Notre bibliothèque d'aperçus de données va plus loin dans les sujets d'actualité et les grands dossiers mondiaux. À la recherche de plus d'informations ? Découvrez la façon dont nous intégrons des données et les services de visualisation d'experts avec nos outils intelligents, nos espaces personnalisés et les portails de données d'entreprise.
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.
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
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.
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).
Source Details:US Data (Table: 12.1) http://www.eia.gov/totalenergy/data/monthly/#environment
States Data http://www.eia.gov/environment/emissions/state/
Emission per capita has been calculated by dividing emission value with residential population of states.
The International Energy Outlook 2016 (IEO2016) presents an assessment by the U.S. Energy Information Administration (EIA) of the outlook for international energy markets through 2040. U.S. projections appearing in IEO2016 are consistent with those published in EIA's Annual Energy Outlook 2015 (AEO2015). IEO2016 is provided as a service to energy managers and analysts, both in government and in the private sector. The projections are used by international agencies, federal and state governments, trade associations, and other planners and decisionmakers. They are published pursuant to the Department of Energy Organization Act of 1977 (Public Law 95-91), Section 205(c).
Data is by country and region 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.
The monthly survey Form EIA-860M, ‘Monthly Update to Annual Electric Generator Report’ supplements the annual survey form EIA-860 data with monthly information that monitors the current status of existing and proposed generating units at electric power plants with 1 megawatt or greater of combined nameplate capacity. EIA estimates the current and near-term unit inventory of electric power generating capacity by integrating the information on these surveys along with ongoing EIA research of new units. However, creating this monthly estimate sometimes requires the use of data submitted on the annual EIA-860 before it has been fully verified by EIA. For this reason, reported capacities are EIA’s preliminary estimates of capacity for that month. Estimates will be corrected without specific acknowledgement or explanation in subsequent month’s inventory.
Capacities reported in this preliminary inventory are best estimates of current generating capacity, but are not meant to be capacity commitments by the associated facilities.
EIA has expanded the Monthly Energy Review (MER) to include annual data as far back as 1949 for those data tables that are found in both the Annual Energy Review (AER) and the MER. In the list of tables below, grayed-out table numbers now go to MER tables that contain 1949-2012 (and later) data series.
* Indicator "Electric Price" source link:http://www.eia.gov/electricity/data/browser/#/topic/7?agg=2
* Value for "Spark Spread" has been calculated from "Electric Price" and "Average Cost of Natural Gas"
Formula: Spark Spread = (Electricity Price-((100*Average Cost of Natural Gas)/293.29722222222))
The State Energy Data System (SEDS) is the U.S. Energy Information Administration's (EIA) source for comprehensive State energy statistics. Included are estimates of energy production, consumption, prices, and expenditures broken down by energy source and sector. Production and consumption estimates begin with the year 1960 while price and expenditure estimates begin with 1970.
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.