
34.92719776
9,855,000,000
3,639
2001
284,915,024
128.4
40.55946169
11,556,000,000
4,267
2002
287,501,476
141.0
44.13890383
12,690,000,000
4,686
2003
289,985,771
159.0
49.34724883
14,310,000,000
5,284
2004
292,805,643
182.0
55.94154482
16,380,000,000
6,049
2005
295,583,436
208.0
63.33237157
18,720,000,000
6,913
2006
298,442,420
233.0
70.26481021
20,970,000,000
7,744
2007
301,279,593
255.0
76.17508963
22,950,000,000
8,475
2008
304,228,257
269.5
79.73421088
24,257,400,000
8,958
2009
307,212,123
290.0
84.94764204
26,096,945,455
9,637
2010
310,232,863
310.4
90.05006961
27,936,490,909
10,316
2011
313,232,044
330.8
95.06063295
29,776,036,364
10,996
2012
316,265,537
351.3
99.96530801
31,615,581,818
11,675
2013
319,330,342
371.7
100
31,933,034,200
11,792
2014
322,422,965
100
32242296500
11,906
2015
325,539,790
100
32553979000
12,021
2016
328,677,531
100
32867753100
12,137
2017
331,833,494
100
33183349400
12,254
2018
335,005,223
100
33500522300
12,371
2019
338,190,395
100
33819039500
12,489
2020
341,386,665
100
34138666500
12,607
2021
344,591,727
100
34459172700
12,725
2022
347,803,053
100
34780305300
12,844
2023
351,018,246
100
35101824600
12,962
Team # 5904
Page 37 of 43
2024
354,235,045
100
35423504500
13,081
2025
357,451,620
100
35745162000
13,200
2026
360,666,783
100
36066678300
13,319
2027
363,879,699
100
36387969900
13,437
2028
367,090,055
100
36709005500
13,556
2029
370,297,901
100
37029790100
13,674
2030
373,503,674
100
37350367400
13,793
2031
376,708,065
100
37670806500
13,911
2032
379,912,056
100
37991205600
14,029
2033
383,116,539
100
38311653900
14,148
2034
386,322,606
100
38632260600
14,266
Note on “U.S. Population Projections”: The U.S. Bureau of the Census published figures of their
projections for the population in the United States between 2000 and 2050 (As indicated by the boxed in
region of the above chart). After determining that the data follows a linear model, we used a linear
regression to extrapolate the data beyond the date ranges presented by the U.S. Bureau of the Census.
Note on “Number of Cell Phone Subscriptions”: The Global Wireless Matrix 4Q07 Report published by
Merrill Lynch gives the total number of cell phone subscriptions for the U.S. between 1998 and 2007 (As
indicated by the boxed in region of the above chart). After determining that the data follows a linear
model, we used a linear regression to extrapolation the date beyond the date ranges presented by The
Global Wireless Matrix 4Q07 Report.
Note on “Percentage of Population with Cell Phones”: These figures were calculated by taking 90% of
the number of subscriptions (taking of 10% because of our assumed number of people with multiple cell
phones) and dividing by the number of people within the population.
Note on “Total Number of People with Cell Phones”: These figures were calculated by taking the
percentage of population with cell phones and multiplying the by the forecasted population of the
United States.
Note on “Total Energy Used by Cell Phones (Barrels of Oil per Day)”: The figures in this data set are
derived by the method described in Requirement 1 using the data from Table 1.5 and using the
conversion rates found in Bio-energy Conversion Factors.
Team # 5904
Page 38 of 43
Appendix E: Household Phantom energy consumption
Year
HouseHolds
GWh per HouseHold
1990
91,966,534
200.5679754
Barrels of Oil
Consumed per Day
117981.162
1991
93,097,766
203.0350552
119432.3854
1992
94,228,997
205.5021349
120883.6088
1993
95,360,228
207.9692147
122334.8322
1994
96,491,460
210.4362945
123786.0556
1995
97,722,883
213.1218811
125365.8124
1996
98,856,603
215.5943884
126820.2284
1997
99,965,175
218.0120509
128242.3829
1998
101,042,864
220.3623612
129624.9184
1999
102,118,600
222.7084124
131004.9485
2000
103,245,963
225.1670558
132451.2093
2001
104,344,445
227.5627132
133860.4195
2002
105,456,124
229.9871517
135286.5598
2003
106,566,127
232.4079351
136710.55
2004
107,672,899
234.821672
138130.3953
2005
108,818,659
237.320437
139600.2571
2006
109,981,970
239.8574787
141092.6345
2007
111,162,259
242.4315474
142606.7926
2008
112,362,848
245.0498879
144146.9929
2009
113,567,967
247.6781079
145693.0046
2010
114,825,428
250.4204794
147306.1644
2011
115,722,392
252.3766505
148456.8533
2012
116,853,623
254.8437303
149908.0767
2013
117,984,855
257.3108101
151359.3
Team # 5904
Page 39 of 43
2014
119,116,086
259.7778898
152810.5234
2015
120,247,317
262.2449696
154261.7468
2016
121,378,549
264.7120494
155712.9702
2017
122,509,780
267.1791292
157164.1936
2018
123,641,011
269.6462089
158615.417
2019
124,772,243
272.1132887
160066.6404
2020
125,903,474
274.5803685
161517.8638
2021
127,034,705
277.0474482
162969.0872
2022
128,165,937
279.514528
164420.3106
2023
129,297,168
281.9816078
165871.534
2024
130,428,399
284.4486875
167322.7574
2025
131,559,631
286.9157673
168773.9808
2026
132,690,862
289.3828471
170225.2042
2027
133,822,093
291.8499268
171676.4276
2028
134,953,325
294.3170066
173127.6509
2029
136,084,556
296.7840864
174578.8743
2030
137,215,787
299.2511661
176030.0977
2031
138,347,019
301.7182459
177481.3211
2032
139,478,250
304.1853257
178932.5445
2033
140,609,481
306.6524055
180383.7679
2034
141,740,713
309.1194852
181834.9913
2035
142,871,944
311.586565
183286.2147
2036
144,003,175
314.0536448
184737.4381
2037
145,134,407
316.5207245
186188.6615
2038
146,265,638
318.9878043
187639.8849
2039
147,396,869
321.4548841
189091.1083
2040
148,528,101
323.9219638
190542.3317
2041
149,659,332
326.3890436
191993.5551
2042
150,790,563
328.8561234
193444.7785
2043
151,921,794
331.3232031
194896.0018
Team # 5904
Page 40 of 43
2044
153,053,026
333.7902829
196347.2252
2045
154,184,257
336.2573627
197798.4486
2046
155,315,488
338.7244424
199249.672
2047
156,446,720
341.1915222
200700.8954
2048
157,577,951
343.658602
202152.1188
2049
158,709,182
346.1256818
203603.3422
2050
159,840,414
348.5927615
205054.5656
2051
160,971,645
351.0598413
206505.789
2052
162,102,876
353.5269211
207957.0124
2053
163,234,108
355.9940008
209408.2358
2054
164,365,339
358.4610806
210859.4592
2055
165,496,570
360.9281604
212310.6826
2056
166,627,802
363.3952401
213761.906
2057
167,759,033
365.8623199
215213.1294
2058
168,890,264
368.3293997
216664.3527
2059
170,021,496
370.7964794
218115.5761
2060
171,152,727
373.2635592
219566.7995
2061
172,283,958
375.730639
221018.0229
2062
173,415,190
378.1977187
222469.2463
2063
174,546,421
380.6647985
223920.4697
2064
175,677,652
383.1318783
225371.6931
2065
176,808,884
385.5989581
226822.9165
2066
177,940,115
388.0660378
228274.1399
2067
179,071,346
390.5331176
229725.3633
2068
180,202,578
393.0001974
231176.5867
2069
181,333,809
395.4672771
232627.8101
2070
182,465,040
397.9343569
234079.0335
Team # 5904
Page 41 of 43
Appendix F: Calculating projections of % of households with landlines:
Estimates the time period in which cell phones will become the sole means of communication.
Year:
2004
2005
2006
2007
Total
# Years from
2004
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
14
% of Households with
wireless only
5.0
6.1
7.3
8.4
10.5
12.8
13.6
15.8
79.5
% of Households with Landlines
92.7
91.2
90.0
88.8
86.8
84.1
84.4
81.9
699.9
X = # of years from 2004 (data measured bi-annually)
Y1 = % of Households with wireless only
Y2 = % of Households with Landlines
Simple Linear Regression Model (Least Squares Estimate): 𝑌𝑖 = 𝛽0 + 𝛽1 𝑋𝑖 + 𝜀𝑖
We will assume that the errors of this models are normally distributed with mean 0.
Thus our model will become: 𝑌̂𝑖 = 𝛽̂0 + 𝛽̂1 𝑋𝑖 where
𝛽̂1 =
𝑛
𝑛
𝑛 ∑𝑛
𝑖=1 𝑋𝑖 𝑌𝑖 −∑𝑖=1 𝑋𝑖 ∑𝑖=1 𝑌𝑖
𝑛
2
𝑛 ∑𝑛
𝑖=1 𝑋𝑖 −(∑𝑖=1 𝑋𝑖 )
𝛽̂0 =
2
𝑛
∑𝑛
𝑖=1 𝑌𝑖 −𝛽1 ∑𝑖=1 𝑋𝑖
𝑛
̂ 𝑖:
Calculations for 𝑌1
∑𝑛𝑖=1 𝑋𝑖 = 14, ∑𝑛𝑖=1 𝑌1𝑖 = 79.5, ∑𝑛𝑖=1 𝑋𝑖2 = 35, ∑𝑛𝑖=1 𝑋𝑖 𝑌1𝑖 = 172.05
𝛽̂1 =
8∗(172.05)− 14∗(79.5)
8∗(35)−(14)2
= 3.136,
̂ 𝑖 = 4.450 + 3.136𝑋𝑖
Thus: 𝑌1
𝛽̂0 =
79.5−3.136(14)
8
= 4.450
Team # 5904
Page 42 of 43
We can use this linear approximation to calculate the time for Households to become
completely wireless (0% Landlines).
100 = 4.450 + 3.136𝑋𝑖 , solving for X yields: X= 30.47 Years.
We can predict that at the year 2034 (2004 + 30.47), Households will have become 100%
wireless. To check this approximation, we will also use a linear regression model to extend the
data trend on percentage of households with landlines. We would like to see this data trend
correlate with the percentage of wireless only households, and approximate the same year.
̂ 𝑖 : (Using the same simple linear model 𝑌̂𝑖 = 𝛽̂0 + 𝛽̂1 𝑋𝑖 )
Calculations for 𝑌2
∑𝑛𝑖=1 𝑋𝑖 = 14, ∑𝑛𝑖=1 𝑌2𝑖 = 699.9, ∑𝑛𝑖=1 𝑋𝑖2 = 35, ∑𝑛𝑖=1 𝑋𝑖 𝑌2𝑖 = 1191.3
𝛽̂1 =
8∗(1191.3)− 14∗(699.9)
8∗(35)−(14)2
= −3.193,
𝛽̂0 =
699.9+3.193∗(14)
8
= 93.075
̂ 𝑖 = 93.075 − 3.193𝑋𝑖
Thus: 𝑌2
Now we can use this model to check our calculation that households will become completely
wireless in 2034.
0 = 93.075 – 3.193X, solving for X yields: X= 29.150 years.
Therefore, both calculations have shown that households will have completely made this shift
from landline phones to wireless by the year 2034. Thus it is most likely that the US will spend
another 25 years transitioning from a combination of landline and wireless phones to just
relying on wireless phones. After 2034, the US will be in a steady state in which, assuming no
new technological breakthroughs, its sole means of telephone communications will be wireless
devices.
Graphical representation of changing trends from landline telephones to wireless cell phones.
Team # 5904
Page 43 of 43
100
90
80
70
60
50
Total Landline - Households
40
Wireless Only - Households
30
20
10
2036
2034
2032
2030
2028
2026
2024
2022
2020
2018
2016
2014
2012
2010
2008
2006
2004
0
```