an official journal of: published by:
Editor in Chief: RAFFAELLO COSSU


  • Francesca Tagliaferri - Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” , Politecnico di Milano , Italy
  • Marzio Invernizzi - Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” , Politecnico di Milano , Italy
  • Selena Sironi - Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” , Politecnico di Milano , Italy
  • Laura Capelli - Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” , Politecnico di Milano , Italy

DOI 10.31025/2611-4135/2020.13998

Released under CC BY-NC-ND

Copyright: © 2019 CISA Publisher

Editorial History

  • Received: 27 Nov 2019
  • Revised: 24 Mar 2020
  • Accepted: 25 Mar 2020
  • Available online: 26 Jul 2020


Landfills are an important source of odour pollution, potentially causing nuisance to adjacent populations. The most commonly used odour impact assessment for this type of plants usually involves a combination of dynamic olfactometry with dispersion modelling. Despite the advantages associated with the use of dispersion models, there are still some important issues related to their uncertainty. The dispersion model requires the Odour Emission Rate (OER) as input, expressed as units of odour emitted per unit time. Source term characterization and the estimation of the OER are typically the most important steps in the model’s implementation, accounting for the highest contribution to the overall uncertainty. Another important element of uncertainty when modelling emissions from landfill surfaces is the geometrical implementation of the emission source in the dispersion model. This entails the definition of the initial dimensions of the emission, which is critical in the case of large area sources. This paper discusses issues related to uncertainty in the use of dispersion models for the evaluation of landfill odour impacts, particularly focusing on the estimation of the OER and the emission’s initial vertical dimension. This study shows that modelling choices may lead to a variance in the resulting modelled odour concentrations at receptors differing by up to a factor 3. This variability should not cause distrust in the method, but rather indicates the importance of having odour dispersion modelling studies carried out by experts with deep knowledge of the physical-chemical mechanisms underlying atmospheric emissions.



Brancher, M., Griffiths, K. D., Franco, D., & de Melo Lisboa, H., 2017. A review of odour impact criteria in selected countries around the world. Chemosphere 168, 1531-1570.
DOI 10.1016/j.chemosphere.2016.11.160

Brancher, M., Piringer, M., Grauer, A. F., & Schauberger, G., 2019. Do odour impact criteria of different jurisdictions ensure analogous separation distances for an equivalent level of protection?. J. Environ. Manage. 240, 394-403.
DOI 10.1016/j.jenvman.2019.03.102

Capelli, L., Sironi, S., Del Rosso, R., Bianchi, G., & Davoli, E., 2012. Olfactory and toxic impact of industrial odour emissions. Water Sci. Technol. 66(7), 1399-1406.
DOI 10.2166/wst.2012.352

Capelli, L., Sironi, S., Del Rosso, R., & Guillot, J. M., 2013. Measuring odours in the environment vs. dispersion modelling: A review. Atmos. Environ. 79, 731-743.
DOI 10.1016/j.atmosenv.2013.07.029

Capelli, L., Dentoni, L., Sironi, S., & Del Rosso, R., 2014. The need for electronic noses for environmental odour exposure assessment. Water Sci. Technol. 69(1), 135-141.
DOI 10.2166/wst.2013.544

Capelli, L., & Sironi, S., 2018. Combination of field inspection and dispersion modelling to estimate odour emissions from an Italian landfill. Atmos. Environ. 191, 273-290.
DOI 10.1016/j.atmosenv.2018.08.007

Che, Y., Yang, K., Jin, Y., Zhang, W., Shang, Z., & Tai, J., 2013. Residents’ concerns and attitudes toward a municipal solid waste landfill: integrating a questionnaire survey and GIS techniques. Environ. Monit. Assess. 185(12), 10001-10013

Chemel, C., Riesenmey, C., Batton-Hubert, M., & Vaillant, H., 2012. Odour-impact assessment around a landfill site from weather-type classification, complaint inventory and numerical simulation. J. Environ. Manage. 93(1), 85-94.
DOI 10.1016/j.jenvman.2011.08.016

Di Trapani, D., Di Bella, G. & Viviani, G., 2013. Uncontrolled methane emissions from a MSW landfill surface: Influence of landfill features and side slopes. Waste Manage. 33, 2108-2115.
DOI 10.1016/j.wasman.2013.01.032

Hayes, E. T., Curran, T. P., & Dodd, V. A., 2006. A dispersion modelling approach to determine the odour impact of intensive poultry production units in Ireland. Bioresource Technol. 97(15), 1773-1779.
DOI 10.1016/j.biortech.2005.09.019

Henshaw, P., Nicell, J., & Sikdar, A., 2006. Parameters for the assessment of odour impacts on communities. Atmos Environ. 40, 1016-1029.
DOI 10.1016/j.atmosenv.2005.11.014

Lucernoni, F., Tapparo, F., Capelli, L., & Sironi, S., 2016. Evaluation of an Odour Emission Factor (OEF) to estimate odour emissions from landfill surfaces. Atmos Environ. 144, 87-99.
DOI 10.1016/j.atmosenv.2016.08.064

Lucernoni, F., Capelli, L., & Sironi, S., 2017. Comparison of different approaches for the estimation of odour emissions from landfill surfaces. Waste Manage. 63, 345-353.
DOI 10.1016/j.wasman.2016.09.041

Marchand, M., Aissani, L., Mallard, P., Béline, F., & Réveret, J. P., 2013. Odour and life cycle assessment (LCA) in waste management: a local assessment proposal. Waste Biomass Valori. 4(3), 607-617.
DOI 10.1007/s12649-012-9173-z

Moussiopoulos, N., Berge, E., Bøhler, T., de Leeuw, F., Grønskei, K. E., Mylona, S., Tombrou, M., 1996. Ambient air quality, pollutant dispersion and transport models. European Topic Centre on Air Quality

Oettl, D., Kropsch, M., & Mandl, M., 2018. Odour assessment in the vicinity of a pig-fatting farm using field inspections (EN 16841-1) and dispersion modelling. Atmos. Environ. 181, 54-60.
DOI 10.1016/j.atmosenv.2018.03.029

Piringer, M., Knauder, W., Petz, E., & Schauberger, G., 2016. Factors influencing separation distances against odour annoyance calculated by Gaussian and Lagrangian dispersion models. Atmos. Environ. 140, 69-83.
DOI 10.1016/j.atmosenv.2016.05.056

Rachor, I. M., Gebert, J., Gröngröft, A., & Pfeiffer, E. M., 2013. Variability of methane emissions from an old landfill over different time‐scales. Eur. J. Soil. Sci. 64(1), 16-26.
DOI 10.1111/ejss.12004

Ranzato, L., Barausse, A., Mantovani, A., Pittarello, A., Benzo, M., & Palmeri, L., 2012. A comparison of methods for the assessment of odor impacts on air quality: Field inspection (VDI 3940) and the air dispersion model CALPUFF. Atmos. Environ. 61, 570-579.
DOI 10.1016/j.atmosenv.2012.08.009

Sakawi, Z., SA, S. M., Jaafar, O., & Mahmud, M., 2017. Community perception of odour pollution from landfills. Geografia Malays. J. Soc. Space 7(3)

Saral, A., Demir, S., & Yıldız, Ş., 2009. Assessment of odorous VOCs released from a main MSW landfill site in Istanbul-Turkey via a modelling approach. J. Hazard. Mater. 168(1), 338-345.
DOI 10.1016/j.jhazmat.2009.02.043

Sarkar, U., Longhurst, P. J., & Hobbs, S. E., 2003. Community modelling: a tool for correlating estimates of exposure with perception of odour from municipal solid waste (MSW) landfills. J. Environ. Manage. 68(2), 133-140.
DOI 10.1016/S0301-4797(03)00027-6

Schauberger, G., Piringer, M., Jovanovic, O., & Petz, E., 2012a. A new empirical model to calculate separation distances between livestock buildings and residential areas applied to the Austrian guideline to avoid odour nuisance. Atmos Environ. 47, 341-347.
DOI 10.1016/j.atmosenv.2011.10.056

Schauberger, G., Schmitzer, R., Kamp, M., Sowa, A., Koch, R., Eckhof, W., ... & Hartung, E., 2012b. Empirical model derived from dispersion calculations to determine separation distances between livestock buildings and residential areas to avoid odour nuisance. Atmos Environ. 46, 508-515.
DOI 10.1016/j.atmosenv.2011.08.025

Schroth, M. H., Eugster, W., Gómez, K. E., Gonzalez-Gil, G., Niklaus, P. A., & Oester, P., 2012. Above-and below-ground methane fluxes and methanotrophic activity in a landfill-cover soil. Waste Manage. 32(5), 879-889.
DOI 10.1016/j.wasman.2011.11.003

Scire, J. S., Strimaitis, D. G., & Yamartino, R. J., 2000. A user’s guide for the CALPUFF dispersion model. Earth Tech, Inc. Concord, MA, 10

Sironi, S., Capelli, L., Céntola, P., Del Rosso, R., & Il Grande, M., 2006. Odour emission factors for the prediction of odour emissions from plants for the mechanical and biological treatment of MSW. Atmos Environ. 40(39), 7632-7643.
DOI 10.1016/j.atmosenv.2006.06.052

Sucker, K., Both, R., & Winneke, G., 2001. Adverse effects of environmental odours: reviewing studies on annoyance responses and symptom reporting. Water Sci. Technol. 44(9), 43-51.
DOI 10.2166/wst.2001.0505

Tansel, B., & Inanloo, B., 2019. Odor impact zones around landfills: Delineation based on atmospheric conditions and land use characteristics. Waste Manage. 88, 39-47.
DOI 10.1016/j.wasman.2019.03.028

US Environmental Protection Agency, 2004. User’s guide for the AMS/EPA regulatory model—AERMOD

US Environmental Protection Agency, 2011. Haul Road Workgroup final report to the Air Quality Modeling Group

Ying, D., Chuanyu, C., Bin, H., Yueen, X., Xuejuan, Z., Yingxu, C., Weixiang, W., 2012. Characterization and control of odorous gases at a landfill site: A case study in Hangzhou, China. Waste Manage. 32, 317 – 326.
DOI 10.1016/j.wasman.2011.07.016

Zhao, Y., Lu, W., & Wang, H., 2015. Volatile trace compounds released from municipal solid waste at the transfer stage: evaluation of environmental impacts and odour pollution. J. Hazard. Mater. 300, 695-701.
DOI 10.1016/j.jhazmat.2015.07.081