Advertisement

An Outlook on the Biomass Energy Development Out to 2100 in China

  • Zhihui Li
  • Xiangzheng Deng
  • Xi Chu
  • Gui Jin
  • Wei Qi
Article
  • 299 Downloads

Abstract

Biomass energy is critical to future low-carbon economic development facing the challenge to mitigate the high carbon emission from conventional energy exploitation. Biomass energy developed from energy plants will play a more important role in future energy supply in China. As cultivated land resources are limited and critical to food security, the development of energy plants in China should rely on the exploitation of marginal land. In this study, based on three scenario-based (RCP2.6, RCP4.5 and RCP8.5) land cover datasets, the Net Primary Productivity (NPP) dataset, the dataset of marginal land suitable resources for cultivating bioenergy crops, and protected area dataset, firstly, we spatially identify and quantify the available areas of three types of marginal land, including abandoned agricultural land, low-productivity land and the ‘rest land’; then, the geographical potentials of biomass energy are calculated through multiplying the available area for energy plants by the corresponding productivity out to 2100 in China. The results show that significant potentials for biomass production are found in the south of China, such as Yunnan, Sichuan, Guizhou and Guangxi provinces. The total geographical potential biomass energy of the marginal land ranges from 17.813 to \(19.373\,\hbox {EJ}\,\hbox {year}^{-1}\) under the three scenarios, reaching the highest under RCP8.5 scenario, and the geographical potential biomass energy of the ‘rest land’ is the largest contributor, accounting for more than 90% of the total potential biomass production.

Keywords

Potential biomass energy Land use/cover changes Marginal land RCPs China 

Notes

Acknowledgements

This research was supported by the National Key Research and Development Plan of China (Grant No. 2016YFA0602500), China National Natural Science Funds for Distinguished Young Scholar (Grant No. 71225005) and Key Projects in the National Science & Technology Pillar Program (Grant No. 2013BAC03B03). The data support was provided by the Resources and Environment Model and System Simulation Research Team in the Institute of Geographic Sciences and Natural Resources Research (REMSSRT/IGSNRR).

Compliance with Ethical Standards

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

References

  1. Bartholomé, E., & Belward, A. (2005). GLC2000: A new approach to global land cover mapping from Earth observation data. International Journal of Remote Sensing, 26(9), 1959–1977.CrossRefGoogle Scholar
  2. Cai, X., Zhang, X., & Wang, D. (2010). Land availability for biofuel production. Environmental Science and Technology, 45(1), 334–339.CrossRefGoogle Scholar
  3. Campbell, J. E., Lobell, D. B., Genova, R. C., & Field, C. B. (2008). The global potential of bioenergy on abandoned agriculture lands. Environmental Science and Technology, 42(15), 5791–5794.CrossRefGoogle Scholar
  4. Chen, S., & Chen, B. (2015). Life cycle assessment of biogas systems, Handbook of clean energy systems. New York: Wiley.Google Scholar
  5. Chen, Z., Chen, G., & Chen, B. (2013). Embodied carbon dioxide emission by the globalized economy: A systems ecological input–output simulation. Journal of Environmental Informatics, 21(1), 35–44.CrossRefGoogle Scholar
  6. Chong-Hai, X., & Ying, X. (2012). The projection of temperature and precipitation over China under RCP scenarios using a CMIP5 multi-model ensemble. Atmospheric and Oceanic Science Letters, 5(6), 527–533.Google Scholar
  7. Demirbas, M. F., Balat, M., & Balat, H. (2009). Potential contribution of biomass to the sustainable energy development. Energy Conversion and Management, 50(7), 1746–1760.CrossRefGoogle Scholar
  8. Dornburg, V., Faaij, A., Verweij, P., Langeveld, H., van de Ven, G., Wester, F., et al. (2008). Biomass assessment: Assessment of global biomass potentials and their links to food, water, biodiversity, energy demand and economy: Main report. Report/WAB(500102 012)Google Scholar
  9. Drigo, R. (2007). Woodenergy supply/demand scenarios in the context of poverty mapping. A WISDOM case study in Southeast Asia for the years 2000 and 2015. Rome: Food & Agriculture Org.Google Scholar
  10. Fan, Z., Li, J., Yue, T., Zhou, X., & Lan, A. (2015). Scenarios of land cover in Karst area of Southwestern China. Environmental Earth Sciences, 74(8), 6407–6420.CrossRefGoogle Scholar
  11. Fan, Z. M., Yue, T. X., Liu, J. Y., & Ma, S. N. (2005). Spatial and temporal distribution of land cover scenarios in China. Acta Geographica Sinica, 60(6), 941–952 (in Chinese).Google Scholar
  12. Feng, K., Siu, Y. L., Guan, D., & Hubacek, K. (2012). Analyzing drivers of regional carbon dioxide emissions for China. Journal of Industrial Ecology, 16(4), 600–611.CrossRefGoogle Scholar
  13. Field, C. B., Campbell, J. E., & Lobell, D. B. (2008). Biomass energy: The scale of the potential resource. Trends in Ecology and Evolution, 23(2), 65–72.CrossRefGoogle Scholar
  14. Fischer, G., Prieler, S., van Velthuizen, H., Berndes, G., Faaij, A., Londo, M., et al. (2010). Biofuel production potentials in Europe: Sustainable use of cultivated land and pastures, Part II: Land use scenarios. Biomass and Bioenergy, 34(2), 173–187.CrossRefGoogle Scholar
  15. Fischer, G., & Schrattenholzer, L. (2001). Global bioenergy potentials through 2050. Biomass and Bioenergy, 20(3), 151–159.CrossRefGoogle Scholar
  16. Fu, J., Jiang, D., Huang, Y., Zhuang, D., & Ji, W. (2014). Evaluating the marginal land resources suitable for developing bioenergy in Asia. Advances in Meteorology, 2014, 9. doi: 10.1155/2014/238945.CrossRefGoogle Scholar
  17. Gibbs, H. K., Brown, S., Niles, J. O., & Foley, J. A. (2007). Monitoring and estimating tropical forest carbon stocks: making REDD a reality. Environmental Research Letters, 2(4), 045023.CrossRefGoogle Scholar
  18. Hall, D. O., Rosillo-Calle, F., Williams, R. H., & Woods, J. (1993). Biomass for energy: Supply prospects. London: Earthscan.Google Scholar
  19. Hoogwijk, M., Faaij, A., de Vries, B., & Turkenburg, W. (2009). Exploration of regional and global cost-supply curves of biomass energy from short-rotation crops at abandoned cropland and rest land under four IPCC SRES land-use scenarios. Biomass and Bioenergy, 33(1), 26–43. doi: 10.1016/j.biombioe.2008.04.005.CrossRefGoogle Scholar
  20. Hoogwijk, M., Faaij, A., Eickhout, B., de Vries, B., & Turkenburg, W. (2005). Potential of biomass energy out to 2100, for four IPCC SRES land-use scenarios. Biomass and Bioenergy, 29(4), 225–257. doi: 10.1016/j.biombioe.2005.05.002.CrossRefGoogle Scholar
  21. Hoogwijk, M., Faaij, A., van den Broek, R., Berndes, G., Gielen, D., & Turkenburg, W. (2003). Exploration of the ranges of the global potential of biomass for energy. Biomass and Bioenergy, 25(2), 119–133. doi: 10.1016/s0961-9534(02)00191-5.CrossRefGoogle Scholar
  22. Hui, D., & Jackson, R. B. (2006). Geographical and interannual variability in biomass partitioning in grassland ecosystems: A synthesis of field data. New Phytologist, 169(1), 85–93.CrossRefGoogle Scholar
  23. Jiang, D., Hao, M., Fu, J., Zhuang, D., & Huang, Y. (2014). Spatial–temporal variation of marginal land suitable for energy plants from 1990 to 2010 in China. Scientific Reports, 4, 5816.Google Scholar
  24. Kajimoto, T., Matsuura, Y., Sofronov, M., Volokitina, A., Mori, S., Osawa, A., et al. (1999). Above-and belowground biomass and net primary productivity of a Larix gmelinii stand near Tura, central Siberia. Tree Physiology, 19(12), 815–822.CrossRefGoogle Scholar
  25. Kanazawa, Y., Osawa, A., Ivanov, B., & Maximov, T. (1993). Biomass of a Larix gmelinii (RUPR.) LITV. stand in Spaskayapad, Yakutsk. In Proceedings of the second symposium on the joint Siberian permafrost studies between Japan and Russia in (pp. 153–158).Google Scholar
  26. Kou, J. P., Bi, Y. Y., Zhao, L. X., Gao, C. Y., Tian, Y. S., Wei, S. Y., et al. (2008). Investigation and evaluation on wasteland for energy crops in China. Renewable Energy Resources, 26(6), 3–9 (in Chinese).Google Scholar
  27. Li, J., Fan, Z. M., & Yue, T. X. (2014). Spatio-temporal simulation of land cover scenarios in southwersern of China. Acta Ecologica Sinica, 34(12), 3266–3275 (in Chinese).Google Scholar
  28. Lin, T., Yu, Y., Bai, X., Feng, L., & Wang, J. (2013). Greenhouse gas emissions accounting of urban residential consumption: A household survey based approach. PloS ONE, 8(2), e55642.CrossRefGoogle Scholar
  29. Litton, C. M., Ryan, M. G., Tinker, D. B., & Knight, D. H. (2003). Belowground and aboveground biomass in young postfire lodgepole pine forests of contrasting tree density. Canadian Journal of Forest Research, 33(2), 351–363.CrossRefGoogle Scholar
  30. Liu, Z., Guan, D., Wei, W., Davis, S. J., Ciais, P., Bai, J., et al. (2015). Reduced carbon emission estimates from fossil fuel combustion and cement production in China. Nature, 524(7565), 335–338.CrossRefGoogle Scholar
  31. Luo, Y., Wang, X., Zhang, X., Ren, Y., & Poorter, H. (2013). Variation in biomass expansion factors for China’s forests in relation to forest type, climate, and stand development. Annals of Forest Science, 70(6), 589–599.CrossRefGoogle Scholar
  32. Metz, B., Davidson, O. R., Bosch, P. R., Dave, R., & Meyer, L. A. (2007). Climate change 2007: Mitigation: Contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change. Geneva: Intergovernmental Panel on Climate Change.Google Scholar
  33. Mooney, H., & Chiariello, N. (1984). Study of plant function—The plant as a balanced system. In R. Dirzo, & J. Sarukhan (Eds.), Perspectives on plant population ecology. Sinauer Associates Inc.Google Scholar
  34. Moreira, R. (2006). Global biomass energy potential. Mitigation and Adaptation Strategies for Global Change, 11(2), 313–333.CrossRefGoogle Scholar
  35. Morhart, C., Sheppard, J. P., Schuler, J. K., & Spiecker, H. (2016). Above-ground woody biomass allocation and within tree carbon and nutrient distribution of wild cherry (Prunus avium L.)—a case study. Forest Ecosystems, 3(1), 1.CrossRefGoogle Scholar
  36. Offermann, R., Seidenberger, T., Thran, D., Kaltschmitt, M., Zinoviev, S., & Miertus, S. (2011). Assessment of global bioenergy potentials. Mitigation and Adaptation Strategies for Global Change, 16(1), 103–115. doi: 10.1007/s11027-010-9247-9.CrossRefGoogle Scholar
  37. Openshaw, K., Mastorakis, N., & Corbi, I. (2015). Energy values of unprocessed biomass, charcoal and other biomass fuels and their role in greenhouse gas mitigation and energy use. Advances in Environmental Science and Energy Planning, 30–40Google Scholar
  38. Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., et al. (2011). RCP 8.5—A scenario of comparatively high greenhouse gas emissions. Climatic Change, 109(1–2), 33–57.CrossRefGoogle Scholar
  39. Saha, M., & Eckelman, M. J. (2015). Geospatial assessment of potential bioenergy crop production on urban marginal land. Applied Energy, 159, 540–547.CrossRefGoogle Scholar
  40. Schlesinger, W. H. (1991). Biogeochemistry, an analysis of global change. New York: Academic Press.Google Scholar
  41. Shi, Y. (2011). China’s resources of biomass feedstock. Engineering Sciences, 13(2), 16–23 (in Chinese).Google Scholar
  42. Smeets, E. M., & Faaij, A. P. (2007). Bioenergy potentials from forestry in 2050. Climatic Change, 81(3–4), 353–390.CrossRefGoogle Scholar
  43. Smil, V. (1999). Crop residues: Agriculture’s largest harvest crop residues incorporate more than half of the world’s agricultural phytomass. Bioscience, 49(4), 299–308.CrossRefGoogle Scholar
  44. Song, M., Wang, S., Yu, H., Yang, L., & Wu, J. (2011). To reduce energy consumption and to maintain rapid economic growth: Analysis of the condition in China based on expended IPAT model. Renewable and Sustainable Energy Reviews, 15(9), 5129–5134.CrossRefGoogle Scholar
  45. Tang, Y., Xie, J. S., & Geng, S. (2010). Marginal land-based biomass energy production in China. Journal of Integrative Plant Biology, 52(1), 112–121.CrossRefGoogle Scholar
  46. Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012). An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93(4), 485–498.CrossRefGoogle Scholar
  47. Thomas, S. C., & Martin, A. R. (2012). Carbon content of tree tissues: A synthesis. Forests, 3(2), 332–352.CrossRefGoogle Scholar
  48. Thomson, A. M., Calvin, K. V., Smith, S. J., Kyle, G. P., Volke, A., Patel, P., et al. (2011). RCP4. 5: A pathway for stabilization of radiative forcing by 2100. Climatic Change, 109(1–2), 77–94.CrossRefGoogle Scholar
  49. Turley, D., Taylor, M., Laybourn, R., Hughes, J., Kilpatrick, J., Procter, C., et al. (2010). Assessment of the availability of ‘marginal’and ‘idle’land for bioenergy crop production in England and Wales. DEFRA, NF0444, London, 86. Available at http://randd.defra.gov.uk/Document.aspx?Document=NF0444_9473_FRP.pdf. Accessed 30 Mar 2016.
  50. Van Vuuren, D. P., Stehfest, E., den Elzen, M. G., Kram, T., van Vliet, J., Deetman, S., et al. (2011). RCP2. 6: Exploring the possibility to keep global mean temperature increase below 2 C. Climatic Change, 109(1–2), 95–116.CrossRefGoogle Scholar
  51. Wang, Z.-X. (2015). A predictive analysis of clean energy consumption, economic growth and environmental regulation in China using an optimized grey dynamic model. Computational Economics, 46(3), 437–453.CrossRefGoogle Scholar
  52. Williams, K., Percival, F., Merino, J., & Mooney, H. (1987). Estimation of tissue construction cost from heat of combustion and organic nitrogen content. Plant, Cell and Environment, 10(9), 725–734.Google Scholar
  53. Williams, R. (1995). Variants of a low \(\text{CO}_{2}\) -emitting energy supply system (LESS) for the world-prepared for the IPCC second assessment report working group IIa. Pacific Northwest Laboratories (p. 39).Google Scholar
  54. Wolf, J., Bindraban, P., Luijten, J., & Vleeshouwers, L. (2003). Exploratory study on the land area required for global food supply and the potential global production of bioenergy. Agricultural Systems, 76(3), 841–861.CrossRefGoogle Scholar
  55. Xie, G., Liu, Q., Duan, Z., & Zhang, B. (2015). Review on resource of non-food land suitable for energy plant production in China. Journal of China Agricultural University, 20(2), 1–10 (in Chinese).Google Scholar
  56. Yamamoto, H., Fujino, J., & Yamaji, K. (2001). Evaluation of bioenergy potential with a multi-regional global-land-use-and-energy model. Biomass and Bioenergy, 21(3), 185–203.CrossRefGoogle Scholar
  57. Yan, L., Zhang, L., Wang, S., & Hu, L. (2008). Potential yield of bioethanol from energy crops and their regional distribution in China. Transactions of the Chinese Society of Agricultural Engineering, 24(5), 213–216 (in Chinese).Google Scholar
  58. Yue, T. X. (2010). Surface modeling: High Accuracy and high speed methods. Boca Raton: CRC Press.Google Scholar
  59. Yue, T. X., Fan, Z. M., & Liu, J. Y. (2005). Changes of major terrestrial ecosystems in China since 1960. Global and Planetary Change, 48(4), 287–302. doi: 10.1016/j.gloplacha.2005.03.001.CrossRefGoogle Scholar
  60. Yue, T. X., Fan, Z. M., & Liu, J. Y. (2007). Scenarios of land cover in China. Global and Planetary Change, 55(4), 317–342. doi: 10.1016/j.gloplacha.2006.10.002.CrossRefGoogle Scholar
  61. Yue, T. X., Fan, Z. M., Liu, J. Y., & Wei, B. X. (2006). Scenarios of major terrestrial ecosystems in China. Ecological Modelling, 199(3), 363–376. doi: 10.1016/j.ecolmodel.2006.05.026.CrossRefGoogle Scholar
  62. Yue, T. X., Zhao, N., Ramsey, R. D., Wang, C. L., Fan, Z. M., Fa, C. C., et al. (2013a). Climate change trend in China, with improved accuracy. Climatic Change, 120, 137–151.CrossRefGoogle Scholar
  63. Yue, T. X., Zhao, N., Yang, H., Song, Y. J., Du, Z. P., Fan, Z. M., et al. (2013b). A multi-grid method of high accuracy surface modeling and its validation. Transactions in GIS, 17(6), 943–952.CrossRefGoogle Scholar
  64. Zhang, Q., Ma, J., Qiu, G., Li, L., Geng, S., Hasi, E., et al. (2012). Potential energy production from algae on marginal land in China. Bioresource Technology, 109, 252–260.CrossRefGoogle Scholar
  65. Zhao, N., & Yue, T. X. (2014). A modification of HASM for interpolating precipitation in China. Theoretical and Applied Climatology, 116, 273–285.CrossRefGoogle Scholar
  66. Zhou, X., Xiao, B., Ochieng, R. M., & Yang, J. (2009). Utilization of carbon-negative biofuels from low-input high-diversity grassland biomass for energy in China. Renewable and Sustainable Energy Reviews, 13(2), 479–485.CrossRefGoogle Scholar
  67. Zhuang, D., Jiang, D., Liu, L., & Huang, Y. (2011). Assessment of bioenergy potential on marginal land in China. Renewable and Sustainable Energy Reviews, 15(2), 1050–1056.CrossRefGoogle Scholar
  68. Zomer, R. J., Neufeldt, H., Xu, J., Ahrends, A., Bossio, D., Trabucco, A., et al. (2016). Global tree cover and biomass carbon on agricultural land: The contribution of agroforestry to global and national carbon budgets. Scientific Reports, 6, 29987.Google Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Zhihui Li
    • 1
    • 2
    • 3
  • Xiangzheng Deng
    • 1
    • 3
  • Xi Chu
    • 4
  • Gui Jin
    • 4
  • Wei Qi
    • 1
    • 3
  1. 1.Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Center for Chinese Agricultural PolicyChinese Academy of SciencesBeijingChina
  4. 4.Faculty of Resources and Environmental ScienceHubei UniversityWuhanChina

Personalised recommendations