U.s. energy information administration (eia) – ap electricity symbols ks2 worksheet

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Table 1 decomposes the rates of change by sector for electricity (indirect) and primary (direct) energy consumption and separates those rates of change in electricity and primary energy consumption from the changes in the respective carbon gas laws worksheet intensities. The sums of those changes multiplied by the share of CO2 emissions from each energy type approximate the CO2 changes in each sector.

For example, the residential sector—with the 1.4% decrease in electricity consumed between 2016 and 2017 was enhanced by a decline in carbon intensity of the electricity supply (-3.0%)—has a total change of -4.4% (not shown in the table). When -4.4% is multiplied by the 2017 electricity CO2 emissions share of 68.3%, the resulting electricity-weighted change is -3.0%. Adding -3.0% to the residential sector’s weighted change of primary energy (0.5%) results in a total sector change of -2.6%. Finally, when weighted by the residential share of total CO2 emissions (18.6%), the weighted-sector share is -0.5%. The sectors are summed to determine total energy-related CO2 emission changes. Rounding errors account for slight differences in totals.

Sources: U.S. Energy Information Administration, August 2018 Monthly Energy Review, calculations made for this analysis based on Table 7.3c Consumption of Selected Combustible Fuels for Electricity Generation electricity rates el paso: Commercial and Industrial Sectors (Subset of Table 7.3a). Carbon factors used: Coal, 95.35 million metric tons per quadrillion Btu for both sectors; natural gas, 53.07 million metric tons per quadrillion Btu for both sectors; and petroleum, 78.8 million metric tons per quadrillion Btu for the commercial sector, and 72.62 million metric tons per quadrillion Btu for the industrial sector.

For EIA’s forecasts and projections on emissions and their key drivers, see the Short‐Term Energy Outlook (STEO), with monthly forecasts through 2019, and the Annual Energy Outlook (AEO), with annual projections through 2050. EIA’s International Energy Outlook (IEO) contains projections of international energy consumption and emissions through 2050.

Carbon intensity (economy): The amount of carbon by weight emitted per unit of economic activity. It is most commonly applied to the economy as a whole, where output is measured as the gross domestic product (GDP). The carbon intensity of the economy is the product of the energy intensity of the economy and the carbon intensity of the energy supply. Note electricity 101 powerpoint: this value is currently expressed in the full weight of the carbon dioxide emitted (CO2/GDP).

Carbon intensity (energy supply): The amount of carbon by weight emitted per unit of energy consumed. A common measure of carbon intensity is weight of carbon per Btu of energy. When only one fossil fuel is under consideration, the carbon intensity and the emissions coefficient are identical. When several fuels are under consideration, carbon intensity is based on their combined emissions coefficients weighted by their energy consumption levels. Note: this value is currently measured as the full weight of the carbon dioxide emitted (CO2/energy or CO2/Btu).

Cooling degree days (CDD): A measure of how warm a location is over a period of time relative to a base temperature, most commonly specified as 65 degrees Fahrenheit. The measure is computed for each day by subtracting the base temperature (65 degrees) from the average of the day’s high and low temperatures, with negative values set equal to zero. Each day’s cooling degree days are summed to create a cooling-degree day measure for a specified reference period. Cooling degree days are used in energy analysis as an indicator of air conditioning energy requirements or use.

Energy intensity: A measure relating the output of an activity to the energy input to that activity. Energy intensity is most commonly applied to the economy as a whole, where output is measured as the gross domestic product (GDP), and energy is measured in Btu to allow for the summing of all energy forms. On an economy‐wide level, energy intensity is reflective of both energy efficiency and the structure of the economy. Economies in the process of industrializing tend to have higher energy intensities than economies in their post‐industrial phase. The term energy intensity can also be used on a smaller scale to relate, for k electric bill payment online example, the amount of energy consumed in buildings to the amount of residential or commercial floor space.

Heating degree days (HDD): A measure of how cold a location is over a period of time relative to a base temperature, most commonly specified as 65 degrees Fahrenheit. The measure is computed for each day by subtracting the average of the day’s high and low temperatures from the base temperature (65 degrees), with negative values set equal to zero. Each day’s heating degree days are summed to create a heating-degree-day measure for e85 gas stations in iowa a specified reference period. Heating degree days are used in energy analysis as an indicator of space heating energy requirements or use.

Figure 2. Changes in CO2 emissions attributed to Kaya Identity factors from 2016 to 2017 compared with the trend from the prior decade: This figure gives context to the most recent year‐to‐year change by comparing it with the average change for key parameters over the previous decade. The key parameters are population, per capita GDP (GDP/population), energy intensity, and carbon intensity of the energy supply—which are the factors in the Kaya Identity. The changes in these key parameters determine changes in energy‐related CO2. By comparing the rate of change for each parameter from 2016 to 2017 with the average rate of change for that parameter for the previous decade, the contribution of each parameter to the overall deviation from trend can be calculated. The table below summarizes the rates of change used in the calculations. The larger the positive value, the greater the increase in emissions. The larger the negative value, the lesser the increase in emissions. Parameter

Figure 9. Electricity generation CO2 savings from changes in the fuel mix since 2005: This figure shows the emissions savings from two factors that have resulted in decreases in emissions from 2005 to 2017, while total generation has risen slightly. The first factor is the shift within fossil fuel generation from coal to natural gas. The second factor is the increase in non-carbon electricity generation.

To capture this CO2 savings from the shift to natural gas, the fossil fuel carbon electricity khan academy factor (fossil fuel CO2/fossil fuel generation) remains constant at the 2005 level. This factor is then multiplied by the actual fossil fuel generation for subsequent years. The difference between that value and the actual value for fossil fuel-generated CO2 emissions is the savings in that year. For example, the carbon factor in 2005 for fossil fuel generation was 0.851 metric tons per megawatthour (mt/MWh). By 2017, the carbon intensity had declined to 0.712 mt/MWh. Multiplying the 2005 value by the 2017 level of generation yields 2,130 million metric tons (MMmt) of CO2, versus the actual value of 1,781 MMmt. Therefore, the savings from the shift to natural gas is estimated to have been 348 MMmt of CO2 in 2017.

Because non-carbon generation (the second factor) has a zero-carbon factor for direct emissions, the overall reduction in total carbon intensity was applied to total generation, i.e., multiplying total generation by the 2005 value of 0.608 mt/MWh. The savings in fossil fuel generation was subtracted from the total, and the difference was credited gas zone pricing to non-carbon electricity generation. For example, the total savings in 2017 was 674 MMmt, so the amount allocated to non-carbon generation (674 MMmt minus 348 MMmt) equals 325 MMmt of CO2.