International Baccalaureate Extended Essay

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Extended Essay

INTERNATIONAL BACCALAUREATE DIPLOMA PROGRAM

[CORE]

The Adverse Effects of Electromagnetic Radiation from

Cellular Phones on the Human Brain

Candidate Name Rukmal Weerawarana

Candidate Session Number 001426-005

Candidate Code dwd913

Examination Session MAY 2013

Pages 48

Word Count 3797

Date 01/28/13



Rukmal Weerawarana 001426-005|dwd913 IBDP

IB [CORE] EE 01/28/13 1

ABSTRACT

This essay investigates the question “Could electromagnetic radiation from cellular phoneshave adverse effects on the human brain?” To further study this question, it was analyzed in the

form of three separately approached hypotheses; “radiation from mobile phone use has an adverse

effect on the human brain”, “the extent of radiation damage varies inversely with the age of the

user” and “the general population is safe from the damaging effects of radiation from cellular

phones.”

The investigation was approached both experimentally and empirically, with all data used

gathered first hand. However, a wide range of external source material from government

organizations such as the Federal Communications Commission (FCC) of the United States and theTelecommunications Regulatory Commission (TRC) of Sri Lanka. Apparatus from the TRC was

used to measure the Specific Absorption Rate caused by different cellular phones in a indirect

manner, as the apparatus used was designed to measure power intensity from mobile base stations.

Additionally, a survey was conducted within the British School to address the third hypothesis.

This dissertation is structured in the form of a formal report, with a brief introduction to the

theory behind the adverse effects on the human brain, and it ends by validating the hypotheses.

However, due to the manner in which the data was collected, there is a high possibility that it could

have been false. Extensive measures were taken to prevent this, and all data was validated andrectified in the best possible manner.

Using the data, it was evident that all of the hypotheses were true and that extended

exposure to cellular phones does indeed have adverse effects on the human brain. These adverse

effects are inversely proportional to the age of the user of the phone, and the general population is

safe from these effects.

Word Count – 297




IB [CORE] EE 01/28/13 2

ACKNOWLEDGEMENTS

First and foremost, I would like to thank my Extended Essay Supervisor, Mr. Aravinthan

Suseendirarajah for his undying support and encouragement to write this essay. I would not have

been able to complete this dissertation without his guidance. I would also like to sincerely thank

Mr. Sampath Munasinghe, Senior Technician at the Telecommunications Regulatory Commission

for his guidance and support at the TRC. Furthermore, I would also like to extend my gratitude to

Professor Dileeka Dias, of the Faculty of Engineering at the University of Moratuwa for her constant

assistance with my essay, by giving me access to the TRC’s amazing resources. Lastly, I would also

like to sincerely thank my parents for allowing me to conduct this research, and for keeping up with

my hectic schedule. I would not have been able to complete this essay without them.




IB [CORE] EE 01/28/13 3

Table of Contents

1. Introduction ................................................................................................................... 5

The Issue ............................................................................................................................................................. 5

Research Question ............................................................................................................................................. 6

Hypotheses ......................................................................................................................................................... 6

1. Radiation from mobile phone use has an adverse effect on the human brain ............................................ 6

2. The extent of radiation damage varies with inversely with the age of the user ........................................ 6

3. The general population is safe from the damaging effects of radiation from cellular phones ...................... 6

2. Methodology and Concepts ....................................................................................... 7 Outline ................................................................................................................................................................. 7

GSM Radio Transmission Technology ........................................................................................................... 7

GSM Bands in Sri Lanka ................................................................................................................................. 7

Measurement and Regulation .......................................................................................................................... 8

Specific Absorption Rate (SAR) ....................................................................................................................... 8

Effects of Electromagnetic Radiation Exposure ............................................................................................ 8

3. Experiment Conception ............................................................................................... 9

Narda® NBM-550 Broadband Field Meter .................................................................................................... 9

Modification of the SAR Equation .................................................................................................................. 9

Variables ............................................................................................................................................................ 11

Procedure .......................................................................................................................................................... 12

Observations ..................................................................................................................................................... 13

Qualitative Observations ............................................................................................................................... 13

Quantitative Observations ............................................................................................................................. 13

Changes Made Due to Observations ............................................................................................................ 13

4. Data Computation ...................................................................................................... 14

Outline ............................................................................................................................................................... 14 Processed SAR Values ..................................................................................................................................... 14

Adult Skull ..................................................................................................................................................... 14

Infant Skull ..................................................................................................................................................... 15

Processed Survey Data .................................................................................................................................... 17

5. Data Processing .......................................................................................................... 18

Overview ........................................................................................................................................................... 18

Hypothesis 1 and 2 ......................................................................................................................................... 18

Hypothesis 3 ................................................................................................................................................... 18 Explicit Data Processing ................................................................................................................................. 19




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Adults ............................................................................................................................................................. 19

Infants ............................................................................................................................................................. 20

Phone Brand Survey Data Processing .......................................................................................................... 21

6. Analysis ........................................................................................................................ 23

Hypothesis 1 - Radiation from mobile phone use has an adverse effect on the human brain ............. 23

Hypothesis 2 – The extent of radiation damage varies with inversely with the age of the user ......... 24

Hypothesis 3 – The general population is safe from the damaging effects of radiation from cellular

phones ............................................................................................................................................................... 25

7. Conclusion and Evaluation ....................................................................................... 26

8. Bibliography ................................................................................................................ 27

Appendix A – Index of Cellular Phones Used in Study .................................................. 31

Phone 1 – Apple® iPhone 4 ............................................................................................................................ 31 Phone 2 – Apple® iPhone 5 ............................................................................................................................ 31

Phone 3 – RIM® Blackberry Bold 9790 ......................................................................................................... 32

Phone 4 – Sony® XPERIA sola ....................................................................................................................... 32

Phone 5 – Sony Ericsson® XPERIA Mini ..................................................................................................... 33

Phone 6 – Sony Ericsson® XPERIA Mini Pro .............................................................................................. 33

Phone 7 – Nokia® 1202 ................................................................................................................................... 34

Phone 8 – Nokia® E72 ..................................................................................................................................... 34

Phone 9 – Nokia® 2220 slide .......................................................................................................................... 35

Phone 10 – Nokia® C7 .................................................................................................................................... 35 Phone 11 – Nokia® E5 ..................................................................................................................................... 36

Phone 12 – Nokia® Lumia 820 ....................................................................................................................... 36

Phone 13 – HTC® 7 Trophy ........................................................................................................................... 37

Phone 14 – Samsung® Galaxy Ace 2 ............................................................................................................ 37

Phone 15 – Samsung® Galaxy S .................................................................................................................... 38

Phone 16 – Samsung® Galaxy S3 .................................................................................................................. 38

Appendix B – Raw Data from Experiment ...................................................................... 39

Appendix C – Raw Data from Phone Manufacturer Survey ......................................... 41

Appendix D – Calculation of Average SAR Values ....................................................... 42

Brand 1 – Apple ............................................................................................................................................... 42

Brand 2 – Blackberry ....................................................................................................................................... 43

Brand 3 – HTC .................................................................................................................................................. 44

Brand 4 – Motorola .......................................................................................................................................... 45

Brand 5 – Nokia................................................................................................................................................ 46

Brand 6 – Samsung .......................................................................................................................................... 47

Brand 7 – Sony .................................................................................................................................................. 48




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1. Introduction

The IssueThe last decade has seen what is probably one of the most drastic technological upheavals in

human history. Today, we live

in a world where more people

have access to a cellular phone

than they do to a clean toilet.1

The sheer number of cellular

phones in use today has

resulted in the birth of a new

categorizing system forphones, which divides them

into three classes:

smartphones, mobile phones

and feature-phones.2

However, as with all

progress in technology, there

is a host of risks associated with it. One of the most pressing issues

however, is the effect of prolonged usage of cellular phones on the brain,which is arguably the most important organ in the human body. An

amalgamation of the ‘new’ nature of cellular phones and the relative

absence of research conducted in this area has contributed our general lack

of knowledge when electromagnetic radiation from cellular phones is

considered.

In this essay, I plan to explore the potential effects of cellular phones

available to me on the human brain, using a combination of past research

material and first-hand readings taken at the TelecommunicationsRegulatory Commission (TRC) of Sri Lanka. In addition to this, I also plan

to conduct a survey within my school to evaluate the usage of each

popular brand of cellular phones, and to analyze which users at the

greatest risk of damage from electromagnetic radiation. Armed with this

information; I hope to achieve a first-hand perspective of the actual

dangers posed by electromagnetic radiation from cellular phones in Sri

Lanka.

1 (water.org)2 (Fraser)

Figure 1 The evolution of the cellular phone

Figure 2 The Apple iPhone

- a typical smartphone




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Research QuestionAs per the issue outlined above, the research question I have formulated for this assignment

is as follows:

Could electromagnetic radiation from cellular phones have adverse effects on

the human brain?

HypothesesDue to the broad nature of the research question, three hypotheses were formulated as

follows. By defining hypotheses, each can be analyzed individually, which would improve the

focus and quality of the essay.

1.

Radiation from mobile phone use has an adverse effect on the human brainThis hypothesis was formulated for the purpose of measuring and analyzing electromagnetic

radiation from readily available phones. First hand data collected experimentally was used to

evaluate this hypothesis.

2. The extent of radiation damage varies with inversely with the age of the user

Using the equations for the Specific Absorption Rate (SAR) from the FCC, the density of the

skull of an infant can be substituted to calculate the new SAR for an infant. Using this data, along

with other third party information, this hypothesis was evaluated effectively.

3. The general population is safe from the damaging effects of radiation fromcellular phones

This hypothesis was evaluated by conducting a survey of the brands of phones used within

the British School in Colombo, among students and teachers. To analyze this data effectively, the

average SAR values for the most popular phones of a given brand, and analyzing this empirical

data with the data from the survey.




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2. Methodology and Concepts

OutlineCellular phones have two different types of radio transmissions. They are GSM (Global System

for Mobiles) and CDMA (Code Division Multiple Access).3 Technologically speaking, these twotechnologies do not have many differences, apart from the fact

that they are built and mandated by different companies. As this

study is to be conducted in Sri Lanka however, only the GSM

transmission system used in Sri Lanka will be discussed in this

essay, as it alone is used exclusively.4

GSM Radio Transmission TechnologyThe Global System for Mobiles (GSM) radio transmission

technology operates in two ‘bands’ depending on the geographicregion in which it is implemented. Typically, the USA uses the

1900MHz band, while Europe and Asia use the 900MHz band.5

Simply defined, a GSM transmission ‘band’ is a range of

frequencies in which providers transmit signals to phones on their

network.

GSM Bands in Sri Lanka

In a GSM transmission system, the range of frequencies contained within a ‘band’ can be

allocated to different cellular companies in a country or region. In Sri Lanka, the 900MHz bandextends from 869MHz to 915MHz. As per the norm however, within this range, smaller ranges are

awarded to cellular companies for their use, and to ensure the proper separation margins of

frequencies.

To ensure uniformity throughout the experiment, the same cellular company was used

across all phones tested. Due to its high popularity and consistent service, the Dialog® Network6

was selected. Dialog® is allocated the frequencies between 907.5MHz and 915.0Mhz.7

3 (Segan)4 (Telecommunications Regulatory Commission of Sri Lanka Spectrum Management Division)5

(HowStuffWorks Inc.)6 (Dialog Axiata PLC)7 (Telecommunications Regulatory Commission of Sri Lanka Spectrum Management Division)

Figure 3 The spread of EM radiation

from cellular phones




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Measurement and RegulationAs with all dangers posed by any widely used apparatus, the levels of electromagnetic

radiation from cellular phones are carefully monitored by entities such as the United States’ Federal

Communications Commission (FCC). 8 In Sri Lanka too, the law states that all phones sold and used

in the country must comply with the FCC’s rules and regulations when levels of electromagneticradiation are considered.9

Specific Absorption Rate (SAR)

The specific absorption rate is the rate at which electromagnetic radiation is absorbed by the

human body. By using the electric field strength caused by the cellular phone, the SAR of the phone

can be calculated using the following equation:10

=×

!"#

!

2×10!!×

Where = ,!"#

= ℎ = .

Effects of Electromagnetic Radiation ExposureAs per Max Planck’s quantum theory, energy in electromagnetic radiation can be quantified

into packets called photons. The theory also states that the energy carried by a given photon

corresponds to a frequency in the electromagnetic spectrum, as shown by one of Planck’s most well

known equations:11

= ℎ

Where = ,ℎ = ! = .

Einstein’s theory of the photoelectric effect theorizes the interactions between electrons and

photons. Concisely described, his theory states that unless a photon has enough energy to excite an

electron, the electron will merely absorb it, and the atom will be ‘excited’. However, when the

electron returns to its neutral state, electromagnetic radiation is given off in the form of photons.

Unfortunately, some of these photons are transformed into photons of the IR (infrared) spectrum,

due to the staggering motion of the electron when returning to the ground stage. It is this influx of

infrared photons that has adverse implications, as it heats the brain tissue, which could potentially

cause damage.12

8 (Federal Communications Commisssion)9 (Telecommunications Regulatory Commission of Sri Lanka Spectrum Management Division) 10

(Khalatbari, Sardari and Mirzaee)11 (The Nobel Foundation)12 (Hamper)




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3. Experiment ConceptionDue to the unique nature of the issue, specialist equipment was required to conduct this

experiment. Currently, Sri Lanka does not have a dedicated SAR meter. However, the TRC

possesses a meter used to measure the radiation output from cellular phone transmission towers.Using the readings from this apparatus in conjunction and by modifying the equation on page 8, it

was possible to obtain a value for the specific absorption rate for each phone. The TRC apparatus

used in the experiment is discussed below:

Narda® NBM-550 Broadband Field Meter The apparatus used to measure the

power output from cellular antennae by the

TRC is pictured on the right: the Narda®

NBM-550 Field Meter. As this apparatus is

not used to measure the SAR output of a

phone by design, the accuracy of its

measurement (i.e. least count) is more suited

to measuring large power intensities.13

Furthermore, the design of the probe

used is such that the actual location of the

antenna used to measure the value is

unknown; the phones were placed in a

constant position throughout the experiment.

Modification of the SAR EquationDue to the fact that the meter discussed above does not measure the maximum electric field

strength, the equation used to calculate the SAR of the cellular phones tested in the experiment

must be modified.

Upon further investigation, it was discovered that the Narda® meter measures the

maximum power intensity as opposed to the maximum electric field strength. Thus, using

equations that relate the power density and electric field strength, the SAR equation can bemodified to accept values from the Narda® meter,14 as shown overleaf.

13 (Narda Safety Test Solutions)14 (Granite Island Group)

Figure 4 Narda NBM-550 Broadband Field Meter




IB [CORE] EE 01/28/13 10

1 → = !×!

2 → = !×

Where = ,! = = ℎ.

[2] → = !×

⇒ =

!

∴ 1 → = !×

!

!

=!×

!

!

!

=!

!

⇒ != ×!

∴ !"#

!=

!"#×!

Thus, as a relationship between the maximum electric field strength and the maximum

power intensity has been established, the Narda® NBM-550 Field Meter can be used to measure the

SAR of cellular telephones. Hence, the relationship is substituted into the SAR equation as shown

below:

=×

!"#

!

2×10!!×

Where = = .

∴ =×

!"#×!

2×10!!×




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VariablesAs per the SAR equation and the other conditions of the testing area, a list of variables can

be formulated and regulated for the experiment as follows:

Table 1 Table of variables

Variable Type Justification Value (if any)

Bone Density () Constant

As this value is not

dependent on the

experiment, it is a

constant.

-

Impedance of Free Space () Constant


dependent on the

experiment, it is aconstant.

377Ω 15

Brain Tissue Conductivity () Constant


dependent on the

experiment, it is a

constant.

1.1!! 16

Distance between phone and

receiver Constant

As this value would

change the values of

the same reading, it

was kept constant.

5 ± 0.1

Other electromagnetic

radiation Constant

As otherelectromagnetic

radiation would affect

the accuracy of the

readings, an attempt

was made to keep it

constant.

-

Maximum Power Intensity

(

) Independent


dependent on any of

the other variables, it is

independent.

-

Specific Absorption Rate

(SAR) Dependent

As this value is

dependent on the

Maximum Power

Intensity, it is the

dependent variable.

-

15 (Bogatin)16 (Khalatbari, Sardari and Mirzaee)




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Procedure• A piece of paper was kept under the receiving probe. This was done to accurately and

efficiently measure the distance between the phone and the receiver.

• A separate phone was placed in the adjoining room, with a laptop to record the data.

• A call was placed from the phone in the second room to the phone to be tested, in the first

room.

• At 30-second intervals (with the first one being 30 seconds after the call begins), the

maximum power intensity within each 30-second block was recorded.

• During this time, all of the other phones were switched off.

• This process was repeated with each of the phones used in the experiment. A list of phones

used can be seen in Appendix A (page 30).

• Due to the small nature of the numbers, a computer model was used to calculate the final

values and uncertainties for the readings obtained. The raw data collected can be seen in

Appendix B (page 36).




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ObservationsQualitative Observations

• The tip of the detection probe because slightly warm after prolonged use.

Quantitative Observations

• When the level of noise detected by the cellular phone microphone increased, the powerintensity would increase sharply.

• When using cellular phones across networks, the power intensity readings would vary

greatly to when two phones of the same network were used.

Changes Made Due to ObservationsAs it was discovered that the power intensity varied with the sound transmitted during the

call, the procedure followed during the experiment was varied slightly. As opposed to simply

making a call and measuring the resulting power intensity, a song was played on one phone during

the call, whilst the microphone on the other was muted, causing the same audio transmission

channels to activate, normalizing the test.

Furthermore, it was also noted that using two phones from different networks (i.e. with

different Subscriber Identity Modules17 [SIMs]) increased the levels of variation of consecutive

readings. To remedy this, it was decided that only phones of the same network would be used, by

changing the Subscriber Identity Modules of some of the phones in the sample.

Thus, by making the changes discussed above, the validity and accuracy of the readings

obtained were increased, leading to a more coherent analysis of the hypotheses. The experiment

was repeated after making the above changes.

17 (Conjecture Corporation)




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4. Data Computation

OutlineTo effectively analyze the hypotheses discussed in the introduction of this essay, the raw

data collected (Appendix B) must be computed twice. Once for an adult skull, and a second time foran infant’s skull. Using both of these SAR values, it will be possible to effectively analyze both

hypotheses.

Due to the extremely small and recursive nature of some of the readings, they were

calculated directly using a computer application 18 to increase accuracy. For the purpose of

calculation, the readings were rounded off to 6 decimal places. Additionally, the absolute

uncertainty of the raw data was also calculated using the computer model and rounded off to 4

decimal places.

Processed SAR ValuesTo calculate the different SAR values for adults and infants, the bone density () in the SAR

equation (page 9) was varied using values for each of the corresponding skulls (i.e. Adults and

Infants) from third party research. As the conductivity as the brain tissue remains the same

regardless of age, this value was not varied. The calculated SAR values with the changing bone

densities are shown below.

Adult Skull

19 = = 1914!!

⟹ =×

!"#×!

2×10!!×

=

1.1!!×377Ω×

!"#

2×10!!×1914!!

∴ = !"#

×

414.7

3.828!!

18 (Microsoft Corporation)19 (Fry and Barger)




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Table 2 Processed SAR values for an adult

Phone Name SAR (!) [±.!]

Apple® iPhone 4 0.

014444

Apple® iPhone 5 0.010833

RIM® Blackberry Bold 9790 0.108333

Sony® XPERIA sola 0.895556

Sony Ericsson® XPERIA Mini 0.281667

Sony Ericsson® XPERIA Mini Pro 0.303333

Nokia ® 2220 slide 0.162500

Nokia® E72 0.144444

Nokia® 1202 2.123333

Nokia® C7 0.050556

Nokia® E5 0.061389

Nokia® Lumia 820 0.046944

Samsung® Galaxy Ace 2 0.036111

Samsung® Galaxy S 0.

072222

Samsung® Galaxy S3 0.028889

HTC® 7 Trophy 0.025278

Infant Skull

20 = = 1739!!

⟹ =×

!"#×!

2×10!!

×

=

1.1!!×377Ω×

!"#

2×10!!×1739!!

∴ = !"#

×

414.7

3.478!!

20 (Fry and Barger)




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Table 3 Processed SAR values for an infant

Phone Name SAR (!) [±.!]



RIM® Blackberry Bold 9790 0.119235

Sony® XPERIA sola 0.985678

Sony Ericsson® XPERIA Mini 0.310012

Sony Ericsson® XPERIA Mini Pro 0.333859

Nokia ® 2220 slide 0.178853

Nokia® E72 0.158980

Nokia® 1202 2.337010

Nokia® C7 0.055643

Nokia® E5 0.067559

Nokia® Lumia 820 0.051669

Samsung® Galaxy Ace 2 0.039745

Samsung® Galaxy S 0.

079482

Samsung® Galaxy S3 0.031796

HTC® 7 Trophy 0.027821




IB [CORE] EE 01/28/13 17

Processed Survey DataTo effectively evaluate the third hypothesis (page 6), the raw data collected in the survey of

phones used by teachers and students of the British School in Colombo (Appendix C) must be

processed. Furthermore, due to the fact that only a small number of phones from a limited selection

of manufacturers were sampled, online popularity ratings per manufacturer from reputedtechnology website, TechCrunch®21 in conjunction with previously measured SAR values from the

FCC22 will be used to determine the average SAR of the (if possible) ten most popular smartphones

of a selection of the most popular cellular phone manufacturers. The phone manufacturers analyzed

in the study are as follows:

• Apple Inc.23

• Blackberry24

• HTC25

• Motorola26

• Nokia27

• Samsung28

• Sony29

The names and calculation of the average SAR for the ten most popular phones for each of the

above brands can be seen in Appendix D.

21 (AOL Tech.)22 (Federal Communications Commission) 23 (Apple Inc.)24 (Research in Motion Inc.)25 (HTC Corporation)26 (Motorola Mobility LLC.)27

(Nokia)28 (SAMSUNG)29 (Sony Mobile Communications AB.)




IB [CORE] EE 01/28/13 18

5. Data Processing

OverviewHypothesis 1 and 2

To completely analyze the hypotheses discussed in the introduction, it was decided thateach set of SAR readings would be analyzed explicitly. The reasons for which this method was

chosen can be seen below.

Each set of SAR values will be analyzed independently using a bar graph, with the FCC

limitation exposure limit to clearly judge the cellular phone(s) that violate the limit. Using this

method, all phones that violate the SAR limit set out by the FCC can be clearly seen. Additionally,

this explicit analysis can also be used to see the differences between the adult and infant SAR values

graphically, thus leading to a better understanding of the issue.

Using the data from each of the graphs, each hypothesis will be evaluated and discussed

thoroughly, effectively appraising both.

Hypothesis 3

To evaluate the third and final hypothesis to be discussed in this essay, a pi chart of the

usage of each of the phone manufacturers will be plotted to evaluate the usage of each of the phone

models, whilst also evaluating the dangers faced by each group of users. Furthermore, a bar graph

will also be plotted to evaluate the average SAR per phone wile referring to the FCC limit.

By doing this, the third hypothesis can be effectively appraised by evaluating the graphs

and charts plotted, whilst also analyzing the brands of phones that meet the SAR limit.




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Explicit Data ProcessingTo analyze each of the SAR readings explicitly, they readings will be judged against the FCC

recommended SAR limit; 1.6!!.30 The graphs are shown below.

Adults

Graph 1 Explicit SAR analysis for Adults

30 (Federal Communications Commission)

0

0.5

1

1.5

2

2.5

S p e c i fi c A b s o r p t i o n R a t e ( W / k

g )

Cellular Telephone




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Infants

Graph 2 Explicit SAR analysis for Infants

0

0.5

1

1.5

2

2.5

S p e c i fi c A b s o r p t i o n R

a t e ( W / k g )

Cellular Telephone




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Phone Brand Survey Data ProcessingThe data from the phone manufacturer survey was processed and an average SAR value for

each phone brand was calculated. The average brand SAR data alongside the phone brand survey

results are shown tabulated below.

Brand Number of Users Brand SAR (!)

Apple 66 0.48325

Blackberry 30 0.659125

HTC 25 0.6777

Motorola 8 0.6637

Nokia 73 0.7182

Samsung 48 0.4985

Sony 19 1.1369

Figure 5 Pi Chart of phone brand usage from survey

Apple

Blackberry

HTC

Motorola

Nokia

Samsung

Sony




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Graph 3 Average SAR values for phone manufacturers

0

0.2

0.4

0.6

0.8

1

1.2

Apple Blackberry HTC Motorola Nokia Samsung Sony




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6. AnalysisThe objectives of this assignment were simple; establish a relationship between the radiation

from cellular telephones and adverse effects on the human brain, and to investigate the influence of

age on the extent of the adverse effects while also evaluating the safety of the general populationfrom electromagnetic radiation. Using an amalgamation of first hand data collected using

equipment from the TRC, a school-wide survey and a wide range of second hand information from

a plethora of sources, these objectives can be achieved. To do this effectively, each hypothesis will

be addressed individually.

Hypothesis 1 - Radiation from mobile phone use has an adverse effect

on the human brainThe Federal Communications Commission (FCC) of the USA has conducted extensive

research into the field of radiation damage. Using advanced technology and dedicated SAR meters,

they have asserted that a maximum safe radiation level from cellular phones is 1.6!!.31 The

explicit data analysis for adults (page 19) can be used to determine the cellular phones that exceed

the limit defined by the FCC. When experimentally determined, only one phone exceeded the SAR

limit of 1.6!! , the Nokia® 1202.

However, the qualitative observation made during the experiment; the measurement probe

heating up after prolonged use as a direct result of extended electromagnetic radiation exposure is

conclusive evidence that prolonged exposure to radiation from cellular phones is indeed a cause

that would have adverse effects on the human brain.

Additionally, it can also be implied that as the time of exposure to electromagnetic radiation

increases, the adverse effects would increase proportionally, as the number of photons bombarding

the surface of the brain would increase, which would again cause a rise in temperature.32

Furthermore, it can also be stated that while users of cellular phones in general will

eventually experience adverse effects, users in countries that use phones of a higher transmission

band, such as the USA33 are at a greater risk, as the photons used in transmission carry a greater

amount of energy, which allows them to excite a greater number of electrons.34

Thus, it can be said that the first hypothesis is indeed true, as its effects were observed both

during the experiment and in the results.

31 (Federal Communications Commission) 32

(Hamper) 33 (Hill) 34 (Elert)




IB [CORE] EE 01/28/13 24

Hypothesis 2 – The extent of radiation damage varies with inversely with

the age of the user Medical research shown that not only is the SAR threshold for infants lower than that of

adults,35 but that they are also more sensitive to other forms of radiation, such as radio waves and

micro waves, due to the fact that their brains are still developing.36

For infants however, the effects are mostly unknown, due to the relative lack of research

done in the area. However, it can be logically and mathematically assumed that the SAR exposure

limit is indeed lower. As the density of the infant’s skull is less than that of an adult, more

electromagnetic radiation will be absorbed, as is seen in the SAR equation, reproduced below.

=×

!"#×!

2×10

!!

×

Studies on beef show that the tenderness of the tissue is directly proportional to the

conductivity of the sample.37 To use this discovery, it can be assumed that the similarities between

cow and human tissue are sufficient to allow this to occur in humans as well. Thus, it can be

assumed that the conductivity of infant tissue is greater than that of an adult. Additionally, it is a

known fact that infant tissue is indeed less dense than adult tissue,38 so it can be said that the

denominator of the equation reduces whilst the numerator increases, which makes the readings

larger.

Thus, it can be inferred from the readings taken with an infant’s skull density that not only is the

SAR higher, but the SAR exposure limit is lower, which would and could lead to more adverse

effects than previously thought possible.

Thus, due to the low density of the infant skull, it can be seen that the SAR readings are

substantially higher than that of an adult. Therefore, it can be concluded that as the SAR level is

higher, and as the harmless SAR threshold is lower for infants, that hypothesis 2 is also true; the

extent of radiation damage varies inversely with the age of the user.

35 (Brain Imaging and Analysis Center)36

(Stokowski) 37 (Troy) 38 (Gallo, Vanstone and Weiler)




IB [CORE] EE 01/28/13 25

Hypothesis 3 – The general population is safe from the damaging

effects of radiation from cellular phonesThe results of the calculation of the average SAR limit per manufacturer shows that none of

the manufacturers exceed the SAR limit. However, the phone manufacturer Sony came extremely

close to the FCC mandated limit of 1.6 Wkg-1.

Despite this proximity however, the results of the survey show that none of the users of any

of the phones are at risk of the adverse effects of radiation exposure, as none of the manufacturers’

exceed the SAR limit. However, the users of phones with higher average SAR values will

experience greater adverse effects eventually than users of low SAR phones. This phenomenon can

be explained using the photoelectric effect, as discussed in hypothesis 2.




IB [CORE] EE 01/28/13 26

7. Conclusion and EvaluationThis investigation sought to answer the question ‘Could electromagnetic radiation from cellular

phones have adverse effects on the human brain?’ To further explore the scope of the question, it

was split into three hypotheses:

1. Radiation from mobile phone use has an adverse effect on the human brain.

2. The extent of radiation damage varies with inversely with the age of the user.

3. The general population is safe from the damaging effects of radiation from cellular phones.

Using data collected first hand, both experimentally and through a survey, and a wide variety

of source material, an equation was constructed to calculate the SAR of the mobile phones with

apparatus that is designed to measure the power intensity from cellular base stations.

The evidence and results considered has led me to the conclusion that I can indeed validate all

three of the hypotheses considered in this experiment. Nevertheless, my studies demonstrate that

there are clearly problems with data collection, where a wide variety of external factors could have

affected the final outcome. Thus, by realizing that though the data collected in this experiment may

not be completely valid, I have to the best of my ability eliminated all random error, whilst ensuring

that all tests and calculated were carried out fairly and correctly.

As a part of the evaluation of the experiment, it can be concluded that the results obtained as

a part of the experimental process are not accurate. This can be attributed to a wide variety of

reasons, the chief of them being the fact that the readings were not taken in a electromagnetically

isolated room. Thus, third party radiation from sources such as the TRC wireless Internetconnection, other phones and other apparatus may have affected the readings.

Furthermore, the use of the NARDA® apparatus in the experiment would have greatly reduced

accuracy. As this apparatus is conventionally used to measure the power output from cellular

phone transmission towers, the level of accuracy would have been greatly reduced as it is

conventionally used to measure large values. Furthermore, the absence of a proper substitute for

the human skull in the experiment may have also affected the readings obtained in the experiment.

Finally, to address the survey conducted in the experiment, it can be said that despite the fact

that conclusive results were obtained to prove the hypothesis, the fact that the survey was

conducted at the British School would result in not getting an accurate perspective of the society of

Sri Lanka. Due to the fact that most of the students at the British School do not endure financial

hardship, the phones used within the school may not reflect the phones used in the society of the

country, where fake, unregulated ‘cloned’ phones are a large problem.

In conclusion, I feel that despite the shortcoming of the experiment, the manner in which it was

conducted, in addition to the removal of error to the best of my abilities has allowed me to deem

this investigation successful.




IB [CORE] EE 01/28/13 27

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IB [CORE] EE 01/28/13 30

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IB [CORE] EE 01/28/13 31

Appendix A – Index of Cellular Phones Used in Study

Phone 1 – Apple® iPhone 4

Phone 2 – Apple® iPhone 5

Release Date: June 2010

FCC ID: BCG-E2380B

Manufacturer: Apple Inc.

Website: http://www.apple.com/iphone/iphone-

4/specs.html

Release Date: September 2012

FCC ID: BCG-E2599A

Manufacturer: Apple Inc.

Website: http://www.apple.com/iphone/specs.html

Figure 6 Apple iPhone 4

Figure 7 Apple iPhone 5




IB [CORE] EE 01/28/13 32

Phone 3 – RIM® Blackberry Bold 9790

Phone 4 – Sony® XPERIA sola

Release Date: November 2011

FCC ID: L6AREC70UW

Manufacturer: Research in Motion Inc.

Website: http://worldwide.blackberry.com/blackberrybold/blackberry-

bold-9790/

Release Date: March 2012

FCC ID: PY7A3880134

Manufacturer: Sony Inc.

Website: http://www.sonymobile.com/global-

en/products/phones/xperia-sola/

Figure 8 RIM Blackberry Bold 9790

Figure 9 Sony XPERIA sola




IB [CORE] EE 01/28/13 33

Phone 5 – Sony Ericsson® XPERIA Mini

Phone 6 – Sony Ericsson® XPERIA Mini Pro


FCC ID: PY7A3880107

Manufacturer: Sony Ericsson Inc.

Website: http://www.sonymobile.com/gb/products/phones/xperia-

mini/


FCC ID: PY7A3880104

Manufacturer: Sony Ericsson Inc.

Website: http://www.sonymobile.com/gb/products/phones/xperia-

mini-pro/

Figure 10 Sony Ericsson XPERIA Mini

Figure 11 Sony Ericsson XPERIA Mini Pro




IB [CORE] EE 01/28/13 34

Phone 7 – Nokia® 1202

Phone 8 – Nokia® E72

Release Date: April 2009

FCC ID: QTLRH-113

Manufacturer: Nokia Inc.

Website: http://press.nokia.com/products/35/nokia-

1202/

Release Date: October 2009

FCC ID: PYARM-529


Website: http://www.nokia.com/us-

en/support/product/nokia-e72/

Figure 12 Nokia 1202

Figure 13 Nokia E72




IB [CORE] EE 01/28/13 35

Phone 9 – Nokia® 2220 slide

Phone 10 – Nokia® C7

Release Date: February 2010

FCC ID: QTLRM-591


Website: http://www.nokia.com/gb-en/support/product-

archive/?action=productArchive&listType=phones&tid=1569830&s

earchTerm=Nokia+2220+slide


FCC ID: QFXRM-675X


Website: http://www.nokia.com/gb-

en/products/phone/c7-00/specifications/

Figure 14 Nokia 2220 slide

Figure 15 Nokia C7




IB [CORE] EE 01/28/13 36

Phone 11 – Nokia® E5

Phone 12 – Nokia® Lumia 820

Release Date: August 2010

FCC ID: QTKRM-634


Website: http://www.nokia.com/us-

en/products/phone/e5-00/

Release Date: November 2012

FCC ID: PYARM-825


Website: http://www.nokia.com/us-en/products/phone/lumia820/

Figure 16 Nokia E5

Figure 17 Nokia Lumia 820




IB [CORE] EE 01/28/13 37

Phone 13 – HTC® 7 Trophy

Phone 14 – Samsung® Galaxy Ace 2


FCC ID: NM8PC40100

Manufacturer: HTC Corp.

Website: http://www.htc.com/us/smartphones/htc-

trophy-verizon/

Release Date: May 2012

FCC ID: A3LGTI8160

Manufacturer: Samsung Group

Website: http://www.samsung.com/sg/consumer/mobile-

devices/smartphone/android-os/GT-

I8160ZWAXSP

Figure 18 HTC 7 Trophy

Figure 19 Samsung Galaxy Ace 2




IB [CORE] EE 01/28/13 38

Phone 15 – Samsung® Galaxy S

Phone 16 – Samsung® Galaxy S3

Release Date: June 2010

FCC ID: A3LGTI9000


Website: http://www.samsung.com/uk/consumer/mobile-

devices/smartphones/android/GT-

I9000HKDXEU

Release Date: May 2012

FCC ID: A3LGTI9300A


Website: http://www.samsung.com/global/galaxys3/

Figure 20 Samsung Galaxy S

Figure 21 Samsung Galaxy S3




IB [CORE] EE 01/28/13 39

Appendix B – Raw Data from Experiment

Phone

MaximumPowerIntensityOutput

(!)[±

.

!]

Apple®iPhone4

0.0001

0.0001

0.0002

Apple®iPhone5

0.0001

0.0001

0.0001

RIM®BlackberryBold9790

0.0013

0.0003

0.0014

Sony®XPERIAsola

0.0101

0.0047

0.0100

SonyEricsson®XPERIAMini

0.0024

0.0025

0.0029

SonyEricsson®XPERIAMiniPro

0.0031

0.0027

0.0026

Nokia®2220slide

0.0013

0.0014

0.0018

Nokia®E72

0.0012

0.0013

0.0015

Nokia®1202

0.0202

0.0191

0.0195

Nokia®C7

0.0005

0.0006

0.0003

Nokia®E5

0.0007

0.0005

0.0005

Nokia®Lumia820

0.0004

0.0004

0.0005

Samsung®Ace2 0.0002

0.0002




IB [CORE] EE 01/28/13 40

0.0006

Samsung®GalaxyS

0.0005

0.0009

0.0006

Samsung®GalaxyS30.00020.0004

0.0002

HTC®7Trophy

0.0001

0.0004

0.0002




IB [CORE] EE 01/28/13 41

Appendix C – Raw Data from Phone Manufacturer Survey

Grade Apple Blackberry HTC Motorola Nokia Samsung

Sony

XPERIA

6th Grade 0 2 0 1 2 4 3

7th Grade 14 13 5 0 15 9 3

8th Grade 6 1 1 5 5 4 1

9th Grade 10 5 8 0 6 8 3

10th

Grade 8 6 5 0 9 6 2

11th Grade 8 1 4 1 13 8 5

12th Grade 12 1 2 0 12 8 1

Teachers 8 1 0 1 11 1 1

TOTAL 66 30 25 8 73 48 19

= 269




IB [CORE] EE 01/28/13 42

Appendix D – Calculation of Average SAR Values

Brand 1 – Apple

Phone FCC ID SAR (!)

iPhone 5 BCG-E2599A 0.380

iPhone 4S BCG-E2430A 0.372

iPhone 4 BCG-E2380A 0.661

iPhone 3GS BCGA1303A 0.520

.

=

0.380 + 0.372 + 0.661 + 0.520

4!!

= 0.48325!!




IB [CORE] EE 01/28/13 43

Brand 2 – Blackberry


Blackberry Curve 9320 L6ARFE70UW 0.610

Blackberry Bold 9900 L6ARDV70UW 0.690

Blackberry Bold 9790 L6AREC70UW 0.461

Blackberry Curve 3G 9300 L6ARDA70UW 0.453

Blackberry Curve 9360 L6ARDD70UW 0.964

Blackberry Torch 9860 L6ARDP70UW 0.880

Blackberry Bold 9700 L6ARCM70UW 0.785

Blackberry Torch 9800 L6ARCY70UW 0.443

=

0.610 + 0.690 + 0.461 + 0.453 + 0.964 + 0.880 + 0.785 + 0.443

8!!

= 0.659125!!




IB [CORE] EE 01/28/13 44

Brand 3 – HTC


HTC One X NM8PJ83100 0.514

HTC Droid DNA NM8PL83200 0.263

HTC One X+ NM8PM63100 0.835

HTC Windows Phone 8X NM8PM23200 0.952

HTC One VX NM8PM36100 0.381

HTC EVO 4G LTE NM8PJ75100 0.747

HTC Rezound NM8PH98100 0.756

HTC Vivid NM8PH39100 0.534

HTC Sensation 4G NM8PG58100 0.615

HTC One S NM8PJ40110 1.180

=. 514 + .263 + .835 + .952 + .381 + .747 + .756 + .534 + .615 + 1.180

10 −1

= 0.6777!!




IB [CORE] EE 01/28/13 45

Brand 4 – Motorola


DROID RAZR MAXX HD IHDT56NG1 0.386

DROID RAZR HD IHDT56NG1 0.386

DROID RAZR IHDP56ME1 0.474

DROID Bionic IHDT56MX1 0.850

DROID RAZR M IHDT56NS1 0.796

DROID RAZR MAXX IHDP56ME1 0.474

DROID 4 IHDP56MN1 1.050

Motorola Atrix 2 IHDT56MV1 0.914

Motorola Photon 4G IHDP56MD1 0.893

Motorola Atrix HD IHDP56MB4 0.414

= .

386 +.

386 +.

474 +.

850 +.

796 +.

474 + 1.

050 +.

914 +.

893 +.

414

10!

!

= 0.6637!!




IB [CORE] EE 01/28/13 46

Brand 5 – Nokia


Nokia Lumia 920 PYARM-821 0.535

Nokia Lumia 900 QMNRM-808 0.543



Nokia Lumia 820 PYARM-824 0.780


Nokia Lumia 800 LJPA 1.080

Nokia 808 Pureview PDNRM-807 0.500

Nokia N8 PDNRM-596 0.830

Nokia E7 PDNRM-626 0.910

= .

535 +.

543 +.

629 +.

453 +.

780 +.

920 + 1.

080 +.

500 +.

830 +.

910

10!!

= 0.7182!!




IB [CORE] EE 01/28/13 47

Brand 6 – Samsung


Samsung Galaxy S3 A3LSGHI747 0.531

Samsung Galaxy Note II A3LSGHT889 0.184

Samsung Galaxy Nexus A3LGTI9250 0.630

Samsung Galaxy S2 A3LSGHT989 0.510

Samsung Galaxy S2 Skyrocket A3LSGHI727 0.850

Samsung Epic 4G Touch A3LSPHD710 0.240

Samsung Galaxy Note A3LSGHI717 0.750

Samsung Epic 4G A3LSPHD700 0.680

Samsung Infuse 4G A3LSGHI997 0.200

Samsung Droid Charge A3LSCHI510 0.410

= .

531 +.

184 +.

630 +.

510 +.

850 +.

240 +.

750 +.

680 +.

200 +.

410

10!!

= 0.4985!!




Brand 7 – Sony


Sony XPERIA TL PY7PM-0140 1.472

Sony XPERIA Ion PY7A8880001 0.967

Sony XPERIA S PY7A3880120 1.310

Sony XPERIA TX PY7PM-0010 0.916

Sony XPERIA P PY7A3880135 1.261

Sony XPERIA miro PY7PM-019 1.220

Sony XPERIA V PY7PM-0060 0.831

Sony XPERIA J PY7PM-0170 1.170

Sony XPERIA Z PY7PM-0280 1.096

Sony Ericsson Mix Walkman PY7A1880032 1.126

=

1.472 + .967 + 1.310 + .916 + .1.261 + 1.220 + .831 + 1.170 + 1.096 + 1.126

10!!

= 1.1369!!

International Baccalaureate Extended Essay

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