Space monitoring of balance of greenhouse gases to clarify their inventory
Heading:
| 1Lyalko, VI, 1Sakhatsky, AI, 1Kostyuchenko, Yu.V, 2Artemenko, IG, 1Zholobak, GM, 1Levchik, EI, 3Movchan, DM 1State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine», Kyiv, Ukraine 2State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Science of the National Academy of Sciences of Ukraine», Kyiv, Ukraine 3State institution «Scientific Centre for Aerospace Research of the Earth” of the Institute of Geological Science of the National Academy of Sciences of Ukraine, Kyiv, Ukraine |
| Kosm. nauka tehnol. 2012, 18 ;(2):03-14 |
| https://doi.org/10.15407/knit2012.02.003 |
| Publication Language: Ukrainian |
Abstract: In Ukraine, during 2006—2011, the scientists from the Scientific Centre for Aerospace Research of the Earth of the IGS of the NAS of Ukraine have been elaborating a method for the monitoring of the balance of the greenhouse gases to clarify the amount of their emission and absorption using satellite data. The proposed methods allow one to carry out an independent monitoring of the balance of carbon dioxide in the atmosphere on the basis of information from different satellites. According to expert estimates the CO2 component is over 75 % of the total greenhouse gas emissions within the territory of Ukraine. We propose to use satellite data for the estimation of the balance of natural and anthropogenic emissions of carbon dioxide and its absorption by vegetation photosynthetic activity of large areas and for the monitoring of the CO2 content in the atmosphere in different landscapes of various climatic zones and territorial units of Ukraine
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| Keywords: anthropogenic emissions, carbon dioxide, greenhouse gases |
References:
1. Bun R.A., Gusti M.I., Dachuk V.S. et al. Information technology of industry inventories of the greenhouse gases and prediction of the carbon balance of Ukraine, Ed.by R.A. Bun, 376 p. (Ukr. akademija drukarstva, Lviv, 2004) [in Ukrainian].
2. Voronin P.Yu. Chlorophyll index and photosynthetic carbon sequestration in Northern Eurasia, Fiziologija rastenij, 53 (5), 777—785 (2006) [in Russian].
3. Larher V. Plant Ecology, 384 p. (Mir, Moscow, 1978) [in Russian].
4. Lyalko V.I., Artemenko I.G., Zholobak G.M., et al. Research of the CO2 and CH4 change effect into atmosphere on the climate from satellite imaging data, Geological journal, No. 4, 7—16 (2007) [in Ukrainian].
5. Rudenko L. G., Chabanjuk V. S. Bochkovs'ka A. I. et al. Atlas Ukraine: Intelligent GEO Systems. (1999—2000) [in Ukrainian].
6. Barton C. V. M., North P. R. J. Remote sensing of canopy light use efficiency using the photochemical reflectance index. Model and sensitivity analysis, Remote Sens. Environ., 78, 264—273 (2001).
https://doi.org/10.1016/S0034-4257(01)00224-3
https://doi.org/10.1016/S0034-4257(01)00224-3
7. Buchwitz M., de Beek R., Noël S., et al. Atmospheric carbon gases retrieved from SCIAMACHY by WFM-DOAS: version 0.5 CO and CH4 and impact of calibration improvements on CO2 retrieval, Atmospheric Chemistry and Physics, 6, 2727—2751 (2006).
https://doi.org/10.5194/acp-6-2727-2006
https://doi.org/10.5194/acp-6-2727-2006
8. Drolet G. G., Huemmrich K. F. A MODIS-derived photochemical reflectance index to detect inter-annual variations in the photosynthetic light-use efficiency of a boreal deciduous forest, Remote Sens. Environ., 98, 212—224 (2005).
https://doi.org/10.1016/j.rse.2005.07.006
https://doi.org/10.1016/j.rse.2005.07.006
9. Gamon J. A., Huemmrich K. F., Peddle D. R., et al. Remote sensing in BOREAS: Lessons learned, Remote Sens. Environ., 89, 139—162 (2004).
https://doi.org/10.1016/j.rse.2003.08.017
https://doi.org/10.1016/j.rse.2003.08.017
10. Penuelas J., Filella I., Gamon J. A. Assessment of photosynthetic radiation-use efficiency with spectral reflectance, New Phytologist, 131, 291—296 (1995).
https://doi.org/10.1111/j.1469-8137.1995.tb03064.x
https://doi.org/10.1111/j.1469-8137.1995.tb03064.x
11. Rahman A. F., Gamon J. A., Fuentes D. A., et al. Modeling CO2 flux of boreal forests using narrow-band indices from AVIRIS imagery, AVIRIS Workshop, JPL/NASA, (Pasadena, California, 2000).
12. Rahman A. F., Gamon J. A., Fuentes D. A., et al. Modeling spatially distributed ecosystem flux of boreal forest using hyperspectral indices from AVIRIS imagery, J. Geophys. Res., 106D (24), P. 33,579—33,591 (2001).
https://doi.org/10.1029/2001JD900157
https://doi.org/10.1029/2001JD900157
13. Ruimy A., Kergoat L., Bondeau A. Comparing global models of terrestrial net primary productivity (NPP): Analysis of differences in light absorption and light-use efficiency, Global Change Biology, 5, 56—64 (1999).
https://doi.org/10.1046/j.1365-2486.1999.00007.x
https://doi.org/10.1046/j.1365-2486.1999.00007.x
14. User’s Guide GPP and NPP (MOD17A2/A3) Products. Version 2.0 –MODIS Land Team, 57 p. (2003).