Carbon Credit Trading Research Articles

All the loners mingle — Where do they all come from and belong? Regulating sectoral emissions and carbon markets in Brazil

To comply with emissions targets pledged in their NDCs (Nationally Determined Contributions) to the Paris Agreement, several countries have opted for incentive-based instruments. Brazil sits among them, which prefer carbon markets over taxation to control emissions, on the one hand, while keeping the stimulus to economic development, on the other. Therefore, the country has just enacted its legal framework allowing its economic sectors for trading carbon credits and thus reducing emissions. However, one elementary yet puzzling question in the design of carbon markets is the selection of the sectors to be regulated. Too many of them turn the system costly and unwieldy; too few undermine compliance with the emissions target. Drawing on the linkage hypothesis, backward (BL) and forward (FL) linkage indices offer a rational criterion to guide sectors' regulation. These indices respectively rely on the relative importance (dependence) of each sector and utilisation of the (by-)product they supply. Applied to the latest (2018) Brazil's input-output table available, the analysis carried out here found that the sectoral scope of the country's actual regulatory provisions is either too narrow or too wide and leaves out important key sectors in the Brazilian economy.

Benefits and Challenges of Carbon Credit trading in India: An Exploratory Study

Benefits and Challenges of Carbon Credit trading in India: An Exploratory Study

Climate Change Policy, Emissions Trading Schemes and Carbon Pricing: California and Tokyo

In this paper, we provide explicit critical comparisons of two very important and successful regional emissions trading schemes: California and Tokyo. We focus on the contrasts of the different rules and functioning of the carbon credit trading markets. We also compare the carbon leakages and the compliance of the two schemes. We highlight the “negative” carbon leakage and the voluntary compliance associated with the Tokyo- Saitama Prefecture schemes. Finally, we provide a formal model linking some “unique” Japanese labour market practices to the incentives facing the Japanese facilities.

Opportunity for Islamic Finance in Blockchain Solutions for Climate Change: A Case Study of DCarbonX Model

Abstract: The climate change is one of the biggest problems that humanity is facing and there is a dearth of solutions in tackling this grave impediment to the long-term sustainability of our planet. Accountability, greenwashing, traceability, impact assessment and trading of carbon credits are unresolved issues in the ESG sector. The paper aims at identifying the opportunity for Islamic finance by reviewing the novel business model of DCarbonX, a Decentralized Application (DApp) that solves the enumerated problems using NFTs on the blockchain platform through smart contracts. The paper combined the inductive method and descriptive approach to describe the functional architecture of DCarbonX, while elaborating on its salient features and highlighting opportunity in sustainable finance for Islamic finance players. The paper encompasses a study on the applications of DApps in DeFi, Web 3.0 and ESG, among other areas and gives a comparative analysis of blockchain platforms for DApp development. The paper concluded that there is a harmony in the SDGs and the primary goals of Maqasid al-Shariah. The blockchain platforms can be utilized to develop DApps for solving the issues related ESG and climate change. The Islamic finance can seize the untapped opportunity in blockchain based solutions for climate change by launching the DApps in the domains of Capital Market (like green Sukuk), Embedded Finance, Takaful, NFTs, RegTech, and SupTech. Keywords: Blockchain, DApp, DCarbonX, Climate Change, Carbon Market, NFT, Islamic Finance.

A simulation-assessment-optimization approach towards energy self-sufficiency and carbon reduction in regional-scale sewage systems

Utilizing renewable energy is a practical pathway for realizing energy self-sufficiency and offsetting carbon emissions in wastewater treatment plants (WWTPs). The holistic optimization of hybrid renewable energy of multiple WWTPs overweighs individual WWTPs studies by providing global optimal solutions and cost-effective resources management schemes with expended spatial scales. Few studies have focused on the overall optimal utilization and management of hybrid renewable energy from WWTPs on a regional scale. This study aims to explore how to optimize the configuration of renewable energy facilities for multiple WWTPs to achieve the cost-effective use of renewable energy for the overall system. Uncertainty associated with PV power generation and the size effects of WWTPs were considered in the general framework to enhance the reliability and cost effectiveness of the utilization of renewable energy. The developed approach was then applied to the hybrid renewable energy management of a city-scale WWTP system comprising 31 plants in Guangzhou, China. Results indicated that the energy self-sufficiency of sewage systems can be realized by recovering renewable energy. The levelized cost of energy generation in the overall system was approximately 0.19 CNY/kW·h, and the overall reduction in greenhouse gas (GHG) emissions was approximately 129.5 t CO2-eq/d. The overall optimization reduced the total cost by approximately 3% than did the traditional individual WWTP studies. The thermal energy recovered from wastewater could further reduce the operational costs of WWTPs through carbon credit trading. The developed approach can also be applied to other areas of the world to promote sustainable wastewater treatment and strengthen the utilization of renewable energy.

Bubble in Carbon Credits during COVID-19: Financial Instability or Positive Impact (“Minsky” or “Social”)?

Incentivizing businesses to lower carbon emissions and trade back excess carbon allowances paved the way for rapid growth in carbon credit ETFs. The use of carbon allowances as a hedging alternative fueled this rally further, causing a shift to speculation and forming repetitive bubbles. Speculative bubbles are born from euphoria, yet, they are relatively predictable, provided their pattern matches the log periodic power law (LPPL) with specific stylized facts. A “Minsky moment” identifies a clear speculative bubble as a signal of financial system instability, while a “Social bubble” is regarded as relatively positive, increasing in the long run, infrastructure spending and development. The aim of this paper is to investigate whether various carbon credit bubbles during the pandemic period caused financial instability or had a positive impact (“Minsky” or “Social”). Particularly, we investigate the carbon credit bubble behavior in the ETF prices of KRBN, GRN (Global Carbon Credit tracking ETFs), and the SOLCARBT index during the COVID-19 pandemic period by adopting the log-periodic power law model (LPPL) methodology, which has been widely used, over the past decade, for detecting bubbles and crashes in various markets. In conclusion, these bubbles are social and propelled by the newfound interest in carbon credit trading, for obvious reasons.

Capitalizing on the global financial interest in blue carbon

Natural climate solutions are crucial interventions to help countries and companies achieve their net-zero carbon emissions ambitions. Blue carbon ecosystems such as mangroves, seagrasses, and tidal marshes have attracted particular attention for their ability to sequester and store carbon at densities that can far exceed other ecosystems. The science of blue carbon is now clear, and there is substantial interest from companies and individuals who wish to offset greenhouse gas emissions that they cannot otherwise reduce. We characterise the rapid recent rise in interest in blue carbon ecosystems from the corporate sector and highlight the huge scale of demand (potentially $10 billion or more) from companies and investors. We discuss why, despite this interest and demand, the supply of blue carbon credits remains small. Several market-related challenges currently limit the implementation of blue carbon projects and the sale of resulting credits, including the cost and burden of verification of blue carbon compared to verifying carbon credits in other ecosystems, the general small scale of current blue carbon projects, and double counting of credits between commercial and national institutions. To overcome these challenges, we discuss other supplementary financial instruments beyond carbon credit trading that may also be viable to fund the conservation and restoration of coastal habitats, such as bonds and ecosystem service insurance. Ultimately, a portfolio of financial instruments will be needed in order to generate funding streams that are substantial and reliable enough to realise the potential of blue carbon ecosystems as a natural climate solution.

A permissioned blockchain enabled trustworthy and incentivized emission trading system

The emission trading systems (ETSs) have encouraged the more usage of renewable energy, aiming for energy generation. However, the existing ETSs suffer from carbon credit scams, poor monitoring, verification and reporting (MRV), participants’ unwillingness and non-transparent trading. To address these issues, we propose a trustworthy and incentivized emission trading system using hyperledger (a permissioned blockchain) and smart contracts. It assures a transparent trading of carbon credits (CC) with better MRV. It applies three smart contracts viz; CC selling, CC buying and CC trading to achieve reliable and secure transactions of the energy trading with the improved trust. For emission trading, we propose a priority based auction, in which priority to CC sellers is assigned based on their carbon credits, while priority to CC buyers is assigned based on their reputation. This strategy rewards the participants for their efforts towards avoiding the deforestification and the use of renewable energy. In addition, it is incentivized for both CC buyers as well as sellers, and thus, it encourages more number of participants. The proposed system satisfies more than 84.37% bids with minimum transaction latency (0.41 s) and sufficient throughput (102.42 tps). In addition, multi-criteria analysis using different statistical methods is performed to evaluate and compare the effectiveness of the proposed systems.

Exploring mechanisms to pay for ecosystem services provided by mussels, oysters and seaweeds

This explorative study identifies and evaluates mechanisms for payment for ecosystem services provided by mussel, oyster and seaweed aquaculture. Concerns about the economic profitability of farming mussels, oysters and seaweeds hamper upscaling of production. It is argued that valuing and capitalizing the ecosystem services provided by the production of these lower trophic species can benefit the business case. The Delphi method is used to consult experts across the world in various sectors, including industry, NGO, science and government. Six payment mechanisms for ecosystem services were considered feasible; tax-payer funded payments, tradeable credits, encouraging subsidies, social licenses to produce, production cost-sharing schemes and increased utility for consumers. The latter was deemed most feasible, with little differences in feasibility found in the other five. There are however barriers to implementation in a lack of solid quantification, inadequate regulatory framework and lack of independent validation. Future payment mechanisms for ecosystem services provided by mussels, oysters and seaweeds need solid, science-based measurements based on sound monitoring indicators to quantify effects on the ecosystem services, liaised with relevant existing carbon and nitrogen credit trading schemes and an independent checks-and-balances for long-term trust in such payment schemes. The need for better mechanisms for capitalization justify further development of better data and knowledge of these mechanisms, inclusion of ecosystem services in new regulations and more political and societal support to implement them.

Review of Blockchain Potential Applications in the Electricity Sector and Challenges for Large Scale Adoption

Blockchain technology applications in the electricity sector are getting considerable attention from both academia and industry. It is expected that blockchain will play an important role in the transition to the smart grid. The blockchain applications in the electricity sector can be classified to optimizing existing processes like metering and billing or grid management and using blockchain for emerging applications such as creating new platforms for value exchange like peer-to-peer (P2P) energy trading. This paper briefly introduces the fundamentals of blockchain technology, such as different types of blockchain networks and consensus mechanisms, in addition to introducing a few blockchain platforms that are widely used in current studies, projects, and startups or may have future potential in the electricity sector applications. The contribution of this paper is to provide a review of potential applications of blockchain in many electricity sector use cases, and they are categorized into eight categories such as P2P energy trading, wholesale markets, retail markets, metering and billing, trading of renewable energy certificates (RECs) and carbon credits, electric mobility, enhancement of power system cyber security, investments in renewable energy sources (RESs), and power system operation and management. Moreover, examples of research studies, pilot projects, industrial projects, startups, or companies investigating the blockchain capabilities at each potential application are introduced. Furthermore, the studies presented in each use case are compared to clarify and highlight the blockchain functions and involved actors. Finally, the paper discusses the challenges that blockchain technology is facing that obstruct large-scale adoption in different sectors and in the electricity sector specifically and potential solutions to these challenges that are being developed.

How did COVID-19 affect green-fuel supply chain? - A performance analysis of Brazilian ethanol sector

The COVID-19 pandemic affected many supply chains worldwide, including the Brazilian green-fuel ethanol supply chain. Our analysis considered sustainability variables (social, environmental, and economic) to investigate the pandemic's effects on the ethanol industries of 15 ethanol producing Brazilian states, comparing data from 2020 to 2019 and applying a novel Data Envelopment Analysis (DEA): the Double Frontier Slack-Based Measure Malmquist Productivity Index (DF-SBM MPI). The findings show that all states suffered negative impacts from the pandemic and some incurred a risk of collapsing it. The least negatively impacted states were São Paulo and Mato Grosso. São Paulo's ethanol sector is a benchmark for income derived from trade in carbon-credits by RenovaBio certified mills, while Mato Grosso's sector is able to take advantage of the largest spread between ethanol and gasoline prices, certainly a competitive advantage for ethanol producers. We recommend the implementation of public policies to support, mainly, the most affected states by assisting their mills to become environmentally certified participants to take advantage of income opportunities available in the carbon-credit trading market. We recommend, among other actions, a temporary ethanol sales tax reduction, an extension of debt repayment schedules, and stimulating an increase in the fleet of flex-fuel vehicles.

Analysis of carbon credit trading (CCT) practices: a study of manufacturing organizations in British Columbia, Canada

PurposeFactors that affect the use of carbon credit trading (CCT) by industries include as follows: avoiding carbon taxes, international expansion, venture capital, competitive advantage and clean technology. The impact of these factors is examined here in relation to the profile of 14 Canadian organizations to investigate factors that influence CCT practices.Design/methodology/approachThis research involves a survey of 150 employees at 14 industries in British Columbia (BC) Canada to review and analyze their perceptions of factors that impact CCT.FindingsResults demonstrate the potential for enhancing the use of CCT by organizations. It was shown that organizations perceive that CCT enhances their competitive advantage, which is an incentive that needs further investigation as having potential for encouraging CCT and greenhouse gas (GHG) reduction.Research limitations/implicationsDue to limited funding and workforce, as well as geographical constraints, only 14 industrial organizations were engaged in this research in BC Canada. The scope of future research needs to be enlarged by considering neighboring countries such as the USA and Mexico. This research regarding factors that impact organizations in adopting carbon crediting trading has the potential to provide and shape inter-continental comparisons.Practical implicationsThis study illustrates how CCT has the potential to enhance competitive advantage and may impact the industry toward reducing GHG emissions through CCT. This concept adds a new environmental protection factor and dimension to trade and industry. As organizations plan to invest funds in different carbon reduction projects this may result in expanded employment opportunities.Social implicationsOrganizations are interested in CCT but may hesitate in engaging in CCT as it can be a complex procedure. In addition to further research, workshops and seminars regarding CCT and dissemination of research should be organized by the universities, related authorities and government organizations to make CCT more known and feasible. This study shows that financial and non-financial benefits may be gained by any organization when involved in CCT. Larger advertising and information campaigns may motivate more organizations in this regard.Originality/valueThis study extends the study of Garg et al. (2017) regarding challenges for CCT practices. International Journal of Management, 10(1), 85–96. It contributes evidence that the size (revenue) of an organization does not affect the level of carbon credits traded and shows potential for smaller organizations to be encouraged to take part in CCT.

Enviro-economical feasibility of groundnut drying under greenhouse and indoor forced convection hot air dryers

In the present paper, groundnut samples were dried under natural convection greenhouse drying (NCGHD), forced convection greenhouse drying (FCGHD), and indoor forced convection hot air drying (IFCHAD) modes in the climatic conditions of Rohtak, India (28°54′ N 76°34′E). Samples of groundnut were dried up-to-the-safe storage moisture level of 8–10%. Drying cost per kg of dried groundnut under NCGHD, FCGHD, and IFCHAD modes were found to be ₹ (Indian National Rupee) 25.18 (0.34 US$), ₹ 42.18 (0.57 US$), and ₹ 135.85 (1.84 US$), respectively for the same wire mesh sieve size. Cost under greenhouse drying modes decreases with the increase in wire mesh sieve size. Cost under NCGHD and FCGHD modes was 81.46%–69% less than the average drying cost per kg of dried groundnut under IFCHAD mode for the same sieve size. Critical parameters such as embodied energy, energy payback time (EPBT), CO2 mitigation, and carbon credit earn (CCE), which help study the cost analysis of a greenhouse dryer have also been evaluated. Cost of manufacturing a greenhouse decreases with a decrease in embodied energy. Maximum utilization of a greenhouse dryer can reduce CO2 emission. Carbon credit trading is used to control pollution. It provides an economic incentive to achieve a reduction in pollutants emission. EPBT was found to be about 1.66, 1.72, and 4.67 years for natural convection greenhouse dryer, forced convection greenhouse dryer, and hot air dryer, respectively.

Current carbon prices do not stack up to much land use change, despite bundled ecosystem service co-benefits.

Biological sources of carbon sequestration such as revegetation have been highlighted as important avenues to combat climate change and meet global targets by the global community including the Paris Climate Agreement. However, current and projected carbon prices present a considerable barrier to broad-scale adoption of tree planting as a key mitigation strategy. One avenue to provide additional economic and environmental incentives to encourage wider adoption of revegetation is the bundling or stacking of additional co-beneficial ecosystem services that can be realized from tree planting. Using the World's largest land-based carbon credit trading scheme, the Australian Emissions Reduction Scheme (ERF), we examine the potential for three pairs of ecosystem services, where the carbon sequestration value of land use change is paired with an additional co-benefit with strong prospects for local tangible benefits to land owners/providers. Two cases consider agricultural provisioning values that can be realized by the landowners in higher returns: increased pollination services and reduced lamb mortality. The third case examined payments for tree plantings along riparian buffers, with payments to farmers by a water utility who realizes the benefit from reduced treatment cost due to water quality improvements. Economic incentives from these co-benefit case studies were found to be mixed, with avoided treatment costs from water quality paired with carbon payments the most promising, while pollination and reduced lamb mortality paired with carbon payments were unable to bridge the economic gap except under the most optimistic assumptions. We conclude that the economics case for significant land use change are likely to be geographically dispersed and only viable in relatively niche landscape positions in high establishment, high opportunity cost areas even when carbon payments are augmented with the value of co-benefits classified as providing direct and local benefits.

New allometric equations for quantifying tree biomass and carbon sequestration in seasonally dry secondary forest in northern Thailand

As tropical deforestation and forest degradation accelerate, carbon-credit trading could provide a financial incentive to preserve and regenerate forests. Since carbon trading relies on the accurate quantification of carbon stocks, allometric equations are urgently needed to derive above-ground dry biomass (AGB) from easily measured variables. Few allometric equations have been published for regenerating secondary forests in Southeast Asia. This study established new allometric equations, to determine AGB and carbon in regenerating secondary forests on shifting cultivation fallows in northern Thailand. To develop the equations, data were collected from 78 trees (136 felled individual stems, including coppices) ranging in size from 1 to 32.9 cm diameter at breast height (D). The dependent variable was AGB. The independent variables were D, tree height (H) and wood density (WD). Wood density varied significantly among species (p < 0.05). Consequently, including WD in the function D2H × WD predicted AGB most accurately, compared with other functions that excluded it. Mean carbon concentration in stems, branches, and leaves was 44.84% ± 1.63 of dry mass, but it varied significantly among tree species (p < 0.05). The new allometric equation revealed that tree ABG was highest in secondary forest, followed by the 7-year-fallow and the 4-year-fallow: 105.3, 38.3 and 10.3 Mg ha−1, respectively, while above-ground carbon was 47.7, 17.4, and 4.6 Mg C ha−1, respectively. Natural regeneration accumulated carbon slower than reported for active restoration, suggesting that managed restoration is preferable to passive regeneration on fallows in northern Thailand. The allometric equations, derived from this study, can be used to accurately determine tree ABG and carbon storage in regenerating secondary forest, with higher precision than has hitherto been possible, thus satisfying the monitoring requirements of REDD+ and other carbon-trading schemes.

Challenges and opportunities for quantifying greenhouse gas emissions through dairy cattle research in developing countries.

The global dairy sector is facing the challenge of reducing greenhouse gas (GHG) emissions whilst increasing productivity to feed a growing population. Despite the importance of this challenge, many developing countries do not have the required resources, specifically funding, expertise and facilities, for quantifying GHG emissions from dairy production and research. This paper aims to address this challenge by discussing the magnitude of the issue, potential mitigation approaches and benefits in quantifying GHG emissions in a developing country context. Further, the paper explores the opportunities for developing country dairy scientists to leverage resources from developed countries, such as using existing relevant GHG emission estimation models. It is clear that further research is required to support developing countries to quantify and understand GHG emissions from dairy production, as it brings significant benefits including helping to identify and implement appropriate mitigation strategies for local production systems, trading carbon credits and achieving the nationally determined contribution obligations of the Paris Agreement.

A mathematical model for optimizing a biofuel supply chain with outsourcing decisions under the carbon trading mechanism

Carbon trading is a market-based mechanism for controlling carbon emissions by providing economic incentives to reduce emissions. In recent years, there has been an increasing interest in modeling supply chain networks under this scheme; however, to date, only a limited number of researchers have investigated the implication of this mechanism for biofuel supply chains. The optimization model presented in this paper examines a trade-off between the cost of trading carbon credits and costs associated with outsourcing of the biomass pretreatment process when carbon emissions exceed the predetermined carbon cap in a biofuel supply chain. To demonstrate the applicability of the model, we analyzed challenges in supplying different sources of biomass to two biorefinery plants and shipping the produced biofuels to multiple demand zones. The results showed that carbon emission reductions have a relatively nonlinear pattern when the carbon credit price increases linearly. Furthermore, we presented significant managerial and policy insights on the impact of different carbon emission caps on total costs and total emissions. Moreover, we analyzed the cost adjustment between trading carbon credits and outsourcing decisions for different carbon cap settings. This paper ends with suggestions for further development of the presented model for future researches.

Advantage and Disadvantage of Carbon Credit Trading and Taxation Practice in Energy Sector Organizations: A

The result of the Kyoto Protocol is the trade in units of CO2 dioxide. The main purpose of this idea is to practically trade units of CO2 in the bazaar. Today, this category of business is one of the dissolute growing business bazaars in Uttarakhand. In the long run, a low-CO2 economy will force companies that do not yet have CO2 caps to prepare for CO2 regulation. This study examines the various advantages and disadvantages directly or indirectly related to CO2Merchandise. Many organizations have achieved financial and non-financial advantages, but today many are interested in this business. In pricing, CO2 credits create a bazaar for reducing GHG discharges.

The Hidden Disequities of Carbon Trading: Carbon Emissions, Air Toxics, and Environmental Justice

So long as transaction costs are low, the creation of a tradeable permit to emit carbon should allow bargaining for emission rights among buyers and sellers, resulting in an efficient allocation of carbon emission rights. However, the trading of carbon credits may have socially unjust consequences. In this article, we explore some hitherto unrecognized disequities. One of these may be the creation of toxic hotspots as the trade of carbon may bring with it a transfer of air toxics, as well. We illustrate the argument by examining emissions from refineries participating in California's cap-and-trade program. These considerations are a concern for the larger question of carbon mitigation as the global community strives to identify feasible, yet just, approaches to reducing greenhouse gas emissions. Contrary to the idea of alienable rights, the transfer of carbon affects people and place in ways not internalized by these market instruments.

Optimal GENCO's bidding strategy in a power exchange facilitating combined power and emission trading using Intelligent Programmed Genetic Algorithm

Currently, for developing optimal bidding strategy considering carbon credit trading, Generating Company (GENCO) separately participates in electric power and emission market. Recently, researchers proposed a new scheme in which emission trading is facilitated within Power Exchange (PX). Developing optimal GENCO's bidding strategy considering carbon credit trading within PX is a complex single-objective optimization problem with generator's surplus as the main objective function. Obtaining its solution using a simple evolutionary optimization algorithm is difficult and time-consuming. Therefore, this paper presents an application of Intelligent Programmed Genetic Algorithm (IPGA) equipped with advanced deterministic diversity creating operator for solving optimal GENCO's bidding strategy problem with minimum number of objective function evaluations. The performance of IPGA is first tested on three different categories of standard test functions by comparing its simulation results with that obtained using binary-coded GA, simulated annealing, particle swarm optimization, biogeography-based optimization, teaching learning-based optimization, and differential evolution-based hybrid GA. A system comprising of six GENCOs and two buyers is used to validate the applicability of IPGA. IPGA along with other algorithms was used to obtain optimal bidding curve for 24 hours for GENCO GC-1. Simulation results clearly show much faster convergence for IPGA in terms of the number of objective function evaluations required to reach optima. Result also shows that GENCO GC-1 can obtain much higher GC-1 surplus, carbon credit limit, and social welfare by utilizing the obtained bidding strategy using IPGA as compared with the bidding strategy obtained by other algorithms.