An error occured. Details Hide
You have unsaved pages. Restore Cancel

U.S. Energy Information Administration

The U.S. Energy Information Administration (EIA) is a principal agency of the U.S. Federal Statistical System responsible for collecting, analyzing, and disseminating energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment. EIA programs cover data on coal, petroleum, natural gas, electric,  renewable and nuclear energy.

All datasets:  C D E G I N R U W
  • C
  • D
    • December 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 14 December, 2017
      Select Dataset
      The Drilling Productivity Report uses recent data on the total number of drilling rigs in operation along with estimates of drilling productivity and estimated changes in production from existing oil and natural gas wells to provide estimated changes in Oil and Natural gas production for seven key regions: Bakken, Eagle Ford, Haynesville, Marcellus, Niobrara, Permian and Utica
  • E
    • November 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 21 November, 2017
      Select Dataset
    • November 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 20 November, 2017
      Select Dataset
      Energy & Environment Statistics of Louisiana
    • November 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 28 November, 2017
      Select Dataset
      The yearly data is the sum of the monthly data for all indicators. Energy consumption data by different sector are developed from a group of energy-related surveys, typically called "supply surveys," conducted by the U.S. Energy Information Administration (EIA). Supply surveys are directed to suppliers and marketers of specific energy sources. They measure the quantities of specific energy sources produced, or the quantities supplied to the market, or both. The data obtained from EIA's supply surveys are integrated to yield the summary consumption statistics.
    • June 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 13 July, 2017
      Select Dataset
    • January 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 12 December, 2017
      Select Dataset
      Energy-related carbon dioxide (CO2) emissions vary significantly across states, whether considered on an absolute (Figure 1) or per capita basis. Total state CO2 emissions include those from direct fuel use across all sectors, including residential, commercial, industrial, and transportation, as well as primary fuels consumed for electric generation. The overall size of a state, as well as the available fuels, types of businesses, climate, and population density, play a role in determining the level of both total and per capita emissions. Additionally, each state’s energy system reflects circumstances specific to that state. For example, some states have abundant hydroelectric supplies, while others contain abundant coal resources. This paper presents a basic analysis of the factors that contribute to a state’s CO2 profile. This analysis neither attempts to assess the effect of state policies on absolute emissions levels or on changes over time, nor does it intend to imply that certain policies would be appropriate for a particular state. The term energy-related CO2 emissions, as used in this paper, includes emissions released at the location where fossil fuels are consumed. Therefore, to the extent that fuels are used in one state to generate electricity that is consumed in another state, emissions are attributed to the former rather than the latter. Analysis attributing emissions to the consumption of electricity, rather than the production of electricity, would yield different results. For feedstock application, carbon stored in products such as plastics are subtracted from reported emissions for the states where they are produced.
    • November 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 22 November, 2017
      Select Dataset
      Estimates of Annual Fossil-Fuel CO2 Emitted for Each State in the U.S.A. and the District of Columbia for Each Year from 1960 through 2001. Consumption data for coal, petroleum, and natural gas are multiplied by their respective thermal conversion factors, which are in units of heat energy per unit of fuel consumed (i.e., per cubic foot, barrel, or ton), to calculate the amount of heat energy derived from fuel combustion. Results are expressed in terms of heat energy obtained from each fuel type. These energy consumption data were multiplied by their respective carbon dioxide emission factors, which are called carbon content coefficients by the U.S. Environmental Protection Agency (EPA). These factors quantify the mass of oxidized carbon per unit of energy released from a fuel. In the U.S.A., they are typically expressed in units of teragrams of carbon (Tg-C = 10^12 grams of carbon) per quadrillion British thermal units (quadrillion Btu = 10^15 Btu, or "quad"), and are highest for coal and lowest for natural gas. Our results are given in teragrams of carbon emitted. To convert to carbon dioxide, multiply by 44/12 (= 3.67).    
  • G
    • December 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 08 December, 2017
      Select Dataset
      Source: https://www.eia.gov/dnav/pet/pet_stoc_gp_a_EPLLB0I_SKN_mbbl_a.htm https://www.eia.gov/dnav/ng/ng_stor_sum_dcu_nus_m.htm
  • I
    • November 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 01 December, 2017
      Select Dataset
    • September 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 21 September, 2017
      Select Dataset
      The International Outlook presents an assessment by the U.S. Energy Information Administration of the outlook for international energy markets through 2050. In the International Energy Outlook 2017 (IEO2017) Reference case, total world energy consumption rises from 575 quadrillion British thermal units (Btu) in 2015 to 736 quadrillion Btu in 2040, an increase of 28%. Most of the world’s energy growth will occur in countries outside of the Organization for Economic Cooperation and Development (OECD), where strong, long-term economic growth drives increasing demand for energy. Non-OECD Asia (including China and India) alone accounts for more than half of the world’s total increase in energy consumption over the 2015 to 2040 projection period. By 2040, energy use in non-OECD Asia exceeds that of the entire OECD by 41 quadrillion Btu in the IEO2017 Reference case.
    • December 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 06 December, 2017
      Select Dataset
      Data by country, region, for 217 countries including total and crude oil production, oil consumption, natural gas production and consumption, coal production and consumption, electricity generation and consumption, primary energy, energy intensity, CO2 emissions and imports and exports for all fuels.
  • N
  • R
  • U
  • W
    • November 2017
      Source: U.S. Energy Information Administration
      Uploaded by: Knoema
      Accessed On: 13 November, 2017
      Select Dataset
      Correlation defined as linear relationship between two variables. Correlation coefficient (r) is used to measure linear association between two variables and its range varies between -1 to +1. There are two types of correlation namely positive and negative. r=+1 represents perfect positive correlation whereas r=-1 represents perfect negative correlation. Positive correlation tells both indicators are moving in same direction for e.g. If prices of crude oil and Natural gas are positively correlated and there is an increase in price of crude oil then price of Natural gas will also increase. On the other hand negative correlation between the same indicators, if there is increase in price of one will decrease the price of others.