Eora is an environmentally extended MRIO database, meaning it documents both monetary flows and the embodied resource or pressure footprints associated with those flows. This is done by extending the production recipe for each sector with a set of non-monetary inputs to production. In the same way that a sector purchases goods A, B, and C from other sectors, it also uses resources W and X, exerts social impact Y, and emits pollution Z. These non-monetary inputs are technically known as satellite accounts. They are also commonly referred to as ESG indicators. This page provides documentation on the satellite accounts included in Eora.
Gg [1 Gg = 1 kiloton]
Several
Eora offers several different satellite accounts for GHG emissions. Our recommendation is to use the PRIMAP dataset. We also provide the EDGAR and archived CDIAC datasets. IEA data is no longer provided, since that is no longer free. The available GHG line items are:The PRIMAP-HIST model homepage is https://www.pik-potsdam.de/paris-reality-check/primap-hist/. We are currently using the HISTCR scenario v2.3_28_Jul_2021.
PRIMAP's emissions categories, which are based on the IPCCC emissions categories, are shown in this table:
Category Code | Description |
IPCM0EL | National Total exlcuding LULUCF |
IPC1 | Energy |
IPC1A | Fuel Combustion Activities |
IPC1B | Fugutive Emissions from Fuels |
IPC1B1 | Solid Fuels |
IPC1B2 | Oil and Natural Gas |
IPC1B3 | Other Emissions from Energy Production |
IPC1C | Carbon Dioxide Transport and Storage (currently no data available) |
IPC2 | Industrial Processes and Product Use (IPPU) |
IPC2A | Mineral Industry |
IPC2B | Chemical Industry |
IPC2C | Metal Industry |
IPC2D | Non-Energy Products from Fuels and Solvent Use |
IPC2E | Electronics Industry (no data available as the category is only used for fluorinated gasses which are only resolved at the level of category IPC2) |
IPC2F | Product uses as Substitutes for Ozone Depleting Substances (no data available as the category is only used for fluorinated gasses which are only resolved at the level of category IPC2) |
IPC2G | Other Product Manufacture and Use |
IPC2H | Other |
IPCMAG | Agriculture, sum of IPC3A and IPCMAGELV |
IPC3A | Livestock |
IPCMAGELV | Agriculture excluding Livestock |
IPC4 | Waste |
IPC5 | Other |
The I-GHG-* are deprecated and will no longer be updated. It is recommended to use the PRIMAP these CO2 rows instead. The text describing the I-GHG-* rows has been moved to the bottom of this document and is in strikethrough text.
‘000 full-time equivalent (FTE) employees
I-EMPLOYMENT
Employment (labour), per sector, by gender. Units are ‘000 Full-Time Equivalent. Data do not cover all countries; for countries where no data are avaialble the value will be 0. Source: ILO. For further information see:
Alsamawi, A., Murray, J., Lenzen, M., D. Moran, Kanemoto, K.. (2014) The Inequality Footprint of Nations: A Novel Approach to Quantitative Accounting of Income Inequality. PLOS One10.1371/journal.pone.0110881
Employment data is available for the following countries: Albania, Algeria, Antigua, Argentina, Armenia, Aruba, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Bermuda, Bolivia, Botswana, Brazil, Brunei, Bulgaria, Cambodia, Canada, Cayman Islands, Chile, China, Colombia, Costa Rica, Croatia, Cuba, Cyprus, Czech Republic, Denmark, Dominican Republic, Ecuador, Egypt, El Salvador, Estonia, Ethiopia, Finland, France, French Polynesia, Georgia, Germany, Greece, Guatemala, Guyana, Honduras, Hong Kong, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Kazakhstan, Kuwait, Kyrgyzstan, Latvia, Lesotho, Lithuania, Luxembourg, Macao SAR, Madagascar, Malaysia, Maldives, Mali, Malta, Mauritius, Mexico, Mongolia, Montenegro, Morocco, Namibia, Nepal, Netherlands, Netherlands Antilles, New Zealand, Nicaragua, Norway, Gaza Strip, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, South Korea, Moldova, Romania, Russia, Samoa, San Marino, Saudi Arabia, Senegal, Serbia, Sierra Leone, Singapore, Slovakia, Slovenia, South Africa, Spain, Sri Lanka, Suriname, Sweden, Switzerland, Syria, Taiwan, Tajikistan, Thailand, TFYR Macedonia, Trinidad and Tobago, Turkey, Uganda, Ukraine, UAE, UK, Tanzania, USA, Uruguay, Uzbekistan, Venezuela, Viet Nam, Yemen, Zambia
metric tonnes
I-MFA
Material usage, by 36 material categories. From the EWMFA Database by CSIRO. Units are tonnes. The latest year is 2008. Users may also ignoreLicenseRequirementForThisRequest to the materialflows.net database which has more recent data, but at the present time there is no plan to integrate that into Eora. Data are described in:
Wiedmann, T., H. Schandel, D. Moran, J. West, M. Lenzen, K. Kanemoto, S. Suh. The Material Footprint of Nations – Reassessing Resource Productivity. Proceedings of the National Academy of Sciences10.1073/pnas.1220362110
Wiedmann, T., H. Schandel, D. MoranThe footprint of using metals: new metrics of consumption and productivity. Environmental Economics and Policy Studies10.1007/s10018-014-0085-y
The line items are:
Code | Description |
A.999 | TOTAL |
A.1.1.1 | Cereals |
A.1.1.10 | Other crops |
A.1.1.2 | Roots and tubers |
A.1.1.3 | Sugar crops |
A.1.1.4 | Pulses |
A.1.1.5 | Nuts |
A.1.1.6 | Oil bearing crops |
A.1.1.7 | Vegetables |
A.1.1.8 | Fruits |
A.1.1.9 | Fibres |
A.1.2.1 | Crop residues (used) |
A.1.2.2.2 | Grazed biomass |
A.1.3.1 | Timber (Industrial roundwood) |
A.1.3.2 | Wood fuel and other extraction |
A.2.1 | Iron Ores |
A.2.2.1 | Copper ores - gross ore |
A.2.2.2 | Nickel ores - gross ore |
A.2.2.3 | Lead ores - gross ore |
A.2.2.4 | Zinc ores - gross ore |
A.2.2.5 | Tin ores - gross ore |
A.2.2.6 | Gold, silver, platinum and other precious metal ores - gross ore |
A.2.2.7 | Bauxite and other aluminium ores - gross ore |
A.2.2.8 | Uranium and thorium ores - gross ore |
A.2.2.9 | Other metal ores - gross ore |
A.3.1.1 | Ornamental or building stone |
A.3.1.2 | Chalk and dolomite |
A.3.1.4 | Chemical and fertilizer minerals |
A.3.1.5 | Salt |
A.3.1.6 | Other mining and quarrying products n.e.c |
A.3.2 | Non-Metallic minerals - primarily construction |
A.4.1.1 | Brown coal |
A.4.1.2 | Hard coal |
A.4.1.4 | Peat |
A.4.2.1 | Crude oil and natural gas liquids |
A.4.2.2 | Natural gas |
kg
I-TERR-NFertilizer
I-TERR-PFertilizer
I-TERR-NManure
I-TERR-PManure
I-TERR-N-FrtlAndMnr
I-TERR-P-FrtlAndMnrCrop
Nitrogen and Phosphorus use by Fertilizer and Manure, in kg. Source: http://sedac.ciesin.columbia.edu/data/collection/ferman-v1/sets/browse
Potter, P., N. Ramankutty, E.M. Bennett, and S.D. Donner (2011)Global Fertilizer and Manure, Version 1: Phosphorus Fertilizer Application. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC)10.7927/H4FQ9TJR
Potter, P., N. Ramankutty, E.M. Bennett, and S.D. Donner (2010) Characterizing the Spatial Patterns of Global Fertilizer Application and Manure Production. Earth Interactions10.1175/2009EI288.1
Accessed July 1 2015. Data were converted from kg/ha per grid cell to total kg per country.
Note: there are newer, per-crop maps available from http://www.earthstat.org/data-download/ but these have not been incorporated into Eora yet.
ha
CroplandHa
PastureHa
Crop and pasture area, per country, in hectares (ha). Note: 1 km2 = 100 ha, and 10000 m2 = 1 ha. Source: http://www.earthstat.org/data-download/
Ramankutty, N., A.T. Evan, C. Monfreda, and J.A. Foley (2008) Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles10.1029/2007GB002952
ha, metric tonnes, yield (t/ha)
I-RCROP-AREA
I-RCROPPRDOUCTION
I-RCROP-AVERAGEYIELD
Crop harvested area (hectares), production (tonnes), and average yield (t/ha) for 172 major crops, for every year.
The crop names are identical to those used by Monfreda and Ramankutty (2008), but data are taken from FAOSTAT3. This is for convenience in linking the accounts to the Monfreda maps.
Monfreda Maps:
Source: http://www.earthstat.org/data-download/ and
metadata
Monfreda, C., N. Ramankutty, and J.A. Foley (2008). Farming the planet. Part 2: Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000.Global Biogeochemical Cycles10.1029/2007GB002947
Million cubic meter (Mm3)
WaterFootprintNetwork
WF
WATER-
WSCARCITY-
For water footprint data, the satellite rows 2485:2502, designated WaterFootprintNetwork are the current data source.
Rows with the WF-, WATER-, and WSCARCITY- code prefixes are deprecated.
The new satellite rows come directly from the Water Footprint Network, dataset “National Water Footprint Statistics: water footprints of national production (1996-2005)” at this web page: http://waterfootprint.org/en/resources/water-footprint-statistics/#CP3 These data were originally published as part of: Hoekstra, A.Y. and Mekonnen, M.M. (2012) The water footprint of humanity’ Proceedings of the National Academy of Sciences, 109(9): 3232–3237.
There is no time-series data for water use. Eora uses interpolation to provide a simplistic estimate for water use over time. The WFN data are provided as the annual average usage during the period, 1996-2000. To create a timeseries, we assumed that the water intensity of each sector (Mm3/yr/$) remains constant and scaled the water use according to the growth in each sector, using the year 2000 as the base year. For use by industry, the sectoral gross output was used to calculate intensity. For water use by households, total final demand by households in each country was used to calculate intensity.
More details about the original water satellite account can be found in:
Lenzen, M., Moran, D. et al. (2013) International Trade in Scarce WaterEcological Economics10.1016/j.ecolecon.2013.06.018
Gg
N_N2O
N_NH3
N_NOx
N_Nwp
Source:
Oita, A., Malik, A., Kanemoto, K., Geschke, A., Nishijima, S., & Lenzen, M. (2016) Substantial nitrogen pollution embedded in international tradeNature Geoscience10.1038/ngeo2635
The satellites are calculated from three data sets: the related EDGAR air emissions data, the calculated agricultural emissions data, and the calculated emissions from household wastewater. The agricultural emissions are calculated with coefficients taken from the 2006 IPCC guideline and data from FAOSTAT and IFA (International Fertilizer Industry Association). The emissions from household wastewater are calculated using FAO food balance sheets, FAO food waste data, OECD wastewater treatment data, and some related literature. The account contains several line items:
Primary data sources:
TJ
I-ENERGY
The energy satellite accounts have been deprecated. It is not recommended to use these rows as the data may be outdated or inaccurate.