Gasoline Prices in Costa Rica decreased to 1.31 USD/Liter in June from 1.36 USD/Liter in May of 2025. This dataset provides the latest reported value for - Costa Rica Gasoline Prices - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Gasoline Prices in Philippines increased to 1.06 USD/Liter in June from 0.98 USD/Liter in May of 2025. This dataset provides the latest reported value for - Philippines Gasoline Prices - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Gasoline Prices in Saudi Arabia remained unchanged at 0.62 USD/Liter in June. This dataset provides the latest reported value for - Saudi Arabia Gasoline Prices - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

A dataset of average pence per litre and per gallon petrol and diesel fuel prices in the UK regions including England, Scotland, Wales, and Northern Ireland.

Context

The data is daily diesel price across the various city in India. The charge varies state to state has Indian state government levy extra tax on the fuel. The government changed over time. The new fuel charge update rule came into effect.

Content

The data consist of the date, fuel price and city name. There are a total of seven cities, such as Bengaluru, Chennai, Mumbai, Hyderabad, Delhi, Kolkata and Coimbatore. The fuel price is Indian rupees.

Acknowledgements

The data is parsed from mypetrolprice.com. The code used to parse data is present in github repository.

Inspiration

How to handle missing data in time-series data? What is the price change with respect to a global price change?

The Total Water Produced during 2000 through Conventional Oil and Gas Operations dataset contains the locations of the production wells in the Northeast Wyoming River Basins Planning Area with the total volume of water (in barrels = 42 gallons) produced for the year 2000. The data was reported by the well owners to the Wyoming Oil and Gas Conservation Commission (OGCC) each month, who then tabulate the data and post it on the internet. The OGCC locates each well by both Latitude-Longitude and Township-Range-Section-Quarter-Quarter. All locational information and attributes were imported from the OGCC Production Wells Database stored in a MS Excel spreadsheet.

The Total Water Produced during 2000 through Conventional Oil and Gas Operations dataset contains the locations of the production wells in the Powder/Tongue River Basin Planning Area with the total volume of water (in barrels = 42 gallons) produced for the year 2000. The data was reported by the well owners to the Wyoming Oil and Gas Conservation Commission (OGCC) each month, who then tabulate the data and post it on the internet. The OGCC locates each well by both Latitude-Longitude and Township-Range-Section-Quarter-Quarter. All locational information and attributes were imported from the OGCC Production Wells Database stored in a MS Excel spreadsheet.

The Alberta Natural Gas Reference Price is a monthly weighted average field price of all Alberta gas sales, as determined by the Alberta Department of Energy through a survey of actual sales transactions. This price is used for royalty purposes.

This dataset contains Saudi Arabia Oil Database for 2002-2021. Data from Joint Organisations Data Initiative. Follow datasource.kapsarc.org for timely data to advance energy economics research.

Data Description Managed turfgrass is a common component of urban landscapes that is expanding under current land use trends. Previous studies have reported high rates of soil carbon sequestration in turfgrass, but no systematic review has summarized these rates nor evaluated how they change as turfgrass ages. We conducted a meta-analysis of soil carbon sequestration rates from 63 studies. Those data, as well as the code used to analyze them and create figures, are shared here. Dataset Development We conducted a systematic review from Nov 2020 to Jan 2021 using Google Scholar, Web of Science, and the Michigan Turfgrass Information File Database. The search terms targeted were "soil carbon", "carbon sequestration", "carbon storage", or “carbon stock”, with "turf", "turfgrass", "lawn", "urban ecosystem", or "residential", “Fescue”, “Zoysia”, “Poa”, “Cynodon”, “Bouteloua”, “Lolium”, or “Agrostis”. We included only peer-reviewed studies written in English that measured SOC change over one year or longer, and where grass was managed as turf (mowed or clipped regularly). We included studies that sampled to any soil depth, and included several methodologies: small-plot research conducted over a few years (22 datasets from 4 articles), chronosequences of golf courses or residential lawns (39 datasets from 16 articles), and one study that was a variation on a chronosequence method and compiled long-term soil test data provided by golf courses of various ages (3 datasets from Qian & Follett, 2002). In total, 63 datasets from 21 articles met the search criteria. We excluded 1) duplicate reports of the same data, 2) small plot studies that did not report baseline SOC stocks, and 3) pure modeling studies. We included five papers that only measured changes in SOC concentrations, but not areal stocks (i.e., SOC in Mg ha-1). For these papers, we converted from concentrations to stocks using several approaches. For two papers (Law & Patton, 2017; Y. Qian & Follett, 2002) we used estimated bulk densities provided by the authors. For the chronosequences reported in Selhorst & Lal (2011), we used the average bulk density reported by the author. For the 13 choronosequences reported in Selhorst & Lal (2013), we estimated bulk density from the average relationship between percent C and bulk density reported by Selhorst (2011). For Wang et al. (2014), we used bulk density values from official soil survey descriptions. Data provenance In most cases we contacted authors of the studies to obtain the original data. If authors did not reply after two inquiries, or no longer had access to the data, we captured data from published figures using WebPlotDigitizer (Rohatgi, 2021). For three manuscripts the data was already available, or partially available, in public data repositories. Data provenance information is provided in the document "Dataset summaries and citations.docx". Recommended Uses We recommend the following to data users:

Consult and cite the original manuscripts for each dataset, which often provide additional information about turfgrass management, experimental methods, and environmental context. Original citations are provided in the document "Dataset summaries and citations.docx". For datasets that were previously published in public repositories, consult and cite the original datasets, which may provide additional data on turfgrass management practices, soil nitrogen, and natural reference sites. Links to repositories are in the document "Dataset summaries and citations.docx". Consider contacting the dataset authors to notify them of your plans to use the data, and to offer co-authorship as appropriate.

This dataset provides observations of atmospheric carbon dioxide (CO₂) amounts obtained from observations collected by several current and historical satellite instruments. Carbon dioxide is a naturally occurring Greenhouse Gas (GHG), but one whose abundance has been increased substantially above its pre-industrial value of some 280 ppm by human activities, primarily because of emissions from combustion of fossil fuels, deforestation and other land-use change. The annual cycle (especially in the northern hemisphere) is primarily due to seasonal uptake and release of atmospheric CO2 by terrestrial vegetation. Atmospheric carbon dioxide abundance is indirectly observed by various satellite instruments. These instruments measure spectrally resolved near-infrared and/or infrared radiation reflected or emitted by the Earth and its atmosphere. In the measured signal, molecular absorption signatures from carbon dioxide and other constituent gasses can be identified. It is through analysis of those absorption lines in these radiance observations that the averaged carbon dioxide abundance in the sampled atmospheric column can be determined. The software used to analyse the absorption lines and determine the carbon dioxide concentration in the sampled atmospheric column is referred to as the retrieval algorithm. For this dataset, carbon dioxide abundances have been determined by applying several algorithms to different satellite instruments. Typically, different algorithms have different strengths and weaknesses and therefore, which product to use for a given application typically depends on the application. The data set consists of 2 types of products:

column-averaged mixing ratios of CO2, denoted XCO2 mid-tropospheric CO2 columns.

The XCO2 products have been retrieved from SCIAMACHY/ENVISAT, TANSO-FTS/GOSAT, TANSO-FTS2/GOSAT2 and OCO-2. The mid-tropospheric CO2 product has been retrieved from the IASI instruments on-board the Metop satellite series and from AIRS. The XCO2 products are available as Level 2 (L2) products (satellite orbit tracks) and as Level 3 (L3) product (gridded). The L2 products are available as individual sensor products (SCIAMACHY: BESD and WFMD algorithms; GOSAT: OCFP and SRFP algorithms) and as a multi-sensor merged product (EMMA algorithm). The L3 XCO2 product is provided in OBS4MIPS format. The IASI and AIRS products are available as L2 products generated with the NLIS algorithm. This data set is updated on a yearly basis, with each update cycle adding (if required) a new data version for the entire period, up to one year behind real time. This dataset is produced on behalf of C3S with the exception of the SCIAMACHY and AIRS L2 products that were generated in the framework of the GHG-CCI project of the European Space Agency (ESA) Climate Change Initiative (CCI).

Heating Oil rose to 2.47 USD/Gal on July 11, 2025, up 3.46% from the previous day. Over the past month, Heating Oil's price has risen 11.10%, but it is still 1.60% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Heating oil - values, historical data, forecasts and news - updated on July of 2025.

The Total Water Injected during 2000 through Conventional Oil and Gas Operations dataset contains the locations of the injection wells in the Powder/Tongue River Basin Planning Area with the total volume of water (in barrels = 42 gallons) injected for the year 2000. The data was reported by the well owners to the Wyoming Oil and Gas Conservation Commission (OGCC) each month, who then tabulate the data and post it on the internet. The OGCC locates each well by both Latitude-Longitude and Township-Range-Section-Quarter-Quarter. All locational information and attributes were imported from the OGCC Injection Wells Database stored in a MS Excel spreadsheet.

The data shows the date-wise details of the retail selling price of petrol and diesel in metro cities for Indian Oil Corporation (IOC) Note: 1. Daily price change is applicable in India since 16.6.2017 2. Daily Price change is applicable from 6.00 AM 3. Data for 2002 to 2017 is available only for Delhi

This isopach map shows the thickness of the interval from the top of the Cotton Valley Group to the top of the Smackover Formation. It was necessary to contour this expanded interval, instead of just the upper part of the Cotton Valley Group, because of the limited availability of data. Ideally, just the part of the Cotton Valley Group above the Bossier Shale would have been contoured, but there are a limited number of Bossier picks in the database, and many of the Bossier picks are not at a consistent stratigraphic break (J.L. Ridgley, oral commun., 2002). Data for units below the Bossier, such as the Haynesville or Buckner Formations, are also limited on a regional basis. The Smackover Formation is the first unit below the top of the Cotton Valley that has abundant data available on a regional level. The data are provided as both lines and polygons, and the proprietary wells that penetrate this interval are graphically displayed as quarter-mile cells. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data are current as of April 2001.