Tools
Tools
Bun, R., Gusti, M., Kujii, L., Tokar, O., Tsybrivskyy, Y., & Bun, A. (2007). Spatial GHG inventory: analysis of uncertainty sources. A case study for ukraine. In: Accounting for Climate Change. pp. 63-74 Dordrecht, The Netherlands: Springer. ISBN 978-1-4020-5930-8 10.1007/978-1-4020-5930-8_6.
Full text not available from this repository.Abstract
A geoinformation technology for creating spatially distributed greenhouse gas inventories based on a methodology provided by the Intergovernmental Panel on Climate Change and special software linking input data, inventory models, and a means for visualization are proposed. This technology opens up new possibilities for qualitative and quantitative spatially distributed presentations of inventory uncertainty at the regional level. Problems concerning uncertainty and verification of the distributed inventory are discussed. A Monte Carlo analysis of uncertainties in the energy sector at the regional level is performed, and a number of simulations concerning the effectiveness of uncertainty reduction in some regions are carried out. Uncertainties in activity data have a considerable influence on overall inventory uncertainty, for example, the inventory uncertainty in the energy sector declines from 3.2 to 2.0% when the uncertainty of energy-related statistical data on fuels combusted in the energy industries declines from 10 to 5%. Within the energy sector, the ‘energy industries’ subsector has the greatest impact on inventory uncertainty. The relative uncertainty in the energy sector inventory can be reduced from 2.19 to 1.47% if the uncertainty of specific statistical data on fuel consumption decreases from 10 to 5%. The ‘energy industries’ subsector has the greatest influence in the Donetsk oblast. Reducing the uncertainty of statistical data on electricity generation in just three regions — the Donetsk, Dnipropetrovsk, and Luhansk oblasts — from 7.5 to 4.0% results in a decline from 2.6 to 1.6% in the uncertainty in the national energy sector inventory.
| Item Type: | Book Section |
|---|---|
| Uncontrolled Keywords: | energy sector; geoinformation system; greenhouse gas; greenhouse gas inventory; multilevel model; spatial analysis; uncertainty |
| Research Programs: | Forestry (FOR) |
| Depositing User: | Romeo Molina |
| Date Deposited: | 12 May 2016 14:16 |
| Last Modified: | 27 Aug 2021 17:26 |
| URI: | https://pure.iiasa.ac.at/13195 |
Actions (login required)
 |
View Item |