@article{JRC30995,
	address = {Oxford (United Kingdom)},
	year = {2005},
	author = {Kioutsioukis I and Tarantola S and Saltelli A and Gatelli D},
	abstract = {In this paper, we present the results obtained in the framework of a European research project on the Assessment and Reliability of Transport Emission Models and Inventory Systems. As recommended by the European Commission in its Emissions Ceiling Directive, and also in the guidelines of the Inter-Governmental Panel of Climate Change on emissions inventories, atmospheric emission estimates from all sectors (transport, industry, agriculture, etc.) must be accompanied by uncertainty estimations. This has important implications in policy-making. Very little has been done so far, mainly because the characterization of the full chain of uncertainties (from errors in primary data down to model selection and use) is the most difficult step of the analysis.
		We use a methodological approach for the characterisation of the uncertainty in emission estimates which is based on the Monte Carlo method. The sensitivity analysis of the model-based emission estimates is conducted using the so-called Extended FAST, a technique based on the decomposition of the output variance developed at the JRC.
		We illustrate the results of two case studies for Italy, based on CO2, NOX, VOC and PM10 emissions for year 2000 and forecasts for year 2010. 
		
		
		
		
		
		
		
		
		},
	title = {Uncertainty and Global Sensitivity Analysis of Road Transport Emission Estimates},
	type = {},
	url = {},
	volume = {38},
	number = {},
	journal = {ATMOSPHERIC ENVIRONMENT},
	pages = {6609-6620},
	issn = {},
	publisher = {PERGAMON-ELSEVIER SCIENCE LTD},
	doi = {}
}