Multivariate experimental design in environmental analysis

Uncovering the key determinants of electrode passivation and faradaic efficiency in electrocoagulation: Depassivation and sustainable performance via polarity reversal

The buildup of metal precipitates and aqueous-phase species as surface layers (SLs) on electrodes presents a significant challenge in electrocoagulation (EC), leading to electrode passivation, hindering coagulant production, and ultimately diminishing the efficiency of wastewater treatment. Despite its critical importance, the understanding of electrode passivation/corrosion and the efficacy of strategies to address the passivation issue, particularly in dye wastewater, remains limited. This study aims to provide novel insights into the key determinants of electrode passivation and Faradaic efficiency, along with evaluating the overall performance of EC concerning energy consumption and dye removal efficiency. Through a detailed analysis of SLs formed on Al and Fe electrodes, the research further explores how polarity reversal (PR), as an alternative to direct current (DC), influences SL characteristics, aids in depassivating electrodes, and enhances the sustainability of EC. A fractional factorial design is employed to investigate the main and interaction effects of various factors, including electrode type (Al and Fe), current mode (DC and PR), current density, treatment time, and concentrations of reactive dye and dye auxiliary (Na2CO3 and NaCl). The findings revealed that Na2CO3 severely passivated both electrode types, lowering Faradaic efficiency and dye removal. In contrast, NaCl alleviated passivation effects and reduced energy consumption. PR application in Al-based EC reduced SL buildup, improved Faradaic efficiency, and converted the Al2O3 insulating layer into porous Al(OH)3. These collectively contributed to decreased energy usage and enhanced dye removal. Conversely, PR in Fe-based EC could not consistently reduce SL mass and negatively affected Faradaic and decolorization efficiency. Nevertheless, PR reduced poorly crystalline Fe(III) precipitates and facilitated uniform distribution of SLs between electrodes, decreasing energy consumption.

A novel quality-by-design assisted HPLC-DAD method for the simultaneous quantification of tryptophan, tryptophol, and voriconazole for early diagnosis and prognosis of fungal infections decoding quorum sensing phenomenon

For the first time, a comprehensive analytical approach is introduced that simultaneously quantifies a metabolic precursor (tryptophan), a quorum-sensing biomarker for fungal infections (tryptophol), and an antifungal drug (voriconazole) within a single platform using reversed-phase high-performance liquid chromatography coupled with diode array detection (HPLC-DAD). The method utilizes a Pursuit PFP column featuring a unique pentafluorinated structure, with a mobile phase of methanol: water (60:40, v/v), a flow rate of 1.0 mL/min, and a detection wavelength set at 254.0 nm. An Analytical Quality-by-Design (AQbD) methodology was employed, incorporating a full factorial design for optimal method development. Validation was performed in accordance with ICH guidelines, demonstrating exceptional linearity (2.0-60.0 μg/mL) for all target analytes, along with high precision, accuracy, and system suitability. Furthermore, the method proved robust and versatile when applied to complex matrices, including spiked human serum and pharmaceutical tablet formulations. Noteworthy is the integration of green and white chemistry principles for evaluating the method's sustainability, representing a significant advancement in analytical technique development. Assessment of greenness, blueness, and whiteness with AGREE, ComplexGAPI index, BAGI and RGB 12 Tools, respectively. This innovative analytical platform provides a powerful tool for the early detection and real-time therapeutic monitoring of fungal infections. By enabling the simultaneous analysis of a metabolic marker, a quorum-sensing specific biomarker, and an antifungal agent, the method advances personalized medicine. It offers a novel, efficient, and sustainable solution for the personalized management of fungal infections, enhancing both diagnostic and therapeutic strategies.

Method development and optimization for dispersive liquid-liquid microextraction factors using the response surface methodology with desirability function for the ultra-high performance liquid chromatography quadrupole time of flight mass spectrometry determination of organic contaminants in water samples: risk and greenness assessment

A simple, cost effective, and efficient dispersive liquid-liquid microextraction method was developed and optimized for the determination of organic contaminants in different environmental water matrices followed by UHPLC-QTOF-MS analysis. In the preliminary experiments, the univariate optimization approach was used to select tetrachloroethylene and acetonitrile as extraction and disperser solvents, respectively. The significant factors influencing DLLME were screened using full factorial design, and the optimal values for each variable were then derived through further optimization using central composite design with desirability function. The optimal conditions were achieved with 195 μL of tetrachloroethylene as the extraction solvent, 1439 μL of acetonitrile as the disperser solvent, and a sample pH of 5.8. Under these conditions, the method provided detection limits ranging from 0.11-0.48 μg L-1 and recoveries ranging from 23.32-145.43% across all samples. The enrichment factors obtained ranged from 11.66-72.72. The proposed method was then successfully applied in real water samples. Only benzophenone was detected in the concentration range of 0.79-0.88 μg L-1 across all the water samples. The calculated risk quotient resulting from benzophenone exposure in water samples showed a low potential risk to human health and the aquatic ecosystem. The method was also evaluated for its environmental friendliness using various metrics tools such as Analytical Eco-Scale (AES), Green Analytical Procedure Index (GAPI), Analytical GREEnness (AGREE), Analytical Greenness for Sample Preparation (AGREEprep), and Sample Preparation Metric of Sustainability (SPMS). Only AES qualified the method as green while it was considered acceptable and sustainable when assessed using SPMS.

Optimization of the Erythrosine-mediated photodynamic therapy against Escherichia coli using response surface methodology

BACKGROUND

The efficacy of photodynamic therapy (PDT) depends on the combination of light and a photosensitizer for inactivation of microorganisms. However, finding the ideal conditions for the factors involved in this technique is time and cost-consuming. The rotational composite central design (RCCD) is a tool that can be allied with PDT to achieve precise results within a shorter working time.

METHODS

This study used the response surface methodology to optimize the parameters of PDT mediated by Erythrosine (ERY) and green light-emitting diodes (LED) in different Escherichia coli strains by applying RCCD.

RESULTS

The RCCD predicted optimum values of ERY and light exposure on PDT. According to the experimental results, the light exposure time showed the most significant influence on the inactivation of the evaluated bacteria. The optimized operating conditions were validated in laboratory tests, and no viable cells were recovered with ERY at 116 µmol L-1 and 30 min of light (33.34 J cm2) for E. coli ATCC 25922, 108 µmol L-1 and 40 min (44.38 J cm2) for E. coli ATCC 35218, and 108 µmol L-1 and 29.3 min (32.5 J cm2) for E. coli O157:H7 EDL 933.

CONCLUSION

The adjusted polynomial models provided accurate information on the combined effects of ERY and lighting time with green LED on PDT. The application of the RCCD, in addition to reducing the number of experiments, also allows for increased quantity and quality of the results. Therefore, surface response methodology combined with PDT is a promising approach to inactivate E. coli.

Simultaneous Determination of Steroids and NSAIDs, Using DLLME-SFO Extraction and HPLC Analysis, in Milk and Eggs Collected from Rural Roma Communities in Transylvania, Romania

This research aims to determine five steroids and four non-steroidal anti-inflammatory drugs in milk and egg samples collected from rural Roma communities in Transylvania, Romania. Target compounds were extracted from selected matrices by protein precipitation, followed by extract purification by dispersive liquid-liquid microextraction based on solidification of floating organic droplets. The extraction procedure was optimized using a 24 full factorial experimental design. Good enrichment factors (87.64-122.07 milk; 26.97-38.72 eggs), extraction recovery (74.49-103.76% milk; 75.64-108.60% eggs), and clean-up of the sample were obtained. The method detection limits were 0.74-1.77 µg/L for milk and 2.39-6.02 µg/kg for eggs, while the method quantification limits were 2.29-5.46 µg/L for milk and 7.38-18.65 µg/kg for eggs. The steroid concentration in milk samples was Collapse

Key Words

• dispersive liquid–liquid microextraction based on solidification of floating organic droplets (DLLME-SFO)
• eggs
• milk
• non-steroidal anti-inflammatory drugs (NSAIDs)
• rural Roma communities
• steroids

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MESH Headings

• Humans
• Animals
• Anti-Inflammatory Agents, Non-Steroidal
• Ketoprofen
• Naproxen
• Ibuprofen
• Milk
• Romania
• Chromatography, High Pressure Liquid
• Roma
• Estrone

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Grants

• Project contract no. 23 / 2020 EEA and Norway Grants

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Affiliation(s)

Mihaela Cătălina Herghelegiu Faculty of Environmental Science and Engineering, Babeș-Bolyai University, 1 Kogălniceanu Str., 400084 Cluj-Napoca, Romania
Vlad Alexandru Pănescu Faculty of Environmental Science and Engineering, Babeș-Bolyai University, 1 Kogălniceanu Str., 400084 Cluj-Napoca, Romania
Victor Bocoș-Bințințan Faculty of Environmental Science and Engineering, Babeș-Bolyai University, 1 Kogălniceanu Str., 400084 Cluj-Napoca, Romania
Radu-Tudor Coman Faculty of Medicine, “Iuliu Hațieganu” University of Medicine and Pharmacy, 8 Babeș Str., 400012 Cluj-Napoca, Romania
Vidar Berg Faculty of Veterinary Medicine, Norwegian University of Life Sciences, 1433 Ås-Oslo, Norway
Jan Ludvig Lyche Faculty of Veterinary Medicine, Norwegian University of Life Sciences, 1433 Ås-Oslo, Norway
Maria Concetta Bruzzoniti Department of Chemistry, University of Turin, Via P. Giuria 5, 10125 Turin, Italy;
Mihail Simion Beldean-Galea Faculty of Environmental Science and Engineering, Babeș-Bolyai University, 1 Kogălniceanu Str., 400084 Cluj-Napoca, Romania

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Collaborators Collapse

Cost estimation of synthesis and utilization of nano-adsorbents on the laboratory and industrial scales: A detailed review

The recent regulations pertaining to the circular economy have unlocked new prospects for researchers. In contrast to the unsustainable models associated with the linear economy, integration of concepts of circular economy braces reducing, reusing, and recycling of waste materials into high-end products. In this regard, adsorption is a promising and cost-effective water treatment technology for handling conventional and emerging pollutants. Numerous studies are published annually to investigate the technical performance of nano-adsorbents and nanocomposites in terms of adsorption capacity and kinetics. Yet, economic performance evaluation is rarely discussed in the literature. Even if an adsorbent shows high removal efficiency towards a specific pollutant, its high preparation and/or utilization costs might hinder its real-life use. This tutorial review aims at illustrating cost estimation methods for the synthesis and utilization of conventional and nano-adsorbents. The current treatise discusses the synthesis of adsorbents on a laboratory scale where the raw material, transportation, chemical, energy, and any other costs are discussed. Moreover, equations for estimating the costs at the large-scale adsorption units for wastewater treatment are illustrated. This review focuses on introducing these topics to non-specialized readers in a detailed but simplified manner.

Design of experiment techniques for the optimization of chromatographic analysis conditions: A review

Design of experiment (DoE) techniques have been widely used in the field of chromatographic parameters optimization as a valuable tool. A systematic literature review of the available DoE techniques applied to the development of a chromatographic analysis method is presented in this paper. First, the most common available designs and the implementation steps of DoE are comprehensively introduced. Then the studies in recent 10 years for the application of DoE techniques in various chromatographic techniques are discussed, such as capillary electrophoresis, liquid chromatography, gas chromatography, thin-layer chromatography, and high-speed countercurrent chromatography. Current problems and future outlooks are finally given to provide a certain inspiration of research in the application of DoE techniques to the different chromatographic techniques field. This review contributes to a better understanding of the DoE techniques for the efficient optimization of chromatographic analysis conditions, especially for the analysis of complex systems, such as multicomponent drugs and natural products.

Databionic Swarm Intelligence to Screen Wastewater Recycling Quality with Factorial and Hyper-Parameter Non-Linear Orthogonal Mini-Datasets

Electrodialysis (ED) may be designed to enhance wastewater recycling efficiency for crop irrigation in areas where water distribution is otherwise inaccessible. ED process controls are difficult to manage because the ED cells need to be custom-built to meet local requirements, and the wastewater influx often has heterogeneous ionic properties. Besides the underlying complex chemical phenomena, recycling screening is a challenge to engineering because the number of experimental trials must be maintained low in order to be timely and cost-effective. A new data-centric approach is presented that screens three water quality indices against four ED-process-controlling factors for a wastewater recycling application in agricultural development. The implemented unsupervised solver must: (1) be fine-tuned for optimal deployment and (2) screen the ED trials for effect potency. The databionic swarm intelligence classifier is employed to cluster the L9(34) OA mini-dataset of: (1) the removed Na+ content, (2) the sodium adsorption ratio (SAR) and (3) the soluble Na+ percentage. From an information viewpoint, the proviso for the factor profiler is that it should be apt to detect strength and curvature effects against not-computable uncertainty. The strength hierarchy was analyzed for the four ED-process-controlling factors: (1) the dilute flow, (2) the cathode flow, (3) the anode flow and (4) the voltage rate. The new approach matches two sequences for similarities, according to: (1) the classified cluster identification string and (2) the pre-defined OA factorial setting string. Internal cluster validity is checked by the Dunn and Davies–Bouldin Indices, after completing a hyper-parameter L8(4122) OA screening. The three selected hyper-parameters (distance measure, structure type and position type) created negligible variability. The dilute flow was found to regulate the overall ED-based separation performance. The results agree with other recent statistical/algorithmic studies through external validation. In conclusion, statistical/algorithmic freeware (R-packages) may be effective in resolving quality multi-indexed screening tasks of intricate non-linear mini-OA-datasets.

Wastewater Quality Screening Using Affinity Propagation Clustering and Entropic Methods for Small Saturated Nonlinear Orthogonal Datasets

Wastewater recycling efficiency improvement is vital to arid regions, where crop irrigation is imperative. Analyzing small, unreplicated–saturated, multiresponse, multifactorial datasets from novel wastewater electrodialysis (ED) applications requires specialized screening/optimization techniques. A new approach is proposed to glean information from structured Taguchi-type sampling schemes (nonlinear fractional factorial designs) in the case that direct uncertainty quantification is not computable. It uses a double information analysis–affinity propagation clustering and entropy to simultaneously discern strong effects and curvature type while profiling multiple water-quality characteristics. Three water quality indices, which are calculated from real ED process experiments, are analyzed by examining the hierarchical behavior of four controlling factors: (1) the dilute flow, (2) the cathode flow, (3) the anode flow, and (4) the voltage rate. The three water quality indices are: the removed sodium content, the sodium adsorption ratio, and the soluble sodium percentage. The factor that influences the overall wastewater separation ED performance is the dilute flow, according to both analyses’ versions. It caused the maximum contrast difference in the heatmap visualization, and it minimized the relative information entropy at the two operating end points. The results are confirmed with a second published independent dataset. Furthermore, the final outcome is scrutinized and found to agree with other published classification and nonparametric screening solutions. A combination of modern classification and simple entropic methods which are offered through freeware R-packages might be effective for testing high-complexity ‘small-and-dense’ nonlinear OA datasets, highlighting an obfuscated experimental uncertainty.

Optimal degradation of organophosphorus pesticide at low levels in water using fenton and photo-fenton processes and identification of by-products by GC-MS/MS

This study aiming to determine the optimal conditions to degrade an organophosphate pesticide diazinon (DZN) at low levels concentrations (μg.mL^-1) and to identify the by-products generated. The degradation processes utilized were the Fenton and photo-Fenton. The iron concentration [Fe²⁺], the hydrogen peroxide concentrations [H₂O₂], and the solution pH are the investigated parameters. The Doehlert three-parameter experimental design was applied to model and optimize both degradation processes. The mathematical models suggested were assessed and validated by application of analysis of variances ANOVA. In the case of Fenton process, the greatest yield of degradation (79%) was obtained at [Fe²⁺] = 35 mg.L^-1 (0.63 mmol.L^-1), [H₂O₂] = 423 mg.L^-1 (12.44 mmol.L^-1), and pH = 5.0. In photo-Fenton process, the maximum yield of degradation (96%) was obtained under the conditions of [Fe²⁺] = 29 mg.L^-1 (0.52 mmol.L^-1), [H₂O₂] = 258 mg.L^-1 (7.59 mmol.L^-1) and pH = 4.6. QuEChERS (quick, easy, cheap, effective, rugged, and safe), as extraction technique, and GC-MS/MS (gas chromatography coupled with triple quadrupole mass spectrometry) were used to identify the by-products degradation of DZN. The identified compounds are diazoxon, triethyl phosphate, triethyl thiophosphate, 2-isopropyl-5-ethyl-6-methylpyrimidine-4-ol, 2-isopropyl-6-methylpyrimidine-4-ol (IMP) and hydroxydiazinon. Three possible pathways for diazinon degradation have been suggested and the hydroxylation, oxidation and hydrolysis are likely probable degradation mechanisms.

Optimization of a saccharin molecularly imprinted solid-phase extraction procedure and evaluation by MIR hyperspectral imaging for analysis of diet tea by HPLC

Saccharin was determined based on a new molecularly imprinted solid-phase extraction (MISPE) procedure. The polymer was synthesized with a hybrid monomer of metacrylic acid and 3-amino propril tetraethoxysilane and saccharin as template. After the synthesis, the saccharin removal from the MIP was verified by the UV analysis of the solutions used in the template removal procedure, as well as by the direct MIP analysis using FTIR hyperspectral image and chemometrics. The residual saccharin concentrations observed in the image analysis revealed a narrow concentration distribution consistent with a homogenous material. The MISPE was performed with homemade cartridges containing 200 mg of the MIP. The results obtained with standards and diet tea samples confirmed high affinity, adsorption capacity and selectivity of the MIP. The MISPE cartridge exhibited recoveries of 100 ± 3% in six extraction cycles. The diet tea analysis showed a significant reduction of the interferences, which can considerable simplifies the HPLC-UV analysis.

Multivariate optimization of a dispersive liquid-liquid microextraction method for determination of copper and manganese in coconut water by FAAS

In this study, multivariate methodologies were applied in the optimization of a dispersive liquid-liquid microextraction (DLLME) method, aiming at the determination of Cu and Mn in coconut water samples by flame atomic absorption spectrometry. Some extractors (chloroform and CCl₄), dispersants (ethanol, methanol and acetonitrile) and complexing agents (5-Br-PADAP and Dithzone) were previously tested in the extraction. A mixture design was used to optimize the component proportions formed by chloroform (10%), acetonitrile (76%), and 0.020% 5-Br-PADAP solution (14%). Doehlert design optimized the variables pH, NaCl, and buffer amounts for the extraction of both metals. The following analytical characteristics, respectively for Cu and Mn, were accessed: limit of quantification (4.83 and 3.32 µg L^-1), enrichment factors (11 and 8 fold), and precision (6.6 and 6.0% RSD, n = 10). Addition/recovery tests of the analytes allowed to find values in the range of 96.5-120% for Cu and 99-107% for Mn.

Doehlert design in the optimization of procedures aiming food analysis - A review

In the present paper is presented a review on the application of Doehlert design in the optimization of some of the steps of analytical procedures aimed the analysis of food samples. The theoretical principles and the main characteristics of this type of design are described. In addition, the main advantages and limitations of Doehlert design over other designs (Central Composite Design and Box-Behnken) and its application in the area of food analysis are discussed. Finally, to illustrate its potential, some examples of Doehlert design application in other areas of food chemistry without the purpose of analytical determination will be briefly presented.

Multivariate optimization of a goat meat alkaline solubilization procedure using tetramethylammonium hydroxide for metals determination using FAAS

In the present work, multivariate designs were used to optimize an alkaline dissolution, assisted by ultrasound energy, procedure of goat meat using tetramethylammonium hydroxide (TMAH) aiming to determine Ca, Cu, Fe, K, Mg, Na and Zn by flame atomic absorption (FAAS) and emission (FAES) spectrometry. The optimal conditions found for the dissolution were in the following ranges: 0.4-0.5 g for the sample mass, 12-15 min of sonication and using 700-1000 µL of 25% TMAH at a temperature of 50 °C. The obtained limits of quantification varied between 0.221 (Mg) and 7.60 (Ca) μg g^-1. Accuracy was assessed by comparing the results obtained by applying the proposed method with the digestion in an acid medium using a digesting block and by analyzing bovine liver certified reference material. The application of a t-test revealed that, at a 95% confidence level, there were no significant differences between the values obtained.

Speciation analysis of organoarsenic species in marine samples: method optimization using fractional factorial design and method validation

Organoarsenic species in marine matrices have been studied for many years but knowledge gaps still exist. Most literature focuses on monitoring of arsenic (As) species using previously published methods based on anion- and cation-exchange high-performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS). These studies are often limited to few As species and/or only specific method performance characteristics are described. Most marine certified reference materials (CRMs) are only certified for arsenobetaine (AB) and dimethylarsinate (DMA), making it difficult to evaluate the accuracy of analytical methods for other organoarsenic species. To address these gaps, the main objective of this work was to develop and validate a method for speciation analysis of a broad range of organoarsenic species in marine matrices. Optimum extraction conditions were identified through a 2^7–3 fractional factorial design using blue mussel as test sample. The effects of sample weight, type and volume of extraction solution, addition of H₂O₂ to the extraction solution, extraction time and temperature, and use of ultrasonication were investigated. The highest As recoveries were obtained by using 0.2 g as sample weight, 5 mL of aqueous methanol (MeOH:H₂O, 50% v/v) as extractant, extraction carried out at 90 °C for 30 min, and without ultrasonication. Anion- and cation-exchange HPLC-ICP-MS settings were subsequently optimized. The method detected a total of 33 known and unknown As species within a run time of 23 and 20 min for cation-exchange and anion-exchange, respectively. A single-laboratory validation was conducted using several marine CRMs: BCR 627 (tuna fish tissue), ERM-CE278k (mussel tissue), DORM-4 (fish protein), DOLT-5 (dogfish liver), SQID-1 (cuttlefish), TORT-3 (lobster hepatopancreas), and CRM 7405-b (hijiki seaweed). Method performance characteristics were evaluated based on selectivity, limits of detection and quantification, linearity, trueness, precision, and measurement uncertainty. This work proposes an extraction procedure which allowed satisfactory quantification of As species with low solvent and energy consumption, supporting “Green Chemistry” principles. The study also presents a new set of As speciation data, including methylated arsenic species and arsenosugars, in recently issued marine CRMs, which will be valuable for future speciation studies on As. This work is the first to report a total of 33 different As species in marine CRMs.

Adsorption of phenol and bisphenol A on river sediments: Effects of particle size, humic acid, pH and temperature

Phenolic Endocrine Disrupting Chemicals (EDCs) have drawn more and more interest due to their prevalence and persistence in aquatic environment. To study the adsorption of various phenolic EDCs on river sediments under natural conditions, we first sought to analyze the distribution characteristics of phenol and bisphenol A (BPA) in sediment from the Bahe River. The static adsorption experiments contained either single- or dual-contaminant of phenol and/or BPA in the system; they were conducted to characterize the adsorption of these two pollutants in the surface sediments and the main factors affecting the adsorption processes of the dual-contaminant system, including particle size, humic acid (HA) concentration, pH, and temperature. Results showed that in certain seasons, there was a significant correlation between the levels of phenol and BPA in Bahe sediments. When comparing the adsorption behaviors of phenol and BPA on sediments in single- and dual-contaminant systems, we found that the phenol adsorption behavior varied, while that of BPA remained consistent across the different systems. Moreover, different effects were observed with regards to a single factor and the interaction of multiple factors on the adsorption of pollutants. Of the four single factors, only HA concentration had a significant effect on the phenol adsorption in sediment. When considering the interaction of multiple factors, the interaction between HA concentration and temperature significantly promoted the adsorption of phenol. The influence of factors on the adsorption of BPA was in the following order: particle size > HA concentration > pH > temperature. Particle size significantly inhibited BPA adsorption in the sediment, while the interaction between particle size and pH increased BPA adsorption.

Gas sensors based on mass-sensitive transducers. Part 2: Improving the sensors towards practical application

Within the framework outlined in the first part of the review, the second part addresses attempts to increase receptor material performance through the use of sensor systems and chemometric methods, in conjunction with receptor preparation methods and sensor-specific tasks. Conclusions are then drawn, and development perspectives for gravimetric sensors are discussed.

Development of a simple method to quantify fipronil and its intermediates in soil

A simple and reproducible method was developed and validated for simultaneous quantification of the pesticide fipronil and its intermediates fipronil desulfinyl, fipronil sulfone and fipronil sulfide, in soil. The analytes were extracted by ultrasonic bath and the ratio of solvents (hexane/acetone), number and time of cycles were optimized by Box-Behnken design with a triplicate central point. The optimal extraction conditions were achieved through a response surface analysis. The clean-up step was conducted by cartridges of solid phase extraction (SPE) containing silica (Florisil®) and aluminum oxide. Gas chromatography with electron capture detection (GC-ECD) was employed for separating fipronil and its intermediates with a suitable resolution and runtime of 20 minutes. The best quantification was achieved with 1 : 1 (v/v) acetone/hexane and 2 ultrasound cycles of 15 minutes each. The recovery values were between 81 to 108%, with relative standard deviation (RSD) lower than 6%, with no effect of the used matrix. Analytical curves presented regression coefficients values above 0.9908 for a concentration range from 0.005 to 0.6 μg g-1. Limits of detection (LOD) from 0.002 to 0.006 μg g-1 and limits of quantification (LOQ) from 0.006 to 0.020 μg g-1 were reached for all analytes. This method can be used to monitor and quantify fipronil and its intermediates in soil.

Analytical protocol for determination of endosulfan beta, propham, chlorpyrifos, and acibenzolar-s-methyl in lake water and wastewater samples by gas chromatography-mass spectrometry after dispersive liquid-liquid microextraction

This study describes the development of a sensitive and accurate dispersive liquid-liquid microextraction strategy for the preconcentration and determination of selected pesticides in wastewater and lake water samples by gas chromatography-mass spectrometry. Determination of these pesticides at high accuracy and precision is important because they can be still be found in environmental samples. The type of extraction solvent and type of disperser solvent were optimized using the univariate approach. Furthermore, a Box-Behnken experimental design was used to set up a working model made up of 18 combinations of three variables, tested at three levels. The parameters fitted into the design model were volume of extraction solvent, disperser solvent volume, and mixing period. Analysis of variance was used to evaluate the experimental data to determine the significance of extraction variables and their interactions, before selecting optimum extraction conditions. The method was then applied to aqueous standard solutions between 2.0 and 500 μg L^-1, and the limit of detection (LOD) and quantification (LOQ) values obtained for the analytes were between 0.37-2.8 and 1.2-9.4 μg L^-1, respectively. The percent recoveries were calculated in the range of 92-114 and 96-110% for wastewater and lake water, respectively. These results validated the accuracy and applicability of the method to the selected matrices.

Analysis of multiclass organic pollutant in municipal landfill leachate by dispersive liquid-liquid microextraction and comprehensive two-dimensional gas chromatography coupled with mass spectrometry

We propose a simple, fast, and inexpensive method for the analyses of 72 organic compounds in municipal landfill leachate, based on dispersive liquid-liquid microextraction and comprehensive two-dimensional gas chromatography coupled with mass spectrometry. Forty-one organic compounds belonging to several classes including hydrocarbons, mono- and polyaromatic hydrocarbons, carbonyl compounds, terpenes, terpenoids, phenols, amines, and phthalates, covering a wide range of physicochemical properties and linked to municipal landfill leachate, were quantitatively determined. Another 31 organic compounds such as indoles, pyrroles, glycols, organophosphate flame retardants, aromatic amines and amides, pharmaceuticals, and bisphenol A have been identified based on their mass spectra. The developed method provides good performances in terms of extraction recovery (63.8-127%), intra-day and inter-day precisions (< 7.7 and < 13.9 respectively), linearity (R² between 0.9669 and 0.9999), detection limit (1.01-69.30 μg L^-1), quantification limit (1.87-138.6 μg L^-1), and enrichment factor (69.6-138.5). Detailed information on the organic pollutants contained in municipal landfill leachate could be obtained with this method during a 40-min analysis of a 4-mL leachate sample, using only 75 μL of extraction solvent.

Fast and effective simultaneous determination of metals in soil samples by ultrasound-assisted extraction and flame atomic absorption spectrometry: assessment of trace elements contamination in agricultural and native forest soils from Paraná - Brazil

This study proposes a simple and effective method for determination of Al, Cd, Cu, Ni, and Zn in soil samples, associating ultrasound-assisted extraction and flame atomic absorption spectrometry (FAAS). Ultrasound-assisted extraction conditions were optimized using a central composite design. This method required small volumes of HCl, HNO₃, and HF as an extraction solvent blend to ensure effective analyte extraction. Limits of detection and quantification were determined to assess the minimum accurate concentration of the studied elements that can be detected and quantified in a soil sample. Therefore, the ultrasound-assisted extraction was concluded as a simple and straightforward pretreatment technique to determine Al, Cd, Cu, Ni, and Zn concentrations in soil samples. Eight sites of agricultural and native forest areas of the city of Ponta Grossa and Guarapuava, State of Paraná, Brazil, were evaluated for metals, and compared with the reference values for trace elements provided by the Brazilian National Environment Council. Environmental assessment of soils from those eight sites was accomplished through I_geo, EF, CF, and PLI parameters, which aimed at the evaluation of agricultural sites in comparison with adjacent natural forest sites with no history of anthropogenic mobilization to determine the degree of the contribution of anthropogenic sources to metal concentrations. According to the I_geo, EF, and CF parameters, all sites were classified as unpolluted to moderately polluted and none or minor enrichment due to anthropogenic activities were noticed. PLI parameter evaluated the concentration of all studied metals in soils to stipulate an order of contamination, which was concluded as site 8 <site 4 <site 3 <site 7 <site 2 <site 6 <site 1 <site 5 for the sites under study.

Optimization by response surface methodology of a dispersive magnetic solid phase extraction exploiting magnetic graphene nanocomposite coupled with UHPLC-PDA for simultaneous determination of new oral anticoagulants (NAOs) in human plasma

In this paper a dispersive magnetic-solid phase extraction (MSPE) using a graphene nanocomposite (rG/Fe₃O₄) followed by ultra high performance liquid chromatography with photodiode array detection has been developed for the simultaneous analysis of new class of oral anticoagulants (NOAs) in human plasma. The performance of the nanocomposite graphene@Fe₃O₄ on the magnetic solid phase extraction of apixaban, rivaroxaban and dabigatran has been optimized using a Box-Behnken design of experiment. The amount of graphene nanocomposite, the sample pH and the adsorption time were the investigated parameters as a function of the extraction recovery. The analytical method was fully validated based on linearity, limit of detection (LOD), limit of detection (LOQ), inter- and intra-day precision and trueness, and extraction yield. Under optimal condition, excellent linearity (R² > 0.9987) over the range (0.001-5.0 μg/mL), limit of detection (0.003 μg/mL), precision (0.81-8.97% RSD) and trueness (-5 to 9 % BIAS%) were observed for the target drugs. The average extraction recovery under optimal from plasma samples ranged between 96.6-98.6% for apixaban, rivaroxaban and dabigatran and the internal standard. The proposed method was developed, validated and successfully applied to the measurement of these NOAs in patients. The new approach offers an attractive alternative for the simultaneous analysis of the selected NOAs from plasma samples, providing several advantages including fewer sample preparation steps, ease of performance, and higher recoveries compared to traditional methodologies.

Framework for a Systematic Parametric Analysis to Maximize Energy Output of PV Modules Using an Experimental Design

Use of photovoltaic modules in buildings has been reported to be an effective tool in managing energy consumption. The novelty in the research herein is in a framework that integrates different performance parameters through the use of an experimental design to expect all variables via linear regression analysis. An emphasis is placed on making the method readily available to practitioners and experts in the area of renewable energy, using standard procedure and easily accessible software. This work empowers the decision-making process and sustainability through a parametric analysis of the installation of photovoltaic modules to increase their energy output towards nearly zero energy buildings. A case study of a group of photovoltaic modules is examined in four cities with different locations and climate data to validate the proposed framework. Results demonstrate that the installation of photovoltaic modules on the mounted roof is better than elevations, and the vertical installation of modules is the worst possible inclination to maximize the yielded energy. The impact of inclination is higher than orientation in influencing the energy productivity of photovoltaic modules. This work specifies integrating such modules mounted on roofs and elevations towards the equator line, by a proportion of inclination/latitude equal to 85 ± 3%, to maximize the energy output.

Integrating Parametric Analysis with Building Information Modeling to Improve Energy Performance of Construction Projects

Buildings demand a significant amount of energy during their life cycles, hence, effective design measures need to be adopted to ensure efficient energy usage and management in buildings. This study proposes a framework based on various performance parameters to enable decision-makers utilizing standard procedures and software to empower the process of sustainable energy use and management in buildings, through a parametric analysis in different climatic conditions. Experimental design is adopted within the framework via the use of various performance parameters related to the building design (i.e., construction materials for exterior walls and roofs, as well as a set of window-to-wall ratios). Results indicate that climate data plays a fundamental role in the choice of design factors that are best suited for effective energy consumption in buildings. In particular, sub-type climate classifications, as opposed to the primary climate group, have a minor influence. Around 15% improvement in the energy consumption in buildings is noticed due to changes to the design factor such as the window-to-wall ratio. Insights that can be gleaned from this study include the impact of space area, exterior openings and material thickness and choice for the envelope of the building in all climate classifications, aiding in the design of low-energy buildings.

The response surface methodology speeds up the search for optimal parameters in the photoinactivation of E. coli by photodynamic therapy

Antimicrobial Photodynamic Inactivation (a-PDI) is based on the oxidative destruction of biological molecules by reactive oxygen species generated by the photo-excitation of a photosensitive molecule. When a-PDT is performed with the use of mathematical models, the optimal conditions for maximum inactivation are found. Experimental designs allow a multivariate analysis of the experimental parameters. This is usually made using a univariate approach, which demands a large number of experiments, being time and money consuming. This paper presents the use of the response surface methodology for improving the search for the best conditions to reduce E. coli survival levels by a-PDT using methylene blue (MB) and toluidine blue (TB) as photosensitizers and white light. The goal was achieved by analyzing the effects and interactions of the three main parameters involved in the process: incubation time (IT), photosensitizer concentration (C_PS), and light dose (LD). The optimization procedure began with a full 2³ factorial design, followed by a central composite one, in which the optimal conditions were estimated. For MB, C_PS was the most important parameter followed by LD and IT whereas, for TB, the main parameter was LD followed by C_PS and IT. Using the estimated optimal conditions for inactivation, MB was able to inactivate 99.999999% CFU mL^-1 of E. coli with IT of 28 min, LD of 31 J cm^-2, and C_PS of 32 μmol L^-1, while TB required 18 min, 39 J cm^-2, and 37 μmol L^-1. The feasibility of using the response surface methodology with a-PDT was demonstrated, enabling enhanced photoinactivation efficiency and fast results with a minimal number of experiments.

An overview of experimental designs in HPLC method development and validation

Chemometric approaches have been increasingly viewed as precious complements to high performance liquid chromatographic practices, since a large number of variables can be simultaneously controlled to achieve the desired separations. Moreover, their applications may efficiently identify and optimize the significant factors to accomplish competent results through limited experimental trials. The present manuscript discusses usefulness of various chemometric approaches in high and ultra performance liquid chromatography for (i) methods development from dissolution studies and sample preparation to detection, considering the progressive substitution of traditional detectors with tandem mass spectrometry instruments and the importance of stability indicating assays (ii) method validation through screening and optimization designs. Choice of appropriate types of experimental designs so as to either screen the most influential factors or optimize the selected factors' combination and the mathematical models in chemometry have been briefly recalled and the advantages of chemometric approaches have been emphasized. The evolution of the design of experiments to the Quality by Design paradigm for method development has been reviewed and the Six Sigma practice as a quality indicator in chromatography has been explained. Chemometric applications and various strategies in chromatographic separations have been described.

Characterization of a highly efficient N-doped TiO2 photocatalyst prepared via factorial design

The preparation of a highly efficient N-doped TiO₂ photocatalyst was optimized by factorial design and the resulting powder was fully characterized.

Direct Immersion Solid-Phase Microextraction with Matrix-Compatible Fiber Coating for Multiresidue Pesticide Analysis of Grapes by Gas Chromatography-Time-of-Flight Mass Spectrometry (DI-SPME-GC-ToFMS)

A fast and sensitive direct immersion-solid-phase microextraction-gas chromatography-time-of-flight mass spectrometry (DI-SPME-GC-ToFMS) method for the determination of multiresidue pesticides in grapes employing a PDMS-modified PDMS/DVB coating was developed utilizing multivariate approaches for optimization of the most important factors affecting SPME performance. A comprehensive investigation of appropriate internal standards using a bottom-up approach led to the selection of suitable compounds that adequately covered a range of 40 pesticides pertaining to various classes. The validated method yielded good accuracy, precision, and sensitivity and has been successfully applied to the analysis of commercial samples. With regard to the limitations of the proposed method, the DI-SPME method did not provide a satisfactory performance toward more polar pesticides (e.g., acephate, omethoate, dimethoate) and highly hydrophobic pesticides, such as pyrethroids. Despite the challenges and limitations encountered by this method, the practical aspects of the PDMS-modified coating demonstrated here create new opportunities for SPME applied in food analysis.