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The aim of this study is related to the assessment of odour emissions from landfill surfaces. Up to now, there is not a widely accepted method to quantify odour emissions from this particular kind of source. Five different methods were developed and investigated. These methods can be considered as based on three distinct approaches, both experimental and computational. The first approach provides to use models for the estimation the landfill gas production, whereby the second and the third approach are based on direct measurement campaigns on the landfill surface: for the determination of the methane concentration or for the direct measurement of the odour concentration, respectively. The methods were then compared in terms of specific odour emission rates by referring to other literature data. Finally, dispersion modelling was applied in order to allow a further comparison of the resulting odour impacts with other olfactometric data from independent monitoring campaigns on the studied site., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The work focuses on the principles for the design of a specific static hood and on the definition of an optimal sampling procedure for the assessment of landfill gas (LFG) surface emissions. This is carried out by means of computational fluid dynamics (CFD) simulations to investigate the fluid dynamics conditions of the hood. The study proves that understanding the fluid dynamic conditions is fundamental in order to understand the sampling results and correctly interpret the measured concentration values by relating them to a suitable LFG emission model, and therefore to estimate emission rates. For this reason, CFD is a useful tool for the design and evaluation of sampling systems, among others, to verify the fundamental hypotheses on which the mass balance for the sampling hood is defined. The procedure here discussed, which is specific for the case of the investigated landfill, can be generalized to be applied also to different scenarios, where hood sampling is involved., (Copyright © 2016 Elsevier Ltd. All rights reserved.)