بهینه سازی کمومتریکس آنالیز ترکیبات آلی فرار در آب با طیف سنجی جرمی کروماتوگرافی استاتیک

ABSTRACT Chemometrics Optimization of Volatile Organic Compounds Analysis in Water by Static Headspace Gas Chromatography Mass Spectrometry

Volatile organic compounds (VOCs) represent a class of organic substances characterized mainly by high volatility under environmental conditions. The main subgroups of these priority pollutants are halogenated volatile organic compounds (HVOCs), chlorinated short chain hydrocarbons (CHCs) and monocyclic aromatic hydrocarbons (MAHs) [1,2]. Benzene, toluene, ethylbenzene and xylene (BTEX) are widespread pollutants of which the main source in the outside environment is vehicle traffic and indoor the cigarette smoke. They are also present in small quantities in drinking water and food, in painting substances or adhesives [3].

The main anthropogenic sources of VOCs to aquatic environments are the effluents of urban and industrial activities, including wastewater, atmospheric deposition, urban and rural runoff, extraction accidents, transport and/or transformations of fossil fuels, and natural sources (petrogenic and biogenic) [1,2]. The main reason for assessing VOCs in aquatic environments is their neurotoxic and carcinogenic effects (Huybrechts et al., 2005) [2]. Because of their toxicity, some VOCs have been included in the US Environmental Protection Agency (EPA) list of priority pollutants [4-6]. Also the European Union (EU) has classified several VOCs as priority contaminants (E.U. Directive 2004/42/CE) [7].

There are many reports about determination VOCs in environmental samples. For example, Safarova et al. [8] used headspace analysis combined with gas chromatography mass spectrometry for the analysis of 53 volatile organic compounds in river waters, waste waters and treated water samples down to 0.1 μg.L-1 concentration levels. They concluded that the content of VOCs in river water mainly correlates to the content of these compounds in waste waters, which shows the anthropogenic character of the pollutions. Schmidt et al. applied HS-SPME with a Combi-PAL autosampler to the pre-concentration of waters to obtain good reproducibility. Their method had sample recovery values of 105–110% with good sensitivity and reproducibility [9]. For the quantitative work, the methods were validated and showed good linearity, precision, accuracy and limit of detection (LOD) for the compounds studied. Sample preparation may largely influence the sensitivity and accuracy of measurements of VOCs due to their physico-chemical properties. Several sample introduction modules were coupled to chromatographic systems to improve the measurement quality (e.g., headspace sampling, solid phase microextraction, purge and trap) [9,10]. Headspace analysis is a technique that separate and collect volatile compounds (in the gas phase) from different sample matrices such as water, solids, and foods [11,12]. Static or dynamic headspace gas chromatography (GC) analysis is the most adopted methods used by environmental agencies to determine VOCs from solid and liquid matrices [13]. However, direct aqueous injection (DAI) [14], liquid–liquid extraction (LLE) [14], membrane techniques, solid-phase extraction (SPE), solid-phase microextraction (SPME) [8,15] and distillation techniques are also used as sample preparation techniques in analysis of VOCs. A primary benefit of using headspace GC is that one can analyze small amounts of analytes buried in a large amount of matrix without having to inject the matrix into the chromatography column. This technique results in clean, easy sample preparation coupled with less wear on the chromatography columns and the GC instrument. The static headspace (SHS) technique presents a wide linear dynamic range (with a limit of detection of up to 100 mg.L-1) [15], simpler instrumentation [8,9], good repeatability (coefficient of variation 4–10%) and high recuperation [15-17].

Static headspace is a sampling technique based on physicochemical processes of equilibrium between the solution and the headspace. The success of its use depends on factors such as the chemical nature of the compounds to be extracted, the temperature used during extraction, extraction time and amount of added salts [18]. Studies considering the variables one by one to obtain the best possible conditions of SHS sampling have been followed by Gaines et al. [19] and Achten et al. [20], but these procedures requires a lot of experiments and are also time consuming.

In cases such as this, where many factors influence the response of the system, optimization of the extraction procedure can be carried out using multivariate statistical tools. These provide secure information concerning the best analytical conditions, the existence or otherwise of experimental errors, as well as showing any interactions that might exist between the factors involved. While traditional methods of optimization experiments, where only one variable is analyzed at a time, leaving the others fixed, require a large number of experiments, and do not allow investigating possible interactions between variables, and not explore fully the solution space for optimization [21].

Experimental design, that takes into account simultaneously several variables, seems the most convenient approach searching for the optimal operational conditions in a reasonable number of experiments [22-24]. The principles behind these techniques (known as Design of Experiments (DoE)), encompass the use of experimental design and the generation of mathematical equations and graphic outcomes [24]. Employing various rational combinations of factors, statistical experimental design fits experimental data into mathematical equations (known as models) applied in order to predict and optimize the examined responses. This methodology can be used for optimization of SHS conditions to determine VOCs in water. Examples of GC development and optimization attempts with the aid of DoE have shown important advantages [25-28].

The aim of the present paper was to develop and optimize a static headspace gas chromatography-mass spectroscopy method for the determination of VOCs, using experimental design. The significance of the studied factors was evaluated with the aid of a full factorial design (full FD) whilst the optimum SHS conditions were estimated by a central composite design (CCD) using both a graphical and a mathematical global optimization approach. Finally, the proposed method was tested for linearity, specificity, precision, accuracy and robustness (using experimental design).