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Predicting carbon dioxide emissions is crucial for addressing climate change and achieving environmental sustainability. Accurate emission forecasts provide policymakers with a basis for evaluating the effectiveness of policies, facilitating the design and implementation of emission reduction strategies, and helping businesses adjust their operations to adapt to market changes. Various methods, such as statistical models, machine learning, and grey prediction models, have been widely used in carbon dioxide emission prediction. However, existing research often lacks comparative analysis with other forecasting techniques. This paper constructs a new Discrete Fractional Accumulation Grey Gompertz Model (DFAGGM(1,1) based on grey system theory and provides a detailed solution process. The Whale Optimization Algorithm (WOA) is used to find the hyperparameters in the model. By comparing it with five benchmark models, the effectiveness of DFAGGM(1,1) in predicting carbon dioxide emissions data for China and the United States is validated. [ABSTRACT FROM AUTHOR]

This paper presents an empirical investigation into the effects of energy transition and digitization on carbon dioxide emissions, serving as a proxy for environmental sustainability, across 28 Chinese provinces from 2000 to 2021. Utilizing both static and dynamic regression analyses, the study reveals a significant driving effect of the energy transition on environmental sustainability, primarily through a reduction in carbon dioxide emissions. Notably, this influence is more pronounced in the eastern region of China, followed by the central and western regions, indicating regional heterogeneity in the impact of the energy transition. Furthermore, digitization is found to have a substantial moderating effect, enhancing energy conservation and emission reductions. As digitization progresses, its capability to diminish the impact of energy transitions on carbon dioxide emissions becomes more apparent, particularly in the eastern region, while this effect is less marked in central and western China. The study also delves into the nonlinear relationship between energy transitions and carbon dioxide emissions, discovering that increased levels of digitization can exacerbate the negative effects of energy transitions on emissions. These findings offer valuable insights into the dynamics of energy transition and digitalization, highlighting their crucial roles in shaping environmental sustainability in China. [ABSTRACT FROM AUTHOR]

Several countries have focused on achieving optimal economic growth in the past decades, which has caused diverse environmental concerns among policymakers and managers. The present study aims to introduce new metric using mathematical modeling to examine strategies to promote environmental performance in OECD countries. Thus, we propose a target-oriented Distance Friction Minimization (TO-DFM) model to design a practical improvement strategy for low-efficiency DMUs. In this regard, considering the efficient and inefficient frontiers, we present two models, IDMU and ADMU, respectively, based on TO-DFM and DFM models. Then, the distance scores yielded by the two models are combined to evaluate the efficiency of each DMU using the hybrid index of relative closeness (RC). The results reveal that the proposed model has a better distinctive potential compared to the standard TO-DFM model. Overall, implementing the proposed model on a set of sustainability data, for OECD countries, resulted in a more logical performance in classifying countries regarding their distance from the efficient and inefficient frontiers. Therefore, less developed countries should pay considerable attention to implementing environmental policies to improve their performance and control environmental pollution with a reliable and healthy economy. For instance, the implementation of such policies in countries such as Turkey, Estonia, and Hungary, with lower efficiency scores, can affect the sustainability of their development performance. [ABSTRACT FROM AUTHOR]

Since the 1950s, the remarkable amount of global environmental degradation has heightened environmental concerns at both national and international levels. This shift has spurred intensive research into the causes of environmental degradation and potential remedies, including environmental taxes, fines, education, and regulations. The drivers of CO2 emissions have been widely explored in the literature, but the nexus between business climate, human capital, and CO2 emissions has not been examined sufficiently. Therefore, the purpose of this study is to delve into the interplay between renewable energy, business climate, human capital, and CO2 emissions in BRICS countries from 2000 to 2020 using panel causality and cointegration tests. Our research hypotheses suggest that there are significant mutual interactions among renewable energy, business climate, human capital, and CO2 emissions based on the associated literature. The results of the causality test verify the research hypotheses by uncovering a bidirectional causality between business climate, renewable energy use, human capital, and CO2 emissions. Furthermore, the cointegration analysis reveals that increases in renewable energy use and human capital decrease CO2 emissions at the panel level, but a positive business climate increases CO2 emissions at the panel level. However, the impact of business climate on CO2 emissions at the country level varies among BRICS economies based on environmental policies. In conclusion, investing in green energy technologies and education is a useful tool to decrease CO2 emissions. In addition to this, the positive effect of business climate on CO2 emissions should be balanced by regulations to increase environmental, social, and governance awareness of firms. [ABSTRACT FROM AUTHOR]

The EU has committed to make Europe the first climate-neutral continent by 2050. Reaching this objective requires massive changes in the region. The biggest challenge is that the green transition happens without sacrificing economic progress and guaranteeing justice and inclusiveness. This pledge implies that every country be capable of addressing the trade-offs between targets while remaining committed towards the common decarbonisation goal. Our paper analyses the success with which countries are carrying out the energy transition. We propose an enhanced hyperbolic distance function and a stochastic frontier analysis approach to model the joint attainment of economic development, environmental sustainability, and energy equity. We apply our model to an unbalanced panel dataset of 29 European countries for the period 2005–2018. Our estimates show that the average performance of the economies has improved over time. The results also highlight the pivotal role of a sustainable economic development with clean energies for both slashing CO 2 emissions and fostering energy equity. Moreover, we find convergence in countries' performance, being this convergence slightly higher for the EU-15 countries compared to the rest. Finally, we show that a higher share of renewable energy sources helps countries that are lagging behind to reach their optimal performance level. [ABSTRACT FROM AUTHOR]

This paper explores the viability of utilizing agricultural biomass-based energy potential, employing mathematical, engineering, and economic modeling techniques. Moreover, the potential of a biogas-based co-digestion (CD) system, integrating its techno-economic performance and environmental sustainability in terms of electricity generation, has also been studied. In this investigation, the categorization of 25 different plant species into two groups: arable field crops (AFCs) and horticultural plants (HPs), was performed. Data was collected during the 2021‐–2022 cropping season in Bangladesh from various sources, including literature reviews, governmental, and non-governmental organizations. The findings revealed that the available agricultural biomass residues, totaling 1,02,585.75 KT, have the capacity to generate 1,33,815 million m3/year of biogas. This energy potential corresponds to 291,125.85 TJ/year or 9231.60 MW of electricity, which can fulfill 88% of the national total energy demand. In terms of levelized cost, the proposed approach is more competitive and shows a greater promise compared to other technologies. Furthermore, it demonstrates environmental friendliness by reducing CO 2 emissions by 156 tons at a cost of $7/ton while earning $1092 annually from the potential carbon-credit market. This approach presents a potential solution to address Bangladesh's energy crisis. The payback period of the system ranged from 2.93 to 3.75 years, with and without the inclusion of a slurry, respectively. The recommended methods hold significant promise for meeting national energy demands. A case study was provided as a proof-of-concept (PoC) to validate the approach. This study is the first of its kind, providing valuable insights into the renewable energy potential in Bangladesh. The results will assist policymakers in formulating sustainable energy policies. • Mathematics, engineering, economics and environmental modeling explored renewable energy. • Techno-economics and environmental sustainability validated the proposed methodology. • Bioenergy-based electricity could supply 88% of the national energy demand of Bangladesh. • A case study was provided as a proof-of-concept (PoC) to validate the approach. [ABSTRACT FROM AUTHOR]

Blockchain Technology has garnered significant attention due to its immense potential to transform the way transactions are conducted and information is managed. Blockchain is a decentralized digital ledger that is spread across a network of computers, ensuring the secure, transparent, and unchangeable recording of transactions. However, the energy consumption of certain blockchain networks like Bitcoin, Litecoin, Monero, Zcash, and others has generated apprehensions regarding the sustainability of this technology. Bitcoin alone consumes approximately 100 terawatt-hours annually, contributing significantly to global carbon emissions. The substantial energy requirements not only contribute to carbon emissions but also pose a risk to the long-term viability of the blockchain industry. This study reviews articles from eight reputable databases between 2017 to August 2023, employing the systematic review and preferred reporting items for systematic reviews and meta-analyses approach for screening. Therefore, explore the applications of sustainable blockchain networks aimed at reducing environmental impact while ensuring efficiency and security. This survey also assesses the challenges and limitations posed by diverse blockchain applications regarding sustainability and provides valuable foresight into potential future advancements. Through this survey, the aim is to track and verify sustainable practices, facilitating the transition to a low-carbon economy, and promoting environmental stewardship, with a specific focus on highlighting the potential of sustainable blockchain networks in enabling secure and transparent tracking of these practices. Finally, the paper sheds light on pertinent research challenges and provides a roadmap of future directions, stimulating further research in this promising field. • Preferred Reporting Items for Systematic Reviews and Meta- Analyses (PRISMA Study). • Identification of Sustainable Blockchain Use Cases. • Sustainable Blockchain Challenges and Opportunities. • Blockchain for Transparent Sustainability Tracking. • Future Research Directions. [ABSTRACT FROM AUTHOR]

Objectives: Energy consumption and carbon emissions from medical equipment like CT/MRI scanners and workstations contribute to the environmental impact of healthcare facilities. The aim of this systematic review was to identify all strategies to reduce energy use and carbon emissions in radiology. Methods: In June 2023, a systematic review (Medline/Embase/Web of Science) was performed to search original articles on environmental sustainability in radiology. The extracted data include environmental sustainability topics (e.g., energy consumption, carbon footprint) and radiological devices involved. Sustainable actions and environmental impact in radiology settings were analyzed. Study quality was assessed using the QualSyst tool. Results: From 918 retrieved articles, 16 met the inclusion criteria. Among them, main topics were energy consumption (10/16, 62.5%), life-cycle assessment (4/16, 25.0%), and carbon footprint (2/16, 12.5%). Eleven studies reported that 40–91% of the energy consumed by radiological devices can be defined as "nonproductive" (devices "on" but not working). Turning-off devices during idle periods 9/16 (56.2%) and implementing workflow informatic tools (2/16, 12.5%) were the sustainable actions identified. Energy-saving strategies were reported in 8/16 articles (50%), estimating annual savings of thousand kilowatt-hours (14,180–171,000 kWh). Cost-savings were identified in 7/16 (43.7%) articles, ranging from US $9,225 to 14,328 per device. Study quality was over or equal the 80% of high-quality level in 14/16 (87.5%) articles. Conclusion: Energy consumption and environmental sustainability in radiology received attention in literature. Sustainable actions include turning-off radiological devices during idle periods, favoring the most energy-efficient imaging devices, and educating radiological staff on energy-saving practices, without compromising service quality. Relevance statement: A non-negligible number of articles — mainly coming from North America and Europe — highlighted the need for energy-saving strategies, attention to equipment life-cycle assessment, and carbon footprint reduction in radiology, with a potential for cost-saving outcome. Key points: • Energy consumption and environmental sustainability in radiology received attention in the literature (16 articles published from 2010 to 2023). • A substantial portion (40–91%) of the energy consumed by radiological devices was classified as "non-productive" (devices "on" but not working). • Sustainable action such as shutting down devices during idle periods was identified, with potential annual energy savings ranging from 14,180 to 171,000 kWh. [ABSTRACT FROM AUTHOR]

This article provides an overview of the concept of green finance and its role in promoting sustainable economic growth, with a particular focus on the top 15 countries with the highest GDP and green growth index from 2010 to 2019. The article discusses the negative impact of energy consumption on the environment and highlights the need for a shift towards a low-carbon, resource-efficient, and socially inclusive economy. Data from 186 countries were collected from the World Bank and the OECD’s iLibrary for the years 2010 to 2019, and the analysis method involved descriptive statistical analysis and simple linear regression analysis using the DAX function language in Power BI. The research findings reveal that CO2 emissions and economic financial indicators are interrelated, and using Power BI tool visualizing green finance data shows the correlation between GDP and CO2 emissions and highlights the countries that have achieved high levels of green finance. The article concludes by suggesting several solutions to promote green finance on a global scale, including establishing funding sources that prioritize green finance projects, creating green investment opportunities, and improving legal regulations to support the development of green finance. [ABSTRACT FROM AUTHOR]