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Energy-Environment-Economy Analysis of Carbon Emissions and the Carbon Trading System
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Energy-Environment-Economy Analysis of Carbon Emissions and the Carbon Trading System

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B3: Carbon Emission and Utilization".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 6278

Special Issue Editors

Dr. Vladimir Franki

E-Mail Website
Guest Editor
Faculty of Engineering Rijeka, University of Rijeka, Vukovarska 58, 51 000 Rijeka, Croatia Energy Platform Living Lab Zagreb, Unska 3, 10 000 Zagreb, Croatia
Interests: energy security; decision support; sustainable development; energy transition; low-carbon; business models; carbon emissions; e-mobility; energy strategy
Prof. Dr. Alfredo Višković

E-Mail Website
Guest Editor
Energy Platform Living Lab Zagreb, Unska 3, 10 000 Zagreb, Croatia Faculty of Engineering Rijeka, University of Rijeka, Vukovarska 58, 51 000 Rijeka, Croatia
Interests: urban energy systems, sustainable development; energy transition; low-carbon; business models; carbon emissions; e-mobility; energy strategy

Special Issue Information

Dear Colleagues,

Climate change is a significant global environmental issue influencing governmental policies worldwide. Anthropogenic CO2 (carbon dioxide) emissions are directly related to quality of life. The goal of sustainable development entails the facilitation of the transition to low-carbon energy sources as the key driver of change in the energy sector. With increased geopolitical instability, the surge in low-carbon solutions, and the realisation that energy sources are crucial for economic growth, carbon emissions have raised global concerns. The literature as well as policy debates have expressed increasing interest in measures mitigating the negative externalities of climate change policies. Carbon trading and carbon taxes represent important tools in reducing carbon emissions. However, reaching a zero-carbon energy system requires a tailored, multidisciplinary approach based on facilitating policies and infrastructure actions.

Keeping in mind the pressing need for reduced carbon emissions, we would like to invite researchers and professionals from universities, enterprises, and governmental units to share thoughts, trends, innovations, and experiences regarding methods aiding the process of transitioning to low-carbon resources. Both original research articles and review articles are welcome.

Dr. Vladimir Franki
Prof. Dr. Alfredo Višković
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • carbon emissions
  • infrastructure for climate action
  • transition to low-carbon resources
  • greenhouse gas (GHG)
  • climate change
  • carbon trading
  • energy policy
  • carbon policy
  • carbon leakage
  • border carbon adjustment
  • EU emission trading system (ETS)
  • carbon footprint
  • carbon tax
  • carbon offset
  • carbon intensity
  • cap and trade
  • decarbonization
  • low-carbon transition
  • sustainable development

Published Papers (5 papers)

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Research

22 pages, 1916 KiB  
Article
A Life Cycle Analysis of a Polyester–Wool Blended Fabric and Associated Carbon Emissions in the Textile Industry
by Pırıl Tekin, Hakan Alıcı and Tuğçe Demirdelen
Energies 2024, 17(2), 312; https://doi.org/10.3390/en17020312 - 08 Jan 2024
Viewed by 1465
Abstract
The effect of industrialization and technological developments and the rate of population growth have begun to disrupt the ecological balance in the world. A large share of the deterioration of this balance is due to the rapidly increasing energy demands of people. Fossil [...] Read more.
The effect of industrialization and technological developments and the rate of population growth have begun to disrupt the ecological balance in the world. A large share of the deterioration of this balance is due to the rapidly increasing energy demands of people. Fossil fuels and renewable energy sources are used to obtain the energy that is needed by human beings. Most of the world’s energy needs are met by fossil fuels such as coal, oil, and natural gas. These resources, which we call fossil fuels, cause many parallel environmental problems, such as global warming, climate change, and carbon emissions, for the world and nature. The most affected by all these experiences, of course, is the entire production sector, which is dependent on energy. However, textile and apparel, which is a pioneer in taking steps towards harmonization with the Green Agreement, is one of the sectors that started the transition to green energy within the scope of the European Union and brands’ net-zero targets. Within the scope of the Green Agreement, Turkey has participated and started to work for a 70% carbon reduction, which is the target for 2030, and carbon neutrality, which is the target for 2050. Therefore, within the scope of these targets, the textile sector of Çukurova Region, which has the highest export rate in Turkey, was chosen. Within the scope of this study, carbon emission, which is one of the global problems, was examined within the framework of the ISO 14067-ISO Product Based Carbon Footprint (CF) standard by examining the production of a textile company, and the results were analyzed in detail. The main innovation of this article is to follow all stages of the fabric called Tricia, which is the most produced product in the textile industry, from its entry as fiber to its exit as fabric in the factory, and to calculate and analyze the amount of carbon that is released into nature. The dynamic and experimental results showed that it was determined that 6.00 tons of carbon dioxide carbon were released in the time it took for the fabric to go to the sewing room as a fabric. Full article
(This article belongs to the Special Issue Energy-Environment-Economy Analysis of Carbon Emissions and the Carbon Trading System)
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13 pages, 3866 KiB  
Article
Prediction of Carbon Price in EU-ETS Using a Geometric Brownian Motion Model and Its Application to Analyze the Economic Competitiveness of Carbon Capture and Storage
by Gwang Goo Lee and Sung-Won Ham
Energies 2023, 16(17), 6333; https://doi.org/10.3390/en16176333 - 31 Aug 2023
Viewed by 1004
Abstract
To achieve carbon neutrality, many countries and regions are making efforts to promote the commercialization of greenhouse gas (GHG) mitigation technologies using emissions trading systems (ETSs). Accurate predictions of when the cost of GHG reduction technologies will become competitive below carbon prices could [...] Read more.
To achieve carbon neutrality, many countries and regions are making efforts to promote the commercialization of greenhouse gas (GHG) mitigation technologies using emissions trading systems (ETSs). Accurate predictions of when the cost of GHG reduction technologies will become competitive below carbon prices could be invaluable to engineers and policy makers. In this study, carbon price movement in the EU-ETS was analyzed using a geometric Brownian motion (GBM) model. Using daily price data for the last 10 years, it tested whether the price pattern of the latter three years could be predicted by applying the first seven years of data to the GBM model. The results showed that the GBM model could well predict the upper and lower bounds of the actual carbon price. Based on the acceptable predictability of the GBM model, simulations were performed using carbon price data over the last decade, showing that carbon prices would reach around 200 EUR/tCO2 by the start of 2026. This is higher than the cost of CO2 avoided evaluated from the costs of commercial-scale carbon capture facilities for coal-fired power plants. This means that carbon capture technologies in the coal-fired power sector could become economically competitive within the next several years. Full article
(This article belongs to the Special Issue Energy-Environment-Economy Analysis of Carbon Emissions and the Carbon Trading System)
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31 pages, 4191 KiB  
Article
Carbon Peak Scenario Simulation of Manufacturing Carbon Emissions in Northeast China: Perspective of Structure Optimization
by Caifen Xu, Yu Zhang, Yangmeina Yang and Huiying Gao
Energies 2023, 16(13), 5227; https://doi.org/10.3390/en16135227 - 07 Jul 2023
Cited by 2 | Viewed by 883
Abstract
The manufacturing industry is the pillar industry of China’s economy and a major carbon emitter, and its carbon emission reduction efforts directly determine whether the country’s carbon emission reduction target can be successfully met. In the context of the goals of the carbon [...] Read more.
The manufacturing industry is the pillar industry of China’s economy and a major carbon emitter, and its carbon emission reduction efforts directly determine whether the country’s carbon emission reduction target can be successfully met. In the context of the goals of the carbon peak and carbon neutrality policy, we examine the impact of manufacturing structure optimization on carbon emissions from 2003 to 2020 through a spatial econometric model, taking the old industrial centers in Northeast China as an example. We then apply a machine learning model to simulate manufacturing carbon emissions during the carbon peak stage and identify the optimal path for carbon emission reduction, which is important for promoting manufacturing carbon emission reduction in Northeast China. Since the goal of low-carbon economic development has gradually replaced the goal of maximizing economic efficiency in recent years, manufacturing structure optimization has come to focus on energy saving and emission reduction. Therefore, we define manufacturing structure optimization from the dual perspective of technology and energy consumption to broaden the existing research perspective. The results show the following: (1) The overall trend in manufacturing structure optimization in Northeast China is steadily improving, and the level of manufacturing structure optimization from the technology perspective is higher than that from the energy consumption perspective. (2) Manufacturing structure optimization and manufacturing carbon emissions in Northeast China both show a positive spatial correlation. Manufacturing structure optimization in Northeast China can effectively promote carbon emission reduction, and it also has a spatial spillover effect. (3) The carbon emission reduction effect of manufacturing structure optimization from the energy consumption perspective is better than that from the technology perspective, and the carbon emission reduction effect under the institutional innovation scenario is better than that under the baseline scenario and the technological innovation scenario. Focusing on manufacturing structure optimization from both technology and energy consumption perspectives, as well as continuously improving technological innovation and institutional innovation, can help to achieve manufacturing carbon emission reduction in Northeast China. Full article
(This article belongs to the Special Issue Energy-Environment-Economy Analysis of Carbon Emissions and the Carbon Trading System)
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19 pages, 5408 KiB  
Article
A Multi-Strategy Integration Prediction Model for Carbon Price
by Hongwei Dong, Yue Hu, Yihe Yang and Wenjing Jiang
Energies 2023, 16(12), 4613; https://doi.org/10.3390/en16124613 - 09 Jun 2023
Cited by 2 | Viewed by 1133
Abstract
Carbon price fluctuations significantly impact the development of industries, energy, agriculture, and stock investments. The carbon price possesses the features of nonlinearity, non-stationarity, and high complexity as a time series. To overcome the negative impact of these characteristics on prediction and to improve [...] Read more.
Carbon price fluctuations significantly impact the development of industries, energy, agriculture, and stock investments. The carbon price possesses the features of nonlinearity, non-stationarity, and high complexity as a time series. To overcome the negative impact of these characteristics on prediction and to improve the prediction accuracy of carbon price series, a combination prediction model named Lp-CNN-LSTM, which utilizes both convolutional neural networks and long short-term memory networks, has been proposed. Strategy one involved establishing distinct models of CNN-LSTM and LSTM to analyze high-frequency and low-frequency carbon price sequences; the combination of output was integrated to predict carbon prices more precisely. Strategy two comprehensively considered the economic and technical indicators of carbon price sequences based on the Pearson correlation coefficient, while the Multi-CNN-LSTM model selected explanatory variables that strongly correlated with carbon prices. Finally, a predictive model for a combination of carbon prices was developed using Lp-norm. The empirical study focused on China’s major carbon markets, including Hubei, Guangdong, and Shanghai. According to the error indicators, the performance of the Lp-CNN-LSTM model was superior to individual strategy prediction models. The Lp-CNN-LSTM model has excellent accuracy, superiority, and robustness in predicting carbon prices, which can provide a necessary basis for revising carbon pricing strategies, regulating carbon trading markets, and making investment decisions. Full article
(This article belongs to the Special Issue Energy-Environment-Economy Analysis of Carbon Emissions and the Carbon Trading System)
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21 pages, 18785 KiB  
Article
Spatial-Temporal Evolution Characteristics of Industrial Carbon Emissions in China’s Most Developed Provinces from 1998–2013: The Case of Guangdong
by Ran Wang, Hui Ci, Ting Zhang, Yuxin Tang, Jinyuan Wei, Hui Yang, Gefei Feng and Zhaojin Yan
Energies 2023, 16(5), 2249; https://doi.org/10.3390/en16052249 - 26 Feb 2023
Cited by 4 | Viewed by 1048
Abstract
Industry is widely valued as an important contributor to carbon emissions. Therefore, it is of great significance to analyze the industrial carbon emissions (ICE) in Guangdong, the strongest industrial province in China. We have adopted the carbon emission accounting model and standard deviational [...] Read more.
Industry is widely valued as an important contributor to carbon emissions. Therefore, it is of great significance to analyze the industrial carbon emissions (ICE) in Guangdong, the strongest industrial province in China. We have adopted the carbon emission accounting model and standard deviational ellipse analysis model to analyze the temporal and spatial characteristics and evolution trends of the industry carbon emission amount and intensity in Guangdong from 1998 to 2013. The study results include: (1) Due to the rapid development of industry, Guangdong’s ICE showed a steady growth trend; (2) The distribution characteristics of ICE were characterized by the trend of taking the Pearl River Delta (PRD) region as the center and gradually spreading to the surrounding areas. From the perspective of industrial sectors, it can be divided into steady growth type, fluctuant growth type, basically stable type, and decrease type; (3) The spatial pattern of the ICE in Guangdong is basically the same as that of the total industrial output value, that is, the southwest-northeast pattern. This work is helpful for China’s carbon peak, especially for the formulation of industrial carbon peak policy and the sustainable development of the environment. Full article
(This article belongs to the Special Issue Energy-Environment-Economy Analysis of Carbon Emissions and the Carbon Trading System)
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