1. 1
INTERNATIONAL BACCALAUREATE
ENVIRONMENTAL SYSTMES AND SOCIETIES
INTERNAL ASSESMENT
To What Extent Income Levels Is an Important Factor in Deciding the Differences in
Ecological Footprint Between a Village and A City?
Word Count - 2606
3. 3
CRITERIA 1: IDENTIFYING THE CONTEXT
Aim:
The Aim of this lab is to identify how the ecological footprint differs between a village
and a city. I will consider income as a major factor while carrying out my lab. I will
examine how income plays a role in determining the ecological footprint of two different
areas.
Research Question:
To what extent do income levels play a role in deciding the difference in ecological
footprint between a village and a city?
This research would help us determine the correlation between income and ecological
footprint:
1)Ecological footprint determines the impact of an individual on the environment. This
consists of factors like carbon footprint and as carbon footprint increases it impacts
the natural world in a negative manner.
2) Income is a major factor in determining the ecological footprint of an individual. A
higher income level could mean that an individual would have a higher ecological
footprint as their consumption would be at a higher level.
Introduction:
India with a population of 1.3 billion is the world’s second most populated country.
There is a growing gap in India between the amount of natural resources the country
uses and how much it holds. According to a report released by Global Footprint
Network, India now demands the bio capacity of two India’s to provide for its
consumption and absorb its wastes.1
Mahendrapur is a small village located in Jaunpur Tehsil in Tehri Garhwal District of
Uttarakhand State, India. It lies 16 km from Dehradun which is the state capital
Uttarakhand. The village is spread over a total geographical area of 78.23 hectares
and it has a population of 250-450 people.
New Delhi is the capital city of India. The city has an approximate population of 21.75
million and the capital is spread over an area of 1,484 km2
1
“India's Demand on Nature Approaching Critical Limits, Report Finds.” Global Footprint
Network, 10 Mar. 2017, www.footprintnetwork.org/2008/10/03/indias-demand-nature-
approaching-critical-limits-report-finds/.
4. 4
Ecological Footprint focuses on a given population and its current rate of resource
consumption, and estimates the area of environment necessary to sustainably support
that particular population2
Income is the flow of cash or cash-equivalents received from work (wage or salary),
capital (interest or profit), or land (rent).3
Planning:
In the experiment conducted in the village and the city there were a set of questions
asked to various households. The questions were based upon the income and earning
of the household and the ecological footprint.
Environmental Context:
As economies develop consumption increases leading to a higher rate of resource use
therefore living unsustainably. Living unsustainably would lead to the future
generations not having enough resources to fulfill their needs causing the deterioration
of the planet. This also causes various other environmental issues like pollution
leading to global warming, contamination of rivers and water bodies etc.
A high ecological footprint of a particular area would mean that the individuals living in
that particular area are consuming resources and assimilating wastes at an
unsustainable rate and they would require an area of land which is larger than their
ecological footprint in order to be sustainable. A large ecological footprint would be a
result of – greater reliance on fossil fuels, increased use of technology (technology
can also help in reducing ecological footprint), large per capita production of carbon
waste and consumption of food, etc.
In these mentioned ways is the topic related to my research question which is: To
What Extent Income Levels Is an Important Factor in Deciding the Differences in
Ecological Footprint Between a Village and A City?
2
Davis, Andrew, and Garrett Nagle. Environmental systems and societies: supporting every
learner across the 1IB continuum. Pearson Education, 2015.
3
“Income.” BusinessDictionary, www.businessdictionary.com/definition/income.html.
5. 5
Background Information:
Fig 1: Mahendrapur Village
Fig 2: New Delhi (City)
Hypothesis:
My research will identify the link between the ecological footprint and income. This
research will aim to identify to what extent does income play a role in affecting the
ecological footprint of a particular region and it would be compared between a city and
a village. If the questions framed are accurate and the time is sufficient then the data
collected will be sufficient and accurate to make observations and conclusions on the
link between income and ecological footprint of two different areas.
6. 6
Defining Variables:
A variable is any factor, trait, or condition that can exist in differing amounts or types.
Variables:
Dependent Variables:
Serial No. Dependent Variable Impact
1. The accuracy of the data
being collected through the
survey and questionnaires
depends on how clear and
understandable the
questions are to the people
being surveyed.
2. Time The time taken to complete
a survey would depend on
the clarity and
understandibilty of the
questions
3. Number of households
surveyed
The number of households
surveyed depends on the
amount of time spent
surveying each household.
Independent Variables:
Serial No. Independent Variable Impact
1. Time The time of the day is an
important factor which has
to be considered. During
the day many people may
out for work and therefore it
would not be possible to
carry out the survey. The
survey could be carried out
7. 7
in the evening for
convenience and
availability of people.
2. Number of Questions More number of questions
could lead to people
becoming reluctant to
answer.
3. Income A higher income could
mean that the people being
surveyed have a higher
ecological footprint.
Uncontrolled Variables:
Uncontrolled Variables: • Population of the village and city
being surveyed
• Weather conditions on the day of
the surveys being taken place
Controlled Variables:
Serial No. Controlled
Variables
Units How to control? Why to control
?
1. Location Around 30-40
households
were
interviewed in
the village and
the city
Bharakatal
Village and
New Delhi was
chosen for the
survey being
carried out
Different
locations will
lead to different
data being
gathered
causing
inaccurate
assumptions.
2. Number of
Questions
10 questions A fixed number
of questions
were designed
and put on a
questionnaire
to gather
information.
This would
save time and
lead to a fair
survey as all
households
would be
receiving the
8. 8
same set of
questions.
3. Time Morning,
Afternoon or
Evening
The surveys
were
conducted in
the morning or
afternoon
depending on
what was more
suitable for the
households.
People weren’t
always
available at
their homes.
4. No. of
Households
Interviewed
10 households
for each area.
10 households
were
interviewed in
the village and
10 households
were
interviewed in
the city
To keep it fair
the same
number of
households
were used in
both the areas.
Apparatus Required:
Equipment / Material Quantity
1) Questionnaires - The
questionnaire that was designed
beforehand for the surveys.
50 Copies
2) Writing Material- Pen, Pencil and
notepad to write down notes and
results of the survey
Sufficient: 2-3 each (extra just in case)
3) Resource Booklet- The resource
booklet included additional
information and different surveys
and experiments.
1
9. 9
Criteria 2: Planning
Methodology:
• Random sampling was used for the selection of the households to survey.
• Photographs were clicked as evidence of data.
• Once the survey was conducted observations were made on the ecological
footprint of households and the effect of income.
• Graphs were made to represent the information gathered.
• Analysis was done in relation to the data collected and the graphs constructed.
Sampling Strategy:
• Random sampling was used for the selection of the households to survey in the
village and the city.
Justification of Sampling Strategy:
A set of 10 questions were used to survey the households in both the areas. 30-40
households were selected as a sample in the both the areas through random
sampling. The location and members of the household were factors which were
considered. The same set of questions and same techniques of survey were adopted
in both the areas to generate standardized results and gather accurate data.
Techniques Used:
Primary Techniques:
1.Interview Interviews were carried out to gain
knowledge about the area being
surveyed and to get to know the people
of the particular area.
2. Questionnaires Questionnaires were used to gather
information regarding the experiment.
The questionnaires were translated in
Hindi so that the locals of the village
could understand the questions.
3.Observation Observing the area and the state of the
households being surveyed also helped
gather information.
Secondary Techniques:
Briefing We were given a briefing about the
village being surveyed by our instructors
10. 10
and we were given a brief idea about the
history and demographics about the
area.
Internet The internet was used to gather data on
demographics and background
information of the area of the experiment
Procedure:
1. Background Information was gathered about the area to be surveyed - Village
and City. Information was gathered through various sources which included the
internet and interviews. Factors like population and conditions of the area were
taken into consideration as well before conducting the survey
2. Observation of the areas were conducted to gather data on the physical
conditions of both - village and city. This would help make assumptions on the
living conditions and lifestyle of the people located in the areas.
3. Questions were formed in the form of a questionnaire. The questions were
precise and clear to save time and improve the accuracy of the answers. The
questions were formed by the help of the resource booklet and were translated
in Hindi for the convince of the locals being surveyed.
4. 30-40 houses were surveyed in both the areas. The households were chosen
through random sampling. Interviews and surveys were conducted at different
households.
5. Observations were made regarding the ecological footprint and income.
6. Graphs were made to represent the data gathered and make further
assumptions of the relation of Ecological footprint and Income.
7. Further analysis of the data collected and the graphs were done to help make
conclusions regarding the data collected.
Risk Assessment:
1. The questions were accurately framed and translated in Hindi so they could be
understood by the locals in the village.
2. The questions were framed in a way which didn’t make the interviewee
uncomfortable or offended.
3. Time had to be considered as it was a major factor due to the large number of
households needed to be surveyed.
4. Ethical considerations were made like our body language and behavior to
prevent any one being offended or disturbed.
11. 11
Criteria 3: Result, Analysis and conclusion
The Following shows the Ecological Footprint questionnaire and the responses from
households in both the areas (Bharakatal Village and New Delhi)
Bharakatal Village
Household 1 2 3 4 5
Q1 (RS.) 3000-4000 Under 500 3000-4000 3000-4000 2000-3000
Q2 Small
Diesel Car
Don’t own a
vehicle
Don’t own a
vehicle
Don’t own a
vehicle
Don’t own a
vehicle
Q3 2-5 hours - under 2
hours
- Under 2
hours
Q4 Under 1
hour
Under 1
hour
Under 1
hour
2 to 5 hours 2 to 5 hours
Q5 No Yes Yes Yes No
Q6 No Yes Yes Yes Yes
12. 12
Q7 Small
Appliances
- Small
appliances
- -
Q8 1 bag 1 bag 1 bag 2 bags 1
Q9 Little Very little Very little Little A fair
amount
Q10 Yes Yes No Yes Yes
Household 1 2 3 4 5
Q1 (RS.) 2000-3000 1000-2000 5000-6000 Under 500 Under 500
Q2 Don’t own a
vehicle
Don’t own a
vehicle
Motorbike Don’t own a
vehicle
Don’t own a
vehicle
Q3 Under 2
hours
Under 2
hours
Under 2
hours
- -
2 to 5 hours Under 1
hour
2 to 5 hours Under 1
hour
-
Q5 Yes No No No Yes
Q6 No Yes Yes Yes Yes
Q7 Small
Appliances
- Small
Appliances
- -
Q8 0 1 1 1 1
Q9 A fair
amount
Very Little Little Very Little Very Little
Q10 Yes Yes No Yes No
New Delhi
Household 1 2 3 4 5
Q1 (RS.) 50,000-1L 50,000-1L 20,000-
50,000
Above 1L 50,000-1L
Q2 Large
Petrol
Medium
Diesel
Small Petrol Large
Petrol
Medium
Diesel
Q3 15 to 25
hours
5 to 15
hours
15 to 25
hours
15 to 25
hours
15 to 25
hours
Q4 Under 1
hour
Under 1
hour
2 to 5 hours Under 1
hour
Under 1
hour
Q5 Yes Yes No Yes Yes
Q6 No No No Yes No
Q7 Large
Appliances
Small
Appliances
Small
Appliances
Large
Appliances
Large
Appliances
Q8 2 3 1 3 2
13. 13
Q9 A fair
amount
A fair
amount
A fair
amount
A lot A fair
amount
Q10 No No No No No
Household 1 2 3 4 5
Q1(RS.) Above 1L 20,000-
50,000
50,000 to
1L
20,000-
50,000
Above 1L
Q2 Large
Diesel
Medium
Diesel
Medium
Petrol
Motorbike Large
Petrol
Q3 Above 25
hours
5 to 15
hours
15 to 25
hours
15 to 25
hours
15 to 25
hours
Q4 Under 1
hour
2 to 5 hours Under 1
hour
2 to 5 hours Under 1
hour
Q5 Yes Yes Yes Yes Yes
Q6 No No No Yes No
Q7 Large
Appliances
Small
Appliances
Large
Appliances
Small
Appliances
Large
Appliances
Q8 3 2 2 2 3
Q9 A fair
amount
A fair
amount
A fair
Amount
A fair
amount
A Lot
Q10 No No No No No
Data Processing:
Mean and Mode Data for the Ecological Footprint Data gathered from the village and
the city
Village - Bharakatal
Mean
∑#$
#
:
Question Mean
Income Rs. 2,325
Number of hours spent in cars or
motorbikes for personal commenting each
week
0.7 hours
14. 14
Number of hours spent on the bus for
personal use each week
1.3 hours
Number of households which recycle 0.4
Number of garbage bags produced by the
households
1 bag
Number of households using compost 0.7
Number of vegetarians 0.8
Mode (most-common or most-frequently occurring value):
Question Mode
Most common type of vehicle owned No personal Vehicle owned
Number of large purchases made by the
household in the current year
Didn’t make any purchases
Amount of electricity used by the
households
Very Little
New Delhi – City
Mean
∑#$
#
:
Question Mean
Income Rs. 70,500
Number of hours spent in cars or
motorbikes for personal commuting each
week
18.5 hours
Number of hours spent on the bus for
personal use each week
1.4 hours
Number of households which recycle 0.9
Number of garbage bags produced by the
households
2.3 bags
Number of households using compost 0
Number of vegetarians 0.2
15. 15
Mode (most-common or most-frequently occurring value):
Question Mode
Most common type of vehicle owned Large Petrol and Medium Diesel
Number of large purchases made by the
household in the current year
Large Appliances
Amount of electricity used by the
households
A fair amount
Graphs of the data collected from Bharakatal Village:
Graph 1.1: Income
2500
250
3500 3500
2500
0
500
1000
1500
2000
2500
3000
3500
4000
Person 1 Person 2 Person 3 Person 4 Person 5
Income
Income
16. 16
Graph 1.2: Type of Vehicle Used by the households
Graph 1.3: Numbers of hours spent in vehicles each week by each household
10%
80%
10%
Small Diesel Car Don’t Own a Vehicle Motorbike
2.5
0
1.5
0
1.25
0
0.5
1
1.5
2
2.5
3
Household 1 Household 2 Household 3 Household 4 Household 5
HOURS SPENT
Hours Spent
17. 17
Graphs of the data collected from New Delhi:
Graph 2.1 – Income:
Graph 2.2 - Type of Vehicle Used by the households:
75000 75000
35000
1,50,000
75000
0
20000
40000
60000
80000
100000
120000
140000
160000
Person 1 Person 2 Person 3 Person 4 Person 5
Income
Income
30%
30%
10%
10%
10%
10%
Type of Vehicle Used
Large Petrol Medium Diesel Small Petrol Large Diesel Medium Petrol Motrobike
18. 18
Graph 2.3 - Type of Vehicle Used by the households:
Comparison of Mean Data Values between the Village (Bharakatal) and City (New
Delhi):
Graph 3.1:
20
10
20 20 20
0
5
10
15
20
25
Household 1 Household 2 Household 3 Household 4 Household 5
Hours Spent
Hours Spent
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
Village - Bharakatal City - New Delhi
Mean Income Values
Mean Income Values
19. 19
Graph 3.2:
Graph 3.3:
0
2
4
6
8
10
12
14
16
18
20
Village City
Mean number of hours spent in cars or motorbikes for
personal commuting each week
Mean number of hours spent in cars or motorbikes for personal commuting each week
1.24
1.26
1.28
1.3
1.32
1.34
1.36
1.38
1.4
1.42
Village City
Mean number of hours spent on the bus for personal use
each week
Mean number of hours spent on the bus for personal use each week
20. 20
Graph 3.4:
Graph 3.5:
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Village City
Mean number of households which recycle
Mean number of households which recycle
0
0.5
1
1.5
2
2.5
Village City
Mean number of garbage bags produced by the households
Mean number of garbage bags produced by the households
21. 21
Graph 3.6:
Graph 3.7:
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Village City
Mean number of households using compost
Mean number of households using compost
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Village City
Mean number of households using compost
Mean number of households using compost
22. 22
Comparison of Mean Income and Factors Determining the Ecological Footprint
between the Village and the City:
Graph 4.1:
Graph 4.2:
0
10
20
30
40
50
60
70
80
Village City
Mean Income vs Avg. number of hours spent in a vehicle
each week
(Village vs City)
Income in (Rs.000) Avg number of hours spend in a vehicle each week
0
10
20
30
40
50
60
70
80
Village City
Mean Income vs Avg. number of households which recycle
(Village vs City)
Income (Rs.000) Avg. number of households which recycle
23. 23
Graph 4.3
Graph 4.4:
0
10
20
30
40
50
60
70
80
Village City
Mean Income vs Avg. number of garbage bags produced by
the houeholds
(Village vs CIty)
Income (Rs. 000) Avg. number of garbage bags produced by the households
0
2
4
6
8
10
12
14
16
18
20
Village City
Mean Income vs Avg. number of vegetarians
(Village vs City)
Income Avg. number of vegetarians
24. 24
Criteria 4: Discussion and Evaluation
Discussion:
The primary purpose of this lab was to find out the ecological footprint of two different
areas and bring out the link between income and ecological footprint.
This research’s primary motive is to find out the relation between the Income and
Ecological footprint. As we can see in Graph 4.1, it shows the relationship between
the income and the number of hours spent in vehicles commuting each between the
village and the city. We can see that the avg. income in the village (Rs. 2,325) is much
smaller compared to the avg. income of the city (Rs. 70,500). Taking the income of
both the areas in comparison we can see that the people in the village spend much
lesser time commuting in vehicles compared to the city. The graph shows a clear
difference between both and implies that higher the income the more number of hours’
people spend in vehicles creating more pollution and higher resource use.
As we can see from graph 4.2, it shows the relationship between the income and the
avg. number of households which recycle. It shows that households in the village tend
to recycle very less compared to the city. It shows that the higher the income the more
the tendency of households to recycle. The reason could be because people in cities
are more educated compared to people living in villages.
Graph 4.3 shows the relationship between the income and the avg. number of garbage
bags produced by the households each week. This graph shows that households in
cities produce double the amount of garbage each week compared to households in
villages. A higher income would mean people consuming more resources, therefore
producing more waste.
Graph 4.4 shows the relationship between the income and the avg. number of
vegetarians in the village and city. The city has a higher number non-vegetarians
which leads to a higher ecological footprint. One of the major reasons of a higher
percentage of people being vegetarians in the village would be the financial factor.
25. 25
Evaluation:
Limitation Impacts Improvements
1) Only one Village
was surveyed
• It resulted in a
smaller variety of
data being collected
which could lead to
inaccurate results
• Surveying more
number of villages
could have
produced better
quality data and
clearer conclusions
could have been
made.
• More data would
mean the margin of
error could reduced
2) Only one locality in
the city was
surveyed
• It would result in a
smaller variety of
data being collected
causing differences
and affecting the
results
• People living in a
certain locality could
have similar income
levels and lifestyles
which could affect
the results of the
experiment.
• Surveying more
number of localities
would have
produced better
quality data and
results
3) Lack of quantitative
data
• Due to the area of
exploration of this
experiment being
more qualitative:
producing numerical
results (ex- mean,
median, mode),
graphical results
and analysis was
difficult
• Addition and
exploration of
quantitative data
could be in
incorporated during
data collection to
generate results
which could be
analyzed better.
4) Only close ended
questions were
asked
• Questions only
relating to income
and ecological
footprint were asked
• Open ended
questions would
expand the limits of
this research.
26. 26
which narrowed
down the different
aspects of
information which
could be gathered.
5) Time Constraint • Less time led to
surveys not being
thoroughly taken.
• More time could
lead to a variety of
information being
gathered
Conclusion
Through the data collected and the information presented in this report we can
calculate and determine the resource use pattern of people living in both a village and
a city, incomes, waste generation and various other aspects. The average income in
the city is more than ten times larger than the average income in the village. A higher
income would mean a higher level of consumption which would lead to higher resource
use and therefore using resource at an unsustainable rate leading to a higher
ecological footprint. Looking at other factors- villages which have a lower education
level, have lower income levels causing lower development leading to low ecological
footprint levels.
From all the data and information gathered I can conclude by saying that ecological
footprint and income have a major relation. Income determines the
consumption of an individual which impacts the rate of resource use. A high amount
of resource use would cause a high ecological footprint as populations would be using
resources at an unsustainable rate not taking into consideration the needs of the future
generations. Therefore, proving my research question and hypothesis correct.
27. 27
Criteria 5: Application
Solution Strength Weakness
1. Cleaner
Transportation
• The use of smaller
or electric cars
reduce the pollution
emission into the
air resulting in
cleaner air and a
smaller ecological
footprint
• Car Pools or Public
transport are an
efficient way to
reduce carbon
emissions.
• A research by the
European Cycling
Federation has
shown that for
every Kilometer
travelled by a
bicycle 21 grams
on carbon is
released compared
to 271 grams while
driving a car.4
• Electric Cars are
more expensive
causing people not
to purchase a new
electric car if they
currently own a car,
therefore this
change could take
a long period of
time.
• People with higher
incomes would not
prefer to travel in
public transport.
2. The use of energy-
saving products at
home
3. The use of energy
saving products
like- Led lights help
reduce the footprint
of an individual and
if done at a large
scale it would make
a large difference in
bringing down the
Ecological
footprint.
4. People are not
generally aware of
such products
especially in
villages with people
of the lower income
segment.
4
“Reduce Your Ecological Footprint | Climate Protection.” RESET.to,
en.reset.org/act/reduce-your-ecological-footprint-0.
28. 28
3. Save Water • Taking shorter
showers will save
water and reduce
the energy needed
to heat water.
• Wasting less water
will not endanger
the livelihood of the
future generation
therefore resulting
in a reduction in the
footprint and
impact on nature.
• The average
person takes a
shower for 8.2
minutes which uses
up to 65.1 liters.
This is an
immensely large
amount. If this is
reduced,
collectively it would
help reduce the
ecological footprint
in a large way but
this could take a
long period of time.
29. 29
Bibliography:
• Davis, Andrew, and Garrett Nagle. Environmental systems and societies:
supporting every learner across the 1IB continuum. Pearson Education, 2015
• “Lifestyle Factors that Contribute to My Carbon Footprint - Sustainability Post.”
NASPA, www.naspa.org/constituent-groups/posts/my-carbon-footprint.
• Eedula, Jagan. “Mahendra Pur.” ONEFIVENINE.com,
www.onefivenine.com/india/villages/Tehri-Garhwal/Jaunpur/Mahendra-Pur
• “The Free Automatic Bibliography Composer.” EasyBib, Chegg,
www.easybib.com/.
