Decomposition Analysis Of CO2 Emissions Research Articles

LMDI decomposition analysis of CO2 emissions in Algeria during 2000-2019 and the role of energy policy in reducing emission

This study aims to determine the forces and factors driving the change in CO2 emissions in Algeria in 2000-2019. The analytical decomposition methodology used is the logarithmic mean Divisia index (LMDI), which enables us to know the role and magnitude of the impact of economic activity, structural changes, energy intensity, energy mix, and emission factors on the change in CO2 emissions. The results revealed that the total emissions are rising during the period 2000-2019 and that economic activity is the primary driving force for the increase in CO2 emissions in Algeria. Furthermore, the deterioration of energy efficiency and the trans- formation of the Algerian economy into an energy-intensive sector (the service sector at the expense of the industrial and agricultural sector), the energy intensity factor, and the economic structure factor did not help reduce the levels of CO2 emissions. Additionally, the energy mix factor contributed to a slight increase in emissions. In the context of following up on the im- plementation of the National Program for Renewable Energy and Energy Efficiency and its role in reducing the levels of CO2 emissions, it was found that the program failed to achieve its objectives during the first half of its implementation 2011-2020. These results indicate that public policymakers in Algeria should be strict in implementing the National Energy Program by 2030 by dissolving the conflict between economic growth and climate change policy

Decomposition analysis of CO2 emissions of electricity and carbon-reduction policy implication: a study of a province in China based on the logarithmic mean Divisia index method

Abstract As the proportion of electricity in final energy consumption gradually increases, CO2 emissions reduction actions in the power system will become the key to achieving China’s carbon-peak and carbon-neutrality goals. It is essential to analyse and quantify the driving forces of CO2 emissions from electricity generation in the fossil-rich area in China. This paper aims to identify the characteristics of CO2 emissions generated by electricity and provide a basis for formulating CO2-reduction policies in power systems. First, we analyse the current state of CO2 emissions from electricity generation in Anhui Province that was dominated by fossil energy during the period 2010–19. Then, we apply the logarithmic mean Divisia index method to find the nature of the factors influencing the changes in CO2 emissions. Finally, we analyse the CO2-reduction measures of each side of the source–network–load–storage of the power system in Anhui through a power-system carbon-reduction path analysis model proposed in this study and provide policy suggestions. The results showed the following. (i) CO2 emissions in Anhui Province continued to increase from 2010 to 2019 and the trend in the growth rate of CO2 emissions presented approximately a u-shaped curve. (ii) Economic activity has always been the dominant factor driving the growth of electricity CO2 emissions. The increase in the proportion of renewable energy in power generation, the improvement in thermal power-conversion efficiency and the decrease in the intensity of power consumption are the three major driving factors for the reduction in CO2 emissions from power generation in Anhui. (iii) The CO2-reduction measures of the power system are provided in each link of the source–network–load–storage, such as developing the photovoltaic industry and building energy storage, upgrading and transforming coal-fired power stations, reducing the loss rate of transmission lines on the grid side and improving the efficiency of the utilization of electricity on the user side.

Two-Dimensional Decoupling and Decomposition Analysis of CO2 Emissions from Economic Growth: A Case Study of 57 Cities in the Yellow River Basin.

Precise decoupling of CO2 emission and economic development holds promise for the sustainability of China in a post-industrialization era. This paper measures the energy-related CO2 emissions of 57 cities in the Yellow River Basin (YRB) during 2006–2019 and analyzes their decoupling states and dynamic evolution paths based on the derived general analytical framework of two-dimensional decoupling states to decompose their decoupling index using the LMDI method. The results show that (1) from 2006 to 2019, the economic growth and CO2 emissions of cities along the YRB are dominated by weak decoupling at an average contribution of 53.2%. Their dynamic evolution paths show fluctuations of “decoupling–recoupling” states, while the evolution trend is relatively ideal. (2) The factors of economic output, energy intensity and population scale inhibit the decoupling in most cities, which contribute 39.44%, 19.34%, and 2.75%, respectively, while the factors of industrial structure, carbon emission coefficient, and energy structure promote the decoupling in most cities in the YRB, with average contributions of −12.63%, −8.36%, and −0.67%, respectively. (3) The significant increase in the contribution of energy intensity is the main reason for the “Worse” path of cities, while the industrial structure and energy structure factors promote to the “Better” path of cities. This work satisfies the urgent need for the ecological protection of the YRB and opens new avenues for its high-quality development.

Decomposition Analysis of CO2 Emissions in Northeast China: Insights From Investment Factors

Global warming caused by carbon emissions is a central concern across the world. Given the immense contribution of Northeast China to total carbon dioxide emissions, this study explores the driving forces of carbon emissions in that region from the perspective of investment-related factors, applying a logarithmic mean Divisia index (LMDI) model. We assess the driving forces on carbon emissions using a temporal LMDI model and explore interregional differences using a spatial LMDI model. The main findings are as follows. First, the trajectory of investment evolution is consistent with the mitigation of carbon emissions, which indicates that investment-related factors have a significant impact on carbon emissions. Second, the region’s carbon emissions are mainly generated by industry in Inner Mongolia and Liaoning, which suggests that the industry structure in Inner Mongolia should be adjusted to improve its coal-based energy consumption. In Liaoning, in contrast, the investment efficiency effect is a major driving force, which suggests that the regional investment structure should be adjusted to generate a more significant and orderly momentum. Lastly, although the impact of industry structure on carbon emission mitigation has significantly increased over time in Northeast China, local policy needs to be updated regularly. In line with these findings, several potential suggestions are offered for the formulation of practical and appropriate guidelines by the regional government.

Decoupling and decomposition analysis of CO2 emissions from government spending in China

Exploring the role of government spending (GS) in CO2 mitigation is essential for achieving low-carbon development goals; however, the mechanism by which GS affects CO2 emissions remains unclear. The decoupling relationship between GS on energy-savings and environmental protection (GSP) and CO2 emissions in China from 2007 to 2019 was investigated. In addition to evaluating the temporal attribute of the decoupling state, the concept of a dynamic path of the decoupling state was proposed for the first time. Moreover, from the perspective of direct and indirect effects and decoupling elastic factors, the drivers of decoupling elasticity between GSP and CO2 emissions were analysed by developing two non-residual decomposition methods for the Tapio decoupling elastic index. Results based on 30 Chinese provinces showed that these provinces experienced either one or more of the decoupling states: weak, strong, expansive negative, and strong negative decoupling; however, most provinces experienced weak decoupling. Beijing, Tianjin, and Jilin were in the intensive dynamic path of the decoupling state, whereas other provinces remained in the extensive dynamic path. The energy intensity, energy-related carbon intensity, and GS structures of education contributed to the decoupling of GSP from CO2 emissions, however, GS intensity on capital-labour input delayed.

Decomposition Analysis of CO2 Emissions Embodied in the International Trade of Russia

Our study improves the decomposition method based on the input–output approach to analyze CO2 emissions embodied in the international trade of Russia over the period from 1995 to 2014. The research finds out that carbon was transferred from the upstream resource sectors to the downstream manufacturing sectors and service sectors in Russia. Moreover, Russia was a net exporter of CO2 emissions. 31.46% of Russia’s CO2 emissions were generated for other countries’ consumption in 1999 while 10.68% in 2013. Basic resource and energy sectors were the significant emitters of exporting CO2 emissions. Sectors from traditional manufacturing industries and modern technical industries played an important role in importing embodied CO2 emissions of Russia. Moreover, the effect of modern technical industries on importing embodied CO2 emissions was increasing. The period after 2003 witnessed a substantial decline in Russia’s carbon intensities, which was majorly due to the transformation of the energy structure. Decomposition analysis of CO2 emissions embodied in the international trade can show the trading effect on embodied CO2 emissions from both exporting and importing perspectives. Russia’s case is able to provide instructive implications to the global climate mitigation policy. Countries that burden CO2 emissions for other countries’ consumption are encouraged to participate in the climate negotiation effectively and internalize environmental costs by products’ and services’ pricing in the international trade.

Complete Decomposition Analysis of CO2 Emissions in the Health Sector in Portugal

This study uses the “Complete Decomposition” technique to examine the intensity of CO2 emissions in the health sector in Portugal over the period 1997–2014. Our results suggest that improvements in emission intensity in the health sector depend on the design of incentives of replacing fossil fuels with fuels from renewable energy sources and adopting measures to save energy. In addition, capital investment may also contribute to the reduction of the emission intensity in the sector, if the investment is applied to the acquisition of more efficient equipment. We identify areas for action and recommend that public and private sector health professionals should elevate energy efficiency to a top priority. Our results also highlight the importance of the Kyoto protocol.

Spatiotemporal Patterns and Decomposition Analysis of CO2 Emissions from Transportation in the Pearl River Delta

Controlling and mitigating CO2 emissions is a challenge for the global environment. Furthermore, transportation is one of the major sources of energy consumption and air pollution emissions. For this reason, this paper estimated CO2 emissions by the bottom-up method, and presented spatiotemporal patterns by spatial autocorrelation methods from transportation during the period 2006 to 2016. It further analyzed the impact factors of CO2 emissions in the Pearl River Delta by the Logarithmic Mean Divisa Index (LMDI)decomposition method. The results indicated that from 2006 to 2016, total CO2 emissions increased year by year. Guangzhou and Shenzhen were the major contributors to regional transportation CO2 emissions. From the perspective of different transport modes, intercity passenger transport and freight transport have always been dominant in the past 11 years. The results indicated that aviation transport was the largest contributor, and that travel by road was the second one. The CO2 emissions generated by rail and water transport were much lower than those from aviation. Private cars became the main source of urban passenger transport CO2 emissions, and their advantages kept increasing. The results indicated that the spatial agglomeration trend feature was negatively correlated, and the further the distance, the more similar the attributes. The cumulative contribution values of population, economic development, transport intensity, energy intensity and energy structure were all positive values, while the cumulative contribution values of transport structure and emission factor were negative. The findings of this study offer help for the scientific understanding of those CO2 emissions from transportation, and for adopting effective measures to reduce CO2 emissions and for the development of green transportation.

Decomposition Analysis of CO2 Emissions from Coal - Sourced Electricity Production in South Africa

ABSTRACTIn 2013, the electricity sector was the largest source of South Africa’s CO2 emissions, accounting for about 60% of its total. South Africa (SA) is one of the highest CO2 emitters on a per capita basis when compared to many developed and developing countries. For a better understanding of the driving forces leading the electricity-related CO2 emission per person, this paper applies the Log Mean Divisia Index (LMDI) to analyze the influence of the factors which ruled electricity generation-related CO2 emission in SA over the period 1990–2013. We focused on coal which is the dominant fuel used in SA for electricity generation. The results show that the electricity generation intensity effect plays the dominant role in decreasing CO2 emissions. However, the effect of economic activity is the major determinant that contributes to increasing CO2 emissions. In order to reduce its greenhouse gas emissions levels, meet the agreement of the COP21 agreement, and fight against CO2 emissions per-capita associated with electricity generation, it is recommended that SA’s government should improve the efficiency of its existing electricity power generation plants and expand more of its renewable energy sources (nuclear included).

A subsystem input–output decomposition analysis of CO2 emissions in the service sectors: a case study of Beijing, China

The carbon emissions in service sectors have attracted increasing attention around the world. However, few studies have examined the driving forces for CO2 emissions from service sectors in developing countries. With the process of accelerating industrialization, China’s service sectors are facing growing pressure to pursue energy savings and emission reductions, especially in several developed regions. In this paper, in order to better understand how CO2 emissions in Beijing’s service sectors have evolved, we utilized a subsystem input–output decomposition analysis to study the pattern and driving factors of consumption-based emissions in Beijing’s service sectors. The results showed that the transportation sector and the Scientific Studies Technical Services sector caused the most CO2 emissions in Beijing’s service sectors. The emission intensity effect potentially reduced CO2 emissions by 10,833 Mt, primarily due to the decreased energy intensity of non-service sectors. Effects of demand and technology were mainly responsible for the increased CO2 emissions in Beijing’s service sectors. Such influence was mainly related to the external component of service sectors, indicating a strong pull effect exerted by service sectors on non-service sectors. Thus, decarbonizing the supply chain of service sectors and improving the energy intensity are necessary to alleviate CO2 emissions in Beijing.

A decomposition analysis of CO2 emissions: evidence from Malaysia’s tourism industry

ABSTRACTThe most important question raised from issues of environmental degradation is how economic activities bring about changes that will result in pollution. In the pursuit of tourism economy, contrary to popular interest, the travel and tourism (T&T) industry may cause environmental damages through the emissions of carbon dioxide (CO2) from energy consumption in areas such as transportation and delivery of amenities. Given this major concern, this paper attempts to investigate the linkage between tourism and CO2 emissions in Malaysia between 1981 and 2011. In particular, this study fills the knowledge gap by taking a closer look at the impact of international tourist arrivals on CO2 emissions by sector – electricity and heat generation and transport. Results from the bound test method suggest that there exists a long-run relationship among the variables under consideration when CO2 emissions become the dependent variable. The original result is similarly robust to alternatives, which are CO2 emissions from sectors of electricity and heat generation and transport. Furthermore, the vector error correction model causality analysis indicates a causal relationship between tourism and CO2 emissions by transport and electricity and heat generation. Subsequently, several tourism-related policies are drawn from these findings.

The impact of energy efficiency and economic productivity on CO2 emission intensity in Portuguese tourism industries

This study employs the decomposition analysis of CO2 emissions for the period from 2000 to 2012. This technique computes five effects that drive changes in CO2 emissions in five subsectors of the Portuguese tourism industry. The energy over fixed capital, the capital over labour productivity, and the tourism intensity are the most important effects in accommodation, food and beverage services. The carbonisation index constitutes an important effect in transports. The capital over labour productivity intensity effect has the strongest influence, while the carbonisation index exerts a positive influence upon CO2 emissions in tour operators and travel agencies. The energy over gross fixed capital and tourism intensity effects predominate in cultural, sports and recreational services. The results of the econometric analysis further confirm the statistical significance of the aforementioned effects. Policy recommendations are provided.

A spatio-temporal decomposition analysis of energy-related CO2 emission growth in China

This paper presented a coupled decomposition analysis of CO2 emissions due to energy consumption in China. The logarithmic mean divisia index (LMDI) approach was adopted to decompose the driving factors of CO2 emissions in eight sub-periods over 1995 to 2011. Decomposition and heterogeneity analyses of CO2 emission over multiple spatial series were also conducted for the 29 provinces in China. Twelve driving factors in view of four categories of effects were decomposed. The results indicated that (a) driving directions of the factors were highly consistent. All the factors exhibited consistently positive and negative effects both spatially and temporally. Among these factors, the average labor productivity (ALP) was the dominant positive driving factor and energy intensity of production sector (EIP) was the dominant negative driving factor, (b) over multiple temporal scales, China experienced the largest energy-related CO2 emission growth in the sub-periods during 2001–2003 and 2003 to 2005. Additionally, the change in the CO2 emissions from 1997 to 1999 was negative, unlike the other 7 sub-periods, and (c) over multiple spatial scales, contribution values of the factors in different provinces varied significantly, where in general the positive driving effects outweighed the negative inhibiting effects. In total, CO2 emissions in eastern provinces increased to the largest degrees, followed by central and western ones. It is suggested that China should coordinate and balance the relationships between economic development and CO2 emission reduction, further decrease energy intensity of many production sectors, gradually adjust the economic and energy structures, and formulate CO2 emission reduction policies to accommodate regional disparities.

Walking away from a low-carbon economy? Recent and historical trends using a regional decomposition analysis

Using the latest available data, this brief article attempts to provide the first regional decomposition analysis of CO2 emissions from fuel combustion. Covering eight regions of the world, determinants are estimated in relative and absolute terms for the period 1971-2010. We take the 2010 global surge in CO2 emissions as an entry point for the analysis. Overall, results show that most regions have recently performed worse than their historical trends and lack of meaningful progress is identified. Whereas specific drivers for certain regions suggest some level of continuous improvement (e.g. reduced energy intensity in Asia), they are incapable of offsetting the effects of economic growth and energy use. With the exception of Africa, most regions appear to have missed the low-carbon economy opportunity provided by the 2008-2009 global financial crisis. Results suggest a lack of serious environmental effectiveness of regional policy portfolios aiming at reducing CO2 emissions. Highly ambitious energy efficiency and renewable energy policies across all regions are immediately needed. Additionally, absolute reductions in CO2 emissions and energy use from fossil fuels are urgently required in rich regions if we are to align production and consumption patterns with maintaining global warming below the 2°C threshold.

Decomposition analysis of CO2 Emissions from the Greek Manufacturing Sector

The aim of this paper is to identify the factors that have influenced changes in the amount of carbon
 dioxide (CO2) emitted from the Greek manufacturing sector as a whole and from three representative
 subsectors. By means of an algebraic decomposition method the changes recorded during the period
 1985-95 are analysed into four distinct factors: output level, energy intensity, fuel mix and structural
 change. The results show that the observed reduction of industrial CO2 emissions is not only due to the
 decrease of industrial energy intensity but also to the recession of the Greek manufacturing sector. The
 two other factors, namely sectoral and fuel shifts were driving emissions upward, primarily because of
 the increasing share of electricity - intensive sectors and the growing dependence of electricity generation
 from lignite. It is concluded that for the reduction of industrial CO2 emissions in the long term,
 policy measures should aim at further promoting energy saving technologies and encouraging the use
 of natural gas and renewable energies.

Decomposition analysis of CO2 emissions from electricity generation in China

Electricity generation in China mainly depends on coal and its products, which has led to the increase in CO2 emissions. This paper intends to analyze the current status of CO2 emissions from electricity generation in China during the period 1991–2009, and apply the logarithmic mean Divisia index (LMDI) technique to find the nature of the factors influencing the changes in CO2 emissions. The main results as follows: (1) CO2 emission from electricity generation has increased from 530.96Mt in 1991 to 2393.02Mt in 2009, following an annual growth rate of 8.72%. Coal products is the main fuel type for thermal power generation, which accounts for more than 90% CO2 emissions from electricity generation. (2) This paper also presents CO2 emissions factor of electricity consumption, which help calculate CO2 emission from final electricity consumption. (3) In China, the economic activity effect is the most important contributor to increase CO2 emissions from electricity generation, but the electricity generation efficiency effect plays the dominant role in decreasing CO2 emissions.

Decomposition analysis of CO2 emissions in the Mexican industrial sector

The paper presents a decomposition analysis to identify the factors that have influenced the changes in the carbon dioxide emissions in the Mexican industrial sector as a whole, and from sixteen representative industrial branches during the period 1965–2003. By means of the Refined Laspeyres Index method for decomposing carbon dioxide emissions proposed by Sun (1998), the changes in CO2 emissions from energy use are evaluated according to five effects: activity, structure, energy intensity, end-use fuel mix, and fuel mix to generate electricity. The analysis results show that effects of activity, structure, and fuel mix to generate electricity contributed to increase the CO2 emissions by 71.1, 11.8, and 1.7million tons of CO2 equivalent respectively from 1965 to 2003; while energy intensity and end-use fuel mix mitigated them by 32.2, and 5.9million tons of CO2 respectively. The analysis is carried out in three stages: 1965–1982, 1982–1994, and 1994–2003 to show the influence of circumstances such as Mexican oil boom, economic crises, variation in oil prices and Mexico's opening up to international free trade on the growth of CO2 emissions. The results show that industrial branches as petrochemical, chemical, iron and steel, cement, among others played a significant role in the total increase of 250% of industrial emissions of CO2 from 1965 to 2003.

Decomposition analysis of CO2 emissions increase from the passenger transport sector in Shanghai, China

This study identified the relationships between CO2 emissions from passenger transport and its driving factors by taking Shanghai as an example. The Logarithmic Mean Divisia Index (LMDI) technique was used to disassemble the total passenger transport CO2 growth into five driving factors: economic activity, population, modal share, passenger transport intensity and passenger transport CO2 emission factor. The study found that: (1) in 2009, the passenger transport CO2 emissions in Shanghai increased by 2.59 times against that of 2000; (2) the increased economic activity was the main factor driving passenger transport CO2 emissions growth from 2000 to 2009 that accounted for 75% of the total passenger transport CO2 emissions growth in Shanghai; (3) the effects of modal share change and population growth were relatively small but not trivial; and (4) The inhibitory effects of passenger transport CO2 emissions growth were 90% from the improvement of passenger transport intensity, and 10% from the changes of passenger transport CO2 emission factor. However, these effects were too small to offset the whole increase.

An Overall Comparation and Technical Decomposition Analysis of CO2 Emissions in Tokyo and Beijing

An Overall Comparation and Technical Decomposition Analysis of CO2 Emissions in Tokyo and Beijing

Energy CO2 Emissions for 1990–2020: A Decomposition Analysis for EU-25 and Greece

This article deals with the decomposition analysis of energy-related CO2 emissions in Greece and in the EU-25 from 1990 to 2020, by means of the Logarithmic Mean Divisia Index technique and a baseline scenario approach based on the PRIMES simulation modeling system for energy demand and supply. The Logarithmic Mean Divisia Index technique is used and changes in CO2 emissions are decomposed into four factors: income effect, energy intensity effect, fuel share effect, and population effect. For comparison reasons, we have included in our analysis results for three other countries (i.e., Ireland, Portugal, and Belgium) of similar size with Greece and varying energy mix and economy structure. Finally, a sectoral decomposition analysis of CO2 emissions for the Greek economy is applied.