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

Hwang, Young Hwan; Um, Jung‐Sup; Hwang, Junhwa; Schlüter, Stephan

doi:10.3390/en13226009

Cited by 27 publications

(16 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Drivers of carbon emissions Paper Finding Ang and Zhang (2000) The Kaya identity helps quantitatively analyze the impact of interest on the intensity or total amount of carbon emissions. Hwang et al (2020) The indirect effects of the decomposed variables in the Kaya identity on the carbon emission are significant. Jin and Kim (2017) It is necessary to have sufficient public finances to implement measures contained within NDC.…”

Section: Ipat Impact Stirpat and Co-stirpatmentioning

confidence: 98%

An Operational Framework for a Low-carbon, Green Growth Economy: CO-STIRPAT Dynamic System

Jin

2024

JEA

View full text Add to dashboard Cite

This paper presents an operational framework for assessing the trajectories of production, energy, emissions, and capital accumulation to ensure the implementation of Nationally Determined Contributions (NDCs). The framework combines widely used methodologies (STIRPAT, system dynamics, and optimization) to simulate the pathways of variables until a target year. The CO-STIRPAT dynamic system allows us to identify the spillover pathways from carbon policy to economic growth based on output optimization principles; to conduct a more systematic analysis of the interconnections between the main drivers that determine carbon emissions; to develop a cost-effective climate policy mix that is a backbone for the right combination of carbon pricing, energy efficiency, and carbon intensity; and to assess NDC targets with respect to ambition gaps, implementation gaps, and feasibility.

show abstract

Section: Ipat Impact Stirpat and Co-stirpatmentioning

confidence: 98%

An Operational Framework for a Low-carbon, Green Growth Economy: CO-STIRPAT Dynamic System

Jin

2024

JEA

View full text Add to dashboard Cite

show abstract

“…For example, a quantile regression approach can be used to assess the drivers of carbon emission from production activities at different quantile levels, employing an augmented Kaya identity, similar to other authors [72]. The correlation between Kaya identity factors and their decomposed variables can also be analysed [73]. The research can include the modified Kaya identity in the autoregressive distributive lag model (ARDL), which is a time series approach [74].…”

Section: Limitations and Proposals For Future Researchmentioning

confidence: 99%

The Impact of Economic Growth and Urbanisation on Environmental Degradation in the Baltic States: An Extended Kaya Identity

Makutėnienė,

Staugaitis,

Makutėnas

et al. 2023

Agriculture

View full text Add to dashboard Cite

The main aim of this article is to empirically examine the impact of economic growth and urbanisation on environmental degradation, as well as the existence of the environmental Kuznets curve (EKC) in three Baltic States (Lithuania, Latvia, and Estonia) from 2000 to 2020. The main Kaya identity and the extended urban Kaya identity models are applied within the analysis. The multiple regression analysis made it possible to assess the influence of urbanisation and other factors on greenhouse gas (GHG) emissions in the studied countries, as well as test the hypothesis of the inverted U-shaped EKC. The main finding reveals that GDP per capita growth has the largest and increasing effect on GHG emissions in all three countries. It was also found that changes in population in urban areas in Lithuania and Latvia reduced the amount of GHG until 2020, while in Estonia, the growing urban population greatly contributed to increasing GHG emissions. As a result, processes related to urbanisation have not yet had a significant impact on environmental quality in Lithuania and Latvia. Meanwhile, in Estonia, this is a significant factor that policymakers need to focus on when solving environmental pollution reduction problems. The hypothesis of the EKC was mostly supported when analysing GHG emissions in Lithuania and Estonia and using GDP per capita as an indicator for economic growth. On the other hand, it was found that the impact of the urbanisation rate on GHG emissions is not curved, yet there is some evidence that in Estonia, a growing urbanisation rate is related to diminishing GHG emissions, according to the multiple regression analysis. The results of the study showed that policymakers should consider economic growth and, especially in Estonia, urbanisation when solving problems related to environmental degradation.

show abstract

“…Ordinary Least Squares (OLS) Linear Regression Linear regression assumes stationary relationships across the study area. Linear regression and Pearson correlation analyses explain the linear relationship between the two variables based on proportional equations [40][41][42]. Comparative evaluations with linear regression and Pearson correlation can yield the fitness of the SCSTs of malfunctioning solar cells caused by soil debris detected from the photo-mosaic and video-mosaic.…”

Section: 5mentioning

confidence: 99%

Comparative Evaluation for Tracking the Capability of Solar Cell Malfunction Caused by Soil Debris between UAV Video versus Photo-Mosaic

Hwang

Schlüter

Park³

et al. 2022

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Monitoring the malfunction of the solar cells (for instance, 156 mm by 156 mm) caused by the soil debris requires a very low flight altitude when taking aerial photos, utilizing the autopilot function of unmanned aerial vehicle (UAV). The autopilot flight can only operate at a certain level of altitude that can guarantee collision avoidance for flight obstacles (for instance, power lines, trees, buildings) adjacent to the place where the solar panel is installed. For this reason, aerial photos taken by autopilot flight capture unnecessary objects (surrounding buildings and roads) around the solar panel at a tremendous level. Therefore, the autopilot-based thermal imaging causes severe data redundancy with very few matched key-points around the malfunctioned solar cells. This study aims to explore the tracking capability on soil debris defects in solar cell scale between UAV video versus photo-mosaic. This study experimentally validated that the video-based thermal imaging can track the thermal deficiency caused by the malfunction of the solar cell at the level of the photo-mosaic in terms of correlation of thermal signatures (0.98–0.99), detection on spatial patterns (81–100%), and distributional property (90–95%) with 2.5–3.4 times more matched key-points on solar cells. The results of this study could serve as a valuable reference for employing video stream in the process of investigating soil debris defects in solar cell scale.

show abstract

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

Cited by 27 publications

References 63 publications

An Operational Framework for a Low-carbon, Green Growth Economy: CO-STIRPAT Dynamic System

An Operational Framework for a Low-carbon, Green Growth Economy: CO-STIRPAT Dynamic System

The Impact of Economic Growth and Urbanisation on Environmental Degradation in the Baltic States: An Extended Kaya Identity

Comparative Evaluation for Tracking the Capability of Solar Cell Malfunction Caused by Soil Debris between UAV Video versus Photo-Mosaic

Contact Info

Product

Resources

About