Natural gas rose to 4.94 USD/MMBtu on December 3, 2025, up 2.04% from the previous day. Over the past month, Natural gas's price has risen 13.71%, and is up 62.29% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Natural gas - values, historical data, forecasts and news - updated on December of 2025.

About the ProjectKAPSARC is analyzing the shifting dynamics of the global gas markets. Global gas markets have turned upside down during the past five years: North America has emerged as a large potential future LNG exporter while gas demand growth has been slowing down as natural gas gets squeezed between coal and renewables. While the coming years will witness the fastest LNG export capacity expansion ever seen, many questions are raised on the next generation of LNG supply, the impact of low oil and gas prices on supply and demand patterns and how pricing and contractual structure may be affected by both the arrival of U.S. LNG on global gas markets and the desire of Asian buyers for cheaper gas.Key PointsIn the past year, global gas prices have dropped significantly, albeit at unequal paces depending on the region. All else being equal, economists would suggest that this should have generated a positive demand response. However, “all else” was not equal. Prices of other commodities also declined while economic growth forecasts were downgraded. Prices at benchmark points such as the U.K. National Balancing Point (NBP), U.S. Henry Hub (HH) and Japan/Korea Marker (JKM) slumped due to lower oil prices, liquefied natural gas (LNG) oversupply and unseasonal weather. Yet, the prices of natural gas in local currencies have increased in a number of developing countries in Africa, the Middle East, Latin America, former Soviet Union (FSU) and Asia. North America experienced demand growth while gas in Europe and Asia faced rising competition from cheaper coal, renewables and, in some instances, nuclear. Gains to European demand were mostly weather related while increases in Africa and Latin America were not significant. For LNG, Europe became the market of last resort as Asian consumption declined. Moreover, an anticipated surge in LNG supply, brought on by several new projects, may lead to a confrontation with Russian or other pipeline gas suppliers to Europe. At the same time, Asian buyers are seeking concessions on pricing and flexibility in their long-term contracts. Looking ahead, natural gas has to prove itself a credible and affordable alternative to coal, notably in Asia, if the world is to reach its climate change targets. The future of the gas industry will also depend on oil prices, evolution of Chinese energy demand and impact of COP21 on national energy policies. Current low prices mean there is likely to be a pause in final investment decisions (FIDs) on LNG projects in the coming years.

UK Gas fell to 72.60 GBp/thm on December 2, 2025, down 1.67% from the previous day. Over the past month, UK Gas's price has fallen 11.75%, and is down 40.33% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. UK Natural Gas - values, historical data, forecasts and news - updated on December of 2025.

Canadian natural gas consumption is highly variable and is dependent on weather. While Canada is the world’s fifth largest producer of natural gas, production is centralized in Western Canada (primarily in Alberta, British Columbia and Saskatchewan). Eastern Canada is connected to production sources via pipelines. In addition to pipeline flows (inter-provincial or to the U.S.), Canada also imports natural gas in liquefied form (LNG), and to a lesser extent exports LNG. When natural gas is cooled to approximately -162° Celsius, it becomes a liquid and significantly shrinks in volume. This process is utilized to transport natural gas via specialized water-borne tankers around the world. Canada has one large LNG import terminal, Canaport, located in Saint John, New Brunswick. Canada also exports and imports LNG via other land-based and water-based ports. In these instances LNG is stored in specialized modular containers. Canada Energy Regulator regulates the export and import of natural gas. Orders or licenses are required to export or import natural gas to and from Canada, including LNG. Holders of these authorizations report monthly on their activities to CER. LNG import and export activities are available by terminal from 2009 to present. Data is delayed by approximately 2 months.

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TTF Gas fell to 27.92 EUR/MWh on December 3, 2025, down 0.17% from the previous day. Over the past month, TTF Gas's price has fallen 14.22%, and is down 40.94% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. EU Natural Gas - values, historical data, forecasts and news - updated on December of 2025.

Gasoline fell to 1.86 USD/Gal on December 2, 2025, down 0.53% from the previous day. Over the past month, Gasoline's price has fallen 2.79%, and is down 4.95% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gasoline - values, historical data, forecasts and news - updated on December of 2025.

The drilling history documents oil and gas wells in the Lower Miocene 2 sequence as a whole and in 10-year intervals. The wells included in this interval are determined by completion date and by comparing the depth of the wells to structure contours of the Lower Miocene 2 sequence. The data are provided in a single file (lm2_prod.shp) as well as nine 10-year interval files covering 1910 through 1999.

These datasets contain basic data and interpretations developed and compiled by the U.S. Geological Survey's Framework Studies and Assessment of the Gulf Coast Project. Other major sources of data include publicly available information from state agencies as well as publications of the U.S. Geological Survey and other scientific organizations. In cases where company proprietary data were used to produce various derivatives such as contour surfaces, the source is cited but the data are not displayed.

County-level data from oil and/or natural gas producing States—for onshore production in the lower 48 States only—are compiled on a State-by-State basis. Most States have production statistics available by county, field, or well, and these data were compiled at the county level to create a database of county-level production, annually for 2000 through 2011. Raw data for natural gas is for gross withdrawals, and oil data almost always include natural gas liquids. Note that State-provided natural gas withdrawals were not available for Illinois or Indiana; those estimates were produced using geocoded wells and State total production reported by the U.S. Department of Energy’s Energy Information Agency.

In the data file, counties with increases or decreases in excess of $20 million in oil and/or natural gas production during 2000-11 are also identified. See the Documentation for more details.

Currently, an ERS update to this data product is not planned.

Working gas held in storage facilities in the United States decreased by 11 billion cubic feet in the week ending November 21 of 2025 . This dataset provides the latest reported value for - United States Natural Gas Stocks Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Undiscovered Oil and Gas Resources dataset shows the locations of the Assessment Units (AUs) in the U.S. Geological Survey (USGS) World Assessment of Undiscovered Oil and Gas Resources. The assessment was conducted in 2012 and evaluated 313 AUs within 171 geologic provinces (areas where oil and gas occur in commercial quantities). An AU is a mappable volume of rock with homogenous geologic properties. Each AU was assessed for undiscovered oil and gas resources using data from published literature. In each geologic province, total petroleum systems (TPS) were also defined. A TPS is the group of geologic elements needed for oil and gas formation. The Undiscovered Oil and Gas Resources dataset provides an understanding of the quantity, quality and distribution of global conventional oil and gas resources. Conventional oil and gas resources, such as crude oil and natural gas, are found in high porosity/permeability reservoirs. Unconventional oil and gas resources are found in low porosity/permeability reservoirs, such as shale and tar sands. Conventional resources are relatively easy to extract from the earth and do not require fracking. The USGS World Assessment of Undiscovered Oil and Gas Resources determined that a total of 565,298 million barrels of oil, 5,605,626 billion cubic feet of gas and 166,668 million barrels of natural gas liquids remained undiscovered as of 2011. All of these resources are conventionally extractable. However, conventional oil and gas resources are dwindling. Knowing where and how much conventional oil and gas remains undiscovered is important for understanding the world’s energy future. The Undiscovered Oil and Gas Resources dataset is a geologic basis for making decisions about energy. It can help predict future energy production trends and increase understanding of the social and environmental consequences of oil and gas resource exploitation.

This project represents the data used in “Influences of potential oil and gas development and future climate on sage-grouse declines and redistribution.” The data sets describe greater sage-grouse (Centrocercus urophasianus) population change, summarized in different boundaries within the Wyoming Landscape Conservation Initiative (WLCI; southwestern Wyoming). Population changes were based on different scenarios of oil and gas development intensities, projected climate models, and initial sage-grouse population estimates. Description of data sets pertaining to this project: Greater sage-grouse population change (percent change) in a high oil and gas development, low population estimate scenario, and with and without effects of climate change. 1. Greater sage-grouse population change (percent change) over 50-years in a high oil and gas development, low population estimate scenario, and with effects of climate change under an RCP 8.5 scenario (2050) 2. Greater sage-grouse population change (percent change) in a low oil and gas development, high population estimate scenario, and with no effects of climate change (2006-2062) 3. Greater sage-grouse population change (percent change) over 50-years in a low oil and gas development, low population estimate scenario, and with effects of climate change under an RCP 8.5 scenario (2050) 4. Greater sage-grouse population change (percent change) in a moderate oil and gas development, high population estimate scenario, and with no effects of climate change (2006-2062) 5. Greater sage-grouse population change (percent change) in a high oil and gas development, low population estimate scenario, and with no effects of climate change (2006-2062) The oil and gas development scenario were based on an energy footprint model that simulates well, pad, and road patterns for oil and gas recovery options that vary in well types (vertical and directional) and number of wells per pad and use simulation results to quantify physical and wildlife-habitat impacts. I applied the model to assess tradeoffs among 10 conventional and directional-drilling scenarios in a natural gas field in southwestern Wyoming (see Garman 2017). The effects climate change on sagebrush were developed using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM, version 4) climate model and representative concentration pathway 8.5 scenario (emissions continue to rise throughout the 21st century). The projected climate scenario was used to estimate the change in percent cover of sagebrush (see Homer et al. 2015). The percent changes in sage-grouse population sizes represented in these data are modeled using an individual-based population model that simulates dynamics of populations by tracking movements of individuals in dynamically changing landscapes, as well as the fates of individuals as influenced by spatially heterogeneous demography. We developed a case study to assess how spatially explicit individual based modeling could be used to evaluate future population outcomes of gradual landscape change from multiple stressors. For Greater sage-grouse in southwest Wyoming, we projected oil and gas development footprints and climate-induced vegetation changes fifty years into the future. Using a time-series of planned oil and gas development and predicted climate-induced changes in vegetation, we re-calculated habitat selection maps to dynamically modify future habitat quantity, quality, and configuration. We simulated long-term sage-grouse responses to habitat change by allowing individuals to adjust to shifts in habitat availability and quality. The use of spatially explicit individual-based modeling offered an important means of evaluating delayed indirect impacts of landscape change on wildlife population outcomes. This process and the outcomes on sage-grouse population changes are reflected in this data set.

This table contains figures on the supply and consumption of energy broken down by sector and by energy commodity. The energy supply is equal to the indigenous production of energy plus the receipts minus the deliveries of energy plus the stock changes. Consumption of energy is equal to the sum of own use, distribution losses, final energy consumption, non-energy use and the total net energy transformation. For each sector, the supply of energy is equal to the consumption of energy.

For some energy commodities, the total of the observed domestic deliveries is not exactly equal to the sum of the observed domestic receipts. For these energy commodities, a statistical difference arises that can not be attributed to a sector.

The breakdown into sectors follows mainly the classification as is customary in international energy statistics. This classification is based on functions of various sectors in the energy system and for several break downs on the international Standard Industrial Classification (SIC). There are two main sectors: the energy sector (companies with main activity indigenous production or transformation of energy) and energy consumers (other companies, vehicles and dwellings). In addition to a breakdown by sector, there is also a breakdown by energy commodity, such as coal, various petroleum products, natural gas, renewable energy, electricity and heat and other energy commodities like non renewable waste.

The definitions used in this table are exactly in line with the definitions in the Energy Balance table; supply, transformation and consumption. That table does not contain a breakdown by sector (excluding final energy consumption), but it does provide information about imports, exports and bunkering and also provides more detail about the energy commodities.

Data available: From: 1990.

Status of the figures: Figures up to and including 2022 are definite. Figures for 2023 and 2024 are revised provisional.

Changes as of July 2025: Compiling figures on solar electricity took more time than scheduled. Consequently, not all StatLine tables on energy contain the most recent 2024 data on production for solar electricity. This table contains the outdated data from June 2025. The most recent figures are 5 percent higher for 2024 solar electricity production. These figures are in these two tables (in Dutch): - StatLine - Zonnestroom; vermogen en vermogensklasse, bedrijven en woningen, regio - StatLine - Hernieuwbare energie; zonnestroom, windenergie, RES-regio Next update is scheduled in November 2025. From that moment all figures will be fully consistent again. We apologize for the inconvenience.

Changes as of June 2025: Figures for 2024 have been updated.

Changes as of March 17th 2025: For all reporting years the underlying code for 'Total crudes, fossil fraction' and 'Total kerosene, fossiel fraction' is adjusted. Figures have not been changed.

Changes as of November 15th 2024: The structure of the table has been adjusted. The adjustment concerns the division into sectors, with the aluminum industry now being distinguished separately within the non-ferrous metal sector. This table has also been revised for 2015 to 2021 as a result of new methods that have also been applied for 2022 and 2023. This concerns the following components: final energy consumption of LPG, distribution of final energy consumption of motor gasoline, sector classification of gas oil/diesel within the services and transfer of energy consumption of the nuclear industry from industry to the energy sector. The natural gas consumption of the wood and wood products industry has also been improved so that it is more comparable over time. This concerns changes of a maximum of a few PJ.

Changes as of June 7th 2024: Revised provisional figures of 2023 have been added.

Changes as of April 26th of 2024 The energy balance has been revised for 2015 and later on a limited number of points. The most important is the following: 1. For solid biomass and municipal waste, the most recent data have been included. Furthermore data were affected by integration with figures for a new, yet to be published StatLine table on the supply of solid biomass. As a result, there are some changes in receipts of energy, deliveries of energy and indigenous production of biomass of a maximum of a few PJ. 2. In the case of natural gas, an improvement has been made in the processing of data for stored LNG, which causes a shift between stock changes, receipts of energy and deliveries of energy of a maximum of a few PJ.

Changes as of March 25th of 2024: The energy balance has been revised and restructured. This concerns mainly the following: 1. Different way of dealing with biofuels that have been mixed with fossil fuels 2. A breakdown of the natural gas balance of agriculture into greenhouse horticulture and other agriculture. 3. Final consumption of electricity in services

1. Blended biofuels Previously, biofuels mixed with fossil fuels were counted as petroleum crude and products. In the new energy balance, blended biofuels count for renewable energy and petroleum crude and products and the underlying products (such as gasoline, diesel and kerosene) only count the fossil part of mixtures of fossil and biogenic fuels. To make this clear, the names of the energy commodities have been changed. The consequence of this adjustment is that part of the energy has been moved from petroleum to renewable. The energy balance remains the same for total energy commodities. The aim of this adjustment is to make the increasing role of blended biofuels in the Energy Balance visible and to better align with the Energy Balances published by Eurostat and the International Energy Agency. Within renewable energy, biomass, liquid biomass is now a separate energy commodity. This concerns both pure and blended biofuels.

2. Greenhouse horticulture separately The energy consumption of agriculture in the Netherlands largely takes place in greenhouse horticulture. There is therefore a lot of attention for this sector and the need for separate data on energy consumption in greenhouse horticulture. To meet this need, the agriculture sector has been divided into two subsectors: Greenhouse horticulture and other agriculture. For the time being, we only publish separate natural gas figures for greenhouse horticulture.

3. Higher final consumption of electricity in services in 2021 and 2022. The way in which electric road transport is treated has improved, resulting in an increase in the supply and final consumption of electricity in services by more than 2 PJ in 2021 and 2022. This also works through the supply of electricity in sector H (Transport and storage).

Changes as of November 14th 2023: Figures for 2021 and 2022 haven been adjusted. Figures for the Energy Balance for 2015 to 2020 have been revised regarding the following items: - For 2109 and 2020 final consumption of heat in agriculture is a few PJ lower and for services a few PJ higher. This is the result of improved interpretation of available data in supply of heat to agriculture. - During the production of geothermal heat by agriculture natural gas is produced as by-product. Now this is included in the energy balance. The amount increased from 0,2 PJ in 2015 to 0,7 PJ in 2020. - There are some improvements in the data for heat in industry with a magnitude of about 1 PJ or smaller. - There some other improvements, also about 1 PJ or smaller.

Changes as of June 15th 2023: Revised provisional figures of 2022 have been added.

Changes as of December 15th 2022: Figures for 1990 up to and including 2019 have been revised. The revision mainly concerns the consumption of gas- and diesel oil and energy commodities higher in the classification (total petroleum products, total crude and petroleum produtcs and total energy commodities). The revision is twofold: - New data for the consumption of diesel oil in mobile machine have been incorporated. Consequently, the final energy consumption of gas- and diesel oil in construction, services and agriculture increases. The biggest change is in construction (+10 PJ from 1990-2015, decreasing to 1 PJ in 2019. In agriculture the change is about 0.5-1.5 PJ from 2010 onwards and for services the change is between 0 and 3 PJ for the whole period. - The method for dealing with the statistical difference has been adapted. Earlier from 2013 onwards a difference of about 3 percent was assumed, matching old data (up to and including 2012) on final consumption of diesel for road transport based on the dedicated tax specifically for road that existed until 2012. In the new method the statistical difference is eliminated from 2015 onwards. Final consumption of road transport is calculated as the remainder of total supply to the market of diesel minus deliveries to users other than road transport. The first and second item affect both final consumption of road transport that decreases consequently about 5 percent from 2015 onwards. Before the adaption of the tax system for gas- and diesel oil in 2013 the statistical difference was positive (more supply than consumption). With the new data for mobile machines total consumption has been increased and the statistical difference has been reduced and is even negative for a few years.

Changes as of 1 March 2022: Figures for 1990 up to and including 2020 have been revised. The most important change is a different way of presenting own use of electricity of power-generating installations. Previously, this was regarded as electricity and CHP transformation input. From now on, this is seen as own use, as is customary in international energy statistics. As a result, the input and net energy transformation decrease and own use increases, on average about 15 PJ per year. Final consumers also have power generating installations. That's why final consumers now also have own use, previously this was not so. In the previous revision of 2021, the new sector blast

The topic shows the outlines of the oil and gas deposits according to the current geological knowledge. Petroleum or natural gas deposits are economically viable, natural accumulations of petroleum or natural gas and, if necessary, other hydrocarbons in storage rocks. The outlines of the oil and gas deposits presented in the data set represent boundaries that can be of a diverse nature: In a simple case, this is the interface between the oil/gas accumulation and the surrounding marginal water (so-called oil/gas/water contact). In other geological situations, the boundaries can also be formed in whole or in part by the spatially changing rock properties or tectonic structures, such as faults or discordances. Furthermore, for various reasons, the geological structure of a deposit is not always sufficiently known to define its boundaries in an unequivocal and precise manner. In these cases, the limits concerned have been estimated to the best of our knowledge for the present data set, e.g. by using known gas or oil down-to(s) or estimates of the areas of the deposits drained by extraction. The boundaries of the deposits are also subject to temporal variability, which starts with the commencement of production and the associated extraction of oil or natural gas. With a few exceptions, the present dataset reproduces the initial outlines of the deposits, i.e. the outlines found at the beginning of production. In addition to geological boundaries, there may also be boundaries in the dataset that have an administrative background, e.g. to separate storage areas of different operating companies. The data set is based on geological structure maps of the deposits, which are regularly transmitted to the LBEG by the respective operating companies as part of their reporting on their mining activities. The scale of these structural maps depends on the size of the respective deposit and is usually between 1:10,000 and 1:50,000. This data set is therefore not suitable for applications on a larger scale. Since no structural maps are available to the LBEG for a few small deposits that have already been abandoned, in these cases the outline of the deposit was estimated via a strike circle placed around the corresponding production well(s). Cumulative production data refer to the reference date 31.12. of the previous year and are reported in the 3rd or 4th quarter of each year. Updated calendar month of a year. If the cumulative production data are added to totals for federal states, the sums differ slightly from the sums published in the LBEG’s annual report ‘Oil and natural gas in the Federal Republic of Germany’, as the annual report also takes into account test production volumes that originate from individual wells and did not lead to field development. Furthermore, the annual report divides the production volume of the cross-border Sinstorf oil deposit according to a certain ratio between the Länder of Lower Saxony and Hamburg.

This project is a component of a broader effort focused on geothermal heating and cooling (GHC) with the aim of illustrating the numerous benefits of incorporating GHC and geothermal heat exchange (GHX) into community energy planning and national decarbonization strategies. To better assist private sector investment, it is currently necessary to define and assess the potential of low-temperature geothermal resources. For shallow GHC/GHX fields, there is no formal compilation of subsurface characteristics shared among industry practitioners that can improve system design and operations. Alaska is specifically noted in this work, because heretofore, it has not received a similar focus in geothermal potential evaluations as the contiguous United States. The methodology consists of leveraging relevant data to generate a baseline geospatial dataset of low-temperature resources (less than 150 degrees C) to compare and analyze information accessible to anyone trying to understand the potential of GHC/GHX and small-scale low-temperature geothermal power in Alaska (e.g., energy modelers, communities, planners, and policymakers). Importantly, this project identifies data related to (1) the evaluation of GHC/GHX in the shallow subsurface, and (2) the evaluation of low-temperature geothermal resource availability. Additionally, data is being compiled to assess repurposing of oil and gas wells to contribute co-produced fluids toward the geothermal direct use and heating and cooling resource potential. In this work we identified new data from three different datasets of isolated geothermal systems in Alaska and bottom-hole temperature data from oil and gas wells that can be leveraged for evaluation of low-temperature geothermal resource potential. The goal of this project is to facilitate future deployment of GHC/GHX analysis and community-led programs and update the low-temperature geothermal resources assessment of Alaska. A better understanding of shallow potential for GHX will improve design and operations of highly efficient GHC systems. The deployment and impact that can be achieved for low-temperature geothermal resources will contribute to decarbonization goals and facilitate widespread electrification by shaving and shifting grid loads.

Most of the data uses WGS84 coordinate system. However, each dataset come from different sources and has a metadata file with the original coordinate system.

The drilling history documents oil and gas wells in the Lower Miocene 1 sequence as a whole and in 10-year intervals. The wells included in this interval are determined by completion date and by comparing the depth of the wells to structure contours of the Lower Miocene 1 sequence. The data are provided in a single file (lm1_prod.shp) as well as eight 10-year interval files covering 1920 through 1999.

These datasets contain basic data and interpretations developed and compiled by the U.S. Geological Survey's Framework Studies and Assessment of the Gulf Coast Project. Other major sources of data include publicly available information from state agencies as well as publications of the U.S. Geological Survey and other scientific organizations. In cases where company proprietary data were used to produce various derivatives such as contour surfaces, the source is cited but the data are not displayed.

⚡ Energy Crisis and Stock Price Dataset: 2021-2024 📊

📋 About Dataset

This dataset provides a detailed view of how major energy companies' stock prices were influenced by the energy crises between 2021 and 2024. The data covers three prominent energy companies: ExxonMobil (XOM), Shell (SHEL), and BP (BP), with historical stock price information collected via the yfinance library. This dataset is particularly useful for those interested in financial analysis, market behavior, and the impact of global events on the energy sector. 🌍📉📈

📅 Date Range

• Start Date: January 1, 2021
• End Date: Present day (updated periodically)

🔍 Data Overview

The dataset contains the daily adjusted closing prices of the selected companies from January 2021 to the present. The data was gathered to analyze the impact of different energy crises, such as the fluctuations in oil and gas prices during 2021-2024, and to help provide insights into investor behavior during times of energy uncertainty.

The key columns available in each CSV file are:

💡 Potential Use Cases

This dataset can be used for various purposes including, but not limited to:

• Financial Time Series Analysis 📈: Explore trends and volatility in the stock market, particularly in the energy sector.
• Predictive Modeling 🤖: Develop models to predict future stock prices based on historical data.
• Energy Crisis Impact Studies ⚡: Assess the effect of energy crises on global markets, specifically the energy sector.
• Portfolio Analysis 💼: Evaluate the stability and performance of energy companies during different crisis periods.

📊 Data Files

Each CSV file includes the daily stock prices from January 1, 2021, to the present, with columns for open, high, low, close, adjusted close, and volume.

📂 Dataset Structure

• Directory: data/raw/
  • XOM_data.csv
  • SHEL_data.csv
  • BP_data.csv

🚀 Data Collection Process

The data for this dataset was collected using the yfinance Python library, which provides access to historical market data from Yahoo Finance. The collection script (data_collection.py) automates the download of stock data for the selected companies, saving each company's data in CSV format within the data/raw/ directory.

🔧 Tools Used

• Python 🐍: For scripting and data processing.
• yfinance 📈: To download historical stock data.
• pandas 🐼: For data manipulation and cleaning.

📜 License

The dataset is provided under the MIT License. You are free to use, modify, and distribute this dataset, provided that proper attribution is given.

🙌 Contributions

Contributions are welcome! If you have any suggestions or improvements, feel free to fork the repository and make a pull request. Let's make this dataset even more comprehensive and insightful together. 💪🌟

📧 Contact

For any questions or further information, feel free to reach out:

I hope this dataset helps you uncover new insights about the relationship between energy crises and stock prices! If you find it helpful, don't forget to give it a ⭐️ on Kaggle! 😊✨

Active non-wholesale non-transmission Natural Gas Utility Service Areas as listed in the Regulatory Commission of Alaska (RCA) Certificate details for regulated utilities. Likely the most comprehensive collection of State of Alaska utility service areas - but not necessarily definitive for every utility. For complicated large city service areas such as water and sewer the GIS department that represents those cities might have the best representation of the service area. There are also utilities that may not be regulated by RCA which will not be in the data. Footprints in general were lifted from existing KML files created by a contractor in the years 2008-2017. Service area changes that have happened since 2008 may not yet be reflected in the footprints. In a few cases legal descriptions had typos which resulted in service areas miles from the community they intended to cover. In the case of the AsOfDate attribute in this dataset only reflects the date of the last syncing of master certificate metadata with RCA Library database - not the current polygon representation.Source: Regulatory Commission of AlaskaThis data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: Regulatory Commission of Alaska Library

VITAL SIGNS INDICATOR
Greenhouse Gas Emissions (EN3)

FULL MEASURE NAME
Greenhouse gas emissions from primary sources

LAST UPDATED
December 2022

DESCRIPTION
Greenhouse gas emissions refer to carbon dioxide and other chemical compounds that contribute to global climate change. Vital Signs tracks greenhouse gas emissions linked to consumption from the three largest sources in the region: surface transportation, electricity consumption, and natural gas consumption. This measure helps track progress towards achieving regional greenhouse gas reduction targets, including the region's per-capita greenhouse gas target for surface transportation under Senate Bill 375. This dataset includes emissions estimates on the regional and county levels.

DATA SOURCE
US Energy Information Administration: Carbon Dioxide Emissions Coefficients - https://www.eia.gov/environment/emissions/co2_vol_mass.php
1990-2021

California Energy Commission: Retail Fuel Outlet Annual Reporting (Form CEC-A15) - https://www.energy.ca.gov/data-reports/energy-almanac/transportation-energy/california-retail-fuel-outlet-annual-reporting
2010-2021

California Energy Commission: Electricity Consumption by County - http://www.ecdms.energy.ca.gov/elecbycounty.aspx
1990-2021

California Energy Commission: Natural Gas Consumption by County - http://www.ecdms.energy.ca.gov/gasbycounty.aspx
1990-2021

California Department of Finance: Population and Housing Estimates, E-4 - http://www.dof.ca.gov/research/demographic/
1990-2021

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Emissions in this dataset are reported in metric tons. For surface transportation, the dataset is based on a survey of fueling stations, the vast majority of which respond to the survey; the California Energy Commission (CEC) corrects for non-response bias by imputing the remaining share of fuel sales. Note that 2014 data was excluded to data abnormalities for several counties in the region; methodology improvements in 2012 affected estimated by +/- 5% according to CEC estimates. For years 2013 and 2014, a linear trendline assumption was used instead between 2012 and 2015 data points. Data from the CEC is limited to retail sales, therefore Vital Signs surface transportation emissions estimates are limited to GHG from retail fuel sales. Retail gasoline sales represent most of the gasoline consumed for surface transportation, but retail diesel sales are just a fraction of all diesel consumed for surface transportation. Greenhouse gas emissions are calculated based on the gallons of gasoline and diesel sales, relying upon standardized Energy Information Administration conversion rates for E10 fuel (gasoline with 10% ethanol) and standard diesel. Per-capita greenhouse gas emissions are calculated simply by dividing emissions attributable to fuel sold in that county by the total number of county residents; there may be a slight bias in the data given that a fraction of fuel sold in a given county may be purchased by non-residents. Future refinements to the Vital Signs methodology for monitoring GHG emissions from all surface transportation will seek to more closely align monitoring data with estimates from the California Air Resources Board's EMFAC model.

For electricity consumption, the dataset is based on electricity consumption data for the nine Bay Area counties; note that this is different than electricity production as the region imports electricity. Because such data is not disaggregated by utility provider, a simple assumption is made that electricity consumed has the greenhouse gas emissions intensity of Pacific Gas & Electric, the primary electricity provider in the Bay Area. For this reason, with the small but growing market share of low- and zero-GHG community choice aggregation (CCA) providers, the greenhouse gas emissions estimate in more recent years may be slightly overestimated. Per-capita greenhouse gas emissions are calculated simply by dividing emissions attributable to fuel sold in that county by the total number of county residents; data is disaggregated between residential and non-residential customers.

For natural gas consumption, the dataset is based on natural gas consumption data for the nine Bay Area counties; note that this is different than natural gas production as the region imports electricity. Certain types of liquefied natural gas shipped into the region or "makegas" produced at oil refineries during their production process may not be fully reflected in this data. Per-capita greenhouse gas emissions are calculated simply by dividing emissions attributable to fuel sold in that county by the total number of county residents; data is disaggregated between residential and non-residential customers.

Natural gas supplies nearly a quarter of the world's energy and is growing faster than any other energy source. One pathway to reduce the CO2 emission intensity of natural gas without transitioning end-use infrastructure is to synthesize a natural gas substitute from CO2 and renewable energy via electrochemical CO2 reduction. To improve the economic viability of electrogas, this work examines the possibility of using electrolyzer products without downstream separation. We quantify the electrolyzer performance needed to replicate the key heating value, safety, and emissions characteristics of natural gas. We find that, except in the case of unrealistically high device performance, directly synthesized electrogas is unable to reproduce all necessary properties of natural gas. We discover, however, a range of safe and low-emitting electrogas compositions likely achievable with current technology which can be blended with natural gas to reduce its CO2 intensity while retaining sufficient heating value. This repository contains code and resultant datasets for “Strategies for decarbonizing natural gas with electrosynthesized methane” published in Cell Reports Physical Science summarized above. Code includes functions to calculate key combustion characteristics of electrogas and natural gas including Wobbe index, flammability limits, flame speed, ignition temperature, and nitrous oxides (NOx), CO and soot emissions. These combustion characteristics are calculated for potential electrogases as a function of device performance and also for a sampling of potential natural gases through a Monte Carlo study. Scripts are also included which reproduce the figures found in the manuscript and supplemental information. Finally, this repository contains the datasets generated by these scripts as well as input tables and chemical mechanism files. See 1_README.txt for more information on individual files as well as the packages required to run scripts. Note that the 'Original Format' should be downloaded rather than the 'Archival Format' to maintain compatibility for the flammability limit calculations.

The extensive development of oil and natural-gas resources in south Texas during the past 10 years has led to questions regarding possible environmental effects of processes associated with oil and natural-gas production, in particular the process of hydraulic fracturing, on water and other natural resources. Part of the lower San Antonio River watershed intersects an area of oil and natural-gas production from the sedimentary rocks that compose the Eagle Ford Group. The rapid expansion of infrastructure associated with oil and natural-gas production increases potential pathways for inorganic and organic contaminants to enter surface-water systems. The U.S. Geological Survey, in cooperation with the San Antonio River Authority, analyzed geospatial data from different years (2008 and 2015) to evaluate changes in land cover associated with oil and natural-gas production activities in the lower San Antonio River watershed. Additionally, during 2015-17 surface-water samples collected from 5 sites and streambed-sediment samples collected from 17 sites in the lower San Antonio River watershed were analyzed for a broad range of constituents that might be associated with oil and natural-gas production.