The price of carbon under the California Cap-and-Trade program (California CaT) was **** U.S. dollars per metric ton (USD/tCO₂e) on April 1, 2025. By comparison, carbon permits on April 1, 2021 were less than ** USD/tCO₂e. The California CaT covers the transportation, buildings, industry, and power sectors, and is a key element of California's greenhouse gas emissions reductions strategy.

This dataset contains the predicted prices of CANA Holdings California Carbon Credits for the upcoming years based on user-defined projections.

Nature-based climate solutions are a vital component of many climate mitigation strategies, including California's, which aims to achieve carbon neutrality by 2045. Most carbon offsets in California's cap-and-trade program come from improved forest management projects (IFMs). Since 2012, various landowners have set up IFMs following the California Air Resources Board's IFM protocol. As many of these projects approach their tenth year, we now have the opportunity to assess their effectiveness, identify best practices, and suggest improvements toward future protocol revisions. In this study, we used remote sensing-based datasets to evaluate the carbon trends and harvest histories of 37 IFMs in California. Despite some current limitations and biases, these datasets can be used to quantify carbon accumulation and harvest rates in offset project lands relative to nearby similar "control" lands before and after the projects began. Five lines of evidence suggest that the carbon accumulated in offset projects to date has generally not been additional to what might have otherwise occurred: (1) most forests in northwestern California have been accumulating carbon since at least the mid-1980s and continue to accumulate carbon, whether enrolled in offset projects or not; (2) harvest rates were high in large timber company project lands before IFM initiation, suggesting they are earning carbon credits for forests in recovery; (3) projects are often located on lands with higher densities of low-timber-value species; (4) carbon accumulation rates have not yet increased on lands that enroll as offset projects, relative to their pre-enrollment levels; and (5) harvest rates have not decreased on most project lands since offset project initiation. These patterns suggest that the current protocol should be improved to robustly measure and reward additionality. In general, our framework of geospatial analyses offers an important and independent means to evaluate the effectiveness of the carbon offsets program, especially as these data products continue improving and as offsets receive attention as a climate mitigation strategy.

Environment and Climate Change Canada’s (ECCC) data of the impact of carbon pollution pricing on national and provincial gross domestic product for the period 2022 to 2030. This data reflects ECCC’s estimates of the impact of carbon pricing on reducing greenhouse gas emissions published in the report entitled How Pollution Pricing Reduces Emissions. It includes data on the impact of carbon pricing on national and provincial gross domestic product for the period 2022 to 2030, which reflects Environment and Climate Change Canada's estimates of the impact of carbon pricing on reducing greenhouse gas emissions published in the report entitled How Pollution Pricing Reduces Emissions. It also contains data on the economic impacts of carbon pricing in each province and territory (and for Canada as a whole) by sector for the period 2022 to 2030: - The impact of carbon pricing on gross value added. - The corresponding impacts on real (inflation-adjusted) investment (capital) and labour incomes, that is, the income components of gross domestic product. The Output-Based Pricing System (OBPS) Proceeds Fund returns proceeds collected under the federal OBPS and is comprised of two streams: the Decarbonization Incentive Program and the Future Electricity Fund. Further information on projects being funded by federal industrial pollution pricing proceeds has been published on the Open Government Portal.

Canada Residential & Commercial: Carbon Pricing Score: Excluding Emissions from the Combustion of Biomass: EUR 60 per Tonne of CO2 data was reported at 21.203 % in 2018. Canada Residential & Commercial: Carbon Pricing Score: Excluding Emissions from the Combustion of Biomass: EUR 60 per Tonne of CO2 data is updated yearly, averaging 21.203 % from Dec 2018 (Median) to 2018, with 1 observations. The data reached an all-time high of 21.203 % in 2018 and a record low of 21.203 % in 2018. Canada Residential & Commercial: Carbon Pricing Score: Excluding Emissions from the Combustion of Biomass: EUR 60 per Tonne of CO2 data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.ESG: Environmental: Effective Carbon Rates: by Sector: OECD Member: Annual. The carbon pricing score answers the question how close countries are to price carbon in line with carbon costs. EUR 60 is a midpoint estimate for carbon costs in 2020, and a low-end estimate for 2030. Pricing all emissions at least at EUR 60 in 2020 shows that a country is on a good track to reach the goals of the Paris Agreement to decarbonise by mid-century economically. EUR 30 is a historic low-end estimate for carbon costs, and EUR 120 is a midrange estimate for carbon costs in 2030.; The carbon pricing score answers the question how close countries price carbon emissions in line with carbon costs. EUR 60 per tonne CO2 is a midpoint estimate for carbon costs in 2020, and a low-end estimate for 2030. Pricing all emissions, i.e. 100%, at EUR 60 or more in 2020 shows that a country is on good track to reach the goal of the Paris Agreement to decarbonise by mid-century economically.More generally, a carbon pricing score of 100% shows that a country prices all carbon emissions at the carbon cost estimate or more, and a carbon pricing score of 0% shows that a country does not price any carbon emissions. The carbon pricing score by country, by sector answers the question how close countries price carbon emissions in line with carbon costs within a given sector.For additional information, see Effective Carbon Rates 2021

This dataset contains comprehensive hourly data from January 1, 2021, to May 31, 2024, for the California region. The data focuses on electric vehicle (EV) charging demand and renewable energy production, including solar and wind energy. The dataset is structured to support analysis and optimization of EV charging using intelligent forecasting methods for solar and renewable energy in uncertain environments. The integrated solar and wind energy data are taken from https://catalog.data.gov/dataset/.

Dataset Description 1. Time Frame Start Date: January 1, 2021 End Date: May 31, 2024 Frequency: Hourly 2 Key Features Date: The specific date of the recorded data. Time: The hour of the day the data was recorded. EV Charging Demand (kW): The amount of electricity (in kilowatts) demanded by electric vehicles for charging during each hour. Solar Energy Production (kW): The amount of electricity (in kilowatts) produced from solar energy sources during each hour. Wind Energy Production (kW): The amount of electricity (in kilowatts) produced from wind energy sources during each hour. Electricity Price ($/kWh): The price of electricity per kilowatt-hour. Grid Availability: Indicates whether the grid was available ("Available") or not ("Unavailable") during each hour. Weather Conditions: Describes the weather during each hour, with possible values such as "Clear", "Cloudy", "Rainy", "Sunny", and "Partly Cloudy". Battery Storage (kWh): The amount of electricity stored in batteries during each hour. Charging Station Capacity (kW): The maximum capacity of the charging stations in kilowatts. EV Charging Efficiency (%): The efficiency of the EV charging process, expressed as a percentage. Number of EVs Charging: The number of electric vehicles charging during each hour. Peak Demand (kW): The peak electricity demand during each hour. Renewable Energy Usage (%): The percentage of energy used from renewable sources. Grid Stability Index: An index indicating the stability of the grid, with higher values indicating greater stability. Carbon Emissions (kgCO2/kWh): The amount of carbon emissions produced per kilowatt-hour of electricity. Power Outages (hours): The duration of power outages during each hour. Energy Savings ($): The amount of money saved through energy efficiencies during each hour. Derived Features Total Renewable Energy Production (kW): The sum of solar and wind energy production.

Total Renewable Energy Production (kW) = Solar Energy Production (kW) +Wind Energy Production (kW) Effective Charging Capacity (kW): The product of charging station capacity and EV charging efficiency.

\text{Effective Charging Capacity (kW)} = \text{Charging Station Capacity (kW)} \times \left( \frac{\text{EV Charging Efficiency (%)}}{100} \right)

Adjusted Charging Demand (kW): The EV charging demand adjusted by renewable energy usage. \text{Adjusted Charging Demand (kW)} = \text{EV Charging Demand (kW)} \times \left( \frac{\text{Renewable Energy Usage (%)}}{100} \right) Net Energy Cost ($): The product of EV charging demand and electricity price.

\text{Net Energy Cost ($)} = \text{EV Charging Demand (kW)} \times \text{Electricity Price ($/kWh)} Carbon Footprint Reduction (kgCO2): The reduction in carbon emissions due to renewable energy usage.

\text{Carbon Footprint Reduction (kgCO2)} = \text{EV Charging Demand (kW)} \times \text{Carbon Emissions (kgCO2/kWh)} \times \left( 1 - \frac{\text{Renewable Energy Usage (%)}}{100} \right) Renewable Energy Efficiency: The efficiency of utilizing renewable energy for charging electric vehicles.

Renewable Energy Efficiency = Total Renewable Energy Production (kW) / Effective Charging Capacity (kW)

Usage and Applications This dataset is valuable for research and development in the following areas:

• Optimizing EV Charging: By analyzing the data, strategies can be developed to optimize EV charging schedules to minimize costs and maximize the use of renewable energy. Renewable Energy Forecasting: The dataset supports the development of predictive models for solar and wind energy production. Grid Management: Insights from the data can help improve grid stability and manage peak demand periods. Carbon Emission Reduction: The dataset aids in calculating and strategizing ways to reduce carbon emissions from EV charging. Economic Analysis: The data allows for the assessment of energy savings and cost efficiencies in EV charging. This extensive dataset provides a robust foundation for advancing sustainable and intelligent EV charging solutions in the California region.

This data supplements our publication "An unlikely pairing: the mining industry economically benefits from a global tax on carbon emissions". This data is used to test the impact of a hypothetical international carbon taxation regime on a subsection of the mining industry compared to other sectors. A financial model was developed to calculate the cost of carbon taxes for 23 commodities across three industries. The findings show that, given any level of taxation tested, most mining industry commodities would not add more than 30% of their present product value. Comparatively, commodities such as coal could be taxed at more than 150% of their current product value under more intense carbon pricing initiatives, thereby accelerating the transition to renewable energy sources and the consequent demand benefits for mined metals.

CALAND carbon pools.

A survey of Nova Scotians' opinions on climate change and carbon pricing.

Prescribed scenarios for CALAND simulations.

Alberta’s new royalty framework sets out to encourage industry to bring down their costs, just as a price on carbon encourages companies to bring down their emissions. All companies will pay a price on carbon, as detailed in the Climate Leadership Plan. The amount that any company may have to pay depends on their greenhouse gas emissions. With respect to royalties, the price on carbon will be treated as a cost. One in a series of fact sheets created to provide information on the work of the Royalty Review Advisory Panel and Alberta's new royalty framework.

This survey data is from a study exploring the potential to promote lower-emissions air travel by providing consumers with information about the carbon emissions of possible flight choices in the context of online flight search and booking. We surveyed over 450 faculty, researchers, and staff at the University of California, Davis, and asked them to choose among hypothetical flight options for a domestic and an international university-related business trip. Emissions estimates for different flight alternatives were displayed as prominently as price; this simple intervention has been promoted in several demonstration projects, including GreenFLY, a demo we created at UC Davis.

Methods The flight choice experiment involved an online survey in which UC Davis employees were asked to make a series of binary discrete choices between roundtrip flight alternatives, that varied in terms of cost, carbon emissions, layovers (0 or 2: one layover each way), and airport (SMF or SFO), for two hypothetical UC Davis-related business trips, one to Washington, DC and the other to London. We based these hypothetical scenarios (trip destinations and attribute levels of flight alternatives) on data about actual UC Davis employee air travel.

For the layover flight alternatives, we created eight possible cost-carbon combinations, using each cost level and each carbon level twice, and not repeating any pairing. There are many ways to do this, and we chose one which tended to pair high cost with low carbon, to create trade-offs. Our eight layover flights to DC appear in Table 2. The same cost-carbon pairings were used for layover flight alternatives from SFO.

We organized the flight alternatives into sets of two for the choice experiment questions. Criteria for pairing flight alternatives were as follows: 1. Every flight alternative should appear roughly the same number of times in the survey, 2. The distribution of kinds of flights in the questions (eg. layover out of SFO) should match the distribution in the entire set, 3. Avoid questions in which the two flights have the same cost, or the same carbon, and 4. Focus on pairs that might have competitive utility (e.g. an alternative that is lower cost, lower carbon, nonstop and out of SMF is likely to be selected in most cases, so it is not useful for understanding potential trade-offs).

From this, we created seven "buckets" of questions for Washington, and seven for London, and asked each participant a randomly-chosen question from each bucket. We made an error in the online questionnaire-design software, which caused a random bucket to be skipped for London. Nonetheless, each flight option appears freqently (between 40 and 120 times) in the questions we asked.

The original data output from Qualtrics was processed into a format suitable for processing with the mlogit package in R.

CALAND land categories.

Canada CA: CO2 Emissions: Kg per PPP of(GDP) Gross Domestic Product2011 Price data was reported at 0.351 kg in 2014. This records an increase from the previous number of 0.348 kg for 2013. Canada CA: CO2 Emissions: Kg per PPP of(GDP) Gross Domestic Product2011 Price data is updated yearly, averaging 0.491 kg from Dec 1990 (Median) to 2014, with 25 observations. The data reached an all-time high of 0.558 kg in 1992 and a record low of 0.348 kg in 2013. Canada CA: CO2 Emissions: Kg per PPP of(GDP) Gross Domestic Product2011 Price data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Environmental: Gas Emissions and Air Pollution. Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring.; ; Carbon Dioxide Information Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory, Tennessee, United States.; Weighted Average;

Canada Road: Share of Emissions Priced: Including Emissions from the Combustion of Biomass: Above EUR 60 per Tonne of CO2 data was reported at 84.641 % in 2018. Canada Road: Share of Emissions Priced: Including Emissions from the Combustion of Biomass: Above EUR 60 per Tonne of CO2 data is updated yearly, averaging 84.641 % from Dec 2018 (Median) to 2018, with 1 observations. The data reached an all-time high of 84.641 % in 2018 and a record low of 84.641 % in 2018. Canada Road: Share of Emissions Priced: Including Emissions from the Combustion of Biomass: Above EUR 60 per Tonne of CO2 data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.ESG: Environmental: Effective Carbon Rates: by Sector: OECD Member: Annual. The share of emissions priced above EUR Y per tonne of CO2 shows the share of emissions within a country or sector with a carbon price that exceed EUR Y in percent.

Canada All Sectors: Share of Emissions Priced: Excluding Emissions from the Combustion of Biomass: Above EUR 30 per Tonne of CO2 data was reported at 28.103 % in 2021. This records an increase from the previous number of 27.041 % for 2018. Canada All Sectors: Share of Emissions Priced: Excluding Emissions from the Combustion of Biomass: Above EUR 30 per Tonne of CO2 data is updated yearly, averaging 27.572 % from Dec 2018 (Median) to 2021, with 2 observations. The data reached an all-time high of 28.103 % in 2021 and a record low of 27.041 % in 2018. Canada All Sectors: Share of Emissions Priced: Excluding Emissions from the Combustion of Biomass: Above EUR 30 per Tonne of CO2 data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.ESG: Environmental: Effective Carbon Rates: by Sector: OECD Member: Annual. The share of emissions priced above EUR Y per tonne of CO2 shows the share of emissions within a country or sector with a carbon price that exceed EUR Y in percent.

Canada Residential & Commercial: Share of Emissions Priced: Including Emissions from the Combustion of Biomass: Above EUR 60 per Tonne of CO2 data was reported at 0.008 % in 2018. Canada Residential & Commercial: Share of Emissions Priced: Including Emissions from the Combustion of Biomass: Above EUR 60 per Tonne of CO2 data is updated yearly, averaging 0.008 % from Dec 2018 (Median) to 2018, with 1 observations. The data reached an all-time high of 0.008 % in 2018 and a record low of 0.008 % in 2018. Canada Residential & Commercial: Share of Emissions Priced: Including Emissions from the Combustion of Biomass: Above EUR 60 per Tonne of CO2 data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.ESG: Environmental: Effective Carbon Rates: by Sector: OECD Member: Annual. The share of emissions priced above EUR Y per tonne of CO2 shows the share of emissions within a country or sector with a carbon price that exceed EUR Y in percent.

Canada Industry: Share of Emissions Priced: Including Emissions from the Combustion of Biomass: Above EUR 90 per Tonne of CO2 data was reported at 0.000 % in 2018. Canada Industry: Share of Emissions Priced: Including Emissions from the Combustion of Biomass: Above EUR 90 per Tonne of CO2 data is updated yearly, averaging 0.000 % from Dec 2018 (Median) to 2018, with 1 observations. The data reached an all-time high of 0.000 % in 2018 and a record low of 0.000 % in 2018. Canada Industry: Share of Emissions Priced: Including Emissions from the Combustion of Biomass: Above EUR 90 per Tonne of CO2 data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.ESG: Environmental: Effective Carbon Rates: by Sector: OECD Member: Annual. The share of emissions priced above EUR Y per tonne of CO2 shows the share of emissions within a country or sector with a carbon price that exceed EUR Y in percent.

Provides 2018 carbon levy rates and explains who must file an inventory declaration and the process. Tax and Revenue Administration special notices announce changes to, or clarify, administrative policies and practices. These notices are time-specific, and meant to be transitory in nature. The information may eventually be incorporated into other publications such as information circulars or web content. Note: Bill 1, An Act to Repeal the Carbon Tax, received Royal Assent on June 4, 2019. The carbon levy no longer applies to any type of fuel as of the beginning of the day on May 30, 2019. For more information, visit: alberta.ca/carbon-levy.aspx.

Canada Residential & Commercial: Share of Emissions Priced: Excluding Emissions from the Combustion of Biomass: Above EUR 5 per Tonne of CO2 data was reported at 99.985 % in 2021. This records an increase from the previous number of 76.204 % for 2018. Canada Residential & Commercial: Share of Emissions Priced: Excluding Emissions from the Combustion of Biomass: Above EUR 5 per Tonne of CO2 data is updated yearly, averaging 88.094 % from Dec 2018 (Median) to 2021, with 2 observations. The data reached an all-time high of 99.985 % in 2021 and a record low of 76.204 % in 2018. Canada Residential & Commercial: Share of Emissions Priced: Excluding Emissions from the Combustion of Biomass: Above EUR 5 per Tonne of CO2 data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.ESG: Environmental: Effective Carbon Rates: by Sector: OECD Member: Annual. The share of emissions priced above EUR Y per tonne of CO2 shows the share of emissions within a country or sector with a carbon price that exceed EUR Y in percent.