scholarly journals Spatiotemporal Comparison of Drivers to CO2 Emissions in ASEAN: A Decomposition Study

2021 ◽  
Vol 13 (11) ◽  
pp. 6183
Author(s):  
Edwin Bernard F. Lisaba ◽  
Neil Stephen A. Lopez
Keyword(s):  
Carbon Emissions ◽  
Economic Activity ◽  
Carbon Dioxide Emissions ◽  
Energy Intensity ◽  
Geographical Location ◽  
Economic Structure ◽  
Temporal Analysis ◽  
The Philippines ◽  
Policy Recommendations ◽  
Spatial And Temporal Analyses

The Southeast Asian region is one of the most vulnerable to climate change given its geographical location and economic situation. This study aims to conduct a combination of spatial and temporal analyses in order to understand differences between member nations in terms of driving factors to changing emissions. The logarithmic mean Divisia index (LMDI) method was used in order to estimate carbon dioxide emissions due to population, economic activity, economic structure, and energy intensity effects from the year 1990 to 2018. In conducting the study, spatial analysis showed that Singapore was the only country to effectively lessen carbon emissions, due to population and energy intensity, in comparison to the others. Additionally, temporal analysis showed that the ASEAN initially developed at the same rate, before countries such as Singapore, Malaysia, and Thailand, started becoming more economically active, as shown by their economic activity. Finally, results have shown that some countries, especially the Philippines and Indonesia, have undergone significant changes in economic structure, which significantly affected carbon emissions. The results also highlight the increasing per capita emissions as income levels rise. The paper concludes by presenting a summary of the findings and some policy recommendations.

scholarly journals The Potential For Economic Growth And Carbon Dioxide Emissions Reduction: Using Input-Output Framework

2020 ◽  
Vol 214 ◽  
pp. 01038
Author(s):  
Lihao Sun ◽  
Yuxiang Shen
Keyword(s):  
Economic Growth ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Economic Structure ◽  
Emissions Reduction ◽  
Heat Power ◽  
Input Output ◽  
Key Factor ◽  
The Status ◽  
Emissions Intensity

As people’s living standards continue to ameliorate, people become more and more demanding of the status of eco-environment, and carbon emissions are a key factor affecting the eco-environment. We analyze the carbon emissions intensity and carbon emissions potential of different sectors in China based on the input-output model. The results show that the sector of Production and Supply of Electric Power and Heat Power has the highest embodied carbon emissions intensity because the sector provides the country with necessary electricity and heat power for its economic growth. In addition, this paper determines the key carbon emissions sectors using elasticity method, and the results show that Construction is the most influential carbon emissions sector in the future. By restricting key carbon emissions sectors and encouraging the non-key carbon emissions sectors, we can take into account both economic development and carbon emissions reduction with the multi-objective model. The results show that under the present economic scale of China, carbon emissions can decrease from 11591 million ton to 11011 million ton, with a difference of 580 million ton. This indicates that with the assurance of present economic growth, we can achieve the goal of reducing carbon emissions by adjusting the economic structure. Based on results of this paper, we have also made recommendations for adjusting the economic structure to achieve emission reduction targets.

scholarly journals Probing the carbon emissions in 30 regions of China based on symbolic regression and Tapio decoupling

2021 ◽  
Author(s):  
Haiying Liu ◽  
zhiqun zhang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Symbolic Regression ◽  
Car Ownership ◽  
Emissions Reduction ◽  
Policy Recommendations ◽  
The World ◽  
Urbanization Rate

Abstract Against the background of energy shortages and severe air pollution, countries around the world are aware of the importance of energy conservation and emissions reduction; China is actively achieving emissions reduction targets. In this study, we use a symbolic regression to classify China's regions according to the degree of influencing factors, and calculate and analyze the inherent decoupling relationship between carbon emissions and economic growth in each region. Based on our results, we divided the 30 regions of the country into six categories according to the main influencing factors: GDP (13 regions), energy intensity (EI; 7 regions), industrial structure (IS; 3 regions), urbanization rate (UR; 3 regions), car ownership (CO; 2 regions), and household consumption level (HCL; 2 regions). Then, according to the order of the average carbon emissions in each region from high to low, these regions were further categorized as type-EI, type-UR, type-GDP, type-IS, type-CO, or type-HCL regions. The decoupling index of each region showed a downward trend; EI and GDP regions were the most notable contributors to emissions, based on which we provide policy recommendations.

scholarly journals Analysis of Factors Influencing Carbon Emissions in the Energy Base, Xinjiang Autonomous Region, China

2020 ◽  
Vol 12 (3) ◽  
pp. 1089
Author(s):  
Jiancheng Qin ◽  
Hui Tao ◽  
Chinhsien Cheng ◽  
Karthikeyan Brindha ◽  
Minjin Zhan ◽  
...  
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Carbon Emissions ◽  
Energy Intensity ◽  
Economic Structure ◽  
Energy Structure ◽  
Intensity Effect ◽  
Entire Energy ◽  
Key Factor ◽  
Main Factors

Analyzing the driving factors of regional carbon emissions is important for achieving emissions reduction. Based on the Kaya identity and Logarithmic Mean Divisia Index method, we analyzed the effect of population, economic development, energy intensity, renewable energy penetration, and coefficient on carbon emissions during 1990–2016. Afterwards, we analyzed the contribution rate of sectors’ energy intensity effect and sectors’ economic structure effect to the entire energy intensity. The results showed that the influencing factors have different effects on carbon emissions under different stages. During 1990–2000, economic development and population were the main factors contributing to the increase in carbon emissions, and energy intensity was an important factor to curb the carbon emissions increase. The energy intensity of industry and the economic structure of agriculture were the main factors to promote the decline of entire energy intensity. During 2001–2010, economic growth and emission coefficient were the main drivers to escalate the carbon emissions, and energy intensity was the key factor to offset the carbon emissions growth. The economic structure of transportation, and the energy intensity of industry and service were the main factors contributing to the decline of the entire energy intensity. During 2011–2016, economic growth and energy intensity were the main drivers of enhancing carbon emissions, while the coefficient was the key factor in curbing the growth of carbon emissions. The industry’s economic structure and transportation’s energy intensity were the main factors to promote the decline of the entire energy intensity. Finally, the suggestions of emissions reductions are put forward from the aspects of improving energy efficiency, optimizing energy structure and adjusting industrial structure etc.

scholarly journals Study on the Spatial Association and Influencing Factors of Carbon Emissions from the Chinese Construction Industry

2021 ◽  
Vol 13 (4) ◽  
pp. 1728
Author(s):  
Siyao Li ◽  
Qiaosheng Wu ◽  
You Zheng ◽  
Qi Sun
Keyword(s):  
Construction Industry ◽  
Carbon Emissions ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Spatial Association ◽  
Policy Recommendations ◽  
Affecting Factors ◽  
Positive Effects ◽  
The Social ◽  
The Empirical Analysis

As the world’s largest carbon emitter, China is under enormous pressure to decrease carbon emissions. With the economic development in recent years, China has increased its investment in infrastructure, and the construction industry has become an essential source of carbon emissions. Using the social network analysis (SNA) methodology, this article analyzes the evolutionary characteristics of the spatial correlation network for carbon emissions in the construction industry from 2003–2017 and its affecting factors. The results of the empirical analysis in this paper are: (1) the spatial association of carbon emissions in Chinese inter-provincial construction industry shows an intuitive network layout and the spatial network has gradually stabilized since 2014; (2) according to the results of degree centrality, betweenness centrality and closeness centrality, it can be concluded that the regions with higher level of association with other provinces are the central and the eastern regions (Henan, Hubei, Hunan, Guangdong, Jiangsu, etc.) and Xinjiang; the linkage of construction-related carbon emissions was mainly achieved through the regions of Henan, Anhui, Shanxi, Hebei, Guangdong, and Inner Mongolia; the regions with higher level of construction industry development (Jiangsu, Henan, Hunan, Guangdong, etc.) are more closely associated with other provinces; (3) geographical proximity and reduction of difference in energy intensity and in industrial structure have substantial positive effects on the carbon emission association of the construction industry. Finally, based on the research results, this article proposes corresponding policy recommendations.

Factors Leading to Increased Carbon Dioxide Emissions of the APEC Countries: the LMDI Decomposition Analysis

2020 ◽  
pp. 1-20
Author(s):  
Yu-Fang Chang ◽  
Bwo-Nung Huang
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Energy Intensity ◽  
Decomposition Analysis ◽  
Substitution Effect ◽  
The Philippines ◽  
Population Increase ◽  
Intensity Effect ◽  
Energy Substitution ◽  
The Us

This paper explores the factors that lead to increased carbon dioxide emissions in the 18 countries of the APEC. We apply the LMDI multiplicative decomposing method to 18 countries between 1971 and 2012. We summarize these factors that are as follows: (1) population increase and economic growth play a key role in increased carbon dioxide emissions. (2) All the 18 countries of the APEC have improved their energy efficiency as manifested in the change of energy intensity ([Formula: see text]), which is less than 1 in the 42 years; (3) In terms of energy substitution effect ([Formula: see text]) and fuel coefficient effect ([Formula: see text]), the decomposition results point out that Hong Kong, Indonesia, and Malaysia witnessed growth in [Formula: see text] and [Formula: see text], indicating the only factor to reduce the emissions for these three countries is intensity effect, which gives rise to relatively higher emission for these three countries during the period. In the case of Peru, the Philippines, Singapore, Thailand, and Vietnam, we witnessed increases in [Formula: see text], but decreases in [Formula: see text]; In the case of Australia, Canada, Chile, China, Japan, South Korea, Mexico, New Zealand, Taiwan, and the US, there seem to decrease in [Formula: see text], but increases in [Formula: see text] during the 42-year period.

scholarly journals Contribution of agriculture to the economic development of Serbia

2020 ◽  
Vol 15 (2) ◽  
pp. 1-14
Author(s):  
Boban Dašić ◽  
Radmila Trklja ◽  
Valentina Milosavljević
Keyword(s):  
Economic Development ◽  
Economic Activity ◽  
Development Process ◽  
Geographical Location ◽  
Economic Structure ◽  
Developed Countries ◽  
Large Share ◽  
Natural Conditions ◽  
The Subject ◽  
Observation Period

The overall economic development of a national economy depends on the development of individual economic and noneconomic activities. Agriculture as an economic activity occupies a significant place in the overall development process of a country. The dependence of agriculture on natural conditions such as climate, geographical location, quality and other characteristics of the land, has the consequence that the contribution of agriculture to the overall economic development will not be the same depending on the above factors. The place and importance of agriculture in the overall economic development varies depending on the observation period because there are differences related to key development factors, as well as the place and importance of agriculture in the overall economic development. The participation of agriculture in the overall economic structure is especially important, although this certainly does not mean that countries with a higher share of agriculture in the economic structure reach higher levels of development. Countries with a large share of agriculture in the economic structure are usually underdeveloped or less developed, while in developed countries the share of agriculture in the economic structure is at a very low level. In a large number of countries, agriculture is still the main economic activity with which the largest number of inhabitants is engaged in proportion. The subject of this paper refers to the contribution to the development of agriculture from the aspect of its role and importance in the overall economic development.

scholarly journals An Analysis of Disparities and Driving Factors of Carbon Emissions in the Yangtze River Economic Belt

2019 ◽  
Vol 11 (8) ◽  
pp. 2362 ◽  
Author(s):  
Decai Tang ◽  
Yan Zhang ◽  
Brandon J. Bethel
Keyword(s):  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Yangtze River ◽  
Energy Intensity ◽  
Driving Factors ◽  
The Yangtze River ◽  
Stirpat Model ◽  
Per Capita Gdp ◽  
Positive Effects ◽  
Per Capita

As one of the “three major strategies” for China’s regional development, the Yangtze River Economic Belt (YREB) is under severe pressure to reduce carbon dioxide emissions, this paper analyzes the spatiotemporal disparities, and driving factors of carbon emissions based on energy consumption and related economic development data in the YREB over the 2005–2016 11-year period. Using the Stochastic Impacts Regression on Population, Affluence and Technology (STIRPAT) model, we empirically test the factors affecting YREB carbon emissions and key drivers in various provinces and municipalities. The main findings are as follows. First, per capita GDP, both industrial structure and energy intensity have positive effects on increasing carbon emissions. Second, per capita GDP and energy intensity have the largest impact on the increase of carbon emissions, and the urbanization rate has the largest inhibitory effect on carbon emissions.

scholarly journals An Examination of Green Credit Promoting Carbon Dioxide Emissions Reduction: A Provincial Panel Analysis of China

2021 ◽  
Vol 13 (13) ◽  
pp. 7148
Author(s):  
Wenjie Zhang ◽  
Mingyong Hong ◽  
Juan Li ◽  
Fuhong Li
Keyword(s):  
Carbon Dioxide ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Emissions Reduction ◽  
Green Finance ◽  
Carbon Emissions Reduction ◽  
Negative Effect ◽  
Emissions Intensity ◽  
The Impact

The implementation of green finance is a powerful measure to promote global carbon emissions reduction that has been highly valued by academic circles in recent years. However, the role of green credit in carbon emissions reduction in China is still lacking testing. Using a set of panel data including 30 provinces and cities, this study focused on the impact of green credit on carbon dioxide emissions in China from 2006 to 2016. The empirical results indicated that green credit has a significantly negative effect on carbon dioxide emissions intensity. Furthermore, after the mechanism examination, we found that the promotion impacts of green credit on industrial structure upgrading and technological innovation are two effective channels to help reduce carbon dioxide emissions. Heterogeneity analysis found that there are regional differences in the effect of green credit. In the western and northeastern regions, the effect of green credit is invalid. Quantile regression results implied that the greater the carbon emissions intensity, the better the effect of green credit. Finally, a further discussion revealed there exists a nonlinear correlation between green credit and carbon dioxide emissions intensity. These findings suggest that the core measures to promote carbon emission reduction in China are to continue to expand the scale of green credit, increase the technology R&D investment of enterprises, and to vigorously develop the tertiary industry.

Rain or Shine Shield: Language and Ropes of Sadok Making

2020 ◽  
Author(s):  
Loyalda T. Bolivar ◽  
Keyword(s):  
Indigenous Knowledge ◽  
Economic Activity ◽  
Participant Observation ◽  
The Philippines ◽  
Cultural Practice ◽  
Cultural Tradition ◽  
Way Of Life ◽  
The People ◽  
Hands On ◽  
Materials Used

A sadok or salakot is a farmer’s cherished possession, protecting him from the sun or rain. The Sadok, persisting up to the present, has many uses. The study of Sadok making was pursued to highlight an important product, as a cultural tradition in the community as craft, art, and part of indigenous knowledge in central Antique in the Philippines. Despite that this valuable economic activity needs sustainability, it is given little importance if not neglected, and seems to be a dying economic activity. The qualitative study uses ethnophenomenological approaches to gather data using interviews and participant observation, which aims to describe the importance of Sadok making. It describes how the makers learned the language of Sadok making, especially terms related to materials and processes. The study revealed that the makers of Sadok learned the language from their ancestors. They have lived with them and interacted with them since they were young. Sadok making is a way of life and the people observe their parents work and assist in the work which allows them to learn Sadok making. They were exposed to this process through observations and hands-on activities or ‘on-the-job’ informal training. They were adept with the terms related to the materials and processes involved in the making of Sadok as they heard these terms from them. They learned the terms bamboo, rattan, tabun-ak (leaves used) and nito (those creeping vines) as materials used in Sadok making. The informants revealed that the processes involved in the making of Sadok are long and tedious, starting from the soaking, curing and drying of the bamboo, cleaning and cutting these bamboo into desired pieces, then with the intricacies in arranging the tabun-ak or the leaves, and the weaving part, until the leaves are arranged, up to the last phase of decorating the already made Sadok. In summary, socialization is one important factor in learning the language and a cultural practice such as Sadok making. It is an important aspect of indigenous knowledge that must be communicated to the young for it to become a sustainable economic activity, which could impact on the economy of the locality. Local government units should give attention to this indigenous livelihood. Studies that would help in the enhancement of the products can likewise be given emphasis.

Influencing Factors and Decoupling Analysis of Carbon Emissions in China's Manufacturing Industry

2021 ◽  
Author(s):  
baoling jin ◽  
ying Han
Keyword(s):  
Carbon Emissions ◽  
Manufacturing Industry ◽  
Energy Intensity ◽  
Value Added ◽  
Carbon Intensity ◽  
Energy Structure ◽  
Investment Efficiency ◽  
Fixed Asset ◽  
Carbon Productivity ◽  
Fixed Asset Investment

Abstract The manufacturing industry directly reflects national productivity, and it is also an industry with serious carbon emissions, which has attracted wide attention. This study decomposes the influential factors on carbon emissions in China’s manufacturing industry from 1995 to 2018 into industry value added (IVA), energy consumption (E), fixed asset investment (FAI), carbon productivity (CP), energy structure (EC), energy intensity (EI), investment carbon intensity (ICI) and investment efficiency (IE) by Generalized Divisia Index Model (GDIM). The decoupling analysis is carried out to investigate the decoupling states of the manufacturing industry under the pressure of "low carbon" and "economy.” Considering the technological heterogeneity, we study the influential factors and decoupling status of the light industry and the heavy industry. The results show that: (1) Carbon emissions of the manufacturing industry present an upward trend, and the heavy industry is the main contributor. (2) Fixed asset investment (FAI), industry value added (IVA) are the driving forces of carbon emissions. Investment carbon intensity (ICI), carbon productivity (CP), investment efficiency (IE), and energy intensity (EI) have inhibitory effects. The impact of the energy consumption (E) and energy structure (EC) are fluctuating. (3) The decoupling state of the manufacturing industry has improved. Fixed asset investment (FAI), industry value added (IVA) hinder the decoupling; carbon productivity (CP), investment carbon intensity (ICI), investment efficiency (IE), and energy intensity (EI) promote the decoupling.

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