Uncertainty evaluation in air quality planning decisions: a case study for Northern Italy |
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| Affiliation: | 1. University of Brescia, Italy;2. Aristotle University Thessaloniki, Greece;3. Umweltbundesamt, Germany;4. Politecnico di Milano, Italy;5. Instytut Badań Systemowych PAN, Poland;6. European Commission, JRC, Institute for Environment and Sustainability, Air and Climate Unit, Italy;7. University of Strasburg, France;8. Institut National de l’EnviRonnement Industriel et des RisqueS, INERIS, France;1. Department of Economic and Legal Studies – University of Naples “Parthenope”, Via Ammiraglio Ferdinando Acton, 38, 80133 Naples, Italy;2. Department of Philosophical, Pedagogical and Economic-Quantitative Sciences. University “G. D’Annunzio” of Chieti-Pescara. Viale Pindaro, 42, 65127 Pescara, Italy;3. Department of Philosophical, Pedagogical and Economic-Quantitative Sciences. University “G. D’Annunzio” of Chieti-Pescara, Viale Pindaro, 42, 65127 Pescara, Italy;1. Department of Environmental Sciences, Vytautas Magnus University, Vileikos st. 8, 44404 Kaunas, Lithuania;2. Departament of Drug Technology and Social Pharmacy, Lithuanian University of Health Sciences, Eiveniu str. 4, 50009 Kaunas, Lithuania;3. Baltic Institute of Advanced Technology, Sauletekio av. 15, 10224 Vilnius, Lithuania;1. Federal University of Campina Grande and CAPES, R. Aprigio Veloso, 882, B. Universitario, Campina Grande/PB, CEP: 58.429-900, Brazil;2. Salamanca University, Campus Miguel de Unamuno. Edificio FES, Av. Francisco Tomás y Valiente, s/n. 37007, Salamanca, Spain |
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| Abstract: | In recent years, evaluating the robustness of environmental models results has become essential in order to effectively support decision makers to define suitable emission control strategies. This evaluation is performed in literature through uncertainty and sensitivity analyses. Therefore, the application of such methodologies to air quality Integrated Assessment Models (IAMs) is extremely challenging. In fact, in this case uncertainty and sensitivity analyses should be assessed not only for each single component of the system, but also for the overall IAM. In the paper, an attempt is made to extend and systematize the information available on uncertainty/sensitivity analysis, at first considering environmental models in general, and then focusing on air quality IAMs. The study aims to offer a tentative framework addressed to modelers and decision makers in the implementation of IAM and evaluation of its results. The framework has been tested on Lombardy region (Northern Italy). The results show how the uncertainty on Drivers of emissions propagates on the whole modelling chain characterizing an integrated assessment study. |
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| Keywords: | Integrated assessment models Uncertainty analysis Sensitivity Analysis Air quality |
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