scholarly journals Consumption-Based Accounting and the Trade-Carbon Emissions Nexus in Asia: A Heterogeneous, Common Factor Panel Analysis

2018 ◽  
Vol 10 (10) ◽  
pp. 3627 ◽  
Author(s):  
Brantley Liddle
Keyword(s):  
Carbon Emissions ◽  
Fossil Fuels ◽  
Common Factor ◽  
Trade Flows ◽  
Carbon Intensity ◽  
Panel Analysis ◽  
Asian Countries ◽  
Republic Of China ◽  
Domestic Use ◽  
Global Carbon

This paper considers a recently developed consumption-based carbon emissions database from which emissions calculations are made based on the domestic use of fossil fuels plus the embodied emissions from imports minus exports, to test directly for the importance of trade in national emissions. The People’s Republic of China (PRC) alone is responsible for over half the global outflows of carbon via trade. The econometric estimations—which focused on a panel of 20 Asian countries—determined that: (i) trade flows were significant for consumption-based emissions but not for territory-based emissions; and (ii) exports and imports offset each other in that exports lower consumption-based emissions, whereas imports increase them. Hence, all countries should have both an interest and a responsibility to help lower the carbon intensity of energy in countries that are particularly important for global carbon transfers—the PRC and India.

scholarly journals Carbon Leakage Along with the Green Paradox Against Carbon Abatement? A Review Based on Carbon Tax

2020 ◽  
Vol 20 (1) ◽  
pp. 25-44
Author(s):  
Sahin Akkaya ◽  
Ufuk Bakkal
Keyword(s):  
Interest Rates ◽  
Carbon Emissions ◽  
Fossil Fuels ◽  
Fossil Fuel ◽  
Carbon Tax ◽  
Relevant Literature ◽  
Carbon Leakage ◽  
Carbon Abatement ◽  
Green Paradox ◽  
Global Carbon

AbstractResearch background: Insufficient global cooperation in carbon pricing against global warming has the risk of global carbon emissions rise because of carbon leakage. The effect of a carbon tax on the present supply of fossil fuels is also valuable in regard to global carbon emissions.Purpose: The purpose of this study is to gain more insights into the effects of carbon leakage along with the green paradox on global carbon emissions by reviewing the relevant literature.Research methodology: We provide the problem linked to carbon leakage and the green paradox in the introduction. Then, the effects of carbon leakage and the green paradox on global carbon emissions are elaborated separately. Finally the mutual effects of carbon leakage and the green paradox are reviewed comprehensively.Results: It is seen that various factors like interest rates, fossil fuel extraction costs, the fossil fuel reserves to be discovered in the future and carbon tax incidence are equally important determinants in regard to global carbon emissions.Novelty: This study provides an insight into the mutual effects of carbon leakage and the green paradox on global carbon emissions by reviewing the primary literature in the field.

scholarly journals Statistic Equation to Estimate the Amount of CO2 Emission Produced From High Traffic Density Roads

2021 ◽  
Vol 16 ◽  
pp. 78-86
Author(s):  
Rania Rushdy Moussa ◽  
Mahmoud M. M. Mansour ◽  
Naglaa Mohamed Yossif
Keyword(s):  
Co2 Emissions ◽  
Carbon Emissions ◽  
Fossil Fuels ◽  
Primary Energy ◽  
Traffic Density ◽  
Carbon Intensity ◽  
Measuring Device ◽  
Factors Affecting ◽  
High Level ◽  
High Traffic Density

Energy consumption, especially the energy used for electricity supply has doubled in the past three decades, causing a drastic increase in the carbon emissions produced. Between 1990 and 2005 globally, the amount of CO2 emissions increased 25%. It is estimated that vehicles produce approximately 30% of the global NOx and 14% of global CO2 emissions. Egypt is the fourteenth biggest wellspring of CO2 emissions among all GEF program nations. It was proven that 66% of CO2 emissions comes from fossil fuel as a primary energy consuming source, playing a key role in the overall carbon intensity. The problem of this research is that the roads in developing countries produce a high level of carbon emissions, and the level is increasing due to the heavy usage of fossil fuels in the transportation sector. This research presents statistical analysis equation to analyse the amount of CO2 emissions produced from roads without using heavy and expensive equipment’s. Moreover, the equation can be used as a tool to estimate the amount of CO2 emissions produced from roads during the design phase in order to improve the design and reduce carbon emissions in roads. According to the statistics the main factors affecting the amount of CO2 produced in roads are the electricity generations, types of vehicles and vehicles speed. The research used experimental method to validate the equation by measuring CO2 emissions in high traffic density road using measuring device and compared the measuring results with the statistic equation results. The presented equation should help in reducing the amount of CO2 produced in roads, in return it will help in reducing the growth of global problems such as climate change and ozone depletion.

scholarly journals Carbon Emissions and Carbon Intensity in China’s Exports: A Contrast of SRIO and GIRIO Methods

2015 ◽  
Vol 3 (6) ◽  
pp. 499-512
Author(s):  
Hao Xiao ◽  
Jianguo Wang ◽  
Qiao Zhu ◽  
Han Qiao
Keyword(s):  
Developing Countries ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Global Supply Chain ◽  
Trade Flows ◽  
Carbon Intensity ◽  
Input Output ◽  
Dramatic Decrease ◽  
Foreign Countries ◽  
Direct Trade

AbstractThis paper compares differences between single regional input-output (SRIO) model and global interregional IO model (GIRIO) used in the area of carbon emission embodied in exports under global supply chain, and decomposes carbon emissions and carbon intensity in exports according to export path based on KWW (2014). Empirical analysis in China’s exports in 1995, 2000, 2005 and 2009 shows: 1) GIRIO model yielded about 2.11% less domestic emissions absorbed abroad, 0.8% more domestic emissions in exports, 1.5 times more foreign emissions in exports in 2009, compared to SRIO model. 2) USA and EU absorb most carbon emissions in China’s exports, but with declining share. Increasing domestic emissions firstly exported to developing countries but finally returned home and emissions from developing countries in China’s exports show their contribution from developing countries. Discrepancies between bilateral carbon emissions flows changes and direct trade flows changes suggest indirect carbon emissions transfer by third parties are neglected in SRIO model. 3) Despite dramatic decrease, China still bears 1.52 times more carbon emissions per GDP gained than foreign countries in fragmentation of China’s exports production in 2009, indicating different roles in production fragmentation.

scholarly journals Wasting and Associated Factors among Children under 5 Years in Five South Asian Countries (2014–2018): Analysis of Demographic Health Surveys

2021 ◽  
Vol 18 (9) ◽  
pp. 4578
Author(s):  
Nidhi Wali ◽  
Kingsley E. E. Agho ◽  
Andre M. N. Renzaho
Keyword(s):  
South Asia ◽  
South Asian ◽  
Health Surveys ◽  
Associated Factors ◽  
Common Factor ◽  
Household Wealth ◽  
Health Concern ◽  
Demographic And Health Surveys ◽  
Asian Countries ◽  
Sampling Weights

Child wasting continues to be a major public health concern in South Asia, having a prevalence above the emergency threshold. This paper aimed to identify factors associated with wasting among children aged 0–23 months, 24–59 months, and 0–59 months in South Asia. A weighted sample of 564,518 children aged 0–59 months from the most recent demographic and health surveys (2014–2018) of five countries in South Asia was combined. Multiple logistic regression analyses that adjusted for clustering and sampling weights were used to examine associated factors. Wasting prevalence was higher for children aged 0–23 months (25%) as compared to 24–59 months (18%), with variations in prevalence across the South Asian countries. The most common factor associated with child wasting was maternal BMI [adjusted odds ratio (AOR) for 0–23 months = 2.02; 95% CI: (1.52, 2.68); AOR for 24–59 months = 2.54; 95% CI: (1.83, 3.54); AOR for 0–59 months = 2.18; 95% CI: (1.72, 2.77)]. Other factors included maternal height and age, household wealth index, birth interval and order, children born at home, and access to antenatal visits. Study findings suggest need for nutrition specific and sensitive interventions focused on women, as well as adolescents and children under 2 years of age.

Static grid carbon factors – Can we do better?

2021 ◽  
pp. 014362442199196
Author(s):  
Jamie Risner ◽  
Anna Sutherland
Keyword(s):  
Carbon Emissions ◽  
Regional Analysis ◽  
Electricity Consumption ◽  
Carbon Intensity ◽  
External Temperature ◽  
Building Regulations ◽  
Calculation Methodology ◽  
Alternative Methodology ◽  
The Uk ◽  
The Impact

The average carbon intensity (gCO2e/kWh) of electricity provided by the UK National Grid is decreasing and becoming more time variable. This paper reviews the impact on energy calculations of using various levels of data resolution (half hourly, daily, monthly and annual) and of moving to region specific data. This analysis is in two parts, one focused on the potential impact on Part L assessments and the other on reported carbon emissions for existing buildings. Analysis demonstrated that an increase in calculated emissions of up to 12% is possible when using an emissions calculation methodology employing higher resolution grid carbon intensity data. Regional analysis indicated an even larger calculation discrepancy, with some regions annual emissions increasing by a factor of ten as compared to other regions. This paper proposes a path forward for the industry to improve the accuracy of analysis by using better data sources. The proposed change in calculation methodology is analogous to moving from using an annual average external temperature to using a CIBSE weather profile for a specific city or using a future weather file. Practical application: This paper aims to quantify the inaccuracy of a calculation methodology in common use in the industry and key to building regulations (specifically Building Regulations Part L – Conservation of Fuel and Power) – translating electricity consumption into carbon emissions. It proposes an alternative methodology which improves the accuracy of the calculation based on improved data inputs.

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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