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Regional spatial inventories (cadastres) of GHG emissions in the Energy sector: Accounting for uncertainty

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  • Khrystyna Boychuk
  • Rostyslav Bun

Abstract

An improvement of methods for the inventory of greenhouse gas (GHG) emissions is necessary to ensure effective control of commitments to emission reduction. The national inventory reports play an important role, but do not reflect specifics of regional processes of GHG emission and absorption for large-area countries. In this article, a GIS approach for the spatial inventory of GHG emissions in the energy sector, based on IPCC guidelines, official statistics on fuel consumption, and digital maps of the region under investigation, is presented. We include mathematical background for the spatial emission inventory of point, line and area sources, caused by fossil-fuel use for power and heat production, the residential sector, industrial and agricultural sectors, and transport. Methods for the spatial estimation of emissions from stationary and mobile sources, taking into account the specifics of fuel used and technological processes, are described. Using the developed GIS technology, the territorial distribution of GHG emissions, at the level of elementary grid cells 2 km × 2 km for the territory of Western Ukraine, is obtained. Results of the spatial analysis are presented in the form of a geo-referenced database of emissions, and visualized as layers of digital maps. Uncertainty of inventory results is calculated using the Monte Carlo approach, and the sensitivity analysis results are described. The results achieved demonstrated that the relative uncertainties of emission estimates, for CO 2 and for total emissions (in CO 2 equivalent), depend largely on uncertainty in the statistical data and on uncertainty in fuels’ calorific values. The uncertainty of total emissions stays almost constant with the change of uncertainty of N 2 O emission coefficients, and correlates strongly with an improvement in knowledge about CH 4 emission processes. The presented approach provides an opportunity to create a spatial cadastre of emissions, and to use this additional knowledge for the analysis and reduction of uncertainty. It enables us to identify territories with the highest emissions, and estimate an influence of uncertainty of the large emission sources on the uncertainty of total emissions. Ascribing emissions to the places where they actually occur helps to improve the inventory process and to reduce the overall uncertainty. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Khrystyna Boychuk & Rostyslav Bun, 2014. "Regional spatial inventories (cadastres) of GHG emissions in the Energy sector: Accounting for uncertainty," Climatic Change, Springer, vol. 124(3), pages 561-574, June.
    • Handle: RePEc:spr:climat:v:124:y:2014:i:3:p:561-574
    DOI: 10.1007/s10584-013-1040-9
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    1. Jörg Verstraete, 2014. "Solving the map overlay problem with a fuzzy approach," Climatic Change, Springer, vol. 124(3), pages 591-604, June.
    2. Tomohiro Oda & Rostyslav Bun & Vitaliy Kinakh & Petro Topylko & Mariia Halushchak & Gregg Marland & Thomas Lauvaux & Matthias Jonas & Shamil Maksyutov & Zbigniew Nahorski & Myroslava Lesiv & Olha Dany, 2019. "Errors and uncertainties in a gridded carbon dioxide emissions inventory," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 1007-1050, August.
    3. Nadiia Charkovska & Joanna Horabik-Pyzel & Rostyslav Bun & Olha Danylo & Zbigniew Nahorski & Matthias Jonas & Xu Xiangyang, 2019. "High-resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 881-905, August.
    4. Nadiia Charkovska & Mariia Halushchak & Rostyslav Bun & Zbigniew Nahorski & Tomohiro Oda & Matthias Jonas & Petro Topylko, 2019. "A high-definition spatially explicit modelling approach for national greenhouse gas emissions from industrial processes: reducing the errors and uncertainties in global emission modelling," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 907-939, August.
    5. Jörg Verstraete, 2019. "Solving the general map overlay problem using a fuzzy inference system designed for spatial disaggregation," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 1101-1122, August.
    6. Rostyslav Bun & Zbigniew Nahorski & Joanna Horabik-Pyzel & Olha Danylo & Linda See & Nadiia Charkovska & Petro Topylko & Mariia Halushchak & Myroslava Lesiv & Mariia Valakh & Vitaliy Kinakh, 2019. "Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 853-880, August.
    7. Mathieu Fortin, 2021. "Comparison of uncertainty quantification techniques for national greenhouse gas inventories," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 26(2), pages 1-20, February.

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