Dataset
Gridded daily Agricultural Burning Emission Inventory of Eastern China, 2012 - 2015, V0.0
Abstract
The Gridded daily Agricultural Burning Emission Inventory of Eastern China dataset contains a unique high Spatio-temporal resolution agricultural burning inventory for eastern China for the years 2012-2015.
The data was generated using twice daily fire radiative power (FRP) observations from the ‘small fire optimised’ VIIRS-IM FRP product, and combined with fire diurnal cycle information taken from the geostationary Himawari-8 satellite.
This dataset was designed to fully take into account small fires well below the MODIS burned area or active fire detection limit, focusing on dry matter burned (DMB) and emissions of CO2, CO, PM2.5 and black carbon. The fuel for these fires is waste straw and other agricultural residues. Information from a crop rotation map to classify the type of agricultural residue being burned at each observed location and time, in addition to an agricultural area land map was also incorporated in consideration of this.
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s): http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data was generated by Leverhulme Centre for Wildfires, King's College London; NERC National Centre for Earth Observation (NCEO). Data was provided to the Centre for Environmental Data Analysis (CEDA) for publication. |
| Data Quality: |
Data was validated by the Kings College London project team
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| File Format: |
NetCDF V4.0
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Related Documents
Citations: 1
The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.
| Zhang, T., de Jong, M.C., Wooster, M.J., Xu, W. & Wang, L. (2020) Trends in eastern China agricultural fire emissions derived from a combination of geostationary (Himawari) and polar (VIIRS) orbiter fire radiative power products. Atmospheric Chemistry and Physics 20, 10687–10705. https://doi.org/10.5194/acp-20-10687-2020 https://doi.org/10.5194/acp-20-10687-2020 |
Process overview
| Title | Gridded daily Agricultural Burning Emission Inventory of Eastern China, V0.0, Computation |
| Abstract | The data was generated using twice daily fire radiative power (FRP) observations from the ‘small fire optimised’ VIIRS-IM FRP product, and combined with fire diurnal cycle information taken from the geostationary Himawari-8 satellite. Information was incorporated from a crop rotation map data was generated from MIRCA2000 0.08o global monthly crop area dataset and an agricultural area land map which was generated from GlobeLand30 land cover product. These have been archived in the input data directory alongside the main data set. Further information on this data set and all input data sets can be found in the documentation section. |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
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- units: MW/m2
- var_id: FRE
- units: MW
- var_id: FRPday
- units: MW
- var_id: FRPnig
- units: km2
- var_id: agrarea
- units: km2
- var_id: agricultural_land_area
- units: unitless
- var_id: agricultural_land_ratio
- units: g/m2
- var_id: bc
- units: g/m2
- var_id: bcdev
- var_id: co
- units: g/m2
- units: g/m2
- var_id: co2
- units: g/m2
- var_id: co2dev
- units: g/m2
- var_id: codev
- units: kg/m2
- var_id: drymatter
- units: degree_north
- var_id: lat
- units: degree_east
- var_id: lon
- units: g/m2
- var_id: pm25
- units: g/m2
- var_id: pm25dev
- var_id: time
Co-ordinate Variables
Temporal Range
2012-02-01T00:00:00
2015-12-31T00:00:00
Geographic Extent
33.0000° |
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111.0000° |
127.0000° |
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21.0000° |