Abstract
Emission inventories are compiled at regional level. When these sources of information are used, uncertainty of emission estimates is never considered. In this paper, we propose an initial screening to identify whether and to what extent uncertainty related to emission inventories affects quantitative analysis used to set strategies and implement actions at regional and subregional levels. We consider the regional air emission inventory of the Piedmont region in Italy. For each pollutant and each sector, uncertainty is calculated by adapting the insurance-based method. A hybrid accounting matrix is built, three environmental themes are analyzed, and a shift-share analysis is undertaken considering jointly air emission estimates and the number of employees at regional and provincial levels. The same procedure is undertaken for data processed with and without uncertainty. Based on the obtained outcomes, few comments are drawn in order to reach some general conclusion to feed discussion on the importance of integrating and prioritizing uncertainty into decision-making at subnational level.
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Notes
The CORe INventory AIR emissions (CORINAIR) method is the framework supported by the European Environment Agency. It was adopted by all protection agencies in compiling the national inventory. (EMEP refers to the European Monitoring and Evaluation Programme.)
The formula reported by Eurostat (2015) considers SOx with a different coefficient. Because the emission inventory records SO2, we decided to use the ISTAT coefficient.
An economic territory consists of all the institutional units that are resident in that territory. The residence principle assigns each economic unit to the territory with which the unit has the strongest link, i.e., its predominant center of economic interest. Adopting a residence principle for corporations, for example, means considering the corporation a resident of the territory in which it was created.
References
Charkovska N, Halushchak M, Bun R, Jonas M (2015) Uncertainty analysis of GHG spatial inventory from the industrial activity: a case study for Poland. In: Proceedings of the 4th International Workshop on Uncertainty in Atmospheric Emissions. Kraków, Poland. 7–9 October 2015
Charkovska N, Bun R, Danylo O, Horabik-Pyzel J, Jonas M (2018) High resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector. (This issue)
Dalmazzone S, La Notte A (2013) Multi-scale environmental accounting: methodological lessons from the application of NAMEA at sub-national levels. J Environ Manag 130:405–416
De Boo A, Bosch P, Gorter CN, Keuning SJ (1993) An environmental module and the complete system of national accounts. In: Franz A, Stahmer C (eds) Approaches to environmental accounting. Physica, Heidelberg
De Haan M, Keuning SJ (1996) Taking the environment into account: the NAMEA approach. Rev Income Wealth 42:131–148
Esteban J (2000) Regional convergence in Europe and the industry mix: a shift-share analysis. Reg Sci Urban Econ 30(3):353–364
European Environment Agency (2013) EMEP/EEA air pollutant emission inventory guidebook 2013. Technical guidance to prepare national emission inventories 23 pp https://www eea europa eu/publications/emep-eea-guidebook-2013 Cited 8 February 2018
European Environment Agency (2016) EMEP/EEA air pollutant emission inventory guidebook 2016. Technical guidance to prepare national emission inventories Technical report 9/2009 24 pp https://wwweeaeuropaeu/publications/emep-eea-guidebook-2016 Cited 8 February 2018
Eurostat (2015) Manual for air emissions accounts 2015 edition. Luxembourg: http://ec.europa.eu/eurostat/documents/3859598/7077248/KS-GQ-15-009-EN-N.pdf/ce75a7d2-4f3a-4f04-a4b1-747a6614eeb3. Cited 8 February 2018
Gillenwater M, Sussman F, Cohen J (2007) Practical policy applications of uncertainty analysis for national greenhouse gas inventories. Water Air Soil Pollut Focus 7(4–5):451–474
Halushchak M, Bun R, Jonas M, Topylko P (2015) Spatial inventory of GHG emissions from fossil fuels extraction and processing: an uncertainty analysis. In: Proceedings of the 4th International Workshop on Uncertainty in Atmospheric Emissions. Kraków, Poland. 7–9 October 2015
IPCC—Intergovernmental Panel on Climate Change (2006) IPCC guidelines for national greenhouse gas inventories. Volume 1: general guidance and reporting. IPCC, Geneva
ISTAT (2009) Contabilità Ambientale e Pressioni sull’Ambiente Naturale: dagli schemi alle realizzazioni. Annali di Statistica 138(XI). Vol 2
Jonas M, Nilsson S (2007) Prior to economic treatment of emissions and their uncertainties under the Kyoto Protocol: scientific uncertainties that must be kept in mind. Water Air Soil Pollut Focus 7(4–5):495–511
Jonas M, Gusti M, Jęda W, Nahorski Z, Nilsson S (2010) Comparison of preparatory signal analysis techniques for consideration in the (post-) Kyoto policy process. Clim Chang 103(1–2):175–213
Keuning SJ (1993) An information system for environmental indicators in relation to the national accounts. In: de Vries WFM, den Bakker GP, Gircour MBG, Keuning SJ, Lenson A (eds) The value added of national accounting statistics in the Netherlands. Voorburg, Heerlen, pp 287–305
La Notte A, Dalmazzone S (2012) Feasibility and uses of the NAMEA-type framework applied at local scale: case studies in North-Western Italy. In: Costantini V, Mazzanti M, Montini A (eds) Hybrid economic-environmental accounts. Routledge studies in ecological economics. Taylor & Francis Group, London
La Notte A, Tonin S, Nocera S (2015) How uncertainty of air emission inventories impacts policy decisions at sub-national level. A shift-share analysis undertaken in Piedmont (Italy). In: Proceedings of the 4th International Workshop on Uncertainty in Atmospheric Emissions. Kraków Poland, 7–9. October 2015
La Notte A, Tonin S, Lucaroni G (2018) Assessing direct and indirect emissions of greenhouse gases in road transportation, taking into account the role of uncertainty in the emissions inventory. Environ Impact Assess Rev 69:82–93
Leontief W (1970) Environmental repercussions and the economic structure: an input-output analysis. Rev Econ Stat 52:262–271
Lieberman D, Jonas M, Nahorski Z, Nilsson S (eds) (2007) Accounting for climate change uncertainty in greenhouse gas inventories—verification, compliance and trading. Springer, Netherlands
Marland E, Cantrell J, Kiser K, Marland G, Shirley K (2014) Valuing uncertainty part I: the impact of uncertainty in GHG accounting. Carbon Manag 5(1):35–42
Mazzanti M, Montini A, Zoboli R (2007) Territorial productive structure and environmental efficiency indicators through regional NAMEA data. Economia delle fonti di energia e dell'ambiente 1:1–31
Nocera S, Tonin S, Cavallaro F (2015) Carbon estimation and urban mobility plans: opportunities in a context of austerity. Res Transp Econ 51:71–82
Tonin S, La Notte A, Nocera S (2016) A use-chain model to deal with uncertainties. A focus on GHG emission inventories. Carbon Manag 7(5–6):347–359
Topylko P, Halushchak M, Bun R, Oda T, Lesiv M, Danylo O (2015) Spatial greenhouse gas inventory and uncertainty analysis: a case study of electricity generation and fossil fuels processing. In: Proceedings of the 4th International Workshop on Uncertainty in Atmospheric Emissions. Kraków, Poland. 7–9 October 2015
White T, Jonas M, Nahorski Z, Nilsson S (eds) (2011) Greenhouse gas inventories: dealing with uncertainty. Springer Netherlands, Dordrecht
Acknowledgements
We thank the editors and three anonymous reviewers for their constructive comments, which helped us to improve the manuscript.
We thank Gianluigi Truffo (Regione Piemonte Direzione Ambiente, Sistema Informativo Ambientale) for providing the air emission data of the Piedmont Region and for his technical support.
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While undertaking this research Alessandra La Notte was a research fellow at IUAV. Alessandra La Notte’s current position is at the European Commission Joint Research Centre - Directorate D: Sustainable Resources.
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La Notte, A., Tonin, S. & Nocera, S. A screening procedure to measure the effect of uncertainty in air emission estimates. Mitig Adapt Strateg Glob Change 24, 1073–1100 (2019). https://doi.org/10.1007/s11027-018-9798-8
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DOI: https://doi.org/10.1007/s11027-018-9798-8