Abstract
The paper aims at analysing errors in the National Inventory Reports, provided annually since 2001 by parties to the UNFCCC. Each said report contains the data on GHG emission from a given year and revisions of past data (back to 1990), recalculated due to improved knowledge and methodology. We consider these revisions the realizations of a non-stationary stochastic process being a sum of two other processes, indexed by time. One of these component processes corresponds to the years, when emission measurements were taken, and involves data gathering errors. The other one corresponds to the years when revisions were made, and involves data processing errors. To disentangle these two we consider the data matrix of realizations up to 2015 and use a bivariate approach to estimate the mean values of the component processes as functions of time. We analyse both types of errors and their changes over time using the mean values estimated. The analysis is conducted for the EU-15 and its individual member countries.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
It takes about two years to compile the data on GHG emissions, so the data for 2015 originate from the year 2017.
- 2.
- 3.
After the EU enlargement by new members, the reports published also include the emissions reported by these countries, but the EU-15 is still described in these reports separately.
References
Hamal, K.: Reporting GHG emissions: Change in uncertainty and its relevance for detection of emission changes, Interim Report IR-10-003. IIASA, Laxenburg (2010)
Jim, P., Kruger, D., Galbally, I., Hiraishi, T., Nyenzi, B., Emmanuel, S., Buendia, L., Hoppaus, R., Martinsen, T., Meijer, J., Miwa, K., Tanabe, K.: Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories. IPCC (2001). http://www.ipcc-nggipigesorjp/public/gp/english/. Accessed 30 Jun 2017
Eggleston, H.S., Buendia, L., Miwa, K., Ngara, T., Tanabe, K. (eds.): National Greenhouse Gas Inventories Programme. IPCC Guidelines for National Greenhouse Gas Inventories. IPCC (2006)
Jarnicka, J., Nahorski, Z.: A method for estimating time evolution of precision and accuracy of greenhouse gases inventories from revised reports. In: Proceedings of 4th Internatioanl Workshop on Uncertainty in Atmospheric Emissions, Kraków, Poland, pp. 97–102 (2015). http://www.ibspan.waw.pl/unws2015/index.php?go=publications
Jarnicka, J., Nahorski, Z.: Estimation of temporal uncertainty structure of GHG inventories for selected EU countries, In: Ganzha M., Maciaszek, L., Paprzycki, M., (eds.) Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, ACSIS, vol. 8, pp. 459-465 (2016a). https://doi.org/10.15439/2016F318
Jarnicka, J., Nahorski, Z.: Learning in national inventory reporting: a bivariate approach. Report RB/28/2016. SRI PAS, Warsaw (2016b, unpublished)
Jarnicka, J., Nahorski, Z.: Estimation of means in a bivariate discrete-time process. In: Atanassov, K.T., et al. (eds.) Uncertainty and Imprecision in Decision Making and Decision Support: Cross Fertilization, New Models and Applications. Advances in Intelligent Systems and Computing, vol. 559, pp. 3–11. Springer (2018). https://doi.org/10.1007/978-3-319-65545-11
Jarnicka, J., Żebrowski, P.: Learning in GHG emission inventories in terms of uncertainty improvement over time. Mitig. Adapt. Strateg. Glob. Change 24(6), 1143–1168 (2019). https://doi.org/10.1007/s11027-019-09866-5
Marland, G., Hamal, K., Jonas, M.: How uncertain are estimates of CO\(_2\) emissions? J. Ind. Ecol. 13(1), 4–7 (2009). https://doi.org/10.1111/j.1530-9290.2009.00108.x
Nahorski, Z., Jarnicka, J.: Modeling uncertainty structure of greenhouse gases inventories. Report RB/11/2010. SRI PAS, Warsaw (2010, unpublished)
Nahorski, Z., Jȩda, W.: Processing national CO\(_2\) inventory emission data and their total uncertainty estimates. Water Air Soil Pollut. Focus 7(4–5), 513–527 (2007). https://doi.org/10.1007/s11267-006-9114-6
Żebrowski, P., Jonas, M., Rovenskaya, E.: Assessing the improvement of greenhouse gases inventories: can we capture diagnostic learning? In: Proceedings of 4th International Workshop on Uncertainty in Atmospheric Emissions, Kraków, Poland, 90–96 (2015). http://www.ibspan.waw.pl/unws2015/index.php?go=publications
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Jarnicka, J., Nahorski, Z. (2021). Bivariate Analysis of Errors in National Inventory Reporting. In: Atanassov, K., et al. Uncertainty and Imprecision in Decision Making and Decision Support: New Challenges, Solutions and Perspectives. IWIFSGN 2018. Advances in Intelligent Systems and Computing, vol 1081. Springer, Cham. https://doi.org/10.1007/978-3-030-47024-1_39
Download citation
DOI: https://doi.org/10.1007/978-3-030-47024-1_39
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-47023-4
Online ISBN: 978-3-030-47024-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)