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dc.contributor.authorLópez Núñez, Rafael
dc.contributor.authorGiráldez Díaz, Inmaculada 
dc.contributor.authorPalma López, Alberto 
dc.contributor.authorDíaz Blanco, Manuel Jesús 
dc.date.accessioned2015-12-01T08:14:06Z
dc.date.available2015-12-01T08:14:06Z
dc.date.issued2015
dc.identifier.citationLópez Núñez, R., Giráldez Díaz, I., Palma López, A., Díaz Blanco, M. J.: "Assessment of compost maturity by using an electronic nose". Waste Management, (2015). DOI: 10.1016/j.wasman.2015.09.039en_US
dc.identifier.issn0956-053X
dc.identifier.issn1879-2456
dc.identifier.urihttp://hdl.handle.net/10272/11453
dc.description.abstractThe 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, O2, 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.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.otherGreen wastesen_US
dc.subject.otherPruning residuesen_US
dc.subject.otherManureen_US
dc.subject.otherBiomassen_US
dc.subject.otherCompostingen_US
dc.subject.otherCompost maturityen_US
dc.subject.otherVOCsen_US
dc.titleAssessment of compost maturity by using an electronic noseen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.wasman.2015.09.039en_US
dc.identifier.doi10.1016/j.wasman.2015.09.039
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US


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