As of April 2025, the European Union Emission Trading Scheme (EU ETS) carbon price was above ** U.S. dollars per metric tons of carbon dioxide equivalent (USD/tCO₂e). The EU ETS launched in 2005 as a cost-effective way of reducing greenhouse gas emissions, and was the world's first major international carbon market. The UK was formerly part of the EU ETS, but replaced this with its own system after withdrawing from the EU. As of April 2025, the price of carbon on the UK ETS was almost ** USD/tCO₂e.

EU Carbon Permits fell to 70.55 EUR on July 11, 2025, down 0.27% from the previous day. Over the past month, EU Carbon Permits's price has fallen 6.42%, but it is still 1.73% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for EU Carbon Permits.

Voluntary carbon offset prices could reach as high as 238 U.S. dollars per ton of carbon dioxide (USD/tCO₂) by 2050 if integrity issues within the market are resolved. However, if the market continues to operate without rigorous standards, and integrity issues remain a concern for companies, then carbon offset credits would trade at just 14 USD/tCO₂ in 2050. Meanwhile, prices would soar to 146 USD/tCO₂ by 2030 if the market is restricted to only carbon removals.

The Carbon Offsets Market size was valued at USD 938.75 USD Billion in 2023 and is projected to reach USD 2222.23 USD Billion by 2032, exhibiting a CAGR of 13.1 % during the forecast period. The carbon offsets market is a mechanism that lowers the overall global emissions of greenhouse gases by enabling those who generate carbon pollution to purchase and sell carbon credits that represent one metric ton of CO2 or equivalent gases eliminated from the atmosphere. Offsets have become a tool that firms employ in their determination to meet their sustainability objectives as well as fulfilling the legal standards and improving corporate citizenship. The market has voluntary segments achieved through private efforts and compliance segments anchored on government rules. Offset projects include hydro or solar power, forests planted, energy saving or avoiding methane recovery. This market reduces global warming and greenhouse gases, supports sustainable growth, incentivizes technological change, ensures that emissions goals can be met in multiple ways, supports multilateralism and delivers public goods and services benefits. Recent developments include: August 2023 – The Doha-based Global Carbon Council announced plans to list its carbon credits on the MENA exchanges platform. This initiative is expected to increase the number of carbon offset investors and boost the number of active carbon emission projects in the Middle East region.. Key drivers for this market are: Strict Government Regulations to Neutralize Carbon Emissions by 2050 Have Boosted the Market. Potential restraints include: Limited Awareness of the Carbon Offsetting and Low Carbon Credit Scores in Multiple Countries May Hamper Market Growth . Notable trends are: Increasing Adoption of Carbon Offsets by Voluntary Projects is the Emerging Trend in the Market.

The price of emissions allowances (EUA) traded on the European Union's Emissions Trading Scheme (ETS) exceed 100 euros per metric ton of CO₂ for the first time in February 2023. Although average annual EUA prices have increased significantly since the 2018 reform of the EU-ETS, they fell ** percent year-on-year in 2023 to ** euros. What is the EU-ETS? The EU-ETS became the world’s first carbon market in 2005. The scheme was introduced as a way of limiting GHG emissions from polluting installations by putting a price on carbon, thus incentivizing entities to reduce their emissions. A fixed number of emissions allowances are put on the market each year, which can be traded between companies. The number of available allowances is reduced each year. The EU-ETS is now in its fourth phase (2021 to 2030). Carbon price comparisons The EU ETS has one of the highest average annual carbon prices worldwide, with EUAs averaging ** U.S. dollars as of April 2024. In comparison, prices for UK ETS caron credits averaged 45 U.S. dollars during same period, while those under the Regional Greenhouse Gas Initiative (RGGI) in the United States averaged just ** U.S. dollars.

The average price of voluntary carbon market (VCM) credits decreased by *** percent in 2024 year-on-year, to **** U.S. dollars per metric ton of carbon dioxide equivalent. The market value of the VCM totaled just over *** million U.S. dollars that year.

Carbon prices across multiple emissions trading systems worldwide are expected to increase during the period of 2026 to 2030, compared to 2022 to 2026. The average EU ETS carbon price is expected to be **** euros per metric ton of CO₂ during the period 2022 to 2025, but is projected to rise to almost 100 euros per metric ton of CO₂ during the period of 2026 to 2030, according to a survey of International Emissions Trading Association members. EU ETS carbon pricing broke the ** euros per metric ton of CO₂ barrier in February 2022, and in February 2023 it surpassed 100 euros per metric ton of CO₂.

The cost of UK ETS carbon permits (UKAs) was around *** GBP in February 2023, but prices have fallen considerably since then. Prices on January 16, 2025 were just ***** GBP, down ** percent from the same date the previous year. Formerly part of the EU ETS, the UK launched its own cap-and-trade system in 2021 following Brexit. Why has the UK’s carbon price fallen? Several factors have contributed to falling UK carbon prices, including mild winter weather and reduced power demand, as well as a surplus of carbon allowances on the market. While prices have recovered marginally from the record lows, they remain markedly below carbon prices on the EU ETS. The low cost of UK carbon permits has raised concerns that it could deter investment in renewable energy. Future of UK ETS The UK ETS covers emissions from domestic aviation and the industry and power sectors, amounting to some ** percent of the country’s annual GHG emissions. There are plans to expand the system over the coming years to cover CO₂ venting by the upstream oil and gas sector, domestic maritime emissions, and energy from waste and waste incineration. The UK is also looking to introduce a carbon border adjustment mechanism, which would place a carbon price on certain emissions-intensive industrial goods imported to the UK.

Carbon Dioxide Removal Credit Market Outlook

As per our latest research, the global carbon dioxide removal credit market size reached USD 2.8 billion in 2024, reflecting a robust expansion fueled by surging climate action initiatives and regulatory support worldwide. The market is experiencing a significant upward trajectory, with a calculated CAGR of 18.7% from 2025 to 2033, and is projected to attain a value of USD 14.7 billion by 2033. This remarkable growth is primarily driven by increasing commitments to net-zero targets, heightened corporate sustainability mandates, and the accelerated deployment of advanced carbon capture technologies across diverse sectors.

One of the primary growth factors propelling the carbon dioxide removal credit market is the intensifying global focus on climate mitigation and decarbonization. Governments and international bodies are implementing stricter carbon regulations and incentivizing carbon removal projects, which directly enhances the demand for high-quality removal credits. The growing adoption of science-based targets by corporations and the integration of carbon removal into long-term climate strategies further amplify market expansion. The proliferation of voluntary carbon markets and the evolution of compliance frameworks, such as the Article 6 of the Paris Agreement, are creating favorable conditions for the commercialization of carbon removal credits, thereby catalyzing investments in both nature-based and technology-driven solutions.

Another significant growth driver is the technological innovation landscape within the carbon dioxide removal credit market. Breakthrough advancements in direct air capture, bioenergy with carbon capture and storage (BECCS), and ocean-based carbon sequestration are rapidly increasing the scalability, efficiency, and cost-effectiveness of carbon removal solutions. These technologies, alongside improved monitoring, reporting, and verification (MRV) systems, are enhancing the credibility and traceability of carbon credits, which is crucial for attracting investments from environmentally conscious corporations and institutional investors. As these technologies mature and achieve economies of scale, the cost per ton of carbon removed is expected to decrease, making carbon removal credits more accessible to a broader range of market participants.

In addition, the rising participation of the private sector is a pivotal growth factor. Multinational corporations across energy, manufacturing, agriculture, and transportation are committing to ambitious sustainability goals, often requiring the purchase of carbon removal credits to offset residual emissions. The emergence of innovative financing models, such as forward contracts and blended finance, is enabling the rapid deployment of large-scale carbon removal projects. Strategic partnerships between technology providers, project developers, and end-users are fostering ecosystem development and accelerating commercialization. The increasing transparency and standardization in credit issuance, driven by third-party verifiers and international standards, are also enhancing market confidence and facilitating cross-border transactions.

From a regional perspective, North America and Europe are leading the global carbon dioxide removal credit market, owing to their early adoption of carbon pricing mechanisms, strong policy support, and robust corporate sustainability cultures. Asia Pacific is emerging as a high-growth region, supported by expanding industrial bases, rising environmental awareness, and increasing investments in nature-based and technology-based carbon removal projects. Latin America and the Middle East & Africa are gradually entering the market, leveraging their vast natural resources and potential for large-scale land use and forestry projects. Regional disparities in regulatory frameworks, technological readiness, and market maturity are shaping the competitive dynamics and influencing the pace of adoption across geographies.

Technology Analysis

CORSIA-eligible carbon (CEC) credits were assessed at ***** U.S. dollars per metric ton of carbon dioxide equivalent (USD/teCO₂e) in 2024, compared with **** USD/teCO₂e in 2023. CORSIA (Carbon Offsetting and Reduction Scheme for International Aviation) is a global market-based measure designed to offset international aviation CO₂ emissions in order to reduce emissions within the sector. Meanwhile, Platts CRC, which reflects removals-based carbon credit projects, was assessed at ***** USD/teCO₂e in 2024.

Reducing Emissions from Deforestation and forest Degradation (REDD+) voluntary carbon credit prices fell by ** percent year-over-year in 2024, to *****U.S. dollars per metric ton of carbon dioxide equivalent. Forestry and land use credits are the most common on the voluntary carbon market, with REDD+ accounting for the majority of carbon credit issuances within this category.

The average selling price of a metric ton of carbon dioxide removal (CDR) varies greatly by method. In 2023, the average price for CDR by Direct Ocean Removal (DOC) was roughly ***** U.S. dollars per metric ton, a ** percent increase from the previous year. In comparison, the average price for Direct Air Capture (DAC) fell by almost ** percent in 2023, to *** U.S. dollars per metric ton of carbon removal.

Voluntary carbon market (VCM) credit prices in North America averaged ***** U.S. dollars per metric ton of carbon dioxide equivalent in 2024, a year-on-year increase of 59 percent. Meanwhile, the average VCM credit price in Europe grew seven percent y-o-y, to ***** U.S. dollars per metric ton.

This paper employs a computable general equilibrium model (CGE) to analyse how a carbon tax and/or a national Emissions Trading System (ETS) would affect macroeconomic parameters in Turkey. The modelling work is based on three main policy options for the government by 2030, in the context of Turkey’s mitigation target under its Intended Nationally Determined Contribution (INDC), that is, reducing greenhouse gas (GHG) emissions by up to 21% from its Business as Usual (BAU) scenario in 2030: (i) improving the productivity of renewable energy by 1% per annum, a target already included in the INDC, (ii) introducing a new flat rate tax of 15% per ton of CO2 (of a reference carbon price in world markets) imposed on emissions originating from carbon-intensive sectors, and (iii) introducing a new ETS with caps on emission permits. Our base path scenario projects that GHG emissions in 2030 will be much lower than Turkey’s BAU trajectory of growth from 430 Mt CO2-eq in 2013 to 1.175 Mt CO2-eq by 2030, implying that the government’s commitment is largely redundant. On the other hand, if the official target is assumed to be only a simple reduction percentage in 2030 (by 21%), but based on our more realistic base path, the government’s current renewable energy plans will not be sufficient to reach it. Turkey’s official INDC is based on over-optimistic assumptions of GDP growth and a highly carbon-intensive development pathway;A carbon tax and/or an ETS would be required to reach the 21% reduction target over a realistic base path scenario for 2030;The policy options considered in this paper have some effects on major sectors’ shares in total value-added. Yet the reduction in the shares of agriculture, industry, and transportation does not go beyond 1%, while the service sector seems to benefit from most of the policy options;Overall employment would be affected positively by the renewable energy target, carbon tax, and ETS through the creation of new jobs;Unemployment rates are lower, economic growth is stronger, and households become better off to a larger extent under an ETS than carbon taxation. Turkey’s official INDC is based on over-optimistic assumptions of GDP growth and a highly carbon-intensive development pathway; A carbon tax and/or an ETS would be required to reach the 21% reduction target over a realistic base path scenario for 2030; The policy options considered in this paper have some effects on major sectors’ shares in total value-added. Yet the reduction in the shares of agriculture, industry, and transportation does not go beyond 1%, while the service sector seems to benefit from most of the policy options; Overall employment would be affected positively by the renewable energy target, carbon tax, and ETS through the creation of new jobs; Unemployment rates are lower, economic growth is stronger, and households become better off to a larger extent under an ETS than carbon taxation.

The supporting data contains two types of datasets:

1) Social cost of carbon (SCC) values, extrapolated from
UK government carbon values (2010-2100) to cover the range of 2000-2500. The dataset is stored in a csv file ("scc_extended.csv") and contains four columns: 1. year: numeric 2. low: numeric, central series minus 50% sensitivity range 3. central: numeric, central estimated time series of modelled monetary value that society places on one tonne of carbon dioxide equivalent (£/tCO2e) 4. high: numeric, central series plus 50% sensitivity range

The detailed method that the UK government used to model carbon value estimates can be found at: https://www.gov.uk/government/publications/valuing-greenhouse-gas-emissions-in-policy-appraisal/valuation-of-greenhouse-gas-emissions-for-policy-appraisal-and-evaluation#annex-1-carbon-values-in-2020-prices-per-tonne-of-co2

2) sampled yearly carbon loss (tCO2e) in project area and in counterfactual scenario, and yearly additionality (Mg CO2e) in four ongoing REDD+ projects, estimated using a combination of JRC-TMF Landsat-based annual time series of land use cover and GEDI L4A footprint-level aboveground biomass density estimates to track forest cover and carbon stock through time. The datasets are stored in csv files (Gola: "Gola_country.csv"; Alto Mayo: "CIF_Alto_Mayo.csv"; RPA: "VCS_1396.csv"; Mai Ndombe: "VCS_934.csv") in long format, containing five columns: 1. year: numeric 2. var: character, either "project", "counterfactual" or "additionality" 3. val: numeric, total carbon flux (or additionality) from the previous year to this year (Mg CO2e) 4. n_sim: numeric, number of repetition 5. boolean, whether the year is larger than project start (t0)

To quantify how forest cover changes over time, we used the annual change collection in the JRC-TMF dataset (Vancutsem et al. 2021), which provides the spatial extent and the annual change of the tropical moist forest (TMF) biome at the 0.09-hectare (30 m × 30 m pixels) resolution from 1990 to 2022, derived from the L1T archive imagery (orthorectified top of atmosphere reflectance). The six following land cover classes were mapped: 1) undisturbed forest, 2) degraded forest, 3) deforested land, 4) forest regrowth, 5) permanent and seasonal water, and 6) other land cover. To use information on forest cover to quantify how carbon stock changes over time in NBS projects, we assume that for each project, we can calculate a reference carbon density value for each land cover class that is stable over time. For this, we used the GEDI Level 4A dataset, which contains footprint-level aboveground biomass density (AGBD) estimates (Mg ha-1) for each 25-m GEDI shot (Dubayah et al. 2020, Duncanson et al. 2022). The AGBD estimates are generated from models linking GEDI waveform-derived canopy height metrics with field AGBD estimates for multiple regions and plant functional types.

We selected GEDI shots occurring from 1st January 2020 to 1st January 2021, and which falling within the project area plus a 30-km buffer around it. The inclusion of a 30-km buffer around the project area is to ensure that enough GEDI shots can be found for each land cover class. For each land cover class, we selected the subset of GEDI shots associated with it as shots that overlap with a JRC-TMF pixel 1) that belongs to the land cover class in question and 2) whose eight neighboring pixels also belong to the land cover class in question. The second condition was included to account for the potential geolocation error up to 10 m of GEDI shots. For each land cover class, we calculated the median AGBD value of all the GEDI shots associated with it. We then estimated belowground biomass and deadwood biomass to be 20% and 11% of AGB, respectively, calculated the total biomass as the sum of aboveground, belowground and deadwood biomass, and converted total biomass to total carbon density by multiplying it by the average carbon density of biomass, taken to be 0.47 for this study (Cairns et al. 1997, Penman et al. 2003, Martin & Thomas 2011).

We adopted a pixel-based matching approach to find the counterfactual scenario for each project, following the PACT Tropical Moist Forest Accreditation Methodology (doi:10.33774/coe-2023-g584d-v5). We sampled pixels in the project area at a density of 0.25 points/ha for smaller projects (≤ 250k ha) and 0.05 points/ha for large projects (> 250k ha). We then sampled candidate matching pixels from the match destination to the amount of ten times the number of sampled project pixels. The match destination is defined as the area of a 2000-km buffer around the project that falls within the project’s country boundary (from the LSIB dataset) and the RESOLVE ecoregion boundaries for all the ecoregions that lie within the project (Dinerstein et al. 2017), excluding all other REDD+ project areas and a 5-km leakage buffer around each of the REDD+ projects (including the project being matched).

For each project pixel in a 10% sample of the sampled project pixel set, we matched it to one candidate matching pixel which has the exact same value for the following categorical variables: (1) Land cover class at t−10, t−5, and t0 (where t is the project start year), (2) Country, and (3) Ecoregion, and which has the minimum Mahalanobis distance (Mahalanobis 2018) across the following continuous variables: (1) Elevation from the SRTM data (Jarvis et al. 2008), (2) SRTM-derived slope, (3) Accessibility (Weiss et al. 2018), and (4) Coarsened proportional cover of undisturbed forest and deforested land, at 1200 m × 1200 m resolution, within a 1-km radius buffer around the pixels at t−10, t−5, and t0.

We deemed the matching results valid if all the standardized mean differences (SMD) of each continuous matching variable between the sampled project pixels and the matched pixels is smaller than 0.2 (unless if a continuous matching variable with an SMD > 0.2 is distributed in the range [0, 1], and the value in one of the pixel sets is close to 0 or 1: this is because (as near those values SMD becomes misleading). We performed 20 repetitions of the matching process, each time using an independent sample of the project pixels as input and producing a set of matched pixels as output. The matched pixel sets are the ”counterfactual scenarios” of the project area, and can be considered to be representative of the trajectory of forest cover change and carbon flux in the project area if the project had not existed.

We then evaluated the carbon losses of both the pixels in the project area and the pixels in the counterfactual scenarios, at a yearly interval. For each year within the JRC-TMF time series (1990-2021), for both the project area and the counterfactual scenarios, we calculated the proportion of pixels in each JRC-TMF land cover class, and used the GEDI L4A-derived estimates of total carbon density for each land cover class, described in the previous section, to calculate the total carbon stock (Mg CO2), and calculated the mean total carbon stock value of all 100 counterfactual repetitions. We then calculated carbon losses (lt) of each year t in both the project area (p) and the counterfactual (c) as the difference between the carbon stock of that year (bt) and that of the previous year (bt−1): lt = bt−1 − bt. Finally, we calculated annual carbon drawdown (at) as the difference between the project carbon loss (ltp) and counterfactual carbon loss (ltc): at = ltc − ltp.

China launched its national emissions trading system (ETS) in 2021, becoming the world's largest carbon market by emissions coverage. As of April 2025, carbon prices of China's national ETS hovered around ** USD/tCO₂e. The China national ETS builds on the seven pilot projects that have been implemented in seven cities and provinces across the country. These pilot ETS will continue to operate alongside the national ETS, covering emissions not yet included in the national system.

Lithium rose to 63,750 CNY/T on July 11, 2025, up 0.16% from the previous day. Over the past month, Lithium's price has risen 5.11%, but it is still 29.56% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Lithium - values, historical data, forecasts and news - updated on July of 2025.

Details are in : https://doi.org/10.1016/j.ecmx.2022.100299

The Kingdom of Saudi Arabia (KSA) is among the countries that committed to taking measures to cut greenhouse gas emissions in accordance with the 2015 Paris Climate Agreement. KSA has rolled out the 2030 Vision aiming at creating a more diverse and sustainable economy that cascaded into a series of initiatives, including the circular carbon economy, Saudi green initiative, and the national renewable energy program. Furthermore, KSA has recently announced an ambitious goal to reach net-zero goal by 2060. In its updated nationally determined contribution (NDC), the Kingdom committed to reducing its carbon emissions by 278 million tons of CO2eq (equivalent) annually by 2030. This ambition is more than a two-fold increase versus the previously announced target (130 million tons of CO2eq). With no current plans to change its hydrocarbon production rates, this reduction in emissions would be achieved mainly through diversifying its energy mix, increasing the efficiency of industrial processes, and deploying carbon capture utilization and storage (CCUS). To achieve this goal, it is vital to establish a detailed register for CO2 emissions from stationary industrial sources to design optimum and effective CCUS applications. This register includes details about the emission source locations, rates, and characteristics. For the first time, this paper provides a country-wide extensive study that maps out CO2 emissions from stationary industrial emitters associated with the leading six industries in the country, which are electricity generation, desalination, oil refining, cement, petrochemicals, and iron & steel. Moreover, CO2 concentrations within the emitted flue gas from these resources are estimated, which is crucial to determine the capture cost. This study aims to provide a vital resource for researchers and policymakers who seek to reduce greenhouse gas emissions by promoting renewable energy, improving the efficiency of existing fossil-fuel-based industries, and evaluating the potential of CCUS in KSA.

Enhancing marine carbon sequestration through nearshore aquaculture is a novel scientific approach to addressing global climate change and facilitating low-carbon development. Scientifically estimating the quantity and price of China’s marine fisheries carbon sinks provides a crucial foundation for promoting marine carbon trading. In this article, firstly, the long-term carbon storage capacity of China’s marine carbon sequestration fishery available from 1979 to 2022 for carbon trading is calculated. And then a transcendental logarithmic production function model incorporating ridge regression analysis, and an accounting equation for estimating the shadow price of China’s marine fisheries carbon sequestration are established. Simultaneously, the distortion level of China’s marine fisheries carbon sequestration prices from 2015 to 2022 is measured, and the reasons and economic effects of the distortion in prices are analyzed. The research results show that: 1) The capacity of a net carbon sequestration in China’s marine carbon sequestration fishery for carbon trading, ranged from 78,869.01 tons in 1979 to 1,232,762.27 tons in 2022, with an average annual capacity of 592,472.07 tons and an average annual growth rate of 7.48%; 2) The price of China’s marine fisheries carbon sinks increased from 39.46 CNY in 1979 to 375.96 CNY in 2022, with an average annual growth rate of 6.00%. The average annual price was 167.87 CNY; 3) There were varying degrees of distortion in China’s marine fisheries carbon sequestration prices from 2015 to 2022, which decreased annually with the construction of China’s own carbon trading market and the practice of trading. To realize the value of marine fisheries carbon sequestration, it is necessary to actively promote the development of voluntary emission reduction markets, develop carbon trading futures markets, and strengthen the dynamic monitoring system for resources.

European Union Emissions Trading System (EU-ETS) carbon allowances are estimated to average ** euros per metric ton of carbon dioxide (tCO₂e) in 2024. This figure is forecast to more than double by the end of the decade to roughly *** euros/tCO₂e, before reaching nearly *** euros/tCO₂e by 2035. EU-ETS carbon prices surpassed the 100 euros per metric ton threshold for the first time in February 2023.