Decomposition of China’s Carbon Emissions Intensity from 1995 to 2010: An Extended Kaya Identity
International Journal of
Decomposition of China's Carbon Emissions Intensity from 1995 to 2010: An Extended Kaya Identity
Wei Li 0
Qing-Xiang Ou 0
Tadeusz Kaczorek
0 Department of Economic Management, North China Electric Power University , No. 689 Huadian Road, Baoding 071003 , China
This paper employs an extended Kaya identity as the scheme and utilizes the Logarithmic Mean Divisia Index (LMDI II) as the decomposition technique based on analyzing CO2 emissions trends in China. Change in CO2 emissions intensity is decomposed from 1995 to 2010 and includes measures of the effect of Industrial structure, energy intensity, energy structure, and carbon emission factors. Results illustrate that changes in energy intensity act to decrease carbon emissions intensity significantly and changes in industrial structure and energy structure do not act to reduce carbon emissions intensity effectively. Policy will need to significantly optimize energy structure and adjust industrial structure if China's emission reduction targets in 2020 are to be reached. This requires a change in China's economic development path and energy consumption path for optimal outcomes.
1. Introduction
Since reform and opening-up, China has become the second
largest economy in the world where rapid economic growth
was accompanied by rising energy consumption and
carbon emissions. From 1995 to 2010, China’s primary energy
consumption increased sharply from 1.50 to 3.75 billion ton
coal equivalents (tec). China’s carbon emissions continue to
grow rapidly correlating to the level energy consumption.
From 331.21 million tons in 1995 to 8782.58 million tons in
2010, China becomes the world’s biggest emitter of carbon
dioxide [
1, 2
]. But the country’s carbon dioxide emissions per
capita are also relatively high compared to other countries. In
order to actively respond to climate change and to develop
low carbon economy, China has an ambitious goal to reduce
carbon intensity by 40–45% by 2020, from 2005 levels [3]. In
the Twelfth Five-Year Plan of China, China aims to reduce its
energy intensity and carbon emission intensity by as much as
17% and 16% by 2015, respectively, from 2010 levels [
4
]. How
to control carbon emissions in China has become a focus of
policy makers. The way to decrease carbon emission intensity
has a significant impact on China’s economic development,
energy security, and environmental protection in the future.
Therefore, the analysis of factors affecting carbon emissions
intensity constitutes a vital part of low carbon economy.
Logarithmic Mean Divisia Index (LMDI) theory was first
proposed by Ang and Zhang and has over 10 years of
history [
5
]. Logarithmic Mean Divisia Index (LMDI) theory
has been widely used in analysis of energy and carbon
emissions because of its perfect decomposition, consistency
in aggregation, path independency, and an ability to handle
zero values [
6–9
]. In recently years, LMDI has been adopted
to study energy-related carbon emissions in different scale
levels based on different types of energy and sectors. Peters
and Hertwich, Greening et al., and Pani and Mukhopadhyay
study energy consumption and carbon emissions in the world
by utilizing LMDI model [
10–12
]. Greening et al. conduct
the secondary decomposition of CO2 emissions from sectors
[
13, 14
]. Based on completed decomposition technique, many
scholars study CO2 emissions in different countries, such as
Thailand [
15
], India [
16
], the United Kingdom [
17
], Turkey
[
18
], South Korea [
19
], Brazil [
20
], Greece [
21
], and Ireland
[
22
]. Completed decomposition technique is also applied to
research energy-related CO2 emissions in China [
23–30
].
Many of these researches are based on a small number of
kinds of energy and sectors, thereby decreasing the accuracy
of the accounting.
This paper utilizes LMDI model to study energy-related
carbon emissions intensity from 1995 to 2010 based on
different types of energy (such as coal, coke, crude oil,
gasoline, kerosene, diesel oil, fuel oil, and natural gas) and
sectors (such as primary industry, manufacturing industry,
electric power, gas and water production and supply industry,
construction industry, transportation, storage, postal and
telecommunications services industry, wholesale, retail trade
and food services industry, and other tertiary sectors). This
paper extends further the decomposition literature to China,
and aims to identify, quantify, and explain driving forces
(such as industrial structure, energy intensity, and energy
structure) acting to change carbon emissions intensity.
2. Decomposition Methodology
2.1. Extended Kaya Identity of Carbon Emissions Intensity.
Carbon emissions intensity is the carbon dioxide emissions
per capita. Kaya identity was f irst proposed by Professor
Yoichi Kaya on IPCC in 1990 [
31
]. The Kaya identity is as
follows:
=
×
GDP
× GDP × ,
where , , GDP, and denote carbon emissions, energy
consumption, gross (...truncated)