Spatial distribution dataset of biomass resources and energy technology potential in China (2015-2100)

Spatial distribution dataset of biomass resources and energy technology potential in China (2015-2100)


This data integrates a variety of current natural geographic map data, and combines land suitability evaluation, crop growth model, scenario analysis and other methods to generate China's biomass resources and energy technology potential on a 1km grid scale from 2015 to 2100, with a temporal resolution of 5 years and a spatial resolution of 1km. The data set includes 3 categories and 11 types of biomass resources (the residues include dry land agricultural residues, paddy field agricultural residues, forest residues, shrub residues, orchard residues and grassland residues, the wastes include livestock manure, MSW and COD, and the energy crops include sweet sorghum and switchgrass), fully covering the types of biomass that can be used as resources. The data format is raster data (. tiff), which can be opened using ArcGIS, R/Python and other programming languages.

Biomass is a dependent resource for negative carbon technology in China's carbon neutral technology system in the future. The biomass data developed in this research has three advantages: wide coverage (nationwide), fine spatial resolution (1km grid), and wide time span (2015-2100). It can provide detailed quantitative data for China to formulate low-carbon emission reduction strategies and deploy biomass energy technology strategies.


File naming and required software

Data naming method: RCP scenario+biomass type+year. The data format is raster data (. tiff), which can be opened using ArcGIS, R/Python and other programming languages.


Data Citations Data citation guideline What's data citation?
Cite as:

Cai, W., Nie, Y., Wang, R. (2022). Spatial distribution dataset of biomass resources and energy technology potential in China (2015-2100). A Big Earth Data Platform for Three Poles, DOI: 10.11888/HumanNat.tpdc.272826. CSTR: 18406.11.HumanNat.tpdc.272826. (Download the reference: RIS | Bibtex )

Related Literatures:

1. Nie, Y., Li, J., & Wang, C., et al. (2022). A fine-resolution estimation of the biomass resource potential across China from 2020 to 2100. Resources, Conservation and Recycling, 176, 105944-.( View Details | Bibtex)

2. Nie, Y., Cai, W., & Wang, C., et al. (2019). Assessment of the potential and distribution of an energy crop at 1-km resolution from 2010 to 2100 in China–The case of sweet sorghum. Applied Energy, 239, 395-407.( View Details | Bibtex)

3. Nie, Y., Chang, S., & Cai, W., et al. (2020). Spatial distribution of usable biomass feedstock and technical bioenergy potential in China. GCB Bioenergy, 12(1), 54-70.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.


Support Program

Interaction and regional performance of natural and human factors on land surface driven by global change (No:2017YFA06036001)

Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.


License: This work is licensed under an Attribution 4.0 International (CC BY 4.0)


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Keywords
Geographic coverage
East: 135.05 West: 73.33
South: 3.51 North: 53.33
Details
  • Temporal resolution: 1 year < x < 10 year
  • Spatial resolution: 100m - 1km
  • File size: 1,960 MB
  • Views: 2518
  • Downloads: 0
  • Access: Protection period
  • Temporal coverage: 2015-2100
  • Updated time: 2022-09-20

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Contacts
: CAI Wenjia    NIE Yaoyu    WANG Rui   

Distributor: A Big Earth Data Platform for Three Poles

Email: poles@itpcas.ac.cn

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