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1
Awazi, Nyong Princely. "Driving sustainable agroforestry through carbon credit-based policies: Realities and perspectives". Natural Resources Conservation and Research 8, nr 1 (25.01.2025): 10184. https://doi.org/10.24294/nrcr10184.
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Carbon credit-based policies are important to driving sustainable practices worldwide. These policies have in the past focused mainly on wetlands, forests, and other ecosystems, neglecting agroforestry—which is a climate-smart and agroecological practice. This paper therefore seeks to examine how carbon credit-based policies can drive sustainable agroforestry through an in-depth empirical review of literature. It was found that the most common carbon credit-based policies and schemes are government-led, including the CCER (China Certified Emissions Reduction), ETS (EU Emissions Trading System), and the California Global Warming Solutions Act in the United States of America. These schemes focus on heavy emitters such as transportation, steel, and cement. Carbon credits guiding carbon credit-based policy formulation and implementation are mainly: Credits from avoided emissions (not cutting down trees); credits from reduced emissions (energy-efficient technologies); and credits from removed emissions (tree planting and carbon capture tech). Factoring in these 03 main types of carbon credits into the carbon credit policy framework will drive sustainable agroforestry across the world in general and the developing world in particular, as smallholder agroforestry farmers will be encouraged to practice agroforestry. One of the main stumbling blocks to the practice of agroforestry is the financial cost involved in its establishment and management, which the carbon credit scheme would offset. Besides driving sustainable agroforestry, carbon credit-based policies in the domain of agroforestry would provide other co-benefits such as employment generation; technology transfer; improved energy security and access to energy services; improved livelihoods; improved air, water, or soil quality; and infrastructure development.
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Jiao, Jie, Jiyuan Zhang, Jie Yang, Wenwen Zhang, Fengtao Guang i Liying Liu. "The Study of Carbon Neutralization Effects with Green Credit: Evidence from a Panel Data Analysis for Interprovinces in China". Sustainability 15, nr 17 (4.09.2023): 13267. http://dx.doi.org/10.3390/su151713267.
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Giving full play to carbon emission reduction of green credits is essential to achieve carbon neutrality. According to low-carbon pilot policies and the condition of industrial transfer, this paper first sorts those provinces into different research zones. The zones are as follows: (Ⅰ) the first and second batch of low-carbon municipalities and the first batch of pilot provinces (L1) and other provinces (L2) and (Ⅱ) strong industry transfer-out zone (STR), weak industry transfer-out zone (WTR), and industrial transfer-in area (TIR). Then, we employ a dynamic panel data model and systematic GMM (SYS-GMM) approach to empirically test the impact of green credit and nongreen credit on carbon emissions. Further, this paper analyzes how to coordinate two types of credits to achieve carbon neutrality. The results show that, first, at the national level, the nexus of green credit and carbon emissions with an inverted U-shaped curve and the current impact of green credit is still in the first half of the inverted U-shaped stage. The achievement of carbon neutrality is associated with the ratio structure of green credit to nongreen credit and the scale of green credit. Second, the achievement of carbon neutrality is with regional heterogeneity. The achievement of carbon neutrality is associated with the scale of green credit in L2 and TIR, but also with the ratio structure of nongreen credit to green credit in L2 and STR. However, the carbon neutralization effects with green credit are insignificant in L1 WTR. Finally, based on those conclusions, this paper puts forwards some suggestions to provide references for the policy formulation of green credits and carbon neutrality.
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Fernandes, Douglas Celes, Orlando Celso Longo, Rodrigo Garcia Caiano, Eduardo Ribeiro Kaiser i Andrew Lucas Pessoa Baldam. "Governance and Challenges in the Carbon Credit Market: a Comparative Analysis of Industrial Waste and Solid Waste in the State of Rio de Janeiro". Revista de Gestão Social e Ambiental 18, nr 12 (10.12.2024): e09502. https://doi.org/10.24857/rgsa.v18n12-055.
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Objective: The general objective of this study is to analyze the governance and challenges of the carbon credit market, focusing on the comparison between industrial waste and solid waste in Rio de Janeiro. To achieve this objective, the following specific objectives were established: to examine the history and evolution of the carbon credit market; to analyze the global and Brazilian energy scenario and its impact on the greenhouse effect; to investigate the principles of the Clean Development Mechanism (CDM) and its applications; and to evaluate the management of solid and industrial waste in the context of carbon credit. Theoretical Framework: In the early 1980s, the idea of exchanging the national debt of developing countries as a means of preserving natural resources emerged, establishing a model for carbon credits (Albuquerque et al., 2021). Carbon credits are one of the strategies adopted at national and international level to mitigate the increase in greenhouse gas concentrations in the atmosphere. Method: The methodology adopted for this research involves analyzing the governance and challenges of the carbon credit market, with a focus on comparing the management of industrial waste and solid waste in the state of Rio de Janeiro. Comparative analysis is a central part of the study, which examines the differences and similarities in industrial and solid waste management, with the aim of understanding how these practices impact the carbon credit market. Results and Discussion: The results show that the information presented on urban solid waste management in the state of Rio de Janeiro reveals a challenging scenario that requires coordinated action between the state, municipalities and the various sectors of society. The average generation of solid urban waste per capita is 1 kg per day, totaling approximately 6,596,840.90 tons per year in the state (Inea-RJ, 2023). The inadequate disposal of this waste over the decades has caused environmental, social and economic problems. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of governance in the carbon credit market in the context of solid and industrial waste management in the state of Rio de Janeiro, demonstrates that inadequate waste management has been a challenge, generating environmental impacts and limiting the potential for recovery and reuse of materials. In a scenario where the average generation of urban solid waste per capita is 1 kg per day, totaling approximately 6,596,840.90 tons per year, the implementation of sustainable solutions, such as the creation of a carbon credit market, can offer viable alternatives to mitigate these problems. Originality/Value: This study contributes to the literature as the governance and challenges of the carbon credit market in the context of waste management in Rio de Janeiro reflect the complexity of the interactions between production, consumption and disposal. The implementation of integrated policies and the promotion of sustainable practices are essential to overcome current challenges and create opportunities for economic and environmental development.
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Alcasena, Fermín, Marcos Rodrigues, Pere Gelabert, Alan Ager, Michele Salis, Aitor Ameztegui, Teresa Cervera i Cristina Vega-García. "Fostering Carbon Credits to Finance Wildfire Risk Reduction Forest Management in Mediterranean Landscapes". Land 10, nr 10 (19.10.2021): 1104. http://dx.doi.org/10.3390/land10101104.
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Despite the need for preserving the carbon pools in fire-prone southern European landscapes, emission reductions from wildfire risk mitigation are still poorly understood. In this study, we estimated expected carbon emissions and carbon credits from fuel management projects ongoing in Catalonia (Spain). The planning areas encompass about 1000 km2 and represent diverse fire regimes and Mediterranean forest ecosystems. We first modeled the burn probability assuming extreme weather conditions and historical fire ignition patterns. Stand-level wildfire exposure was then coupled with fuel consumption estimates to assess expected carbon emissions. Finally, we estimated treatment cost-efficiency and carbon credits for each fuel management plan. Landscape-scale average emissions ranged between 0.003 and 0.070 T CO2 year−1 ha−1. Fuel treatments in high emission hotspots attained reductions beyond 0.06 T CO2 year−1 per treated ha. Thus, implementing carbon credits could potentially finance up to 14% of the treatment implementation costs in high emission areas. We discuss how stand conditions, fire regimes, and treatment costs determine the treatment cost-efficiency and long-term carbon-sink capacity. Our work may serve as a preliminary step for developing a carbon-credit market and subsidizing wildfire risk management programs in low-revenue Mediterranean forest systems prone to extreme wildfires.
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Chen, Guangyang, Kai Dong, Shaonan Wang, Xiuli Du, Ronghua Zhou i Zhongwei Yang. "The Dynamic Relationship among Bank Credit, House Prices and Carbon Dioxide Emissions in China". International Journal of Environmental Research and Public Health 19, nr 16 (21.08.2022): 10428. http://dx.doi.org/10.3390/ijerph191610428.
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This paper explores the dynamic relationship among bank credit, house prices and carbon dioxide emissions in China by systematically analyzing related data from January 2000 to December 2019 with the help of the time-varying parameter vector autoregression with stochastic volatility (TVP-SV-VAR) model and the Bayesian DCC-GARCH model. Empirical results show the expansion of bank credit significantly drives up house prices and increases carbon dioxide emissions in mosttimes. The rise in house prices inhibits the expansion of bank credit but increases carbon dioxide emissions and aggravates environment pollution, and that the increase in carbon dioxide is helpful to stimulate bank credit expansion and house price rise. In addition, bank credit and house prices are most relevant, followed by bank credit and carbon dioxide emissions, then by house prices and carbon dioxide emissions. Therefore, we believe that in order to stabilize skyrocketing house prices, restrain carbon dioxide emissions, and secure a stable and healthy macro-economy, the government should strengthen management of bank credit, and effectively control its total volume.
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Gong, Lei, Tianxu Wang, Tian Lei, Qin Luo, Zhu Han i Yihong Mo. "Daily Travel Mode Choice Considering Carbon Credit Incentive (CCI)—An Application of the Integrated Choice and Latent Variable (ICLV) Model". Sustainability 15, nr 20 (12.10.2023): 14809. http://dx.doi.org/10.3390/su152014809.
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There have been many implementations of carbon credit incentives (CCIs) for promoting green travel, but research on quantifying the effectiveness remains limited. To fill this gap, this study focuses on residents’ daily transportation mode choices under the incentive of carbon credits by employing an integrated choice and latent variable (ICLV) model to adequately address the role of attitudinal variables related to carbon credits, such as perceived usefulness, perceived ease of use, and behavioral intentions. Data from a questionnaire survey show that the ICLV model provides a richer and more nuanced understanding of the green mode choice than a traditional multinomial logit (MNL) model, where the AIC value of the ICLV model (3901.17) is smaller than that of the MNL model (3910.09). Carbon credits exhibit diverse impacts across various modes of eco-friendly transportation and specific demographic groups. Commuting trips reveal noteworthy positive associations between carbon credits and the use of bicycles as well as metro/bus services. Moreover, carbon credits exert a more pronounced influence on individuals with higher education levels, older age groups, and owners of new energy vehicles, whereas their impact on high-income individuals is relatively constrained. Furthermore, perceptions of carbon credits are pivotal, with perceived utility emerging as the most influential factor. The results provide a scientific basis for formulating more effective policies regarding carbon credit and incentive measures in the future.
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Sushil Bhawaria, Et al. "Machine Learning Enabled Inventory Control for Deteriorating Items with Carbon Emission and Trade Credit under Learning and Forgetting". Communications on Applied Nonlinear Analysis 30, nr 4 (5.01.2024): 85–100. http://dx.doi.org/10.52783/cana.v30.310.
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This research introduces a novel approach to inventory control, leveraging machine learning techniques to optimize inventory decisions for deteriorating items while accounting for carbon emissions and trade credit policies. In contemporary supply chain management, sustainability considerations have become increasingly vital. The carbon footprint associated with inventory management practices necessitates innovative solutions to minimize environmental impact. Moreover, trade credit offers financial flexibility but requires careful management to maintain profitability. To address these complex challenges, our proposed framework integrates machine learning algorithms into inventory control to enhance decision-making precision. The model incorporates dynamic learning and forgetting effects, allowing the system to adapt to changing demand patterns over time. This adaptability is particularly critical when dealing with deteriorating items that exhibit non-constant demand rates. Carbon emissions are assessed throughout the supply chain, and environmentally conscious decisions are made to minimize the carbon footprint. Additionally, trade credit terms are optimized to strike a balance between financial constraints and inventory performance. Our approach demonstrates superior performance in terms of minimizing costs, reducing carbon emissions, and enhancing supply chain resilience compared to traditional inventory management methods. Real-world case studies and simulations validate the effectiveness of our machine learning-enabled inventory control system, showcasing its practical applicability. This research contributes to the advancement of sustainable supply chain management by providing a comprehensive framework that combines AI-driven inventory control, carbon emission reduction, and trade credit optimization, ultimately fostering environmentally responsible and financially viable inventory decisions.
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Mishra, Mowmita, Santanu Kumar Ghosh i Biswajit Sarkar. "Maintaining energy efficiencies and reducing carbon emissions under a sustainable supply chain management". AIMS Environmental Science 9, nr 5 (2022): 603–35. http://dx.doi.org/10.3934/environsci.2022036.
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<abstract><p>Currently, most countries are moving towards digitalization, and their energy consumption is increasing daily. Thus, power networks face major challenges in controlling energy consumption and supplying huge amounts of electricity. Again, using excessive power reduces the stored fossil fuels and affects the environment in terms of $ {\rm CO_{2}} $ emissions. Keep these issues in mind; this study focuses on energy-efficient products in an energy supply chain management model under credit sales, variable production, and stochastic demand. Here, the manufacturer grants a credit period for the retailer to get more orders; thus, the order quantity is related to the credit period envisaged in this model. Considering such components, supply chain members can reduce negative environmental impacts and significant energy consumption, achieve optimal results and avoid drastic financial losses. Additionally, including a credit period increases the possibility of default risk, for which a certain interest is charged. The marginal reduction cost for limiting carbon emissions, flexible production to meet fluctuating demand, and continuous investment to improve product quality are considered here. The global optimality of system profit function and decision variables (credit period, quality improvement, and production rate) is ensured through the classical optimization method. Interpretive sensitivity analyses and numerical investigations are performed to validate the proposed model. The results demonstrate that the idea of credit sales, flexible production, and quality improvement increases total system profit by $ 28.64\% $ and marginal reduction technology reduces $ {\rm CO_{2}} $ emissions up to $ 4.01\% $.</p></abstract>
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Hu, Yi, i Jiayu Zheng. "Is Green Credit a Good Tool to Achieve “Double Carbon” Goal? Based on Coupling Coordination Model and PVAR Model". Sustainability 13, nr 24 (20.12.2021): 14074. http://dx.doi.org/10.3390/su132414074.
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China attaches importance to the combination of credit policy and environmental protection, tries to use credit policy tools to protect ecology and pollution prevention, and prevent environmental credit risk. With the proposal of the goal of “carbon peak and carbon neutralisation” (“double carbon”), green credit is also regarded as an important policy tool to achieve this goal. Firstly, this paper selects the time series data of green credit at the national level from 2013 to 2019 according to the official statistics and evaluates the coupling and coordinated development of credit system and environmental system based on the coupling coordination model. The results show that the two systems show well-coordinated development, but the interaction has annual fluctuations. Secondly, by calculating the provincial carbon emissions and green credit panel data from 2005 to 2019, the dynamic internal mechanism is analysed based on Panel Vector Autoregression (PVAR) model. It is found that green credit has a significant inhibitory effect on carbon emissions. The research results of this paper provide an overall evaluation of the quantity and quality of green credit for China’s banking industry. It also provides reasonable and effective support for green credit as a policy tool to promote realising the “double carbon” goal. In addition, China should maintain the consistency, stability and durability of green credit policy and continue to contribute to the low-carbon transformation of the economy and society.
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Zhang, Wenjie, Mingyong Hong, Juan Li i Fuhong Li. "An Examination of Green Credit Promoting Carbon Dioxide Emissions Reduction: A Provincial Panel Analysis of China". Sustainability 13, nr 13 (25.06.2021): 7148. http://dx.doi.org/10.3390/su13137148.
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The implementation of green finance is a powerful measure to promote global carbon emissions reduction that has been highly valued by academic circles in recent years. However, the role of green credit in carbon emissions reduction in China is still lacking testing. Using a set of panel data including 30 provinces and cities, this study focused on the impact of green credit on carbon dioxide emissions in China from 2006 to 2016. The empirical results indicated that green credit has a significantly negative effect on carbon dioxide emissions intensity. Furthermore, after the mechanism examination, we found that the promotion impacts of green credit on industrial structure upgrading and technological innovation are two effective channels to help reduce carbon dioxide emissions. Heterogeneity analysis found that there are regional differences in the effect of green credit. In the western and northeastern regions, the effect of green credit is invalid. Quantile regression results implied that the greater the carbon emissions intensity, the better the effect of green credit. Finally, a further discussion revealed there exists a nonlinear correlation between green credit and carbon dioxide emissions intensity. These findings suggest that the core measures to promote carbon emission reduction in China are to continue to expand the scale of green credit, increase the technology R&D investment of enterprises, and to vigorously develop the tertiary industry.
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Bansal, Abhay, Aastha Panwar, Bhuvan Unhelkar i Mandeep Mittal. "Optimizing Inventory for Imperfect and Gradually Deteriorating Items Under Multi-Level Trade Credit in a Sustainable Supply Chain". Mathematics 13, nr 5 (25.02.2025): 752. https://doi.org/10.3390/math13050752.
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Reducing carbon emissions is of immense interest to most modern organizations striving for sustainability. Effective inventory management is crucial for achieving resource optimization and minimizing environmental impact. Very little work has been conducted up to this point on slowly declining, low-quality products with multi-level trade credit rules under the influence of carbon emissions. In this study, an inventory model is tailored specifically for imperfect and gradually deteriorating products with a multi-level trade credit policy. Further, the impact of carbon emissions on the retailer’s ordering strategies is also considered. To determine the optimal policy for supply chain partners, three trade credit instances with seven subcases are taken into consideration. To choose the best scenario out of ten cases, an algorithm is also developed. The model’s validity is illustrated through a numerical experiment and sensitivity analysis. This study is an innovative approach to balancing economic trade credit policy in sustainable supply chain management.
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Kumar, Rikesh, Rakesh Kumar, Sambhunath Karmakar, Amit Kumar, Alok Kumar Singh, Abhay Kumar i Jitendra Singh. "Impact of Amide Fertilizer on Carbon Sequestration under the Agroforestry System in the Eastern Plateau Region of India". Sustainability 15, nr 12 (19.06.2023): 9775. http://dx.doi.org/10.3390/su15129775.
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Carbon sequestration is an important aspect of expelling greenhouse gases from the atmosphere and decelerating the rate of global warming. Agroforestry plays an important role in carbon sequestration. Keeping this in mind, the current study was carried out between 2017 and 2021 to assess the effect of integrated nutrient management on biomass production, carbon sequestration, and carbon credit in a mango and turmeric agroforestry system. The study used randomized block design (RBD) with four treatments and five replications. According to the findings of this study, the rate of fertilizer application has a significant impact on the growth of turmeric and mango crops. The physiochemical characteristics of soil show an improvement in soil composition with the application of urea (CO(NH2)2), single super phosphate [Ca(H2PO4)2.2H2O] 226 kg ha−1, MOP [KCl] 309 kg ha−1 100 kg ha−1. The carbon density of the agrihorticulture land use system was six to seven times higher than that of the open agriculture-based land use system. The highest turmeric production (8.98 t ha−1) was reported under the mango-turmeric system rather than turmeric alone (6.36 t ha−1) in the T2-N100kg treatment. Total biomass production (61.2 t ha−1 and 64.6 t ha−1), carbon stock (38.6 t ha−1 and 41.06 t ha−1), carbon sequestration (246.5 t ha−1 and 299.5 t ha−1), and carbon credit (246.57 credits and 299.5 credits) were found to be highest in mango and turmeric-based agroforestry land use system treatments T2-N100 kg and T3-N80 Kg, respectively. The net additional profit from the agrihorticulture land use system was 299.5 carbon credits, which is equivalent to 4,49,250 INR.
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Lupala, Z. J., L. P. Lusambo i Y. M. Ngaga. "Feasibility of Community Management of Miombo Woodlands for Carbon Project in Southern Highlands of Tanzania". International Journal of Ecology 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/8965983.
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In response to the pressing global challenges of climate change, community based management of miombo woodlands in Tanzania is promoted for carbon credit project development. However, evidence on its feasibility is scanty and questionable. This study examined the economic feasibility of carbon credit project development in community based forest management (CBFM) using four similar miombo woodlands from Southern highlands. The analysis was based on 144 sample plots from managed woodlands and 100 plots from business as usual (BAU) (open access). Allometric equation was applied to convert biomass to carbon per hectare. Improved carbon stock was determined and its economic value ascertained based on global voluntary carbon markets. Project feasibility analysis was performed using discounted cash flow, internal rate of return, and benefits/costs methods. Annual opportunity cost and variable costs were subtracted from total revenue to obtain annual net profit. The annual rate of return on investment was calculated by dividing profits by total costs. It was revealed that carbon stock improved significantly in CBFM compared to BAU (P<5%). The improvement had positive net present value and benefit-cost ratio of 1.83. Moreover, sensitivity analysis showed that if any unexpected situation occurs, the project will still be of worthiness. The findings are useful to enrich the debate on carbon credit development under community based management of miombo woodlands in Tanzania.
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Schuett, Lukas. "Permanence and Liability: Legal Considerations on the Integration of Carbon Dioxide Removal into the EU Emissions Trading System". Transnational Environmental Law 13, nr 1 (marzec 2024): 87–110. http://dx.doi.org/10.1017/s2047102524000013.
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AbstractThis article examines how carbon dioxide (CO2) removal credits can be integrated into the European Union (EU) Emissions Trading System (ETS), focusing on questions of permanence and climate liability. It identifies challenges within the integration process and analyzes approaches from practice and literature to cultivate learning. These approaches apply different strategies to address the issue of permanence, including temporary credit issuance, granting credits once a certain number of carbon tonne-years have been accumulated, or issuing credits at the beginning of the project period and relying on liability instead. Drawing from the findings of this research, the article presents legal considerations that may inform a proposal for an EU legislative act on the integration of carbon removal credits into the EU ETS. It suggests that only credits issued for permanent CO2 removal should be integrated to ensure the environmental integrity of the system. Furthermore, the liability of the project operator should transfer to the Member State under certain conditions to make liability risks more predictable.
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Ecklu, John, Alex Johnson, Tessa Landon i Evan Thomas. "Leveraging the Voluntary Carbon Market to Improve Water Resilience in the Colorado and Mississippi River Basins". Water 16, nr 18 (12.09.2024): 2578. http://dx.doi.org/10.3390/w16182578.
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The Colorado and Mississippi River basins are crucial for water supply, agriculture, and ecological stability in the U.S., yet climate change, water management practices, and energy sector demands pose significant challenges to their sustainability. This paper highlights the potential of leveraging the Voluntary Carbon Market (VCM) to address these challenges by creating new revenue streams and incentivizing sustainable water management practices. It provides high-level estimates by extrapolating from existing literature. The paper finds that water projects in these basins could generate over 45 million carbon credits annually, potentially attracting around USD 4.5 billion in investments over the next decade. However, challenges such as high costs, complex regulations, and stakeholder coordination must be addressed. The paper also identifies opportunities for advancing water resiliency projects, including increasing public awareness, engaging corporations, and utilizing innovative financing mechanisms. Recommendations include promoting the VCM–water relationship, encouraging methodology innovation, developing pilot programs, investing in digital monitoring technologies, and conducting localized analysis to optimize carbon credit potential in water management. In conclusion, this paper quantifies the potential of water projects to generate carbon credits and indicates that integrating carbon markets with water management strategies can significantly contribute to global climate goals and improve water resilience in these critical regions.
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Wong, Biing-Teo, K. Y. Show, D. J. Lee i J. Y. Lai. "Carbon balance of anaerobic granulation process: Carbon credit". Bioresource Technology 100, nr 5 (marzec 2009): 1734–39. http://dx.doi.org/10.1016/j.biortech.2008.09.045.
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Li, Xiaomei, Yiwen Zhang, Zijie Yang, Yijun Zhu, Cihang Li i Wenxiang Li. "Modeling Choice Behaviors for Ridesplitting under a Carbon Credit Scheme". Sustainability 15, nr 16 (10.08.2023): 12241. http://dx.doi.org/10.3390/su151612241.
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Ridesplitting, a form of shared ridesourcing service, has the potential to significantly reduce emissions. However, its current adoption rate among users remains relatively low. Policies such as carbon credit schemes, which offer rewards for emission reduction, hold great promise in promoting ridesplitting. This study aimed to quantitatively analyze the choice behaviors for ridesplitting under a carbon credit scheme. First, both the socio-demographic and psychological factors that may influence the ridesplitting behavioral intention were identified based on the theory of planned behavior, technology acceptance model, and perceived risk theory. Then, a hybrid choice model of ridesplitting was established to model choice behaviors for ridesplitting under a carbon credit scheme by integrating both structural equation modeling and discrete choice modeling. Meanwhile, a stated preference survey was conducted to collect the socio-demographic and psychological information and ridesplitting behavioral intentions of transportation network company (TNC) users in 12 hypothetical scenarios with different travel distances and carbon credit prices. Finally, the model was evaluated based on the survey data. The results show that attitudes, subjective norms, perceived behavioral control, low-carbon values, and carbon credit prices have significant positive effects on the choice behavior for ridesplitting. Specifically, increasing the carbon credit price could raise the probability of travelers choosing ridesplitting. In addition, travelers with higher low-carbon values are usually more willing to choose ridesplitting and are less sensitive to carbon credit prices. The findings of this study indicate that a carbon credit scheme is an effective means to incentivize TNC users to choose ridesplitting.
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Salma, Alaa, Lydia Fryda i Hayet Djelal. "Biochar: A Key Player in Carbon Credits and Climate Mitigation". Resources 13, nr 2 (14.02.2024): 31. http://dx.doi.org/10.3390/resources13020031.
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The creation of the carbon market came forth as a tool for managing, controlling, and reducing greenhouse gas emissions, combining environmental responsibility with financial incentives. Biochar has gained recognition as one of potential carbon offset solution. The practical and cost-effective establishment of biochar carbon credit standards is crucial for the integration of biochar into carbon trading systems, thus encouraging investments in the biochar industry while promoting sustainable carbon dioxide sequestration practices on a global scale. This communication focuses on the potential of biochar in carbon sequestration. Additionally, it spotlights case studies that highlight how biochar effectively generates carbon credits, as well as discussing the evolving carbon removal marketplace. Furthermore, we address knowledge gaps, areas of concern, and research priorities regarding biochar implementation in carbon credits, with the aim of enhancing our understanding of its role in climate change mitigation. This review positions biochar as a versatile and scalable technology with the potential to contribute significantly to carbon credits, aligning with sustainable development goals. It calls for continued research, transparency, and international cooperation to explore the full potential of biochar in climate change mitigation efforts.
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Oduor, David Ochieng, Peter Otieno Opeyo i Dorice Anyango Oduor. "Role of Household’s Tree Population, Socio-economic and Behavioural Determinants on Carbon Footprint Mitigation and Carbon Credit Balance in East Ugenya Ward, Kenya". East African Journal of Environment and Natural Resources 6, nr 1 (5.11.2023): 447–58. http://dx.doi.org/10.37284/eajenr.6.1.1553.
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Scope 1 harmful emissions are directly linked to high levels of industrialization; Scope 2 and 3 carbon footprints are locally oriented and indirectly associated with household activities and behavioural alignment. East Ugenya Ward is perceived as the leader in firewood consumption, with the socioeconomically marginalized population in Siaya County resorting to this mode of fuel usage. Conversely, how the mentioned factors relate to both carbon footprints and credits is concluded with no concrete local and global resolution. The effort to reverse households’ carbon emissions through green energy campaigns has proved less operative due to little understanding of carbon-related working concepts and socio-economic hardships. This study analyses the role of household Tree population. It assesses the role of socio-economic and behavioural determinants in relation to carbon footprints and potential credits that can arise through sound environmental management within local community initiatives. Three hundred eighty-four household heads were interrogated. A descriptive cross-sectional research design and simple random sampling were found to be functional. Databases were Questionnaires, field research, measurement, photography, Focused Group Discussions, observation, key informants, and enumeration. Carbon Footprint Calculator (C.F.C.) and (V.C.S.)-Verra were used to assess the household’s emissions and potential credits. The spatial scale for tree population count was 20 m x 20 m quadrat. The tree-based biomass was translated using a conventional carbon sink conversion (Tons of Co2 Equivalent- tCo2eq). Data analysis involved the use of SPSS. The potential net carbon offset was (M = 0.334, SD = 0.006) tCo2eq per household. The Multinomial Logistic Regression model X2 (8, N= 384) = 24.69, Nagelkerke R2=.56, p <. 001, Strongly proved that the belief that Carbon Credit is profitable had a significant statistical association with Carbon Footprint Mitigation. The multiple linear coefficients of determination proved that 67.6%, F (381) = 69.51, p = .031, R2 = .676 of change in Carbon Footprints and 72.1%, F (381) = 72.58, p = .026, R2 =.721 of the variation in Net Carbon Credits, was attributable to combined variation in Tree population, Mean household age, and mean average monthly income. Both the Carbon Footprint and Carbon credit are affected. Therefore, local sensitization is needed to achieve knowledge and understanding of favourable emission budgets and profitable carbon trade
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Gunn, John S., David S. Saah, Kathryn Fernholz i David J. Ganz. "Carbon Credit Eligibility under Area Regulation of Harvest Levels in Northern Minnesota". Forest Science 57, nr 6 (1.12.2011): 470–78. http://dx.doi.org/10.1093/forestscience/57.6.470.
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Abstract We evaluated the implications of area regulation of harvest on eligible carbon under both the Voluntary Carbon Standard (VCS) and the Chicago Climate Exchange (CCX) for public forest lands in north central Minnesota (89,840 ha total). We used data from the carbon submodel of the US Forest Service Forest Vegetation Simulator (Lake States variant) to evaluate changes in forest carbon stocks under different management scenarios. Baseline harvest intensity was defined by considering the manager's short-range tactical plans and the distribution of harvests by cover type and intensity class then became the “business as usual” (BAU) for use in the calculation of eligible carbon under the VCS and CCX. Under VCS, the most effective way to increase carbon stocks while meeting other management objectives was to shift harvest practices to lower intensity entries and retain higher residual basal areas. The carbon stock change rates for each manager varied significantly under the BAU scenario and resulted in a mean annual net decrease. Because CCX carbon credit eligibility requires a net increase of carbon stocking from the base year, area regulation may create periods of time where there is no eligible carbon volume. An alternate management strategy that uses the area regulation method, reduces harvest intensity, and decreases overall acreage harvested was able to provide higher postharvest carbon stocks versus the BAU scenario under VCS.
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Li, Kaifeng, Yun Chen i Jingren Chen. "How to Improve Industrial Green Total Factor Productivity under Dual Carbon Goals? Evidence from China". Sustainability 15, nr 11 (1.06.2023): 8972. http://dx.doi.org/10.3390/su15118972.
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This paper focuses on the relationship between green credit and industrial green total factor productivity under the dual carbon target. In recent years, weather extremes that break historical extremes have occurred frequently around the world, and the resulting loss of life and property has deepened people’s concern about climate change. As a responsible developing country, China has set the goal of reaching peak carbon emissions and reducing carbon intensity by 60–65% by 2030. In this context, based on China’s provincial-level data from 2006 to 2019, this paper first measures the growth rate of industrial green total factor productivity using the SBM-ML model, and then analyzes the impact of green credit on industrial green total factor productivity under the double carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We then analyze the impact of green credit on industrial green total factor productivity under the dual carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We find that green credit can improve the energy consumption structure and thus increase industrial green total factor productivity. In addition, the study finds that the interaction effect of green credit and environmental regulation suppresses the positive impact of green credit on industrial green TFP. This paper provides empirical evidence and policy implications for the orderly promotion of carbon peaking and carbon neutral efforts to effectively improve industrial green total factor productivity and promote high-quality economic development.
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Dumrose, Maurice, i André Höck. "Corporate Carbon-Risk and Credit-Risk: The Impact of Carbon-Risk Exposure and Management on Credit Spreads in Different Regulatory Environments". Finance Research Letters 51 (styczeń 2023): 103414. http://dx.doi.org/10.1016/j.frl.2022.103414.
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Blanc, Simone, Cristian Accastello, Ettore Bianchi, Federico Lingua, Giorgio Vacchiano, Angela Mosso i Filippo Brun. "An integrated approach to assess carbon credit from improved forest management". Journal of Sustainable Forestry 38, nr 1 (6.07.2018): 31–45. http://dx.doi.org/10.1080/10549811.2018.1494002.
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Jones, Ellie-Anne, Lisa Paige, Albany Smith, Annabelle Worth, Lois Betts i Richard Stafford. "Potential for Carbon Credits from Conservation Management: Price and Potential for Multi-Habitat Nature-Based Carbon Sequestration in Dorset, UK". Sustainability 16, nr 3 (2.02.2024): 1268. http://dx.doi.org/10.3390/su16031268.
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Carbon offsetting is currently a major tool in managing carbon emissions and informing sustainability plans of organisations in the drive to net-zero. This study aims to identify the offsetting potential of existing conservation schemes, and whether carbon offsetting credits could provide finance these conservation activities. The results from Dorset, in the UK, indicate that many existing conservation schemes in woodlands, heathlands, and grasslands cannot only enhance biodiversity but also capture significant amounts of carbon, and while habitats differ by region and country, the general results should be applicable elsewhere. We show that the cost per additional tonne of carbon sequestered as a result of conservation activities varies considerably between different conservation projects. On average, across the conservation projects we studied, the cost of this offsetting is GBP 80 per tonne CO2e sequestered and ranging between GBP 120 and GBP 0, depending on the project and whether existing biodiversity grants would be available. However, this figure was based on adapting and refining the existing conservation projects and did not involve expensive factors, such as purchase of land, which make the prices potentially unrealistic, especially in a Global North context. While the costs identified are higher than many offsetting schemes at present, it could present a useful option for those wishing to localise their offsetting. The concept is highly scalable and could remove significant amounts of carbon dioxide. Combining the approach with biodiversity credits or other credit schemes could make the higher costs more attractive to potential buyers.
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Moser, Robert Lane, Marcella A. Windmuller-Campione i Matthew B. Russell. "Natural Resource Manager Perceptions of Forest Carbon Management and Carbon Market Participation in Minnesota". Forests 13, nr 11 (18.11.2022): 1949. http://dx.doi.org/10.3390/f13111949.
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Forests and wood products, through the mechanisms of carbon sequestration and storage, can slow the rate of global climate change that results from greenhouse gas emissions. In recent years, both natural resource managers and the public have placed greater focus on the role of forests and wood products as a solution to help mitigate the effects of climate change. Little is known about the perceptions and viability of carbon sequestration and storage as a management goal for natural resource managers of public agencies. We explored these perceptions in Minnesota, USA. Minnesota has 7.2 million hectares of forest land managed by a diverse array of landowners, from public agencies (55% of forest land) to private (45%) owners. We sought to (1) understand natural resource managers’ and forest owners’ perspectives on forest carbon opportunities and (2) understand the feasibility of management strategies that could be implemented to increase forest carbon sequestration and storage at a state level. We conducted two focus groups with 15 mid- and upper-level natural resource managers and non-industrial private forest landowners, representing both rural and urban perspectives and a variety of agencies and organizations. Minnesota natural resource managers and non-industrial private forest landowners indicated that they thought managing forests for carbon was compatible with other management goals but nonetheless represented a trade-off. However, they viewed the carbon credit market as the “Wild West” and noted several barriers to entering the carbon market, such as inconsistent carbon accounting protocols and a lack of connection between the price of carbon credits and the cost of managing forest land for carbon sequestration and storage.
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Brans, Edward. "Climate Change Liability, Negative Emissions and Biodiversity Restoration". Journal for European Environmental & Planning Law 19, nr 4 (23.11.2022): 311–36. http://dx.doi.org/10.1163/18760104-19040003.
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Abstract This article is about climate liability and the stimulation of negative emissions through nature restoration. Such a measure can contribute to the reduction of greenhouse gas emissions, but can also lead to a restoration of biodiversity and of ecosystem services. In order to finance measures aimed at achieving natural negative emissions, the European Commission is considering introducing a system of carbon credits as part of the ‘Fit for 55’ program. This contribution investigates the advantages and disadvantages thereof and wonders about the nature and extent of the liability risks if, for example, nature is destroyed that is financed with carbon credits and which results in the release of stored co2. In that respect, attention is given to the Environmental Liability Directive. If the stimulation of natural negative emissions is also aimed at restoring biodiversity, in the event of a loss of nature, merely recouping the market price of a ‘carbon credit’ is insufficient to compensate the public for the damage done.
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Lv, Lilong, Chen Yang i Zhao Cai. "Low Carbon Consumer Lending Fintech Product Design Report". Research in Economics and Management 8, nr 3 (11.08.2023): p94. http://dx.doi.org/10.22158/rem.v8n3p94.
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In short, green growth will play a central role on the road to a more resilient recovery, and financial technology will be a key driver. Fintech, as an essential support in building a green financial system, will play a key role in supporting green finance to serve the real economy more efficiently.This article focuses on the design of low-carbon consumer credit as a financial technology product, given the high costs of green transformation for businesses and the financing and credit risks they face. Through big data, cloud computing, machine learning and other technologies, the product will help businesses to go green, create value for users and bring positive energy to society. In response to the national “dual carbon” target, low-carbon consumer credit will become an important driver to foster the development of emerging industries. This design differs from generic financial technology products in that the design focuses on green, economic benefits, while taking into account corporate social responsibility, and the use of machine learning to create an anti-fraud system throughout credit risk management, loan withdrawal, and detection of all aspects to ensure maximum security for users.
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Wang, Yabing, i Qianru Chen. "Research on Enterprise Environmental Risk Management of Industrial Bank under Analytic Hierarchy Process". Frontiers in Business, Economics and Management 12, nr 1 (16.11.2023): 95–99. http://dx.doi.org/10.54097/fbem.v12i1.13967.
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With the frequent occurrence of corporate environmental incidents and the intensification of bank credit risks, the banking industry urgently needs to strengthen the prevention, control and management of corporate environmental risks. Based on the analytic hierarchy process, this paper takes the three enterprises that have been granted credit by IB as samples, selects the enterprise environmental risk model of four sub-indicators: carbon emissions, basic environmental management, environmental risk management measures, and environmental risk emergency management, and selects the appropriate green credit objects according to the calculation results. It also puts forward suggestions on environmental risk management to improve the collection and transmission of enterprise environmental information, strengthen the supervision of enterprise risk management measures, and formulate a unified enterprise environmental risk rating standard, so as to provide reference for the banking industry to carry out enterprise environmental risk management.
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Redondo, Helena, i Elisa Aracil. "Climate‐related credit risk: Rethinking the credit risk framework". Global Policy 15, S1 (marzec 2024): 21–33. http://dx.doi.org/10.1111/1758-5899.13315.
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AbstractClimate change and the challenges associated with the transition to a zero‐carbon economy pose significant financial risks. Climate‐related risks (CRR) indirectly impact banks through their loan portfolios. To examine the integration of CRR into banks' credit risk assessment and monitoring, this article reviews academic and institutional literature using quantitative bibliometric techniques and content analysis of 145 academic documents from policymakers and financial supervisors. A framework emerges that incorporates CRR into credit risk management. We find four thematic areas in the literature: CRR drivers, CRR tools, CRR data and CRR pricing. Overall, uncertainty, non‐linearity, geographic and industrial dependency and non‐reversibility of CRR difficult climate‐related credit risk assessment. Moreover, CRR data present comparability, availability and reliability issues, which Artificial Intelligence can improve. Finally, evidence reveals that current financial prices do not fully reflect CRR. Our findings provide important implications to policymakers for assessing ex‐ante the financial impacts of climate transition regulations, the potential for prudential regulatory action, and the need for supra‐national policies that facilitate access to reliable and comparable climate data.
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Tripathi, Abhishek. "Carbon Credit Management and Strategies to Combat GHGs Emission: An Overview of the Carbon Market". Indian Journal of Economics and Development 15, nr 4 (2019): 619. http://dx.doi.org/10.5958/2322-0430.2019.00081.7.
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Bharti, Ajay, i Biswajit Saha. "Carbon credit from composting of municipal solid waste". International Journal of Environmental Technology and Management 14, nr 1/2/3/4 (2011): 203. http://dx.doi.org/10.1504/ijetm.2011.039270.
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Li, Li, Di Liu, Jian Hou, Dandan Xu i Wenbo Chao. "The Study of the Impact of Carbon Finance Effect on Carbon Emissions in Beijing-Tianjin-Hebei Region—Based on Logarithmic Mean Divisia Index Decomposition Analysis". Sustainability 11, nr 5 (9.03.2019): 1465. http://dx.doi.org/10.3390/su11051465.
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The negative effects of global warming are becoming more and more serious. The fundamental way to prevent global warming is by reducing carbon dioxide emissions. Achieving this has become a key concern for all countries. The logarithmic mean divisia index model was constructed to decompose the total carbon emission increment. Carbon finance effect was divided into green credit effect and carbon trading effect to analyze the impact of carbon finance on carbon emissions. The results showed that the total carbon emission reduction value caused by green credit effect from 2010 to 2016 in the Beijing-Tianjin-Hebei region was 66193.96 million tons, and the added value of carbon emission caused by carbon trading effect was 80266.68 million tons. There are regional differences in the effects of carbon finance on carbon emissions in these regions. It can be concluded that to a certain extent, green credit can reduce carbon emissions, and carbon trading can increase carbon emissions. Using the gradual expansion of carbon finance trading and market mechanism of carbon finance to solve the problem of carbon emission can improve the efficiency of carbon emission reduction.
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Baklaga, Luka. "Synergizing AI and Blockchain: Innovations in Decentralized Carbon Markets for Emission Reduction through Intelligent Carbon Credit Trading". Journal of Computer Science and Technology Studies 6, nr 2 (8.06.2024): 111–20. http://dx.doi.org/10.32996/jcsts.2024.6.2.13.
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This study aims to enhance the paradigm of decentralized carbon markets by proposing an innovative integration of artificial intelligence (AI) and blockchain technology for intelligent carbon credit trading with the goal of attaining sustainable emission reduction. Blockchain systems powered by artificial intelligence (AI) have the potential to boost the effectiveness of current systems and expedite the global implementation of emissions trading. Although still in its infancy, blockchain artificial intelligence (AI) presents a promising solution to some of the world's most pressing environmental issues. Environmental sustainability is greatly affected by artificial intelligence because of its decentralized computation architecture. The Artificial Intelligence and blockchain are outstanding direction for today’s environmental issues starting from carbon footprint emission to earth market unstable management, whereby the AI facilitates the best possible operational control of power systems and the blockchain offers decentralized trading platforms for the energy markets. The paper's theoretical framework, based on advanced mathematical models, serves as the foundation for this study, in which AI algorithms are methodically constructed to anticipate carbon emissions with unprecedented accuracy. Using sophisticated coding simulations and complicated mathematical formulas, the study boldly transitions into a realistic digital implementation that builds on this theoretical foundation. This complex experiment not only validates the theoretical ideas but also illustrates the complex relationship between blockchain and AI in the decentralized carbon market ecosystem. This experiment's mathematical basis is the creation of an integrated pricing model that seamlessly blends blockchain-based trading dynamics with AI-driven forecasts. The model incorporates a dynamic, self-adjusting system that responds to current market conditions, in addition to optimizing the pricing calculation of carbon credits. Complex market dynamics, player tactics, and the overall equilibrium of the carbon credit market are all modeled by mathematical simulations. The project goes deeper into building blockchain-based smart contracts, which enable safe and transparent transactions. The comprehensive mathematical results of the experiment shed light on the best way to price carbon credits while underscoring the disruptive potential of blockchain and artificial intelligence in terms of sustainable emission reduction strategies used in carbon markets. Major conclusions about the potential advantages of Blockchain AI for guaranteeing emissions reduction are drawn from the current study. Additionally, it presents a roadmap for future research in this area.
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Borges, Jatyr Fritsch, João Carlos Manuel Figueiredo, Fidel Luís Felismina Miguel i Adriana Ferreira da Silva. "Municipal Waste Treatment: Climate Change Mitigation Impacts and Carbon Credit Market Effects". Revista de Gestão Social e Ambiental 18, nr 10 (21.10.2024): e08694. http://dx.doi.org/10.24857/rgsa.v18n10-271.
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Objective: Analyze the feasibility of proposing a comprehensive methodology for inventorying greenhouse gas (GHG) emissions from urban waste, with the goal of enhancing the attractiveness of carbon credits and demonstrating their impacts on climate mitigation. Theoretical Framework: The research is grounded in theories related to climate change, the circular economy, and urban waste management. Global warming is discussed through the works of authors such as David Wallace-Wells and José Goldemberg, alongside concepts from the GHG Protocol and Life Cycle Assessment (LCA). Method: The methodology involves a bibliographic review, document analysis, and exploratory research using secondary and qualitative data. Scientific articles and documents from organizations such as the IPCC and EMBRAPA, among other academic sources, were utilized. Results and Discussion: The research emphasizes that proper management of urban waste, aligned with the principles of the circular economy, can substantially reduce GHG emissions. "Zero Waste" projects are analyzed as viable alternatives for mitigating emissions and obtaining carbon credits. The Life Cycle Assessment (LCA) of products is identified as crucial for inventorying emissions across various stages of the life cycle, thereby facilitating the certification process for carbon credits. Research Implications: The proposed methodology can encourage new investments in recycling and waste reuse, as well as support the establishment of waste treatment units that maximize resource recovery and minimize environmental impacts.Originality: This study contributes to the literature by presenting an innovative approach to the management of urban waste and carbon credits, highlighting the importance of LCA in certifying reduced emissions. Originality: This study contributes to the existing literature by introducing an innovative approach to urban waste management and carbon credits, underscoring the importance of LCA in the certification of reduced emissions.
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Chen, Xiaohong, Wei Gong i Fuqiang Wang. "Managing Carbon Footprints under the Trade Credit". Sustainability 9, nr 7 (17.07.2017): 1235. http://dx.doi.org/10.3390/su9071235.
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Taylor, Adam, Bruce Lippke i William Park. "Carbon credit schemes for forest landowners are counterproductive". Environmental Science & Policy 13, nr 2 (kwiecień 2010): 150–53. http://dx.doi.org/10.1016/j.envsci.2009.12.004.
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Bai, Rui, i Boqiang Lin. "Access to Credit and Green Innovation". Journal of Global Information Management 30, nr 1 (1.01.2022): 1–21. http://dx.doi.org/10.4018/jgim.315022.
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Starting with the natural credit relationship between financial institutions and enterprises, this paper examines the relationship between distance-based access to credit and green innovation by using the data of financial licenses and listed enterprises. Based on the resource dependence theory, the authors use the geographical location of bank branches and enterprises to build micro-level credit access indicators. It shows that enterprises with better access to credit have more motivation to carry out green innovation. Taking the number of branches of the Bank of China in 1937 as an instrumental variable, it still supports the above results. Its influence lies in the reduction of financing constraints of enterprises. This paper further discusses the impact of green finance and digitization. The development of green finance and digitization could replace the benefits of distance-based access to credit. Combined with the transformation process of traditional banks in the future, this paper puts forward some policy suggestions to promote green innovation and low-carbon development.
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Anjos, Miguel F., Felipe Feijoo i Sriram Sankaranarayanan. "A multinational carbon-credit market integrating distinct national carbon allowance strategies". Applied Energy 319 (sierpień 2022): 119181. http://dx.doi.org/10.1016/j.apenergy.2022.119181.
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Monga, Mayank, Shilpa Kaushal, Shubham i Urvashi. "Rational Outlook on Carbon Credit and Carbon Footprints in Indian Agricultural System: A Comprehensive Review". Asian Journal of Current Research 9, nr 4 (4.11.2024): 107–19. http://dx.doi.org/10.56557/ajocr/2024/v9i48931.
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Global population is expected to rise about 9 billion by 2050, and thus will bring significant and devastating changes to the earth. CO2 levels have been found to be sharply increased by 31 per cent since 1750, due to numerous land use alterations, faulty and intensive agricultural practices which lead to soil degradation. If such development prevails then it demands innovative and modern management strategies to mitigate the risks associated with climatic change. Earth's surface is continuously warming up due to an irrational land use system, intensive farming without considering the soil health and a surge in global CO2 emissions. Moreover, these adverse conditions can be exacerbated by soil mismanagement, degradation and land exploitation which leads to significant soil carbon depletion. The primary source of carbon emissions is human based activities including land use changes, burning natural biomass, excessive exploitation of renewable natural resources. In the agricultural system, soil plays a crucial role in mitigating the emissions and maintaing food safety and security equilibrium, irrigation water quality and thus impacts the climate positively. Implementation of soil health management strategies not only support the land restoration and crop production levels but also increases the soil carbon sequestration capacity. The key to harnessing the soil hidden potential lies in the adoption of best management practices and restorative land-use strategies. Most of the carbon lost from soil carbon pools due to mismanagement can be reclaimed through conservation practices. Therefore, the present review delves into constructing an understanding on mechanism and role of soil C credit and C sequestration and its impact on the agricultural sector.
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Mi, Kena, Zetao Cui, Xinyi Zhu i Rulong Zhuang. "Can Green Credit Improve the Innovation of Enterprise Green Technology: Evidence from 271 Cities in China". Systems 12, nr 2 (19.02.2024): 63. http://dx.doi.org/10.3390/systems12020063.
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With the promotion of the “carbon neutrality” and “carbon peak” initiatives, green credit plays an important role in helping enterprises to change their high-pollution, high-energy-consumption production methods and establishing a sound green, low-carbon, and circular economic system. This study used spatial correlation analysis and a fixed effects SDM model to examine the spatiotemporal and causal relationship between green credit levels and enterprise green technology innovation in 271 prefecture level cities in China from 2013 to 2021. It found that (1) green credit and green technology innovation levels are both highest in the eastern region, followed by the central region, and exhibit spatial correlation characteristics. The main types of agglomeration are high–high and low–low agglomeration. (2) Green credit has a significant enhancing effect on green technology innovation in enterprises, and this conclusion still holds after robustness and endogeneity tests. (3) There is significant regional heterogeneity in the impact of green credit on green technology innovation, mainly concentrated in the central and western regions. (4) Green credit can significantly increase enterprise R&D investment and enhance the level of green technology innovation through this channel. Finally, some policy implications are provided to the decision-making departments that can be used for reference.
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Vandana, S. R. Singh, Dharmendra Yadav, Biswajit Sarkar i Mitali Sarkar. "Impact of Energy and Carbon Emission of a Supply Chain Management with Two-Level Trade-Credit Policy". Energies 14, nr 6 (12.03.2021): 1569. http://dx.doi.org/10.3390/en14061569.
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Supply chain management aims to integrate environmental thinking with efficient energy consumption into supply chain management. It includes a flexible manufacturing process, more product delivery to customers, optimum energy consumption, and reduced waste. The manufacturing process can be made more flexible through volume agility. In this scenario, production cannot be constant, and with the concept of volume agility, production is taken as a decision variable under the effect of optimum energy consumption. Considering a two-echelon supply chain, we consider a producer and supplier with two-level-trade-credit policies (TLTCP) with the optimum consumption. To reduce the integrated total inventory cost, we believe that demand is a function of the credit period and selling price. The cost function is analyzed, either with the credit period dependent demand rate or with the selling price dependent demand rate through the numerical examples under energy costs. Energy and carbon emission costs are introduced in setup/ordering cost, holding cost, and item cost for producer and supplier. The effect of inflation on the total cost cannot be ignored; this model is being developed for deteriorating items with the simultaneous impact of volume agility, energy, carbon emission cost, and two-level-trade-credit policies with inflation. This supply chain model was solved analytically and obtained the optimum decision variables in a quasi-closed form solution. An illustrative theorem is being utilized to analyze the optimum result for all the decision parameters. The convexity of the objective function is being obtained analytically as well as graphically. Finally, numerical examples and sensitivity analysis are employed to illustrate the present study and with managerial insights.
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Tsai, Wen-Hsien, i Wei-Hong Lin. "Production Decision Model for the Cement Industry in Pursuit of Carbon Neutrality: Analysis of the Impact of Carbon Tax and Carbon Credit Costs". Sustainability 16, nr 6 (7.03.2024): 2251. http://dx.doi.org/10.3390/su16062251.
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One of the solutions to achieve the goal of net-zero emissions by 2050 is to try to reduce the carbon emission by using the carbon tax or carbon credit (carbon right). This paper examines the impact of carbon taxes and carbon credit costs on the cement industry, focusing on ESG indicators and corporate profits. Utilizing Activity-Based Costing and the Theory of Constraints, a production decision model is developed and analyzed using mathematical programming. The paper categorizes carbon tax models into continuous and discontinuous progressive tax rates, taking into account potential government policies like emission tax exemptions and carbon trading. It finds that reducing emission caps is more effective than increasing carbon tax rates in curbing emissions. These insights can assist governments in policy formulation and provide a reference framework for establishing carbon tax systems.
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Tsai, Yun-Cheng. "Enhancing Transparency and Fraud Detection in Carbon Credit Markets Through Blockchain-Based Visualization Techniques". Electronics 14, nr 1 (2.01.2025): 157. https://doi.org/10.3390/electronics14010157.
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Net-zero emission targets require transparent and efficient carbon credit trading systems. This paper introduces a blockchain-based data visualization framework to enhance decision-making in the production and logistics sectors by simplifying blockchain transaction records and identifying potential arbitrage activities. The framework integrates real-time decision support tools, enabling production system managers to monitor carbon offset activities, detect fraudulent behaviors, and streamline operations. This research provides actionable insights into supply chain emissions management and operational risk reduction by leveraging advanced visualization techniques. The proposed approach offers innovative solutions to address the complexities of blockchain-based carbon trading, emphasizing transparency and sustainability. Our analysis demonstrates the effectiveness of these techniques in mitigating fraud and supporting compliance with international carbon trading standards. The findings contribute to integrating advanced technologies into sustainable production systems, offering practical implications for achieving global climate change mitigation goals and fostering a more efficient and secure carbon credit market.
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Yadav, Vineet, George P. Malanson, Elias Bekele i Christopher Lant. "Modeling watershed-scale sequestration of soil organic carbon for carbon credit programs". Applied Geography 29, nr 4 (grudzień 2009): 488–500. http://dx.doi.org/10.1016/j.apgeog.2009.04.001.
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Maalouf, Amani, i Mutasem El-Fadel. "Life cycle assessment for solid waste management in Lebanon: Economic implications of carbon credit". Waste Management & Research: The Journal for a Sustainable Circular Economy 37, nr 1_suppl (styczeń 2019): 14–26. http://dx.doi.org/10.1177/0734242x18815951.
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Solid waste management has witnessed much progress in recent years with considerable efforts targeting the reduction of associated impacts and carbon emissions. Such efforts remain relatively limited in developing economies due to inefficient management practices. In this study, a life cycle assessment (LCA) approach is adopted to identify integrated systems with minimal impacts and reduced emissions in a developing context coupled with an economic valuation and sensitivity analysis to assess the effect of varying influencing parameters individually. The results showed that the highest impact arises from landfilling with minimal material recovery for recycling and composting, while incineration coupled with energy recovery contributed to the least equivalent emissions (–111% with respect to baseline scenario) at a varying cost of −70% to +93% depending on the selected technology and the value of carbon credit. Optimizing material recycling, composting and landfilling with energy recovery contributed to 98% savings in emissions (with respect to baseline scenario) and remained economically attractive irrespective of the carbon credit exchange rate of 0.5–50 US$/MTCO2E. The sensitivity analysis showed that an improvement in landfill gas collection efficiency (up to 60%) can contribute to major savings in emissions (58%). The application of the LCA-based approach supports the development of integrated viable plans while quantifying advantages and disadvantages towards decision-making and policy-planning.
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Kim, Hyeonho, Yujin Kim, Yongho Ko i Seungwoo Han. "Performance Comparison of Predictive Methodologies for Carbon Emission Credit Price in the Korea Emission Trading System". Sustainability 14, nr 13 (4.07.2022): 8177. http://dx.doi.org/10.3390/su14138177.
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Research related to the carbon-emission credit-price prediction model has only considered the effects of specific indicators, such as coal and oil prices, and only long-term prediction studies have been conducted. Recently, carbon emission credits have been recognized as investment assets, such as stocks and real estate. Accordingly, a carbon-emission credit prediction method is needed to establish an industrial strategy with low risk. In this study, an attempt was made to model the behavior of market participants in the time series model by analyzing the correlation between the search query volume data and the Korean Allowance Unit (KAU). Multiple Linear Regression Analysis (MRA) and Auto-Regressive Integrated Moving Average models were developed. In all price prediction models, the error of the prediction model at the 4th time was low. In the case of MRA, the error in the predicted near future price was small, but the error rate increased with increasing analysis period and prediction time. The error rate of ARIMA was lower than that of MRA, but it did not show a rapid change. These research findings will be beneficial to investigating and finding more rigid and reliable methodologies that can be used to predict various important values in similar fields in the future.
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Lee, Jaehong. "Voluntary Disclosure of Carbon Emissions Information, Managerial Ability, and Credit Ratings". Sustainability 14, nr 12 (20.06.2022): 7504. http://dx.doi.org/10.3390/su14127504.
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This paper examines the relationship between the voluntary disclosure of carbon emissions information and credit ratings, and whether managerial ability affects this association. I examine a sample of 7996 non-financial companies with fiscal year-end in December listed in the Korea Stock Exchange Market (KSE) for the period of 2011–2019. Using CDP reports to measure the voluntary disclosure of carbon emissions information, this study reports that, on average, credit ratings can be increased through the proactive disclosure activities of environmental problems in South Korea. Moreover, in companies managed by competent managers, the positive association between the voluntary disclosure of carbon emissions information and credit ratings is pronounced, implying that competent managers encourage the disclosure of qualitative information to assess the intrinsic corporate value. These results are robust even after analyses with different empirical models.
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Ryabokon, Ivan, Serhii Puzko i Olesia Stateshna. "Carbon credit market in the context of environmental and social responsibility of Ukraine". Scientific notes, nr 37 (21.12.2024): 97–107. https://doi.org/10.33111/vz_kneu.37.24.04.09.061.067.
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The article examines the issue of the carbon credit market in the context of Ukraine’s environmental and social responsibility. The current development of Ukraine is significantly affected by the war with Russia, in particular, by environmental management. Military actions have caused significant damage to the environment, which requires urgent measures after the war is over. In addition, as a candidate for EU membership in 2022, Ukraine is obliged to harmonise its environmental legislation with the European one. European integration involves the introduction of a green economy, renewable energy and a carbon credit market. These changes are an important part of the development of the country’s social and environmental responsibility. The author analyses the essence of the phenomenon of environmental responsibility and, based on the scientific literature, offers his own definition of environmental responsibility, namely, it is one of the modern external and internal functions of the State to ensure sustainable development in the field of ecology and the obligation to compensate for environmental degradation if the economic actions and goals of the State have caused relevant environmental damage. It is established that the carbon credit market was introduced by the Kyoto Protocol of 1997 and the Paris Climate Agreement of 2015. Ukraine has also become a party to the Paris Climate Agreement and has committed itself to reducing carbon emissions into the atmosphere. The article examines the effectiveness of the carbon credit market in post-war Ukraine in the context of environmental and social development in the following aspects: a) economic growth; b) creation of new places of jobs; c) environmental improvement; d) international cooperation and further integration into the European Union; and e) sustainable development.
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Clay, Lucas, Marzieh Motallebi i Bo Song. "An Analysis of Common Forest Management Practices for Carbon Sequestration in South Carolina". Forests 10, nr 11 (25.10.2019): 949. http://dx.doi.org/10.3390/f10110949.
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South Carolina (SC) has a variety of different forest types, and they all have potential to sequester a certain amount of carbon. Private forest landowners control a significant portion of the overall forestland in SC, and their management efforts can maintain or improve forest carbon stocks. Currently, the second largest carbon market in the world is the California Carbon Market, which gives a monetary value to sequestered carbon. One carbon credit is equal to one metric ton of carbon and is currently worth around $15.00. Forest management plans are geared toward increasing carbon sequestration over time. This study aims to educate forest landowners about various forest management practices that contribute to increasing carbon stocks by looking at various forest types and locations in SC and their current and projected carbon stocks. Forest Inventory Analysis (FIA) data were utilized in the Forest Vegetation Simulator (FVS) to project carbon sequestration for 100 years for 130 plots. A variety of management practices were employed to see the variance in carbon sequestration. Results showed that carbon sequestration would increase for certain management practices such as thinning and prescribed fire. Clear cutting over time was harmful to sequestration. This data will be beneficial for forest landowners interested in a carbon project and those interested in seeing how different management practices affect carbon sequestration.
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Marino, Bruno D. V., i Nahuel Bautista. "Commercial forest carbon protocol over-credit bias delimited by zero-threshold carbon accounting". Trees, Forests and People 7 (marzec 2022): 100171. http://dx.doi.org/10.1016/j.tfp.2021.100171.
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