View source for Carbon Emissions Data (CDIAC)

The EmissionsCarbonCDIAC data comes from the Carbon Dioxide Information Analysis Center (CDIAC) and is currently [http://cdiac.ornl.gov/trends/emis/tre_coun.html available online]. As this website will no longer be accessible past September 30, 2017, a new link to the data, which will be available through the US Department of Energy, will be provided when necessary.

The CDIAC is located at the Oak Ridge National laboratory and functions underneath the US Department of Energy, focusing on global climate change research. The organization publishes a number of datasets, including data on climate, atmospheric gases, and vegetation. The only data from the CDIAC used in IFs is total fossil-fuel CO<sub>2</sub> emissions, which is available from 1751 to 2013, but has been imported to IFs beginning in the year 1800.

== CDIAC Calculations ==

The CO<sub>2</sub> emissions prior to 1950 were calculated using historical energy statistics found in academic publications. Post-1950 emissions data has mostly come from energy statistics published by the United Nations. See more detail on the CDIAC methods and sources [http://cdiac.ornl.gov/trends/emis/overview_2013.html here].

Two main equations, derived from the work of [http://journals.co-action.net/index.php/tellusb/article/viewFile/14907/16719 Marland and Rotty (1984)] and [https://www.osti.gov/scitech/biblio/207068/ Boden et. al (1995)], were used in calculating carbon emissions for this data. In order to calculate the CO<sub>2</sub> emissions from fossil fuels, three variables were used, including the amount of fuel produced and consumed (P), the fraction of the fuel that becomes oxidized (FO), and a factor for carbon content of the fuel (C). The following equation was used:

<math>CO_2{_i} = (P_i) (FO_i) (C_i) </math>

where <math> _i </math> is the group of fuel being calculated, chosen from gases, liquids, or solids. This equation was used to calculate global CO<sub>2</sub> estimates for each fuel group. A total of the caclulations for each group was then used to calculate the total CO<sub>2</sub> emissions for each country, used in IFs. In order to estimate the amount of fuel consumed (P), another equation was used:

<math>Consumption&nbsp; = production + imports - exports - bunkers - changes in stocks </math>

where "bunkers" refers to fuel used by ships and aircraft used in international trade.

== Negative Emissions ==

There are negative emissions for a number of countries in this dataset, for Australia in the 1950s, Venezuela in 1930, and Iran in 1950, among others. A possible explanation has been provided by the CDIAC in their discussion of the CO<sub>2</sub> trends for the [http://cdiac.ornl.gov/trends/emis/tre_ira.html Islamic Republic of Iran]:

''Energy statistics for the Islamic Republic of Iran in the early 1950s and the corresponding CO<sub>2</sub> emissions estimates should be used with caution. Domestic fuel consumption is calculated as the difference between production plus imports and exports plus changes in stocks. When both production and exports are very large and very similar, a small error in either estimate can make it appear that domestic consumption was negative.''

This is a plausible explanation for other countries with negative emissions, as they were all for years in the late 1800s or early to mid 1900s, or had poor data availability during the years their emissions appear negative.

== Pulling CDIAC Fossil Fuel CO<sub>2</sub> Emissions Data ==

For general instructions on how to import data into IFs, visit the [http://pardee.du.edu/wiki/index.php?title=Importing_data_(general_instructions) data import page].

'''Notes on the CDIAC dataset,'''

1. The country concordance table to be used for this dataset is the CDIAC table. Every year, the CDIAC adds and deletes some countries out of these tables. Therefore the table must be updated along with the dataset

2. Data is available from the year 1700 onwards. However, only data from the year 1800 onwards is used in IFs.

3. The user must update the formula column when importing the dataset through IFs so that the data is recorded in billions and not millions.

4. The user or vetter should also check the earliest and most recent data columns in the access file. In case of datasets with a large number of nulls, IFs does not update the earliest and most recent columns accurately in the case of some countries.&nbsp;