CO2 Emissions and Drivers (Kaya Decomposition)

This dataset contains the annual historical series of CO2 Emissions and Drivers ( Kaya Decomposition) from 1971-2020

Note:

Identifying drivers of CO2 emissions trends

This table presents the decomposition of CO2 emissions into four driving factors following the Kaya identity1, which is generally presented in the form:

Kaya identity

C = P (G/P) (E/G) (C/E)

where:

"C = CO2 emissions;

P = population

G = GDP

E = primary energy consumption"

"The identity expresses, for a given time, CO2 emissions as the product of population, per capita economic output (G/P), energy intensity of the economy (E/G) and carbon intensity of the energy mix (C/E).

Because of possible non-linear interactions between terms, the sum of the percentage changes of the four factors, e.g. (Py-Px)/Px, will not generally add up to the percentage change of CO2 emissions

(Cy-Cx)/Cx. However, relative changes of CO2 emissions in time can be obtained from relative changes of the four factors as follows:"

Kaya identity: relative changes in time

Cy/Cx = Py/Px (G/P)y/(G/P)x (C/E)y/(C/E)x

where x and y represent for example two different years.

In this table, the Kaya decomposition is presented as:

"CO2 emissions and drivers

CO2 = P (GDP/P) (TES/GDP) (CO2/TES) "

where:

"C = CO2 emissions;

P = population

GDP/P = GDP/population *

TES/GDP = Total primary energy consumption per GDP *

CO2/TES = CO2 emissions per unit TES"

* GDP in 2015 USD, based on purchasing power parities.

"The Kaya identity can be used to discuss the primary driving forces of CO2 emissions. For example, it shows that, globally, increases in population and GDP per capita have been driving upwards trends in CO2 emissions, more than offsetting the reduction in energy intensity. In fact, the carbon intensity of the energy mix is almost unchanged, due to the continued dominance of fossil fuels - particularly coal - in the energy mix, and to the slow uptake of low-carbon technologies.

However, it should be noted that there are important caveats in the use of the Kaya identity. Most important, the four terms on the right-hand side of equation should be considered neither as fundamental driving forces in themselves, nor as generally independent from each other."

Dataset Identifier

co2-emissions-and-drivers-kaya-decomposition@kapsarc

Source

KAPSARC Data Portal

Downloads

Themes

Climate

Keywords

CO2 Emission, CO2 Emissions, Kaya, Emissions, Emissions

License

CC BY-4.0

Language

English

Modified

November 6, 2024 11:40 AM

Publisher

International Energy Agency

Reference

https://www.iea.org/data-and-statistics/data-product/greenhouse-gas-emissions-from-energy-highlights

Last processing

December 8, 2024 10:08 AM (metadata)

November 6, 2024 11:38 AM (data)

Semantic Metadata

INSPIRE

DCAT

Accrual periodicity

Annual

Temporal

1971-2020

Dublin Core

DCAT-AP High Value Datasets (HVD)

Attachments

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Dataset schema

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Year

No description available for this field.

Name (identifier)	year
Type	date
Sample

Region/Country

No description available for this field.

Name (identifier)	region_country
Type	text
Sample

Type

No description available for this field.

Name (identifier)	type
Type	text
Sample

Value

No description available for this field.

Name (identifier)	value
Type	decimal
Sample

JSON Schema

The following JSON object is a standardized description of your dataset's schema. More about JSON schema.

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CO2 Emissions and Drivers (Kaya Decomposition)

Semantic Metadata

INSPIRE

DCAT

Dublin Core

DCAT-AP High Value Datasets (HVD)

Attachments

Dataset schema

JSON Schema

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