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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 Table of Contents 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 consume a phantom load for 16 hours of each day. -find phantom energy data on cell phone chargers. Phantom load: 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 -Ep = phantom load 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 steady state of this change. 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 Cordless w/ Answering 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 Cordless w/ Answering 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"Charging 2 Lithium-ion batteries" by Battery University "Energy use of set-top boxes and telephony products in the U.S." 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 Cordless with Answering 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 Cordless Phones with Answering Machine 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" by Battery University 10 “Standby Power Summary Table" 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 × 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" 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 or about 64.6 MWh. 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 Negligible Phantom Load 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 Negligible Phantom Load 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 additional 5 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 × Average Watt Per HouseHold Number of Barrels of Oil Used per Day at Time 𝑡 (years) 1W ⏟ 1000kW Conversion from W to kW × 24 ⏟ × Conversion from kW to kWh (devices are on 24 hours) 1 ⏟ 1700 Conversion from kWh to Barrels of Oil × 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 <http://www.cnet.com/1770-5_1-0.html?>. 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 <http://www.census.gov/Press-Release/>. "Bioenergy Conversion Factors." Bioenergy Feedstock Information Network (BFIN) Administration Site. 06 Feb. 2009 <http://bioenergy.ornl.gov/papers/misc/energy_conv.html>. Blumberg, Ph.D, Stephen J., and Julian V. Luke. "N C H S - N H I S - Wireless Substitution Tables, July-December 2007 (Released 5/2008)." Centers for Disease Control and Prevention. Dec. 2007. National Center for Health Statistics. 06 Feb. 2009 <http://www.cdc.gov/nchs/data/nhis/earlyrelease/wireless200805_tables.htm>. Buckmann, Isiodor. "Charging Lithium-ion batteries." Welcome to Battery University. Mar. 2006. 08 Feb. 2009 <http://www.batteryuniversity.com/>. "Cell Phone Battery Guide | Cellular Battery Guide - Cellphone Battery Warehouse." Cell Phone Battery Warehouse - Cell Phone Battery | Cell Phone Batteries | Cellular Battery | Cellular Batteries. 07 Feb. 2009 <http://www.batteries4less.com/contents/Battery_Guide/?module=static&section=Batt ery_Guide>. Edwards, Tom. Nation's Housing Stock Reaches 128 Million. Rep. no. CB08-151. 6 Oct. 2008. U.S Census Bureau News. 5 Feb. 2009 <http://www.census.gov/Press-Release/>. "EIA - Petroleum Basic Data." Energy Information Administration - EIA - Official Energy Statistics from the U.S. Government. 2007. US Government- Federal Statistics. 08 Feb. 2009 <http://www.eia.doe.gov/basics/quickoil.html>. "Global Wireless Matrix 4Q07." Scribd. 21 Apr. 2003. Merrill Lynch. 07 Feb. 2009 <http://www.scribd.com/doc/7656611/Global-Wireless-Matrix-4Q07>. "Phantom Loads Steal Energy." Alternative Technology and Renewable Energy at Home. 07 Feb. 2009 <http://www.alternativetechnology.info/phantom.htm>. "Population Projections - 2008 National Population Projections: Summary Tables." Census Bureau Home Page. 13 Aug. 2008. 05 Feb. 2009 <http://www.census.gov/population/www/projections/summarytables.html>. Rainie, Lee, and Scott Keeter. "Cell Phone Use." Pew Internet & American Life Project. Apr. 2006. Associated Press. 07 Feb. 2009 <http://www.pewinternet.org/pdfs/PIP_Cell_phone_study.pdf>. Team # 5904 Page 26 of 43 "Standby Power Summary Table." Standby Power. 2009. Lawrence Berkeley National Laboratory. 07 Feb. 2009 <http://standby.lbl.gov/summary-table.html>. "Statistical Trends in Telephony." Federal Communications Commission (FCC) Home Page. 08 Dec. 2008. 05 Feb. 2009 <http://www.fcc.gov/wcb/iatd/trends.html>. 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 Kyocera Adreno 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 Prada 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&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 Motorola Renegade 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&T) Palm Centro (Sprint) Palm Centro (Verizon) Palm Treo 650 (Cingular) Palm Treo 650 (Sprint) Palm Treo 650 (Verizon) Palm Treo 680 (AT&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&T) RIM BlackBerry Curve 8310 (AT&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&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 & 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 Business Messenger HTC (AT&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) Shadow HTC (T-Mobile) Wing HTC (Verizon) XV6900 HTC Athena Advantage X7501 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