Continuous monitoring of odours from a composting plant using electronic noses

Sironi, Selena; Capelli, Laura; Cèntola, P.; Rosso, R. Del; Grande, M. Il

doi:10.1016/j.wasman.2006.01.029

Cited by 77 publications

(40 citation statements)

References 23 publications

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“…The W5C sensor is reported to be sensitive towards alkanes, aromatic compounds and less polar compounds. Previous studies [28,45] reported similar results using different composts as packing materials and composting processes. …”

Section: Resultssupporting

confidence: 63%

Biofiltration of α-pinene vapours using municipal solid waste (MSW) – Pruning residues (P) composts as packing materials

Cabeza

López

Giráldez

et al. 2013

Chemical Engineering Journal

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ABSTRAeTIn this study, a biofiltration system was designed using matme composts ofmunicipal solid waste (MSW) or MSW mixed with pruning residues (MSW-P) as packing materials to treat vapours of rt-pinene (a dominant volatile organic compounds (VaC) emitted dming the MSW-P co-composting), Monitoring the efficiency of tlle hiofiltration system was carried out using a photoionization analyser, a commercial ekctronic nosc (e-nose) and gas chromatography -mass spcctrometry (GC/MS). Using an EBRT of 66 s, removal efficiencies for both kinds of biofilters were greater tllan 90% removal at different stages of the experiment. Ihe acc\imatisation periods were 1 U and 25 days for the IVISW biofilter and IVISW-P biofilter. respectively. Removal efficiency of the system was strongly dependent upon the moistllTe content of the packing materials. As moisture content in the biofilters fel! to below 66% for the MSW and 51 % (dry basis) for MSW-P, the removal efficiency decreased to less than 90%. E-nose and GCfMS data indicate a complete degradation of the et-pinene. rhe e-nose detected a characteristical background emission (odom fingerprint) of eaeh type of biofilter. Results suggest that e-nose's will beeome a more powerful tool for monitoring VOCs in biofiltration and composting processes in tbe future.

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Section: Resultssupporting

confidence: 63%

Biofiltration of α-pinene vapours using municipal solid waste (MSW) – Pruning residues (P) composts as packing materials

Cabeza

López

Giráldez

et al. 2013

Chemical Engineering Journal

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“…For this purpose, the determination of the contribution of each source to the perceived annoyance would be a solution. The electronic nose is able to identify the major odour source in a mixture [1] and has been evaluated to determine simultaneously the proportions of pure compounds in a synthetic mixture [2], but never for complex odorous samples in the environment. To study the ability of the e-nose to identify the components of a mixture, an approach similar to the ones used in air pollution to determine the contributions of VOC (Volatile Organic Compound) sources is proposed [3], using receptor models such as CMB (Chemical Mass Balance), applied to e-nose data.…”

Section: Discussionmentioning

confidence: 99%

Identification Of The Different Sources Responsible For The Olfactory Annoyance, Using An E-Nose

Clarke¹,

Locoge²,

Redon³

et al. 2011

AIP Conference Proceedings

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Abstract. The aim of this work is to quantify simultaneously two complex odor sources in a mixture. Odorous samples were taken in the environment, measured with a MOS-based e-nose, then mixed together; the mixture was then measured on the same e-nose. The results proved that even though the results are not accurate du to the high variability of the samples, it is possible to measure simultaneously real odorous samples using an e-nose.Keywords: e-nose, MOS, olfactory annoyance, odor, environment PACS: 07.07.Df, 07.88.+y, 89.60.-k SUMMARYThe olfactory annoyance perceived at the receptor site of an industrial area is often the result of a combination of different smells, emitted by several industrial sources. The major issue in the case of complaints is to identify the responsible. For this purpose, the determination of the contribution of each source to the perceived annoyance would be a solution. The electronic nose is able to identify the major odour source in a mixture [1] and has been evaluated to determine simultaneously the proportions of pure compounds in a synthetic mixture [2], but never for complex odorous samples in the environment. To study the ability of the e-nose to identify the components of a mixture, an approach similar to the ones used in air pollution to determine the contributions of VOC (Volatile Organic Compound) sources is proposed [3], using receptor models such as CMB (Chemical Mass Balance), applied to e-nose data. This paper presents the first results of identification of odour sources contained simultaneously in a mixture, using a metal oxide-based e-nose.

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“…Electronic noses (e-noses) have proven useful to monitor the odour emissions in composting (Littarru, 2007;Sironi et al, 2007), and the aeration conditions (Rajamäki et al, 2005). A significant relationship between the biological activity (measured by the dynamic respiration index), and the odour molecule production (measured by an e-nose), has been found during high-rate food-waste composting processes (D'Imporzano et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Assessment of compost maturity by using an electronic nose

et al. 2016

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The composting process produces and emits hundreds of different gases. Volatile organic compounds (VOCs) can provide information about progress of composting process. This paper is focused on the qualitative and quantitative relationships between compost age, as sign of compost maturity, electronic-nose (e-nose) patterns and composition of compost and composting gas at an industrial scale plant,. Gas and compost samples were taken at different depths from composting windrows of different ages. Temperature, classical chemical parameters, O 2 , CO, combustible gases, VOCs and e-nose profiles were determined and related using principal component analysis (PCA). Factor Analysis carried out to a data set including compost physical-chemical properties, pile pore gas composition and composting time led to few factors, each one grouping together standard composting parameters in an easy to understand way. PCA obtained from e-nose profiles allowed the classifying of piles, their aerobic-anaerobic condition, and a rough estimation of the composting time. That would allow for immediate and in-situ assessment of compost quality and maturity by using an on-line e-nose. The e-nose patterns required only 3-4 sensor signals to account for a great percentage (97-98%) of data variance. The achieved patterns both from compost (chemical analysis) and gas (e-nose analysis) samples are robust despite the high variability in feedstock characteristics (3 different materials), composting conditions and long composting time. GC-MS chromatograms supported the patterns.

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Continuous monitoring of odours from a composting plant using electronic noses

Cited by 77 publications

References 23 publications

Biofiltration of α-pinene vapours using municipal solid waste (MSW) – Pruning residues (P) composts as packing materials

Biofiltration of α-pinene vapours using municipal solid waste (MSW) – Pruning residues (P) composts as packing materials

Identification Of The Different Sources Responsible For The Olfactory Annoyance, Using An E-Nose

Assessment of compost maturity by using an electronic nose

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