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KAYA IDENTITY: ASSESSING THE FUTURE OF CO2 EMISSIONS AND OIL & GAS CONSUMPTION 1

Introduction

The Kaya identity is a mathematical model that is used to forecast future carbon dioxide

emissions through the interrelation of key human aspects that significantly affect climatic

conditions. In its simplest form, the model is expressed as;

CO2 Emission = Population * GDP * Energy Intensity * Carbon Efficiency

According to the expression, the model is aimed at calculating the total carbon dioxide

emissions globally as a product of the four inputs. However, the model is dynamic and can

accommodate both intensive extensive parameters where the extensive qualities can be

expressed as;

CO2 Emission = Population * (GDP/Population) * (Energy Consumption/GDP) * (CO2 Emissions/

Energy Consumption)

The intensive qualities can therefore be expressed as;

CO2 Emission =Population * Per Capita GDP * Energy Intensity of GDP * Carbon Intensity of

Energy

All inputs are measured on a global scale but can also be calculated on a national or regional

level where either of the variants of the formula may be used depending on the data available.

It is evident from the intensive parameters that there are four pertinent inputs that form the

framework of the model namely; Population, Per Capita GDP, Energy Intensity of GDP and

Carbon Intensity of Energy. This report seeks to evaluate these four components of the Kaya

Identity to determine their implications on future global carbon dioxide emissions in deference

to future oil and gas consumption trends.


Population

As an inherent component of the Kaya Identity, population has a significant impact on

CO2 emissions primarily because it is positively correlated to energy consumption which

includes the utilization of oil and gas. According to the United States Census Bureau, the global

population is currently estimated at 6.9 billion, which is proximal to the United Nations

estimate of 7 billion. However, there has been a gradual decline in the population growth rate

from the 2.2% average in the late 20th century to 1.1% in 2011 (World Bank, 2011). As a

multiplier in the Kaya Identity, the population size and population growth rate does not have a

significant impact on the historical CO2 emissions as evidenced in Figure 1 (Appendix A). In

reference to the chart, a relationship between the population growth rate and CO2 emissions

cannot be established, a veracity that is vindicated in Figure 2 which indicates the absence of a

direct correlation between CO2 emissions and populations of the nations with the highest

emissions globally (Figure 2, Appendix A).

Bradshaw et al. (2010) also provide scholarly evidence to the lack of dependence

between the population growth rate/size and CO2 emissions. Using scatter plots, the authors

consider 228 countries with respect to population growth rate and their relative impact on the

environment. The results of their research revealed a slight negative correlation between

environmental impact and population growth, a weak positive correlation between total

population size and environmental impact, but a strong positive correlation between

population density and environmental impact. In line with the data presented, it is arguable

that cumulative emissions are largely contingent upon urbanization, industrialization and


economic expansion, rather than population size or population growth rate (World Bank, 2011).

Case in point is a low income, high fertility country such as Burundi which has a 3.5%

population, a 6.8% urbanization rate and an urban population of 10% growth rate.

Consequently, as of 2005 Burundi had cumulative CO2 emissions of 6.4 megatons (Mt) from

1850, which accounted for 0.00% of the total CO2 emissions globally (Barker et al, 2010).

The implications of population on future global carbon dioxide emissions and future oil

and gas consumption trends can only be assessed in regard to urbanization and industrialization

(Duncan, 2001). Rapid developing countries such as the BRIC countries have high rates of

urbanization and industrialization, which also increases the income levels (Bradshaw et al,

2010). Undeveloped and high income countries on the other hand have low rates of

urbanization and industrialization, implying that the rate of emission from developed countries

will peak and maintain a definite level, while undeveloped nations ceteris paribus, will likely

increase their emissions as they become urbanized (Duncan, 2001). Considering the global

population dynamics ‘as is' it is deducible that there will be an increase in future global CO2

emissions and an increase in future oil and gas consumption trends as more countries become

urbanized and industrialized, both of which are bolstered by the current global population

growth and population density (World Bank, 2011).

Per Capita GDP

The GDP per person is an estimated standard of living at a macro level that is obtained

by dividing the market value of the final goods and services produced by a country (Gross

domestic product) by the country’s population. Depending on the scope of analysis, the per


capita GDP can not only represent the GDP per person on a national scale, but also on a

regional and/or global scale as well. Since the beginning of the 21st century, developed nations

have utilized technology such as wind, biofuels and solar to considerably improve their energy

efficiency which has resulted in a substantial reduction in emissions. Conversely, an increasing

per capita GDP and a high population have increased the consumption of oil and gas which has

negated the advances attained through CO2 efficiency and fuel substitution (World Bank, 2011).

According to Daryl & Harvey (2010), wealth-led consumption attributed to high per

capita GDP is the leading kernel to cumulative emissions and existing elevated emission rates

(p. 515). The authors assert that countries with a high per capita GDP of more than $20,000

such as OPEC countries exhibit a higher propensity for energy use as a result of cheap oil and

gas prices which invariably leads to higher CO2 emissions (Daryl & Harvey, 2010). Using a scatter

plot, the authors show a strong relationship between per capita GDP and energy use by plotting

energy use per capita against GDP per capita. A 2011 report by the World Bank argues that

access to cheap fossil fuel is a key determinant of wealth of which wealth is the primary driver

for energy consumption and emissions (Word Bank, 2011 p.309). A comparative analysis of

energy use per city or family unit also shows a strong relationship between GDP per capita and

energy consumption.

The inference of GDP per capita on future global carbon dioxide emissions is that there

is a close positive correlation between wealth and energy consumption which underscores the

apparent association CO2 emissions per capita and GDP per capita. An evaluation of historical

data from leading emitters indicates that wealthy countries with a high GDP per capita utilize

higher volumes of oil and gas which conversely perpetuate CO2 emissions (Duncan, 2001). The


data analyzed by Daryl & Harvey (2010) from more than 200 countries and regions including

Euro zone OECD lacks any negative correlation between high GDP per capita and decreasing

energy use and emissions that would be predicated on the Environmental Kuznets Curve theory

(Barker et al, 2010). The theory postulates that economic growth leads to the concurrent

utilization of human rather than capital resulting in decreased energy consumption and

emissions. However, the data examined by Daryl & Harvey and the World Bank contradict this

theory suggesting that future oil and gas consumption will increase at a rate relative to the

increase in GDP per capita. Since population growth is a parameter in determining GDP per

capita as per the Kaya identity, it has a secondary impact on energy consumption and

emissions. It is therefore conceivable that rapid developing countries with a high population

rate/size and a significantly higher GDP such the BRIC countries require increased production

which will necessitate increased energy consumption (World Bank, 2011). Therefore according

to the GDP per capita factor of the Kaya identity, the consumption of oil and gas as well as CO2

emissions will increase in the future as more countries develop and increase production to

address the consumer demand created in the local and global markets.

Energy Intensity

Energy intensity of the economy is the quantification of energy efficiency within the

economy and is expressed as units of energy consumed per dollar of GDP. It is expressed as a

ratio of primary energy consumption relative GDP (in U.S dollars) measured at purchasing

power parity (Bradshaw et al, 2010). High energy intensity implies that the cost of converting

energy into GDP is substantial whereas low energy intensity indicates the reverse. Two of the


main drivers of energy intensity are standard of living (wealth) and weather conditions (Barker

et al, 2010). A high standard of living dictates that an economy consumes additional oil and gas

through the production of diverse consumer goods, occupation of more housing units that

require heating, ventilation and electricity and the use of automobiles rather than public

transport (Daryl & Harvey, 2010). Weather conditions also influence energy consumption where

cold or hot seasons or climates increase the demand for heating or cooling systems for

households and workplaces which require gas or oil. Consequently, economically productive

countries or regions with temperate climates such as central Europe that also have proximal

demographic patterns and energy efficient technology for instance Germany and Switzerland

have lower energy as compared to countries that do not meet the aforementioned parameters

(Bradshaw et al, 2010). In addition, countries with undeveloped energy industries as well as

countries that encourage energy efficient lifestyles such as Australia also record lower energy

intensity (World Bank, 2011).

For instance the United States Energy Information Administration reported that the

country consumed approximately 99.7 quadrillion British thermal units (BTUs) of energy in 2004

while the GDP was reported at $11.75 trillion the same year, with a GDP per capita of $40,100.

The US Census Bureau placed the country’s population at 290,809,777, thereby giving the

country energy Intensity of 8,553 BTUs (World Bank, 2011). This implies that in 2004, the U.S

economy consumed 9 Megajoules (MJ) in order to produce one dollar of GDP hence an energy

intensity of 9MJ/$.Various nations have significantly higher or lower energy intensities. In

reference to Enerdata and the statistical energy review for 2010, OECD countries had an energy

intensity of 30 kilograms of oil equivalent per dollar (koe/$) while the U.S reported an energy


intensity of 34 koe/$. Japan and the European Union had 24 koe/$ with Latin America also

showing a relatively low intensity of 28 koe/$. Commonwealth of Independent States recorded

the highest energy intensity of approximately 70 koe/$, with Africa and Middle East also

reporting high intensities of 50 koe/$ and 52 koe/$, with the energy intensity in Asia being

recorded at 44 koe/$ (Barker et al, 2010).

Global trends from 2006 to 2009 indicate that indeed most countries have reduced their energy

intensities which are indicative of the development and adaptation better energy efficiency

methods and technologies. In 2006, the global energy intensity in terms of oil was reported as

40 koe/$ but in 2009, this figure had dropped to 38 koe/$ with most developed and developing

countries contributing to the decline in global energy intensity (Table 1, Appendix B). According

to the table, all of the countries with high energy intensities are countries that are involve in the

production of oil and gas. Uzbekistan is the country with the highest energy intensity which can

be attributed to its continental climate with extreme hot and cold seasons as well as poor

infrastructure necessitating the excessive use of energy to produce a dollar of GDP (World

Bank, 2011). With respect to energy intensity, it is evident that future oil and gas consumption

trends are likely to decline or remain consistent as more countries derive the dollar value of

GDP from lower volumes of oil and gas. With the introduction of technology to reduce

emissions as well as substitution of fuel, future global carbon dioxide emissions will decline in

line with the decreasing or consistent use average volumes of oil and gas globally.


Carbon Intensity of Energy

Carbon intensity of energy is defined as the amount of carbon dioxide emissions by

weight that results from each primary unit of energy produced and is expressed as a ratio of the

generated CO2 emissions relative to primary energy production. The basic unit of carbon

intensity is weight of carbon per BTU of energy (Barker et al, 2010). In the analysis of one fossil

fuel, the carbon intensity and the emissions coefficient are equal, while the analysis of different

fuels requires the weighting of all emissions coefficients by their energy consumption levels to

yield the carbon intensity. Historically, the carbon intensity trend has been declining, with a

trend analysis indicating that the decline can be projected into the future (Daryl & Harvey,

2010). In addition, endogenous advances in technology and fuel efficiency have ameliorated

energy consumption through investment cycles by substituting fossil fuels with renewable

sources of energy such as nuclear, LED and solar. By decomposing the carbon intensity trends

using the Kaya identity it is possible to quantify changes to baseline in energy intensity and GDP

in order to set mitigation targets.

The European Union is among the regions with the lowest carbon intensity despite

being highly industrialized and an importer of oil and gas. In 2007, the region reported a 5%

decline in carbon intensity of energy from 1990 and a 0.3% annual decline in CO2 emissions

despite a 2.3 % annual increase in GDP (Barker et al, 2010). The U.S on the other hand has

recorded an average of a 0.5% increase in CO2 emissions since 1995 before recording an

average of 0.6 % decline in emissions. Comparatively, the Europe reduced its CO2 emissions per

capita from 8.7 tonnes in 1990 to 7.8 tonnes in 2007 which is approximately a 10 % decline in

CO2 emissions within a period of 17 years. Globally the carbon intensity of energy has


decreased by 40 % since 1990 largely due to the utilization of low-emission energy carriers

which resulted in a 2.3% decline in carbon intensity per unit of GDP from 1990 to 2007, a

decline rate that is higher than the energy intensity of 1.4% for the same period (Barker et al,

2010). The implications of carbon intensity of energy on future global carbon dioxide emissions

is therefore clear, global emissions have been on the decline are projected to remain so for the

foreseeable future. In deference to future oil and gas consumption trends, the carbon intensity

of energy does not indicate any positive or negative implications, rather it underscores that the

increase use of technology and energy efficiency models will reduce emissions regardless of the

rate of oil and gas consumption or the use of alternative energy sources (Daryl & Harvey, 2010).

Conclusion

Trends in each of the four major Kaya Identity components can be assessed individually.

The current population growth rate/size suggests that there will be an increase in future CO2

emissions as well as oil and gas consumption since the rise in population and a high life

expectancy will create additional demand for energy. The increase in global GDP as more

countries become industrialized in addition to the current 50% global urbanization rate will also

increase global CO2 emissions, though income growth may also drive counterbalancing

decrease in carbon intensity of energy and/or global energy intensity of GDP. The decreasing

energy intensity and carbon intensity of energy globally indicate that the use of technology and

alternate sources of energy will reduce the CO2 emissions in future but the consumption of oil

and gas is still expected to remain constant according to the energy intensity component.

However, prices of the various types of energy, technological advancements and the global


production framework will ultimately have an impact on GDP, carbon intensity and energy

intensity thereby dictating the rate of CO2 emissions and consumption of oil and gas in future.


Appendix A: Charts

Figure 1: Chart showing the growth rate in population and CO2 emissions for a period of 25 years (1980 to 2005) among nations with different per capita incomes. Data sourced from: Satterthwaite, D. (2009). The implications of population growth and urbanization for climate change. Environment and Urbanization, 21(2), 545–567.

Figure 2: Chart showing population growth rate relative to CO2 emissions from 1980 to 2005 in countries with the highest global emissions. Data sourced from: Satterthwaite, D. (2009). The


implications of population growth and urbanization for climate change. Environment and Urbanization, 21(2), 545–567.

Appendix B: Tables

Country 2006 2007 2008 2009Africa 52 52 50 50Algeria 28 30 30 32Argentina 30 30 28 28Asia 46 44 44 44Australasia 36 36 36 36Australia 36 36 36 36Belgium 34 32 32 30Brazil 28 28 26 26Canada 46 46 44 42Chile 30 28 28 28China 64 60 56 56CIS 78 72 70 70Colombia 18 16 16 18Czech Republic 42 38 38 38Egypt 36 36 36 36EU-27 26 26 24 24Europe 26 26 24 24Finland 44 42 40 40France 28 28 28 26Germany 26 24 24 24India 42 40 40 40Indonesia 48 48 48 48Iran 50 50 50 48Italy 22 20 22 20Japan 26 26 26 24Kazakhstan 88 84 86 90Kuwait 42 42 42 48Latin America 28 28 28 28Malaysia 42 44 42 44Mexico 26 26 26 28Middle-East 52 52 52 52Netherlands 26 26 26 26New Zealand 34 32 32 34Nigeria 80 78 76 72North America 38 36 36 36


Norway 26 24 24 24OECD 30 30 30 30Poland 36 34 32 30Portugal 22 22 22 22Romania 36 34 30 28Russia 74 68 66 64Saudi Arabia 58 58 60 64South Africa 62 62 62 62South Korea 38 38 38 38Spain 24 22 22 22Sweden 34 32 32 30Taiwan 58 56 54 56Thailand 46 44 44 46Turkey 22 24 22 22Ukraine 98 90 86 88United Arab Emirates 42 44 48 50United Kingdom 22 20 20 20United States 36 36 36 34Uzbekistan 174 160 152 146Venezuela 44 42 40 42World 40 40 38 38

Table 1: Table showing the energy intensities of different countries and regions in kilogram(s) of oil equivalent per dollar (koe/$). Data sourced from: Enerdata. (2010). Yearbook Statistical Energy Review 2010: Energy intensity of GDP at constant purchasing power parities. Retrieved on 27 December 2011 from http://yearbook.enerdata.net/2009/energy-intensity-GDP-by-region.html

References

http://yearbook.enerdata.net/2009/energy-intensity-GDP-by-region.html


Barker, T., et al (2010). The Economics of Low Stabilization: Model Comparison of Mitigation

Strategies and Costs. The Energy Journal, 31(1), 11-48.

Bradshaw C.,J., Giam, X., & Sodhi, N., S. (2010). Evaluating the Relative Environmental Impact of

Countries. PLoS ONE 5(5). Retrieved on December 27 2011 from

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0010440

Daryl, L & Harvey, D. (2010). Energy and the new reality 1: energy efficiency and the demand for

energy services. Oxford: Earthscan.

Duncan, R., C. (2001). The Peak of World Oil Production and the Road to the Olduvai Gorge.

Population and Environment. Springer, 22(5), 503–522.

World Bank (2011). World Development Indicators 2011. Washington, DC: World Bank

Publications.

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