Energy use and energy-related carbon dioxide emissions drivers in Egypt's economy: Focus on the agricultural sector with a structural decomposition analysis

Radwan, Amira; Han, Hongyun; Achraf, Abdelhak; Mustafa, Ahmed M.

doi:10.1016/j.energy.2022.124821

Cited by 18 publications

(7 citation statements)

References 82 publications

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“…However, despite the widespread use of this approach, there have been limited applications of IOA and SDA in analyzing the factors influencing agricultural wages. Among the few studies exploring agriculture, SDA has primarily been used to investigate the growth and drivers of environmental variables in the agricultural sector [ 61 , 62 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Exploring the drivers of agricultural wages growth in China: A comprehensive framework utilizing input-output and structural decomposition methods

Zheng,

Li,

2024

PLoS ONE

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This study explores the factors driving agricultural wages growth in China from 1981 to 2020. We propose a comprehensive framework that combines input-output analysis and structural decomposition analysis to investigate the drivers of agricultural wages growth from four perspectives: supply, demand, industrial linkages, and agricultural support policies. The findings indicate that changes in consumer demand, investment demand, and labor mobility play significant roles in driving the growth of agricultural wages in China. Additionally, agricultural support policies have contributed to an increase in agricultural wages to some extent. However, changes in industrial linkages negatively affect agricultural wages growth. A notable strength of this study lies in the methodology employed, which ensures a comprehensive and systematic analysis encompassing diverse factors rather than a restricted perspective.

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Section: Literature Reviewmentioning

confidence: 99%

Exploring the drivers of agricultural wages growth in China: A comprehensive framework utilizing input-output and structural decomposition methods

Zheng,

Li,

2024

PLoS ONE

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“…Another study found that technological improvements in agriculture still worsen emissions. Hopefully, more technological improvements in agriculture will reduce emissions in the future (Radwan et al 2022). Another study even found that agricultural machines emit emissions that can ruin the ozone layer (Yu et al 2023).…”

Section: F-test For Regressionmentioning

confidence: 99%

Correlation of Rice Production and Greenhouse Gas Emissions in North Sulawesi Province

Suli¹,

Damanik²

2023

J. Ilmu. Pertan. Indones.

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This study aimed to reveal correlation, calculate significance, and discover the regression equation of rice production to Green House Gas (GHG) emission in North Sulawesi Province. The data on GHG emissions from rice cultivation (Gg CO2eq) was obtained from the Ministry of Environment and Forestry of Indonesia. Data on rice production from wetland and dryland (Gg) was from the BP Statistical Review annual period of 2000-2021, both for North Sulawesi Province. Data analysis of correlation coefficient, F-test for Regression, and Simple Regression Analysis will be processed with the help application of MS Excel. The results show that the correlation between rice production and emission of rice cultivation in North Sulawesi Province is 0.53 and classified as a moderate correlation. The coefficient of determination stated that the emission of rice cultivation could be explained by about 28.6% from rice production. Therefore, rice production is statistically significant to the emission of rice cultivation with a 5% confidence level for North Sulawesi Province. Furthermore, this study found a regression equation, emission of rice cultivation is 112.67 + 0.516 times rice production. Keywords: correlation coefficient, green house gas emission, rice production

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“…Equation ( 8) converts four multiplicative terms in Equation ( 7) into four additive terms, and each additive term corresponds to the contribution of each factor. Due to the absence of a unique decomposition solution for Equation (8), the average of the polar decompositions was applied to approximate the average of all decompositions [44]. Solving Equation ( 8) with the so-called polar decompositions yields:…”

Section: Structural Decomposition Modelmentioning

confidence: 99%

Urban Low-Carbon Consumption Performance Assessment: A Case Study of Yangtze River Delta Cities, China

et al. 2022

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Urban low carbonization has been an essential element in China’s carbon peak and carbon neutrality strategies. An assessment of urban low-carbon performance could provide valuable information for monitoring and guiding the low-carbon transition in cities. However, due to cross-regional carbon transfer, the actual level of achievement would be masked, if the assessment was based only on a production-based index such as carbon emission intensity (CEI). Focusing, instead, on consumption-based low-carbon performance, this study calculated levels of urban carbon consumption intensity (CCI) based on city-level carbon footprint accounting, investigated the patterns and drivers of changes in CCI of 26 Yangtze River Delta (YRD) cities from 2012 to 2015, and conducted a comparative analysis of CEI and CCI data from both static and dynamic viewpoints. It was found that the CCI of YRD cities decreased from 1.254 to 1.153 over the period. Cities at higher economic levels were found to have lower CCI values. Decomposition results show that shifts in production structure, intensity of emissions and changing consumption patterns contributed to the decline in CCI of the YRD area. Richer cities were found to show greater declines in CCI due to decarbonizing structures in production and consumption. The comparative results show that although the CEI and CCI of cities were generally correlated in both static level and dynamic change, the net carbon transfer impacted the correlation sensitivity between various cities. Finally, our findings provide practical guidance on achieving coordinated emission reductions at an inter-city level from both production and consumption perspectives.

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Energy use and energy-related carbon dioxide emissions drivers in Egypt's economy: Focus on the agricultural sector with a structural decomposition analysis

Cited by 18 publications

References 82 publications

Exploring the drivers of agricultural wages growth in China: A comprehensive framework utilizing input-output and structural decomposition methods

Exploring the drivers of agricultural wages growth in China: A comprehensive framework utilizing input-output and structural decomposition methods

Correlation of Rice Production and Greenhouse Gas Emissions in North Sulawesi Province

Urban Low-Carbon Consumption Performance Assessment: A Case Study of Yangtze River Delta Cities, China

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