Decomposition of Carbon Dioxide (CO2) Emissions in ASEAN Based on Kaya Identity

ASEAN is a region with high carbon dioxide (CO2) emissions, accompanied by an increase in population, gross domestic product (GDP) and energy consumption. Population, GDP, and energy consumption can be linked to CO2 emissions through an identity equation called the Rich Identity. This research is based on Kaya identity to describe CO2 emissions to calculate the impact of population, economic activity, energy intensity and carbon intensity on CO2 emissions in ASEAN and 8 ASEAN countries (i.e., Indonesia, Malaysia, Singapore, Thailand, Philippines, Vietnam, Myanmar and Brunei Darussalam) from 1990 to 2017. The method used is the Logarithmic Mean Division Index (LMDI). The data used are from the International Energy Agency (IEA) and the World Bank. Four effects measured and main findings showed that population, economic activity and carbon intensity factor increased by 293.02 MtCO2, 790.0 MtCO2, and 195.51 MtCO2, respectively. Meanwhile, energy intensity effect made ASEAN's CO2 emissions decrease by 283.13 MtCO2. Regarding contributions to the increase in CO2 emissions in all ASEAN countries, the population effect increases CO2 emissions in all countries in ASEAN and the economic activity effect is also the same, except in Brunei Darussalam which makes CO2 emissions in this country decreased by 1.07 MtCO2. Meanwhile, the effects of energy and carbon intensity are different. The effect of energy intensity causes CO2 emissions in lower-middle income countries to decrease, while in upper-middle and high-income countries, it increases carbon emissions. In contrast to the effect of carbon intensity, that actually makes CO2 emissions increase in lower-middle income countries and reduces carbon emissions in upper-middle and high-income countries.

Impact of Land Urbanization on Carbon Emissions in Urban Agglomerations of the Middle Reaches of the Yangtze River

The urban agglomerations in the middle reaches of the Yangtze River (MYR-UA) are facing a severe challenge in reducing carbon emissions while maintaining stable economic growth and prioritizing ecological protection. The energy consumption related to land urbanization makes an important contribution to the increase in carbon emissions. In this study, an IPAT/Kaya identity model is used to understand how land urbanization affected carbon emissions in Wuhan, Changsha, and Nanchang, the three major cities in the middle reaches of the Yangtze River, from 2000 to 2017. Following the core idea of the Kaya identity model, sources of carbon emissions are decomposed into eight factors: urban expansion, economic level, industrialization, population structure, land use, population density, energy intensity, and carbon emission intensity. Furthermore, using the Logarithmic Mean Divisia Index (LMDI), we analyze how the different time periods and time series driving forces, especially land urbanization, affect regional carbon emissions. The results indicate that the total area of construction land and the total carbon emissions increased from 2000 to 2017, whereas the growth in carbon emissions decreased later in the period. Energy intensity is the biggest factor in restraining carbon emissions, followed by population density. Urban expansion is more significant than economic growth in promoting carbon emissions, especially in Nanchang. In contrast, the carbon emission intensity has little influence on carbon emissions. Changes in population structure, industrial level, and land use vary regionally and temporally over the different time period.

Evaluating the Causal Relations between the Kaya Identity Index and ODIAC-Based Fossil Fuel CO2 Flux

The Kaya identity is a powerful index displaying the influence of individual carbon dioxide (CO2) sources on CO2 emissions. The sources are disaggregated into representative factors such as population, gross domestic product (GDP) per capita, energy intensity of the GDP, and carbon footprint of energy. However, the Kaya identity has limitations as it is merely an accounting equation and does not allow for an examination of the hidden causalities among the factors. Analyzing the causal relationships between the individual Kaya identity factors and their respective subcomponents is necessary to identify the real and relevant drivers of CO2 emissions. In this study we evaluated these causal relationships by conducting a parallel multiple mediation analysis, whereby we used the fossil fuel CO2 flux based on the Open-Source Data Inventory of Anthropogenic CO2 emissions (ODIAC). We found out that the indirect effects from the decomposed variables on the CO2 flux are significant. However, the Kaya identity factors show neither strong nor even significant mediating effects. This demonstrates that the influence individual Kaya identity factors have on CO2 directly emitted to the atmosphere is not primarily due to changes in their input factors, namely the decomposed variables.

Evaluating the Mutual Relationship between IPAT/Kaya Identity Index and ODIAC-Based GOSAT Fossil-Fuel CO2 Flux: Potential and Constraints in Utilizing Decomposed Variables

The IPAT/Kaya identity is the most popular index used to analyze the driving forces of individual factors on CO2 emissions. It represents the CO2 emissions as a product of factors, such as the population, gross domestic product (GDP) per capita, energy intensity of the GDP, and carbon footprint of energy. In this study, we evaluated the mutual relationship of the factors of the IPAT/Kaya identity and their decomposed variables with the fossil-fuel CO2 flux, as measured by the Greenhouse Gases Observing Satellite (GOSAT). We built two regression models to explain this flux; one using the IPAT/Kaya identity factors as the explanatory variables and the other one using their decomposed factors. The factors of the IPAT/Kaya identity have less explanatory power than their decomposed variables and comparably low correlation with the fossil-fuel CO2 flux. However, the model using the decomposed variables shows significant multicollinearity. We performed a multivariate cluster analysis for further investigating the benefits of using the decomposed variables instead of the original factors. The results of the cluster analysis showed that except for the M factor, the IPAT/Kaya identity factors are inadequate for explaining the variations in the fossil-fuel CO2 flux, whereas the decomposed variables produce reasonable clusters that can help identify the relevant drivers of this flux.

ARE THE PARIS AGREEMENT EFFORTS EQUALLY SHARED? GDP AND CO2 PRODUCTION REGULARITIES

<p><strong>ABSTRACT</strong></p><p><strong></strong>This study investigates regularities in the production of GDP and CO2 emissions for 84 countries between 1980-2014. The empirical strategy is derived from an ecological-economic framework in which both outputs are produced employing capital, energy and labor. Moreover, we propose an expanded version of the Kaya identity, which creates a link between the growth rate of CO2 emissions and capital accumulation to evaluate the distribution of abatement efforts under the Paris Agreement. By using a new dataset, we found evidence of relative decoupling in developing countries and absolute decoupling in some developed countries. Our findings show that the individual voluntary definition of the emission targets under the Agreement resulted in an unequal distribution of the abatement efforts among developing and developed countries. In the absence of higher energy or environment-saving technical changes, the required reductions in capital accumulation are sharper for developing than developed countries.</p><p> </p><p>¿SE COMPARTEN LOS ESFUERZOS DEL ACUERDO DE PARÍS IGUALMENTE? <br />REGULARIDADES DE PRODUCCIÓN DEL PIB Y CO2<br /><strong></strong></p><p><strong>RESUMEN</strong><br />Este trabajo investiga las regularidades en la producción del PIB y las emisiones de CO2 en 84 países entre 1980 y 2014. La estrategia empírica deriva de un marco ecológico-económico en el cual los dos bienes se producen utilizando capital, energía y trabajo. Proponemos una versión expandida de la identidad de Kaya que crea un vínculo entre la tasa de crecimiento de las emisiones de CO2 y la acumulación de capital para evaluar la distribución de los esfuerzos de abatimiento del Acuerdo de París. Mediante el uso de una nueva base de datos, encontramos un desacoplamiento relativo en los países en desarrollo y un desacoplamiento absoluto en algunos países desarrollados. Nuestros hallazgos muestran que la definición individual voluntaria de las metas de emisiones del Acuerdo resulta en una distribución desigual de los esfuerzos de abatimiento entre los países en desarrollo y desarrollados. En ausencia de un mayor cambio técnico ahorrador de energía o del ambiente, las reducciones requeridas en la acumulación de capital son más agudas para los países en desarrollo que para los desarrollados.</p>