title: Optimisation of temperature-programmed gas chromatographic separation of organochloride pesticides by response surface methodology.
abstract: A response surface methodology (RSM) approach is applied to optimise the temperature-programme gas-chromatographic separation of 16 organochloride pesticides, including 12 compounds identified as highly toxic chemicals by the Stockholm Convention on Persistent Organic Pollutants. A three-parameter relationship describing both linear and curve temperature programmes is derived adapting a model previously used in literature to describe concentration gradients in liquid chromatography with binary eluents. To investigate the influence of the three temperature profile descriptors (the starting temperature, the gradient duration and a shape parameter), a three-level full-factorial design of experiments is used to identify suitable combinations of the above variables spanning over a useful domain. Resolutions of adjacent peaks are the responses modelled by RSM using two alternative methods: a multi-layer artificial network (ANN) and usual polynomial regression. The proposed ANN-based approach permits to model simultaneously the resolutions of all the consecutive analyte pairs as a function of the temperature profile descriptors. Four critical pairs giving partially overlapped peaks are identified and multiresponse optimisation is carried out by analysing the surface plot of a global resolution defined as the average of the resolutions of the critical pairs. Descriptive/predictive performance and applicability of the ANN and polynomial RSM methods are compared and discussed.
authors.affiliation: Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67010 Coppito, L'Aquila, Italy. Electronic address: angeloantonio.darchivio@univaq.it.
authors.forename: Angelo Antonio
authors.initials: AA
authors.lastname: D'Archivio
authors.affiliation: Hortus Novus, Via Collepietro, 67100 L'Aquila, Italy.
authors.forename: Maria Anna
authors.initials: MA
authors.lastname: Maggi
authors.affiliation: Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67010 Coppito, L'Aquila, Italy.
authors.forename: Cristina
authors.initials: C
authors.lastname: Marinelli
authors.affiliation: Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67010 Coppito, L'Aquila, Italy.
authors.forename: Fabrizio
authors.initials: F
authors.lastname: Ruggieri
authors.affiliation: Agenzia Regionale per la Tutela dell' Ambiente (ARTA) Abruzzo, Caselle di Bazzano, Bivio per Monticchio, 67100 L'Aquila, Italy.
authors.forename: Fabrizio
authors.initials: F
authors.lastname: Stecca
mesh_terms: D002623:Chemistry Techniques, Analytical / Q000379:methods*; D002849:Chromatography, Gas; D006843:Hydrocarbons, Chlorinated / Q000032:analysis / Q000737:chemistry*; D009930:Organic Chemicals; D010575:Pesticides / Q000032:analysis / Q000737:chemistry*; D013696:Temperature
chemical_list: D006843:Hydrocarbons, Chlorinated; D009930:Organic Chemicals; D010575:Pesticides
keywords: Artificial neural network; Organochloride pollutants; Response surface methodology; Separation optimisation; Temperature-programmed gas-chromatography