Drivers of fuel based carbon dioxide emissions: The case of Turkey

Akbostancı, Elif; Tunç, Gül İpek; Türüt-Aşık, Serap

doi:10.1016/j.rser.2017.06.066

Cited by 41 publications

(21 citation statements)

References 13 publications

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“…Akbostancı et al [19] decomposed and analyzed the CO2 emissions of five Turkish economy sectors between 1990 and 2013. These sectors are manufacturing, electricity and heat, transport, and residential industries.…”

Section: Literature Reviewmentioning

confidence: 99%

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The Impact of European Green Deal on Turkey's Iron and Steel Industry: Decomposition Analysis of Energy-Related Sectoral Emissions

Bektaş¹

2020

Celal Bayar Üniversitesi Fen Bilimleri Dergisi

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The European Union has put forward a vision under the EU Green Deal's name to take the lead in its priorities, fulfill the Agreement's criteria, and subsequently accept the first EU climate law on March 5, 2020. The law framework aims to impose tax obligations on consumption goods imported by the EU from abroad, especially on energy-intensive sectors, by applying the carbon border adjustment mechanism. Our main goal is to determine what kind of measures can be taken to ensure that the iron and steel industry is least affected by the EU border carbon regulation. We are an absolute exporter, are least affected by the EU carbon border adjustment. For this reason, the change in energy-related greenhouse gas emissions from the iron and steel industry from 1998 to 2018 was analyzed using the Logarithmic Mean Divisia Index (LMDI) model to investigate the potential effects of carbon border adjustment in the iron and steel industry. The analyzes were made with five significant factors that determine the change of emissions. These factors are; changes in economic activity, activity mix, energy intensity, energy mix, and emission factors. Analysis has suggested that the economic activity effect has raised CO2 emissions. This method indicates that the energy intensity's impact could be the first key determinant of GHG emissions. Turkey should attempt to implement low-carbon development policies and reduce energy-related emissions in the iron & steel sector are the least impacted by the EU's carbon border adjustment.

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Section: Literature Reviewmentioning

confidence: 99%

“…Many studies in recent years have shown that reducing its density limits or reduces energy-related greenhouse gas emissions. [7], [17], [19], [29]- [30].…”

Section: Sectoral Energy Intensity Effectmentioning

confidence: 99%

The Impact of European Green Deal on Turkey's Iron and Steel Industry: Decomposition Analysis of Energy-Related Sectoral Emissions

Bektaş¹

2020

Celal Bayar Üniversitesi Fen Bilimleri Dergisi

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“…Akbostancı et al [25] decomposed and analyzed CO2 emissions of five sectors of the Turkish economy between 1990 and 2013. These sectors are; manufacturing, electricity and heat production, transportation, and residential industries.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This result means that now more output is produced with less energy, or more production acquired with the same amount of energy used [47]. Many recent academic studies have demonstrated that energy intensity reduction is limited or even reduced the increasing energy-related GHG emissions [6], [12], [23], [25], [48]- [51]. Energy intensities for four combustion sectors are presented in Figure 10.…”

Section: Economic Activity Effectmentioning

confidence: 99%

An Analysis of Energy-related Greenhouse Gas Emissions in Turkish Energy-intensive Sectors

Bektaş¹

2020

Preprint

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In recent decades, greenhouse gas (GHG) emissions have been a critical priority of global environmental policy. The leading cause of the increase in GHG triggering global warming in the atmosphere is the continuously growing demand for universal energy due to population and economic growth. Energy efficiency and reduction of CO2 emissions in highly-energy consuming sectors of Turkey are critical in deciding a low-carbon transition. In this study, the change of energy-related CO2 emissions in Turkey’s energy-intensive four sectors from 1998 to 2017 is analyzed based on the Logarithmic Mean Divisia Index (LMDI) method. It is used to decompose CO2 equivalent emissions changes in these sectors into five driving forces; changes in economic activity, activity mix, energy intensity, energy mix, and emission factors. Analytical results indicate that economic activity is a vital decisive factor in determining the change in CO2 emissions as well as sectoral energy intensity. The activity effect has raised CO2 emissions, while energy intensity has decreased. This method indicates that the impact of the energy intensity could be the first key determinant of GHG emissions. Turkey's efforts to be taken in these sectors in adopting low carbon growth policies and reducing energy-related emissions to tackle climate change are clarified in detail.

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“…The average global temperature on Earth has increased by about 0.8 o Celsius since 1880, which two-thirds of it has occurred since 1975 [1]. The global CO2 concentration has grown from 280ppm in the mid-1800s to about 400ppm in the present [2]. The global transport sector accounts for about a third of fossil fuel-based energy consumption and a quarter of greenhouse gas emissions [3].…”

Section: Introductionmentioning

confidence: 99%

Co-Optimization of Energy Losses and Transformer Operating Costs Based on Smart Charging Algorithm for Plug-In Electric Vehicle Parking Lots

Madahi

Nafisi

Abyaneh

et al. 2021

IEEE Trans. Transp. Electrific.

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The global transport sector has a significant share of greenhouse gas emissions. Thus, plug-in electric vehicles (PEVs) can play a vital role in the reduction of pollution. However, high penetration of PEVs can pose severe challenges to power systems, such as an increase in energy losses and a decrease in the transformers expected life. In this paper, a new day-ahead cooptimization algorithm is proposed to reduce the unwanted effects of PEVs on the power system. The aim of the proposed algorithm is minimizing the cost of energy losses as well as transformer operating cost by the management of active and reactive powers simultaneously. Moreover, the effect of harmonics, which are produced by the charger of PEVs, are considered in the proposed algorithm. Also, the transformer operating cost is obtained from a method that contains the purchase price, loading, and losses cost of the transformer. Another advantage of the proposed algorithm is that it can improve power quality parameters, e.g., voltage and power factor of the distribution network by managing the reactive power. Afterward, the proposed algorithm is applied to a real distribution network. The results show that the proposed algorithm optimizes the daily operating cost of the distribution network efficiently. Finally, the robustness of the proposed algorithm to the number and distribution of PEVs is verified by simulation results. Index Terms-plug-in electric vehicle (PEV), transformer aging, energy losses, daily operating cost reduction. NOMENCLATURE A. Indices and Sets ℎ Harmonic order ℎ Maximum harmonic order Set of power system nodes Time slot B. Plug-in Electric Vehicle and Parking Lot Parameters PEV battery capacity [kWh] Capacity of the n-th parking lot

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Drivers of fuel based carbon dioxide emissions: The case of Turkey

Cited by 41 publications

References 13 publications

The Impact of European Green Deal on Turkey's Iron and Steel Industry: Decomposition Analysis of Energy-Related Sectoral Emissions

The Impact of European Green Deal on Turkey's Iron and Steel Industry: Decomposition Analysis of Energy-Related Sectoral Emissions

An Analysis of Energy-related Greenhouse Gas Emissions in Turkish Energy-intensive Sectors

Co-Optimization of Energy Losses and Transformer Operating Costs Based on Smart Charging Algorithm for Plug-In Electric Vehicle Parking Lots

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