extended essay final draft

EVS

EXTENDED ESSAY

Can Personal Carbon trading (PCT) be an effective solution in Reducing Greenhouse Gas (GHG) Emission in

Mumbai?

Anupriy Kanti

Candidate Number: 001425-027

Dhirubhai Ambani International School

Word count: 3936

Anupriy Kanti Candidate Number – 001425‐027

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ABSTRACT One of the biggest unsolved crisis today is of the changing climate due to the continuous (and rising) anthropogenic input of carbon dioxide in the atmosphere. Efforts to mitigate this climate change by various governmental movements and policies around the world and within a country, state, or city do not seem to be able to counteract the problem. Mumbai local government up till now has focused on cleaning of wastes and sewages with few policy enforcements on vehicular air pollution. Mechanisms such as Kyoto and the EU ETS though manage Emission Trading between companies; their focus only is limited to the upstream users leaving a policy gap on individual emission. The current untried proposal by UK research teams of Personal Carbon Trading (PCT) of managing one’s carbon footprint is being studied upon. PCT overcomes the economical drawbacks of adapting to a lower carbon economy by inducing a behavioural change in energy usage. Thus the question comes: Can PCT be an effective solution in reducing Greenhouse Gas emission in Mumbai? The effectiveness has been assessed by taking in considering the adaptability of PCT to Mumbai’s economic structure and its acceptability. For research purpose, 5 Income Groups were formed (with Group 5 earning the highest). Survey was then taken to see CO2e (Carbon Dioxide equivalent) emission of 100 families in Mumbai from different Income Groups and their response to the scheme. It was noted that there was a trend in the Income Group and their emission level. Considering the theoretical literature and discussion of working of PCT in Mumbai, a conclusion was drawn about the scheme that it will be an effective solution to the emission problem in Mumbai. This research was evaluated for effectiveness and hurdles taking in account the unexplored parameters and assumptions.


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PAGE CONTENTS

Table of Contents ACKNOWLEDGEMENT ..................................................................................................................... 4

Introduction..................................................................................................................................... 5

Current Scenario.............................................................................................................................. 6

Carbon Trading: Global Green......................................................................................................... 8

A need for 'new thinking' ‐ Personal Carbon Trading.................................................................... 11

Personal Carbon Trading: Through Economist's eyes ................................................................... 13

Mumbai: Can it work? ................................................................................................................... 15

Working of PCT in Mumbai............................................................................................................ 20

Conclusion ..................................................................................................................................... 24

Evaluation...................................................................................................................................... 26

BIBLIOGRAPHY............................................................................................................................... 27

APPENDIX ...................................................................................................................................... 28


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ACKNOWLEDGEMENT

First and foremost I would sincerely like to thank my Environmental Systems Supervisor, Mr. Authukurala, who despite his long absence due to a bypass surgery, was able to guide me through this project. I would also like to mention my gratitude to Tina Fawcett, Head researcher in UK on Personal Carbon Trading for Data collection techniques and Colonel Prakash Tewari for helping me get in touch with the Eminent Environmentalists and Personalities in this field. Special thanks to all families for the survey and friends who assisted me while collecting data. Finally, heartfelt thanks to my father, Mr. Anurag Kanti, whose unsatisfying quench for new knowledge not only got him to help me collect literature on PCT, give guidance and complete the Essay but further encouraged me to dwell further on this area for higher studies.


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Introduction

In the daily pollution reports in Mumbai, there is indication of high level of GHG in

the air. While being concerned about the alarming increase in air pollution in

Mumbai, the concept of Personal Carbon Trading came originally in UK where the

government has started considering it very actively. The idea of bringing down

carbon footprint1 through behavioral change at an individual level seemed intriguing

and, at the same time, applicable in a metropolitan like Mumbai, thus resulting in

this research paper investigating the effectiveness of Personal Carbon Trading in

Mumbai.

1 Measure of the impact individual has on environment by his activity in terms of the amount of GHG produced measured in units of CO2e (Carbon dioxide equivalent)


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Current Scenario

“In my view, climate change is the most severe problem that we are facing today,

more serious even than the threat of terrorism”

- Sir David King, Chief Scientific Adviser, UK, 2004

For the last two decades or so, the growing evidence of the increasing anthropogenic

activities and its co‐relation to the climatic change has bought the future of the

environmental stability to an alarming concern. While some futurologists and

scientists have already predicted a foreseen ‘Armageddon’ to be occurring in matter

of few decades if the ecological health keeps deteriorating at the similar pace, others

envisage it as having a irreversible mutational effect on the environment and

inevitably, us. Both the results strongly support the possibility of environmental

degradation and the need to design a method (framework to prevent) to reduce the

risk of this phenomenon.

The most observable and significant form of this threat is the emission of

Greenhouse Gases (GHG)2 out of which Carbon Dioxide (CO2) emission has been, by

far, the largest in the atmosphere. Recent meteorological researches found the

current global concentration of CO2 to be around 380 ppm (Parts per million) in

contrast to the pre‐industrial levels of 280 ppm3 still increasing at the rate of 1.5

ppm per annum4.

This increasing in the rate of CO2 emission is primarily due to the cancerous growth

of industries that let out this gas as a waste or a by‐product leading to ongoing

numerous environmental disasters like melting glaciers, rising sea levels, change in

2 Carbon Dioxide (CO2) , Methane (CH4) , Nitrous Oxide (N2O) , and other pollutant gases 3 (Intergovernmental Panel of climatic change 2006) 4 (Siveter 2005)


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weather pattern, ecosystem and biodiversity. Furthermore, the global temperature

is on the rise, and by 2100 will rise to a level around 1.4 ºC to 5.8 ºC. The probability

of these anticipated events is becoming higher.

This alarming crisis and its potential effects have further put pressure on

Government to come up with more effective solutions. United Nation Framework

Convention on Climate Change (UNFCC) has stated their main goal is to ‘prevent

dangerous anthropogenic interference with climate system’. The Royal Commission

on Environment Pollution (RCEP) in UK had set a 60% cut target in CO2 by 2050 but it

was based on capping the level at 550 ppm which no longer appears to be a feasible

objective5.

5 (RCEP report 2000)


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Carbon Trading: Global Green

European Union (EU) further in the European Council stated its goal to capping the

global temperature rise at 2 ºC, a cap which they believed to be the upper limit6 (also

called threshold). Internationally the Kyoto Protocol was put into force on 2006 after

being sanctioned by approximately 164 countries and was used as a policy

framework in which the member nations developed ‘green’ and energy efficient

projects in developing nations to offset their own emission by funding them in

exchange of their emission entitlement. This was the first development of Carbon

Trading, a scheme in which the ‘carbon’ entitlements allocated could be traded

between the Annex I countries7.

Though pollution is an international problem, its spatial growing nature makes it

more manageable if dealt nationally (or better yet – locally). India's high

concentration of pollution is not due to the absence of a sound environmental legal

regime, however, but due to a lack of environmental enforcement at the local level.

In 1992, India signed the United Nations Framework Convention on Climate Change

as a non‐Annex I country, meaning it is not obligated to reduce its emissions of

carbon and Greenhouse gases (GHG). India ratified the agreement in 1993. While

India recognizes the importance of reducing these harmful emissions, the Indian

government also places a high priority on economic development. However,

according to report by John Llewellyn Lehman Brothers, global economist, India’s

GDP would dip by 5% for every 2°C temperature rise8. Up until now, India was not a

signatory to the Kyoto Protocol that mandates specific commitments by countries to

reduce their emissions of greenhouse gases by an average of 5.2% below 1990 levels

by the agreed 2008‐2012 time frame. Between 1990 and 2001, India's carbon

6 The limit above which the minor alterations will lead to significant climatic changes. There have been scientific claims to support this, but the exact value fluctuates in different reports. 7 OECD – mainly EU countries 8( ‘Global warming may melt Indian economy’ 2007).


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emissions increased by an astonishing 61%, a rate surpassed only by China's 111%

increase during the same time period.

Figure 1 – Graph showing India’s rising emission

I

India's carbon emissions are expected to continue to increase throughout the

decade, offsetting the planned reduction in GHGs from the European Union and

other countries that plan to implement the Protocol's emissions cut requirements.

The rise in India's carbon emissions has been exacerbated by the low energy

efficiency of coal‐fired power plants in the country. India's contribution to world

carbon emissions is expected to increase in coming years, with an estimated average

annual growth rate between 2001 and 2025 of 3.0% in the EIA International Energy

Outlook 2003 reference case (compared to 3.4% in China and 1.5% in the United

States).

The absolute increase in emissions will partially be a function of the degree to which

coal is relied upon as a major energy source. If coal consumption is substituted by oil

and natural gas consumption, India's overall carbon emissions which is rising at

alarming rate, would be reduced9.

9 Though Natural gas and oil produce CO2 gas, they are more ‘cleaner’ than coal or LPG as in the process the methane gas is converted to CO2, which is less toxic and harmful to the environment.


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The problem of pollution does not stop at the national level. Major cities like Delhi,

Chennai, Kolkata, Mumbai etc. are often the culprits of being on the higher end of

the GHG emission spectrum because of the excessive energy dependence and need

for urbanization. Though India may take pride in having a low per capita emission (>

1 CO2 tonne annually), it is amongst the highest emitters in the world.

The rising population is one cause of the rising demand for energy. The largest

growth in global GHG emissions between 1970 and 2004 has come from the energy

supply sector (an increase of 145%). The growth in direct emissions10 in this period

from transport was 120%, industry 65% and land use, land use change, and forestry

40%.

The impact of climate change and urban development in Mumbai is a key factor in

increasing the coastal risk flood and rising sea‐ level11 making Mumbai the second

most vulnerable city by 2070 after Kolkata. In the meanwhile, a survey found that

transportation sector contributes to about 60 % of air emission load in Greater

Mumbai. Vehicular traffic contributes to about 54% of NOx emissions and 24% of

Particulate matter emissions in Greater Mumbai. Also ambient air quality,

particularly in respect to PM10 and NOx exceed the National Ambient Air Quality

Standards (NAAQS) in some areas12.

10 Direct emissions in each sector do not include emissions from the electricity sector for the electricity consumed in the building, industry and agricultural sectors or of the emissions from refinery operations supplying fuel to the transport sector 11 Assuming a mean sea-level rise of 1.6 feet by 2070 12 As per the URBAIR' study of 1992 – NOx is a GHG gas with a higher GWP than Carbon.


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A need for 'new thinking' ‐ Personal Carbon Trading

It was around the beginning of May 2007 when there was scientific report released

that was having a coverage all over the television and newspapers. According to this

report, the league of scientist had claimed the earth has reached its ‘tipping point’

and if no measure taken at this point of time, the change will be out of our hand.

Furthermore, this report was followed by the UK government announcement of it

missing its current target of 20% reduction by 2008.

Unquestionably, the problem is not in the aims and the intention but in the

strategies to achieve the carbon reduction. Efforts to mitigate climate change

through managing carbon emissions are now being prompting. Although the EU ETS

does tackle the indirect emissions of individuals from electricity use (charging power

generators), this still leaves a policy gap around direct and indirect emissions from

individuals13. ‘To tackle climate change requires a major transformation in the way

everyone thinks about energy.’ Behavioural change is needed to the basic level

where one can reduce our dependence on fossil fuels and move towards a ‘low‐

carbon‐economy’ by adopting the use of ‘cleaner’ energy.

Though it is one of the (only?) best solutions presently trying to balance national

economic developments and global environmental protection, the problem with

Carbon Trading is that it differentiates responsibilities by allotting different target

ranges (like 10% in Iceland but 8% reduction in the GHG emission in EU). Accordingly,

a logical basis of deciding emission quotas could be on a per capita basis. There

needs to be a scheme that involves the individuals rather than institutions alone. But

practically speaking no scheme without incentive is going to work. There needs to be

a scheme in parallel to the Carbon Trading System.

13 (Siveter 2005)


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Such a scheme is currently being researched and proposed by various

environmental‐economist teams in UK. The scheme is the mandatory introduction of

Carbon Allowances allocated on per capita basis by the government (or the

authority) of the country (or region) annually. All individuals receive an 'average'

number of Carbon Allowances decided on the basis of nation's emission target of

that year. These Allowance (units) gives an individual right to emit GHG gases to a

certain limit and are to be surrendered along with money while purchasing fuel or

energy. Thus, the emission rights are allocated directly to the end users of energy

rather than the producers. The End‐user who emits more than the quota permits

them to (and will need additional units) can 'buy' them from the end‐users who emit

less than they are allowed to (and have surplus units). This creates a carbon market

where individuals can buy or sell carbon units similar to the trading in foreign

exchange. Hence, this 'Personal Carbon Trading' (PCT) incorporates managing one's

carbon emission, providing market signals and incentive to adapt to low carbon‐

consumption at the same time14.

While PCT may seem as economic trading scheme which has fiscal potential, there is

a deeper issue of really understanding carbon budgets and how to manage them

through the behaviour change ‐ or what is known as 'carbon literacy' and implement

them in daily life. This culture of carbon literacy and awareness will require a shift

people's thinking and encourage them to make appropriate environmental decision

due to the monetary attachment. For instance, one may decide that it is better do

without a car while going to the grocery store as it not only saves money on the fuel

but also gives a way to 'earn money' from the surplus units that that remained from

being surrendered at a fuel station.

14 (Seyfang n.d.)


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Personal Carbon Trading: Through Economist's eyes

The idea of Carbon Allowances are for intra‐nation usage, along with the

international trading of Carbon Credits to reduce the carbon emissions from the

planet to a point when nation's right to pollute would be in proportional to the size

of its population. As PCT is currently only an untested theoretical scheme, the only

criteria to assess it are against the 3 'E's ‐ Equity, Efficiency and Effectiveness.

Criteria are –

a. Equity The concept of emission rights on per capita basis seems to have an

increasing political support. This is due to the assumed fiscal progressive

nature PCT bring in theory. ‘The rich’ (who emit more than average)

would need to buy allowances from ‘the poor’ if they wish to sustain their

more carbon‐intensive lifestyles15 thus redistributing the flow of wealth.

b. Efficiency Economically, there will be no need or concern about manipulation of

carbon prices by a governmental authority – its people’s own scheme.

Thus its efficiency lies in the accurate response to market demand and in

its appeal in setting a system where financial instruments are defined in

terms of energy usage – and not price.

c. Effectiveness As it is the quantity of energy or emission that is defined and not the

prices, the carbon budget and cap is a guarantee that target for reduced

15 (Thumim n.d.)


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carbon emissions will be met. (More about effectiveness in Mumbai: Can

PCT work?)

The primary purpose PCT is ‐ a means of reducing emissions of all GHGs that are

altering the climate. Thus, there needs to be a measure of Global warming Potential

(GWP) of each gas on basis of a known and a gas with known emission effect ‐ like

CO2 (GWP of which is taken as 1). Thus all the fuels can be depicted in their carbon

rating or Carbon dioxide equivalent (CO2e). For example, the GWP for methane is

21 and for nitrous oxide is 31016

An approximate guideline for some carbon rating of main forms of energy are shown

below

Translating Emission into Fuels17

1 Kg of CO2 = 1 Carbon Unit

Fuel Carbon Unit

Natural Gas 0.2 per kWh

Petrol 2.3 per kWh

Diesel 2.8 per kWh

Grid Electricity (Thermal) 0.6 per kWh

16 (Fleming n.d.) 17 (Fleming n.d.)The quantities in the table need to be used with caution as the table is modified to suit Indian forms of fuel consumption.


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Mumbai: Can it work?

Now one very innovative question comes in the mind. Can PCT work in Mumbai? Can

it bring down the unhampered emission that the local government has failed to

curb? The question may initially seem as a far‐fetched or a new way of trying to look

for a solution.

The collection and transportation of the huge amount of waste is a matter of

concern for Municipal Corporation of Greater Mumbai (MCGM). So far there have

been no other official steps taken except ‘Pollution under Control (PUC) certificates’

given to vehicles annually only after meeting emission standards.

However, taking in account of the rising CO2 concentration levels (approx. 380 ppm

at present); the current measures taken by the Mumbai government has been

inadequate to cap emission


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Figure 2 – Survey to see the variation of emission by different families

As earlier mentioned, 60% of air emission in Mumbai is due to the Transportation.

On basis of that, a survey was taken during this research on the transportation usage

of families from various sectors and its correlation with the amount of CO2 gas

emitted individually. The result of the survey18 is to a small extent surprising as it

shows a huge variation in the CO2 emission through transports only between the

people. This is to say that there seems to be the deviation from the mean average

emission (red line) is large.

18 The result is shown by the graph. Vehicular emission of 85 families (numbered from 1 to 85) was taken by calculating the average emission of a day and then deducing the annual emission by private transport. As the survey was based on an interview rather than actual testing, the statistics should be dealt with caution.


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For research purpose, the families that were surveyed were categorized in 5 Income

Groups as follows:

Income group Income range per annum

Group 1 < Rs 50000

Group 2 Rs 50000 ‐ Rs 250000

Group 3 Rs 250000 ‐ Rs 1000000

Group 4 Rs 1000000 ‐ Rs 2500000

Group 5 > Rs 2500000

Another survey was done to observe the trend in emission by each group:

Figure 3 – Survey to see the amount of emission by each Group

There is logic in believing that there is a relation between the social strata and the

level of CO2 emitted by them ‐ i.e. the richer the one is, the more one can afford

energy (fuels, private transport etc.) and thus more one pollutes. This trend is seen

in Mumbai, which is a Metropolitan city amassing of people from different Income


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Groups, where the emission by using energy is correlated to the income of the

family. However, the problem with this trend is that there is an uneven distribution

when individual emission is taken within each group:

Figure 4 – Survey to see the emission per capita in each Group

Clearly it is the Income Group 5 that seems to have the highest emitting levels per

person while the Income Group 1's emission per person is very low (this is also due

to the fact, that there are more people in Group 1 thus the average emission per

person is lesser).

This uneven growing pattern is due to the unrestricted allowance of emission. The

main problem that is caused due to this is that majority of the people do not keep an

account on their carbon footprint and thus on the effect on the environment as

there is no law imposing to curb this.


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Considering these pattern, it can be seen how important it is to reduce individual

carbon footprint. The British government has already been 'invoking moral duty and

placing the responsibility for reducing emissions on the purchasing behaviour of

individuals19. But a city like Mumbai, as a financial capital of India, needs to do this

while taking in the economic concerns as moving to a low‐carbon‐economy can be

costly. The moral concern for a beneficial environment has become a hindrance for

modern economic development. ‘People's consumption pattern and the trend is an

integral part of their socio‐economic sphere’20 and this sphere needs to be

fundamentally reconstructed if the consumption patterns have to become more

conducive to the environment ‐ i.e. there needs to be a unique balance between the

two concerns. This is where the concept of PCT can help Mumbai.

19 (ET ‐ Pollu‐shun 2007) 20 (Pollu-shun 2007)


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Working of PCT in Mumbai

While, analogous to its international counterpart, PCT has an advantage of reaching

out to all the income and occupational sectors. The general working of PCT as earlier

discussed can be modified to fit Mumbai's economic structure. Following up on the

UK's and the survey conducted for this research, each individual should be allowed

to emit some amount (that is to say, they have a right to use fuel to a certain

degree). The amount can be decided by the government by having a target GHG

emission annually and dividing it by the number of people in Mumbai.

So to have a general idea,

If the GHG emission level in the Mumbai that should be allowed is kept

approximately 20,000,000 tonnes of CO2e

And the approximate population is 13,300,000

Then emission allowed per capita‐ 20,000,000 / 13,300,000 = 1.5038 tonnes of CO2e

The allocation of these 'Carbon permits' by the local government to the people can

be done on the basis of registrations that can be possible at public places ‐ Post‐

office, nationalized banks, municipal offices etc.

Each individual in Mumbai then has a right to emit up to 1.5 tonnes of CO2e per

annum and is given an equal number of ‘permits’ with each permit allowing certain

amount of GHG (1 Kg of CO2e) to be emitted. The total number of ‘permits’ issued

by the local government would have to be such that it does not allow emission to

exceed a certain limit and thus would cap the emission at that level. Every time one

has to make a carbon related purchase, they have to surrender the required number

depending on the carbon usage (GWP of the good) alongside money. In effect, due

to varying individuals’ need for energy, there will be individuals who would emit

more than allowed (Group 5) and would need to buy permits from those who emit


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less via a Carbon market which will be set up by the concerning government body to

make the transaction.

Figure 5 - Structure of Personal Carbon Trading 21

This Carbon Market is a Market maker (see above chart) which would get units

(permits) initially by bidding on the limited number of units the government auctions

and by buying from below‐limit emitters. The market would buy these units at a low

price and sell it to individuals (and organizations) who need more permits at a higher

price, thus becoming a centre for all the ‘trading’. Being similar to the working of a

bank, this can be done through computers, where one can have a ‘carbon’ account

to electronically make all the transactions. Thus, carbon units can be surrendered in

two ways –

1. Either units can surrendered by the means of a permit ‘card’

2. Or units can be surrendered by direct debit thorough the carbon account.

21(Tyndall n.d.).


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At the point of purchase, the permits are to be surrendered to the Energy Retailers.

If one does not have sufficient permits, one can pay purely be cash depending on

their market value at that time. Energy Retailer would provide the units need to

cover the purchase and charge the customer for them22.

For accounting purpose, the units would be passed up the supply chain and then

through the Primary Suppliers, be surrendered back to the Government.

To see the actual working, we envisage an example ‐

So if an individual (A) get 50 litres of petrol filled in car at petrol pump, he pays the

regular amount (Rs 51.5/ litre × 50) and 100 permits (1 litre produces approximately

2 Kg of CO2e, thus 2 × 50 = 100). If he does not have permits with him at that

moment, he can electronically pay through the permit card which could be swiped to

deduct from his account. But if he was in shortage of carbon units (perhaps being an

above‐limit emitter) he would have to buy those number of permits from the Carbon

Market, which could have bought those number of permits from another individual

(B) who perhaps recently installed Eco‐friendly CFL bulbs in his residence, thus selling

some of his permits that he saved.

Though this is an oversimplified situation, one must remember that the crucial point

here is that while the whole city has to manage within the limit set by the concerning

government. When A needs extra permits, he buys it from B (via Market) who had

more than need. Thus, the scheme makes the above‐limit emitters pay for the extra

pollution that they cause while rewarding the below‐limit emitters for being helpful

to the environment. This will create an incentive for both – for instance, A may

decide to be more economical in his fuel consumption (or perhaps change his mode

of transport) while B would decide to lower his carbon footprint and switching to a

solar powered water‐heater. By allowing to manage within the carbon allowance,

22 (Tyndall n.d.)


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PCT encourages adaption towards a lower carbon economy and reducing energy

demand through conservation and efficiency measure23.

23 (Seyfang n.d.)


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Conclusion

The main purpose of Personal Carbon Trading is to reduce emission of the

Greenhouse gases that is affecting the climate. To achieve that economical usage of

energy is very important but it cannot be a sustainable way of reducing GHG if

individuals are forced to reduce energy use through sanctions and taxes. It is only

possible on a long term basis by bringing ‘behavioral change’ through incentives for

restructuring their way of living for the better. As seen by the income group survey,

where the average emission per capita of Group 5 was disproportionately higher

than the other Groups, there is an immediate need for a policy like this to be

implemented. The rationale of PCT offers intangible benefits surrounding personal

involvement, responsibility and a shared sense of common purpose24.

Though this may seem far‐fetched due the complexity and sophistication of the

scheme to reach out to remote suburban parts and slums of Mumbai, one must

remember that with right enforcement and technical support, Personal Carbon

Trading can be put in use in the same fashion as credit cards. In a recent article the

demand forecast for credit card in India shows highest geographical distribution at

61.6% from the rural class25. This shows that people even from lower economic and

educational strata are not hesitant to use a modern techno‐financial instrument, if it

is to their economic benefit. PCT, if driven by ‘smart card’, is likely to be as

acceptable as credit card across various income groups if they understand benefits of

lowering carbon footprints and associated economic gains.

24 (Siveter 2005) 25 (Invest India Income and Saving Survey 2007)


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Figure 6 – Survey to see the views of the families on PCT

Here, the result of the survey shows that out of 100 families, 43 wanted would

except this scheme wholeheartedly. The purpose of the research was only to

examine whether or not PCT would be effective solution in reducing emission in

Mumbai. With proposal of the scheme to give surety in reduction and by the

response seen from the above survey26, it can be deduced PCT can be very effective

if implemented correctly.

Thus by effective usage of PCT, Mumbai’s emission level can be reduced. Hence PCT

not only prevents further pollution but may also reduce it to a safer level.

26 The survey was done on basis of interviews. Interview questions have been added in the appendix.


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Evaluation

The hurdle of this research lies in the fact that PCT is yet an untested scheme to

confirm the effectiveness. PCT can be seen a having a tremendous effect in the

emission pattern because theoretically on the long run, it succeeds in changing

individuals’ way of thinking about energy and induces a behavioural change in daily

energy consumption. Though it can assure of definite reduction in emission, due to

current lack of literature and research, it is difficult to estimate about the extent to

which it can be effective as the implementation of it needs to be considered not only

at individual level but also at the political level. Furthermore, there needs to be an

understanding of the aim and working of the scheme for it to work. The awareness

of PCT should reach the grassroots level in order to cap the rising emission in

Mumbai.


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BIBLIOGRAPHY " ‘Global warming may melt Indian economy’ ." Economic Times, 2007. Fleming, David. ‘Energy and Common purpose: Descending the Energy Staircase with Tradable Energy Quotas' . The Lean Economy Connection. Intergovernmental Panel of climatic change. "Fourth Assessment." 2006. "Invest India Income and Saving Survey 2007." Economic Times, 2007. "Pollu-shun." Economic times, 2007. "RCEP report." 2000. Seyfang, Gill. Personal Carbon Trading: Lessons from Complemebtary Currencies. Scheme policy, Centre of Social and Economic Research on the Global Environment. Siveter, Robert. Feasibility and Effectiveness of Personal Carbon Trading . PhD Thesis, Centre of Environment Policy, 2005. "4.2.4 Distributional impact, equity and justice." In A Rough Guide To Individual Carbon Trading, by Simon Roberts and Joshua Thumim. "Domestic Tradable Quotas." In Decarbonising UK- Energy for a Climate Conscious Future, by Tyndall.


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APPENDIX

TABLE TO SHOW THE NUMBER, NAME OF A MEMBER AND THEIR EMISSION THROUGH TRANSPORTATION AND ELECTRICITY CONSUMPTION

Family number

Name of a member from the family

Income group

Amount of Carbon emitted in tonnes in a day

by transport

Amount of Carbon emitted in tonnes

per annum by transport

Approximate electricity

consumption in the current

month

Average electricity

consumption per annum

Amount of Carbon

emitted in tonnes by electricity

Total Carbon

emitted in tonnes per annum

1 Akansh 4 0.01086 3.9639 348 4176 2.54736 6.51126

2 Allauki 4 0.00691 2.52215 367 4404 2.68644 5.20859

3 Kirtika 4 0.00299 1.09135 368 4416 2.69376 3.78511

4 Shalin 4 0.00979 3.57335 362 4344 2.64984 6.22319

5 Mou 5 0.03678 13.4247 850 10200 6.222 19.6467

6 Shashwata 4 0.01493 5.44945 401 4812 2.93532 8.38477

7 Elaisha 5 0.04313 15.74245 970 11640 7.1004 22.84285

8 Anupriy 4 0.01447 5.28155 427 5124 3.12564 8.40719

9 Jaidev 4 0.015 5.475 358 4296 2.62056 8.09556

10 Parth 4 0.01853 6.76345 300 3600 2.196 8.95945

11 Siddharth 5 0.02588 9.4462 1017 12204 7.44444 16.89064

12 Karan 5 0.02152 7.8548 703 8436 5.14596 13.00076

13 Niraj 4 0.00204 0.7446 365 4380 2.6718 3.4164

14 Nikunj 4 0.00493 1.79945 386 4632 2.82552 4.62497

15 Deep 3 0.00657 2.39805 229 2748 1.67628 4.07433

16 Harpreet 3 0.00493 1.79945 313 3756 2.29116 4.09061

17 Jayesh 2 0.00674 2.4601 296 3552 2.16672 4.62682

18 Neela 3 0.00657 2.39805 355 4260 2.5986 4.99665

19 Harshal 3 0.00958 3.4967 390 4680 2.8548 6.3515

20 Heenaa 2 0.00144 0.5256 237 2844 1.73484 2.26044

21 Xavier 2 0.00256 0.9344 233 2796 1.70556 2.63996

22 Joshi 4 0.01479 5.39835 435 5220 3.1842 8.58255

23 Indrajeet 2 0.00329 1.20085 273 3276 1.99836 3.19921

24 Mahil 2 0.00184 0.6716 253 3036 1.85196 2.52356

25 Mahsaleen 3 0.00184 0.6716 317 3804 2.32044 2.99204


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26 Sunni 4 0.01438 5.2487 369 4428 2.70108 7.94978

27 Anish 3 0.01102 4.0223 423 5076 3.09636 7.11866

28 Mohan 2 0.00418 1.5257 225 2700 1.647 3.1727

29 Ismail 2 0.00184 0.6716 245 2940 1.7934 2.465

30 Jeetika 3 0.00288 1.0512 209 2508 1.52988 2.58108

31 Gurani 2 0.0043 1.5695 237 2844 1.73484 3.30434

32 Bali 3 0.00674 2.4601 301 3612 2.20332 4.66342

33 Jhunjhunwala 2 0.00246 0.8979 248 2976 1.81536 2.71326

34 Tushar 4 0.00639 2.33235 501 6012 3.66732 5.99967

35 Jugnu 2 0.00209 0.76285 245 2940 1.7934 2.55625

36 Munhi 4 0.00986 3.5989 327 3924 2.39364 5.99254

37 Jyotika 3 0.00584 2.1316 281 3372 2.05692 4.18852

38 Malkani 4 0.00288 1.0512 387 4644 2.83284 3.88404

39 Kamlesh 2 0.0051 1.8615 240 2880 1.7568 3.6183

40 Sammi 3 0.00383 1.39795 244 2928 1.78608 3.18403

41 Kandpile 4 0.00958 3.4967 470 5640 3.4404 6.9371

42 Kapil 2 0.00647 2.36155 217 2604 1.58844 3.94999

43 Asturi 3 0.00598 2.1827 387 4644 2.83284 5.01554

44 Kothari 4 0.0137 5.0005 391 4692 2.86212 7.86262

45 Rishad 4 0.00538 1.9637 344 4128 2.51808 4.48178

46 Kishor 2 0.00314 1.1461 231 2772 1.69092 2.83702

47 Lassi 3 0.00164 0.5986 321 3852 2.34972 2.94832

48 Lokmanya 2 0.00394 1.4381 158 1896 1.15656 2.59466

49 Vivek 3 0.00368 1.3432 217 2604 1.58844 2.93164

50 Madhu 2 0.00382 1.3943 198 2376 1.44936 2.84366

51 Nanad 2 0.00657 2.39805 250 3000 1.83 4.22805

52 Madhulika 2 0.00164 0.5986 244 2928 1.78608 2.38468

53 Pande 4 0.01278 4.6647 601 7212 4.39932 9.06402

54 Thomas 4 0.02004 7.3146 450 5400 3.294 10.6086

55 Leonar 2 0.00345 1.25925 212 2544 1.55184 2.81109

56 Jaideep 4 0.00866 3.1609 325 3900 2.379 5.5399

57 Vohra 4 0.01438 5.2487 458 5496 3.35256 8.60126

58 Jaishree 3 0.01245 4.54425 300 3600 2.196 6.74025

59 Jitendra 3 0.01602 5.8473 334 4008 2.44488 8.29218

60 Sinha 2 0.00383 1.39795 243 2916 1.77876 3.17671


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61 Maulin 2 0.00762 2.7813 253 3036 1.85196 4.63326

62 Patnan 4 0.00975 3.55875 317 3804 2.32044 5.87919

63 Maya 2 0.00575 2.09875 199 2388 1.45668 3.55543

64 Geeta 2 0.00472 1.7228 223 2676 1.63236 3.35516

65 Kamal 2 0.00389 1.41985 237 2844 1.73484 3.15469

66 Usmanbhai 4 0.01065 3.88725 532 6384 3.89424 7.78149

67 Daraksha 2 0.00288 1.0512 215 2580 1.5738 2.625

68 Mahesh 4 0.01 3.65 373 4476 2.73036 6.38036

69 Laksa 4 0.01643 5.99695 373 4476 2.73036 8.72731

70 Milind 2 0.0046 1.679 214 2568 1.56648 3.24548

71 Ravikant 2 0.00575 2.09875 269 3228 1.96908 4.06783

72 Monica 4 0.01889 6.89485 423 5076 3.09636 9.99121

73 Lily 2 0.00736 2.6864 224 2688 1.63968 4.32608

74 Arora 3 0.00329 1.20085 302 3624 2.21064 3.41149

75 Ivan 5 0.0473 17.2645 698 8376 5.10936 22.37386

76 Mukhi 3 0.00418 1.5257 278 3336 2.03496 3.56066

77 Anuradha 3 0.01278 4.6647 237 2844 1.73484 6.39954

78 Prasad 2 0.00383 1.39795 198 2376 1.44936 2.84731

79 Shubham 2 0.00256 0.9344 221 2652 1.61772 2.55212

80 Agnijeet 5 0.02419 8.82935 890 10680 6.5148 15.34415

81 Neelu 3 0.00945 3.44925 324 3888 2.37168 5.82093

82 Binish 2 0.0186 6.789 184 2208 1.34688 8.13588

83 Aditya 2 0.00418 1.5257 230 2760 1.6836 3.2093

84 Rashmi 3 0.01278 4.6647 323 3876 2.36436 7.02906

85 Nigha 2 0.00383 1.39795 200 2400 1.464 2.86195

86 Sanjeev 1 ‐ ‐ 171 2052 1.25172 1.25172

87 Harun 1 ‐ ‐ 209 2508 1.52988 1.52988

88 Kaanta 1 ‐ ‐ 107 1284 0.78324 0.78324

89 Laksmi 1 ‐ ‐ 125 1500 0.915 0.915

90 Vaishali 1 ‐ ‐ 205 2460 1.5006 1.5006

91 Chhotu 1 ‐ ‐ 92 1104 0.67344 0.67344

92 Mupan 1 ‐ ‐ 189 2268 1.38348 1.38348

93 Warsha 1 ‐ ‐ 148 1776 1.08336 1.08336

94 Tannu 1 ‐ ‐ 240 2880 1.7568 1.7568

95 Peepu 1 ‐ ‐ 300 3600 2.196 2.196


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96 Kendhra 1 ‐ ‐ 126 1512 0.92232 0.92232

97 Vishal 1 ‐ ‐ 135 1620 0.9882 0.9882

98 Chandra 1 ‐ ‐ 181 2172 1.32492 1.32492

99 Samir 1 ‐ ‐ 210 2520 1.5372 1.5372

100 Faizan 1 ‐ ‐ 54 648 0.39528 0.39528


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TABLE TO SHOW THE NUMBER OF FAMILY, NAME OF A MEMBER, NAME OF THE CAR MODEL AND THEIR EMISSION BY EACH CAR

Family no.

Name of a member Car Mileage Daily Driven Amount of litre consummed

Amount of CO2 released (Kg)

1 Akansh Swift 9 42.5 4.722222222 10.8611111

2 Allauki Innova 12.5 17.5 3.92

Swing 10 13 1.3 2.99

3 Kirtika Zen 12.5 20 1.6 3.68

4 Shalin Camry 9 12 1.333333333 3.06666667

Octavia 8.55 25 2.923976608 6.7251462

5 Mou Innova 12.5 100 22.4

Maruti 16 100 6.25 14.375

6 Shashwata City 11.5 50 4.347826087 10

Indigo 14 30 2.142857143 4.92857143

7 Elaisha Carolla 8 100 12.5 28.75

Fusion 8 50 6.25 14.375

8 Anupriy Optra 8 45 5.625 12.9375

Alto 15 10 0.666666667 1.53333333

9 Jaidev City 11.5 75 6.52173913 15

10 Parth Swift 9 50 5.555555556 12.7777778

Ikon 8 10 1.25 2.875

Zen 8 10 1.25 2.875

11 Siddharth Ikon 8 50 6.25 14.375

Ikon 8 10 1.25 2.875

Zen 8 10 1.25 2.875

Zen 8 20 2.5 5.75

12 Karan Carolla 8 50 6.25 14.375

Accent 9 20 2.222222222 5.11111111

Esteem 11.3 10 0.884955752 2.03539823

13 Niraj Innova 12.5 10 0.8 1.84

City 11.5 1 0.086956522 0.2

14 Nikunj Indica 14 10 0.714285714 1.64285714

Indigo 14 20 1.428571429 3.28571429

15 Deep Optra 7 20 2.857142857 6.57142857

16 Harpreet Optra 7 15 2.142857143 4.92857143


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17 Jayesh Swift 9 10 1.111111111 2.55555556

City 11 20 1.818181818 4.18181818

18 Neela Indigo 14 40 2.857142857 6.57142857

19 Harshal Innova 12 50 4.166666667 9.58333333

20 Heenaa Optra 8 5 0.625 1.4375

21 Xavier Swift 9 10 1.111111111 2.55555556

22 Joshi Swing 10 50 5 11.5

Optra 7 10 1.428571429 3.28571429

23 Indrajeet Indica 14 20 1.428571429 3.28571429

24 Mahil Innova 12.5 10 0.8 1.84

25 Mahsaleen Innova 12.5 10 0.8 1.84

26 Sunni Optra 8 50 6.25 14.375

27 Anish Maruti 16 25 1.5625 3.59375

Maruti 16 25 1.5625 3.59375

Swift 9 15 1.666666667 3.83333333

28 Mohan City 11 20 1.818181818 4.18181818

29 Ismail Innova 12.5 10 0.8 1.84

30 Jeetika Optra 8 10 1.25 2.875

31 Gurani City 11.5 10 0.869565217 2

Swing 10 10 1 2.3

32 Bali Swift 9 10 1.111111111 2.55555556

City 11 20 1.818181818 4.18181818

33 Jhunjhunwala Indigo 14 15 1.071428571 2.46428571

34 Tushar Swift 9 5 0.555555556 1.27777778

Swift 9 20 2.222222222 5.11111111

35 City 11 10 0.909090909 2.09090909

36 Munhi Optra 7 5 0.714285714 1.64285714

Indigo 14 50 3.571428571 8.21428571

37 Zen 12.5 20 1.6 3.68

Maruti 16 15 0.9375 2.15625

38 Malkani Optra 8 10 1.25 2.875

39 Kamlesh Zen 12 1 0.083333333 0.19166667

Zen 12.5 10 0.8 1.84

Alto 15 20 1.333333333 3.06666667

40 Sammi Swing 10 10 1 2.3


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Alto 15 10 0.666666667 1.53333333

41 Kandpile Zen 12 50 4.166666667 9.58333333

42 Kapil Swing 10 25 2.5 5.75

Maruti 16 5 0.3125 0.71875

43 Asturi Zen 12.5 20 1.6 3.68

Swing 10 10 1 2.3

44 Kothari Zen 12.5 5 0.4 0.92

Swift 9 50 5.555555556 12.7777778

45 Rishad Octavia 8.55 20 2.339181287 5.38011696

46 Kishor City 11 15 1.363636364 3.13636364

47 Lassi Maruti 16 10 0.625 1.4375

City 11.5 1 0.086956522 0.2

48 Lokmanya Indigo 14 10 0.714285714 1.64285714

Swing 10 10 1 2.3

49 Vivek Zen 12.5 20 1.6 3.68

50 Madhu City 11.5 15 1.304347826 3

Indigo 14 5 0.357142857 0.82142857

51 Nanad Indigo 14 20 1.428571429 3.28571429

Optra 7 10 1.428571429 3.28571429

52 Madhulika Optra 7 5 0.714285714 1.64285714

53 Pande Swift 9 50 5.555555556 12.7777778

54 Thomas City 11 20 1.818181818 4.18181818

Indigo 14 10 0.714285714 1.64285714

Optra 8 5 0.625 1.4375

Swift 9 50 5.555555556 12.7777778

55 Leonar Swing 10 15 1.5 3.45

56 Jaideep Optra 7 20 2.857142857 6.57142857

City 11 10 0.909090909 2.09090909

57 Vohra Maruti 16 100 6.25 14.375

58 Jaishree City 11.5 10 0.869565217 2

Esteem 11 50 4.545454545 10.4545455

59 Jitendra Indigo 14 10 0.714285714 1.64285714

Optra 9 20 2.222222222 5.11111111

60 Sinha Optra 9 15 1.666666667 3.83333333

61 Maulin City 11 5 0.454545455 1.04545455


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Optra 7 20 2.857142857 6.57142857

62 Patnan Indigo 14 10 0.714285714 1.64285714

Innova 12.5 5 0.4 0.92

Maruti 16 50 3.125 7.1875

63 Maya Optra 8 20 2.5 5.75

64 Geeta Zen 12 15 1.25 2.875

Zen 12.5 10 0.8 1.84

65 Kamal Alto 15 1 0.066666667 0.15333333

Swing 10 10 1 2.3

Maruti 16 10 0.625 1.4375

66 Usmanbhai Zen 12.5 40 3.2 7.36

Indigo 14 20 1.428571429 3.28571429

67 Daraksha Optra 8 10 1.25 2.875

68 Mahesh City 11.5 50 4.347826087 10

69 Laksa Indigo 14 100 7.142857143 16.4285714

70 Milind Swing 10 20 2 4.6

71 Ravikant Zen 12.5 50 4 9.2

City 11.5 100 8.695652174 20

72 Monica Optra 7 50 7.142857143 16.4285714

Indigo 14 15 1.071428571 2.46428571

73 Lily Indigo 14 20 1.428571429 3.28571429

74 Arora Optra 8 100 12.5 28.75

75 Ivan Zen 12 10 0.833333333 1.91666667

Optra 7 100 14.28571429 32.8571429

Swing 10 10 1 2.3

Swift 9 40 4.444444444 10.2222222

76 Mukhi City 11 20 1.818181818 4.18181818

77 Anuradha Swift 9 50 5.555555556 12.7777778

78 Prasad Camry 9 15 1.666666667 3.83333333

79 Shubham Swift 9 10 1.111111111 2.55555556

80 Agnijeet City 11 100 9.090909091 20.9090909

Optra 7 10 1.428571429 3.28571429

81 Neelu Indigo 14 40 2.857142857 6.57142857

Maruti 16 20 1.25 2.875

82 Binish City 11 50 4.545454545 10.4545455


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Optra 8 15 1.875 4.3125

Zen 12 20 1.666666667 3.83333333

83 Aditya City 11 20 1.818181818 4.18181818

84 Rashmi Swift 9 50 5.555555556 12.7777778

85 Nigha Swift 9 15 1.666666667 3.83333333


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INCOME GROUP DETAILS AND RESULT OF THE SURVEY

Income group

Income range per annum Total Carbon emitted by the

Group

Average emission by a family in the Group

Average emission per capita in the Group

Group 1 < Rs 50000 18.24144 1.216096 0.304024

Group 2 Rs 50000 ‐ Rs 250000 45.30517 3.02034467 0.353947

Group 3 Rs 250000 ‐ Rs 1000000 70.16877 4.677918 0.87711

Group 4 Rs 1000000 ‐ Rs 2500000 96.02507 6.40167133 0.889121

Group 5 > Rs 2500000 110.09896 18.3498267 4.587457

TOTAL 339.83941 6.73317133 1.402332

DETAILS OF THE EMISSION IN EACH GROUP

Group 1

Group 2

Group 3

Group 4

Group 5

1.25172 4.62682 4.07433 6.51126 19.6467

1.52988 2.26044 4.09061 5.20859 22.84285

0.78324 2.63996 4.99665 3.78511 16.89064

0.915 3.19921 6.3515 6.22319 13.00076

1.5006 2.52356 2.99204 8.38477 22.37386

0.67344 3.1727 7.11866 8.40719 15.34415

1.38348 2.465 2.58108 8.09556

1.08336 3.30434 4.66342 8.95945

1.7568 2.71326 4.18852 3.4164

2.196 2.55625 3.18403 4.62497

0.92232 3.6183 5.01554 8.58255

0.9882 3.94999 2.94832 7.94978

1.32492 2.83702 2.93164 5.99967

1.5372 2.59466 6.74025 5.99254

0.39528 2.84366 8.29218 3.88404

4.22805 3.41149 6.9371

2.38468 3.56066 7.86262

2.81109 6.39954 4.48178

3.17671 5.82093 9.06402

4.63326 7.02906 10.6086


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3.55543 5.5399

3.35516 8.60126

3.15469 5.87919

2.625 7.78149

3.24548 6.38036

4.06783 8.72731

4.32608 9.99121

2.84731

2.55212

8.13588

3.2093

2.86195

TOTAL 18.24144 45.30517 70.16877 96.02507 110.099

AVERAGE 0.304024 0.353947 0.87711 0.889121 4.587457


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Interview questions asked to the families Q1. Are you familiar with the ideas of Personal Carbon Trading scheme? (If not, then it was explained briefly to them) Q2. Do you think this scheme feasible? Q3. Do you think it will be more beneficial to Mumbai than Carbon Tax? Q4. According to you, how many citizen/people are going to actively participate in this? Q5. What, according to you, are its weakness and its strength? Q6. Do you think it is a good way to reduce personal emission in the long run? Q7. Do you think that public/business class will accept it?

extended essay final draft

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