Coal fell to 110.60 USD/T on August 21, 2025, down 0.81% from the previous day. Over the past month, Coal's price has risen 0.45%, but it is still 24.63% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coal - values, historical data, forecasts and news - updated on August of 2025.

This dataset contains information about world's coal price from 1987. Data from BP. Follow datasource.kapsarc.org for timely data to advance energy economics research.Notes:- Source: IHS Northwest Europe prices for 1990-2000 are the average of the monthly marker, 2001-2016 the average of weekly prices. IHS Japan prices basis = 6,000 kilocalories per kilogram NAR CIF.- The Asian prices are the average of the monthly marker.- Chinese prices are the average monthly price for 2000-2005, weekly prices 2006 -2016, 5,500 kilocalories per kilogram NAR, including cost and freight (CFR)- Source: Platts. Prices are for CAPP 12,500 Btu, 1.2 SO2 coal, fob. - CAPP = Central Appalachian; cif = cost+insurance+freight (average prices); fob = free on board. &am

International and domestic data on coal production, consumption, prices, reserves, stocks, imports, exports, distribution, and transportation rates. Weekly, monthly, and annual data available.

This dataset provides values for COAL reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Financial yearly statistical coal mining data produced for the Queensland mining industry.

Spreadsheets of raw coal and saleable coal production by mine, discards, overburden, Queensland distribution, interstate distribution, export by mine and country.

Please Note: The data structure has been modified as of 14/11/2023.

historical time series of prevailing industry prices

Annual statistical coal mining data produced for the Queensland mining industry. Spreadsheets of raw coal and saleable coal production by region, overburden, Queensland distribution, interstate distribution, export by port, export by region and export by country, and stockpile balances. Please Note: The data structure has been modified as of 30/04/2023.

Coking Coal - values, historical data, forecasts and news - updated on August of 2025.

Colombia Export Price: Coal: Thermal Coal data was reported at 52.030 USD/Ton in 2016. This records a decrease from the previous number of 58.000 USD/Ton for 2015. Colombia Export Price: Coal: Thermal Coal data is updated yearly, averaging 37.840 USD/Ton from Dec 1984 (Median) to 2016, with 33 observations. The data reached an all-time high of 96.770 USD/Ton in 2011 and a record low of 25.290 USD/Ton in 1989. Colombia Export Price: Coal: Thermal Coal data remains active status in CEIC and is reported by Colombian Mining Information System. The data is categorized under Global Database’s Colombia – Table CO.RB029: Coal Price.

The South China coal spot price reached an average of 120.65 U.S. dollars per metric ton in 2023. The peak price in the period of consideration was reached in 2022 at 177.78 U.S. dollars per metric ton as a result of growing energy demand when the world economy recovered from the coronavirus pandemic-induced slump.

India Coal: Representative Price: Non-Coking: Grade: G13 data was reported at 1,626.000 INR/Ton in Mar 2025. This records a decrease from the previous number of 1,671.000 INR/Ton for Feb 2025. India Coal: Representative Price: Non-Coking: Grade: G13 data is updated monthly, averaging 1,710.000 INR/Ton from Mar 2020 (Median) to Mar 2025, with 61 observations. The data reached an all-time high of 2,960.000 INR/Ton in May 2022 and a record low of 1,180.000 INR/Ton in Jul 2020. India Coal: Representative Price: Non-Coking: Grade: G13 data remains active status in CEIC and is reported by Ministry of Coal. The data is categorized under India Premium Database’s Energy Sector – Table IN.RBT002: Coal: Representative Price.

China's coal mining industry boasts a long history, with most mines entering mid to late stages of development. Consequently, many coal resource-dependent cities are facing gradual resource depletion, leading to a proliferation of internal issues and pronounced conflicts across various dimensions. Annually, significant wastage of energy resources occurs due to coal mining in these cities. Understanding the spatial distribution of energy consumption from coal mining is crucial for advancing energy system transformation and planning future coal mining strategies. This study employs web scraping techniques to gather coal production data from coal resource cities across China. Using a top-down approach, the comprehensive energy consumption based on coal production was estimated, and consequently, the energy consumption per unit of coal production for each province was calculated. The results indicate that cities with energy consumption from coal mining exceeding 5 million tonnes of standard coal are primarily concentrated in the eastern regions and the Jin-Shan-Mongolia-Ningxia-Gansu area.

002 -- Consumer Prices of Hard Coal and Natural Gas in Energy Production (VAT not included)

New York Energy Prices presents retail energy price data. Energy prices are provided by fuel type in nominal dollars per million Btu for the residential, commercial, industrial, and transportation sectors. This section includes a column in the price table displaying gross domestic product (GDP) price deflators for converting nominal (current year) dollars to constant (real) dollars. To convert nominal to constant dollars, divide the nominal energy price by the GDP price deflator for that particular year. Historical petroleum, electricity, coal, and natural gas prices were compiled primarily from the Energy Information Administration. How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

India aims to achieve net-zero emissions by 2070 and has set an ambitious target of 500 GW of renewable power generation capacity by 2030. Coal plants currently contribute to more than 60% of India’s electricity generation in 2022. Upgrading and decarbonizing high-emission coal plants became a pressing energy issue. A key technical parameter for coal plants is the operating station heat rate (SHR), which represents the thermal efficiency of a coal plant. Yet, the operating SHR of Indian coal plants varies and is not comprehensively documented. This study extends from several existing databases and creates an SHR dataset for 806 Indian coal plant units using machine learning (ML), presenting the most comprehensive coverage to date. Additionally, it incorporates environmental factors such as water stress risk and coal prices as prediction features to improve accuracy. This dataset, easily downloadable from our visualization platform, could inform energy and environmental policies for India’s coal power generation as the country transitions towards its renewable energy targets.

description: This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 141, and contains only the reference case. The dataset uses million short tons and the US Dollar. The data is broken down into northern Appalachia, central Appalachia, southern Appalachia, eastern interior, western interior, Gulf, Dakota medium, western Montana, Wyoming, Rocky Mountain, Arizona/New Mexico and Washington/Alaska.; abstract: This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 141, and contains only the reference case. The dataset uses million short tons and the US Dollar. The data is broken down into northern Appalachia, central Appalachia, southern Appalachia, eastern interior, western interior, Gulf, Dakota medium, western Montana, Wyoming, Rocky Mountain, Arizona/New Mexico and Washington/Alaska.

This study deals with three questions: What does gas from coal cost and what affects this cost; How do different approaches and processes compare; and How near to competitive cost-levels is present-day technology. Discussion covers production of both substitute natural gas (SNG) and medium calorific gas (MCG: 10-16 MJ/Nm3 or 250-400 Btu/SCF). Conclusions are that SNG from low-cost U.S. coal and West German brown coal are, on the basis of mature technology and Government rates-of-return, roughly competitive with gas imports into the U.S. and Europe respectively. Similarly MCG from second-generation gasifiers is competitive with gas-oil or No. 2 heating oil in Europe, North America and Japan. However, capital costs form about half total gas costs at 10 percent rate-of-return, so that the competitiveness of gas from coal is sensitive to capital costs: this is the area of greatest uncertainty.

This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 15, and contains only the reference case. The dataset uses gigawatts. The data is broken down into production, net imports, consumption by sector and price.

Miners Object Detection dataset

The dataset consists of of photos captured within various mines, focusing on miners engaged in their work. Each photo is annotated with bounding box detection of the miners, an attribute highlights whether each miner is sitting or standing in the photo.

The dataset's diverse applications such as computer vision, safety assessment and others make it a valuable resource for researchers, employers, and policymakers in the mining industry.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fdb3f193275f5206914a19b127e20138e%2FFrame%2013.png?generation=1695040375509674&alt=media" alt="">

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This is just an example of the data

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Dataset structure

• images - contains of original images of miners
• boxes - includes bounding box labeling for the original images
• annotations.xml - contains coordinates of the bounding boxes and labels, created for the original photo

Data Format

Each image from images folder is accompanied by an XML-annotation in the annotations.xml file indicating the coordinates of the bounding boxes for miners detection. For each point, the x and y coordinates are provided. The position of the miner is also provided by the attribute is_sitting (true, false).

Example of XML file structure

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Febb59bc7d91a28f4e10c3f3da4ce4488%2Fcarbon%20(1).png?generation=1695040600108833&alt=media" alt="">

Miners detection might be made in accordance with your requirements.

TrainingData provides high-quality data annotation tailored to your needs

keywords: coal mines, underground, safety monitoring system, safety dataset, manufacturing dataset, industrial safety database, health and safety dataset, quality control dataset, quality assurance dataset, annotations dataset, computer vision dataset, image dataset, object detection, human images, classification