Integration of Continuous Flow Reactors and Online Raman Spectroscopy for Process Optimization

This report with recommendations is the result of an expert panel meeting on PAT applications in food industry that was organized by the M3C Section of the European Society of Biochemical Engineering Science (ESBES) at the 10th ESBES Symposium. The aim of the panel was to provide an update on the present status of the subject and to identify critical needs and issues for wider applications of PAT in food industry. A brief description of the current state-of-the-art and industrial uptake of the methodology is provided in this report. It concludes with a number of recommendations to facilitate further developments and a wider application of PAT in food industry. Process Analytical Technologies (PAT) [1] (European Medicines Agency EMA-FDA pilot program for parallel assessment of Quality by Design applications; Document EMA/172347/2011) have been extensively discussed in literature, particularly with respect to (bio)pharmaceutical process modelling, monitoring and control [2]. Table 1 provides an historic overview of the PAT development in the context of food applications. Although successful applications within food industry are increasingly being reported [3, 4], the session on PAT in food industries at the ESBES-IFIBiop 2014 in Lille highlighted significant challenges and opportunities for further development in this area. This position paper briefly reviews the current state-of-the-art, industrial needs and opportunities as well as scientific challenges to be addressed in order to extend the use of PAT methodology in the food industries. Currently, quality and safety control are still based mainly on discontinuous analysis with traditional analytical methods in the lab or, at best, at-line measurements. This is no longer sufficient to fulfill the needs of the food industry. Due to higher safety and quality standards and demands and high throughput of production facilities, the number of samples to be analyzed is increasing. Rapid analysis methods and PAT are required to address these needs along the complete production chain leading to a better understanding and control of raw materials, intermediate products in the production process as well as the final products to be packaged and delivered. The goal is to achieve real time analysis in order: • to avoid usage of any out-of-specification raw material and to detect adulteration, substitution, tampering and counterfeiting leading to non-authentic products; • to be able to intervene and stop/change processes in order to secure the target quality; • to assess the final quality to avoid out-of-specification products being packaged and shipped, thus leading to undesirable customer dissatisfaction and costs associated with the resolution of complaints. Over a hundred years ago (on May 22nd, 1913) the first patent on a PAT device ("Pfeiffenanalysator" for measuring the ratio of H2 and N2 gas for ammonia synthesis) was granted to Paul Gmelin from Badische Anilin- und Soda-Fabrik, BASF (Patentschrift Nr. 281157, Klasse 42/. Gruppe 4). Since then, PAT found broad application in chemical industry, which is dominated by highly automated, continuous processes. Today in chemical processes, such as the synthesis of isocyanates, e.g. hexamethylendiisocyanate (HDI), typically 60-130 PAT measurements are collected. In contrast, in sectors like (bio)pharmaceutical or food industry, the application of PAT is significantly less frequent today, especially, in terms of on-line analytics, where the measurement takes place in or close to the production step (or unit operation). One reason for this is the reduced degree of automation of the processes in these industries, which are dominated by unit operations, single production steps consecutively executed after each other, resulting in production batches. Analytics of a production batch takes place mostly off-line in analytical laboratories during hold-up times of the process intermediate between the different unit operations. Regulatory requirements represent an equally important driver for extensive online analytics. With the 2004 FDA's Quality by Design initiative, regulatory agencies demand systematic risk based process development and understanding of the processing space. This also allows for flexible process adjustments within the explored space for producing the desired product quality. In order to achieve the required understanding, more extensive analytical data is required, ideally obtained in-time on raw materials, process intermediates and ideally also on product quality attributes. In food industry, where typically high product titers are obtained, product analytics is sometimes possible by in-line measurements, such as spectroscopy (section 4). In biopharmaceutical processes, product titers are usually very low, the products are proteins with high molecular weight, and quality attributes are challenging to analyse. In these situations, online sampling with automated sample preparation and analytics may open up a solution [5]. But, identifying and implementing analytical methods, which are fast enough for delivering results on product quality attributes (e.g. protein glycosylation) in time, during the unit operation for allowing process modulation, remains a challenge. The overall typical goals in industry are high safety, high and stable product quality, high yield, low consumption of resources (materials, energy, room, time, and people), reduced influence of variability in raw materials as well as an increased shelf life of products which holds also in food processes. However, compared to the chemical and biopharmaceutical industries, food industry has to deal with certain characteristics, which renders PAT a formidable challenge in this context. The characteristic features in food industry are: • Raw materials are not pure substances: they are complex combinations of pure substances with varying compositions • Raw materials are soft, variable size, fragile and slippery • Physical properties of raw materials depend heavily on temperature, pressure, moisture and harvesting, and storage conditions • Raw materials undergo usually a phase transformation during processing and hence change their physical properties during processing • Micro processes (physical, (bio)-chemical, microbiological) are frequently not known • Highly perishable products. Here the challenge is to produce good quality, which maintains for a long time (shelf life) • High demand for hygiene These characteristics lead to a challenge for the application of sensors in the food industry. For important quality and process variables, such as sensory assessment, micro flora or spoilage, reliable and robust sensors are not yet available. Moreover, the sensors which are available are typically used only in isolated applications and frequently provide insufficient reliability. They are often not integrated in a common data management infrastructure. The materials of construction do not always consider suitability of contact with food and the solutions developed within advanced research projects frequently demand high care and maintenance. One reason why PAT is not as common as in other areas is that in food industry knowledge from various subject areas is necessary (such as physics, chemistry, biology, mathematics, informatics, engineering, nutritional science). For unit operations mathematical models are available in principle, but frequently they are too complicated to adapt. One of the biggest challenges in food industries is the dynamic nature of the processes. Changes in geometry, porosity, microstructure, solubility as well as mass and energy transfer coefficients must be addressed. Mostly gradients of temperature and moisture have to be considered as well as changes in kinetic parameters during process run. End product qualities like color, smell and 'brokens' also strongly influence the process. Therefore, food processes can be considered to be significantly more complex then chemical and bio-pharmaceutical processes. To achieve more stable processes PAT applications are necessary to check the quality of the raw and processed materials and their relationship to each other. If the quality is changing, then control actions resulting in online parameter changes are required in order to maintain constant product quality. Measurement systems are required, which guarantee that the process is in accordance with recipe and formulation. Furthermore, disturbances must be compensated for using control actions to reduce process variability and to conform to food regulations. As Glassey [6] argues, PAT methodology can aid in product design and testing as well as in ensuring full compliance with the HACCP and ISO 22000:2005 requirements during processing. As demonstrated below, PAT methodologies have the potential to aid the identification of critical control points and their critical limits, their effective monitoring and control, but also effective communication with suppliers and customers. Documentation which requires measurements of important variables is especially important so that traceability can be guaranteed. Here PAT has to deliver the corresponding measurement systems. Clearly a high demand for PAT in food industry is evident as is the need for further developments in the science and technology that help address the specific challenges posed by the characteristics of the food industry highlighted above. The complexity of raw materials that are typically soft and easily damageable is arguably one of the major scientific and technological challenges in food industry. During storage and processing the quality of such raw materials can decline due to oxidation processes, pressure and temperature effects. In addition, the visual impression of the final product (i.e. its appearance) is much more important than in other industries due to the fact that this will influence the purchase decision of the consumer. During the whole processing from raw material to the storage of the final product, hygiene is of utmost importance. Therefore non-invasive sensor systems are required in these applications. Measurement systems based on optical principles are particularly suitable from this perspective. Such measurement systems, including near infrared (NIR), Raman and fluorescence spectroscopy as well as computer-assisted image-based systems, potentially have a number of advantages in food process supervision and automation. Spectroscopic methods and imaging devices are well suited for PAT purposes because they are fast, non-destructive, provide multiple chemical information, allowing remote in-process analysis via fiber optics or instruments mounted directly on-line. Fluorescence spectroscopy is the most sensitive spectroscopic technique. Recently, many applications have been developed using fluorescence techniques [3, 7, 8]. Raw materials, the supervision of processing as well as product quality and the contamination of the equipment can be monitored by fluorescence. For example, Everard et al. [3] presented a method for detection of fecal contamination on spinach leaves. They coupled three hyperspectral imaging (HSI) configurations with two multivariate image analysis techniques and compared fluorescence imaging in the visible region with ultra violet and violet excitation sources, and reflectance imaging in the visible to near-infrared regions. They showed, that both fluorescence configurations had 100% detection rates for fecal contamination up to 1:10 dilution level and violet HSI had 99% and 87% detection rates for 1:20 and 1:30 levels, respectively. Everard et al. emphasized that on-line detection of fecal contamination on leaves has the potential to reduce the cases of food borne illnesses and their associated costs. A similar approach is presented by Lee et al. [7] where bovine faeces on Romaine lettuce and baby spinach leaves were investigated. They pointed out that two-band ratios using bands at 665.6 nm and 680.0 nm for lettuce and at 660.8 nm and 680.0 nm for spinach effectively differentiated all contamination spots applied. Grote et al. [8] described a fluorescence measurement technique to monitor a sourdough fermentation process. For the prediction of pH value and acidity during rye sourdough fermentations they applied partial least squares regression and principal component regression models for prediction and compared them with an evaluation where principal component analysis was combined with artificial neural networks. Depending on process operation and evaluation technique the average percentage root mean square errors of prediction for pH values were between 2.5 and 5.1%. For the prediction of the acidity level, the best results were between 6.0 and 8.1%. Liu et al. [9] used the Hoffman reaction to convert acrylamide to a compound which shows strong fluorescence emission at 480 nm. They showed good correlation of acrylamide in the range of 0.015 μg/mL to 20 μg/mL. Using this technique the food security will be increased. A fluorescence imaging device to detect deli residues on deli slicers were used by Beck et al. [10] processing four cheeses and four processed meats. The authors suggested that a fluorescence imaging device can be applied for routine use even in delicatessens. Fig. 1 clearly shows that the application of fluorescence for the monitoring of food processes increased from less than 10 before 2003 to more than 60 a year since 2013. This figure includes all papers from a search containing the key words "Food" and "Fluorescence". Although most of these papers describe laboratory applications rather than industrial PAT applications, they indicate potential future applications in this technology in food industry. Number of published papers obtained from the Scopus database searching for the words "Food" and "Image analysis" or "Raman" or "Near infrared spectroscopy" or "Fluorescence spectroscopy". Raman spectroscopy can only be applied if no fluorescence occurs in the corresponding excitation range. He et al. [11] applied the surface enhanced Raman scattering spectroscopy to detect banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. They concluded, that Raman spectroscopy and chemometric evaluation techniques can be used to identify banned food additives to ensure food safety. Ilaslan et al. [12] presented a method based on Raman spectroscopy to provide a rapid method for evaluating the quantitative analysis of glucose, fructose, and sucrose in soft drinks. Wang et al. [13] applied a Raman spectrometer as a process analyzer to monitor the wine fermentation. They demonstrated that sugar, ethanol and glycerol can be measured on-line with high correlation (higher than 0.98) to the HPLC reference measurements. Nache et al. [14] investigated Raman spectra from pork meat to monitor the early postmortem lactate accumulation and pH decline. They suggested that the locally weighted regression applied to the standard normal variate (SNV) normalized Raman spectra provide one of the most accurate and robust models with a cross-validated coefficient of determination (r2cv) of 0.97 for pH and lactate, a cross-validated root mean square error (RMSECV) of 4.5 mmol/kg for the lactate prediction and 0.06 pH-units for the pH prediction. These results demonstrate significant potential of combining chemometrics and Raman spectroscopy for on-line meat quality control applications. Fig. 1 shows the number of papers recorded in Scopus (search words "Food" and "Raman"). Compared to fluorescence, the number of papers describing Raman spectroscopy is twice as high in recent years with a significant rate of increase, demonstrating the increasing interest in this method for food process monitoring. Computer vision systems enable one of the main aspects of consumer preference – the appearance of a product – to be inherently considered. Therefore, computer vision systems for the supervision of food processing also gained importance over the years. An overview of several examples is given by Sun [15]. Especially the supervision of food drying processes is discussed by Aghbashlo at al. [16]. They pointed out that there is a large unexploited potential in the image data captured during various food processing operations. More informative feature extraction algorithms or novel pattern recognition procedures have to be developed. Paquet-Durand et al. [4] described a system for the supervision of the baking process. They demonstrated, by using the Viola–Jones-algorithm as well as neural networks, that the pastry can be identified and the volume increase as well as color development can be monitored. To detect defective apples Zhang et al. [17] used a computer vision system, which was combined with an automatic lightness correction system. For 160 samples they showed a 95% overall detection accuracy. For the evaluation they used a weighted relevance vector machine classifier. Fig. 1 shows the number of papers over time from Scopus searching for "Food" and "Image analysis". Here the applications start earlier compared to the spectroscopic methods, the number of applications per year is higher than in the case of spectroscopic applications; except in the year 2014, where more reports of Raman applications were published. Moreover imaging systems using visible and NIR region are available to perform quality checks based on the spectroscopic information derived from each point in the image. One example is the on-line analysis of the widely varying fat distribution in salmon for sorting purposes [18]. Near infrared (NIR) is a well-established method for rapid analysis of food raw materials and products [18], either on-/in-line, at-line or off-line. In the lab or at-line multiple components such as fat, protein, moisture and many more, can be analyzed without any sample preparation in all kinds of liquid, solid and semi-solid samples. Raw materials can be verified for identity and further characterized regarding composition already in the goods reception. The composition, freshness and adulteration of edible oils [19], e.g. olive oil [20], can be analyzed rapidly before a truck is unloaded. Many other sample types like meat, grains, flour, dairy products [21] and others can be analyzed. Even mixtures like vitamin premixes can be analyzed to make sure that the correct material was delivered and can be used in production. There are several approaches and technologies for PAT available, ranging from simple filter based devices over dispersive diode array spectrometers to Fourier-Transform (FT)-NIR instruments. Samples can be analyzed in-line by fiber optic probes or by contactless systems (Fig. 2). Smaller instruments can be directly attached to pipes, chutes or in other installations. A) NIR reflection probe in a fluid bed dryer. (B) Probe head for contactless measurement of grain and other solids. Applications cover a broad range from a simple monitoring of moisture content of a product on a conveyor belt to more complex control situations. In dairy industry there are demands to control milk powder production by monitoring the feed of the spray tower and the powder after fluid bed drying. Other important production steps to control are the standardization of milk, cream, whey and concentrates [22]. In frying processes with big volumes of oil an in-line monitoring of the oil quality with regards to acid value, anisidine value and the content of polar and polymerized components [23] are of particular interest. Another example of high volume processes where monitoring of protein, moisture and ash is important is the milling of grain to flour and the production of cereals of any kind. Finally there are more and more fermentation processes controlled by in-line NIR to optimize the conditions and follow the feeding and consumption cycles during biomass buildup [24]. In 2013 roughly 120 papers were published, however the recent increase is not as steep as in the case of Raman spectroscopy (Fig. 1). The economic benefits due to PAT can be attributed to higher product quality and yield as well as decreased product variation. This will reduce the overall production costs significantly and increase competitiveness. Furthermore, the knowledge and understanding of the process will increase. However, the level of automation in industrial food processes is significantly lower compared to the chemical and pharmaceutical processes. This is partly due to the complexity of food processes. On the other hand, the lack of reliable sensor systems to determine important process parameters and variables contributed to this in the past. Sensors represent a fundamentalpart of all automation systems, although they only represent a part of the requirements for wider application of PAT in food industry. The areas of further development and recommendations enabling more extensive use of the PAT within this industry also include: • Further industrial case studies and wider dissemination of the positive impact of reliable sensor technology in raw material and product quality as well as process monitoring. • Operational and maintenance requirements of sensor technologies will remain a significant aspect of future sensor technology uptake in this industry. • Data management and analysis software will play a significant role in extending the PAT application within the food industry. Platform solutions, preferably supporting wireless data transfer, at competitive pricing levels are required. • Cost benefit analysis studies are particularly important given the business drivers of this industry. • The impact of PAT is likely to be more pronounced in the new processes, although it is important to continue to encourage the application of PAT approaches within established food processes to enhance the process economics and compliance with the standards ensuring safe food supply chains. • PAT can significantly contribute to the stringent traceability and documentation requirements, although issues of compatibility and data standardization will impact upon data management systems employed by the companies within the supply chain. The authors declare no financial or commercial conflict of interest.

A continuous flow reactor setup as a tool for rapid synthesis of micron sized NaA zeolite

The maleation of polypropylene melt with a peroxide as free radical initiator has been carried out isothermally in a continuous flow reactor and in a batch flow reactor. The continuous flow reactor is designed to provide significant levels of extensional strain in the fluid while the batch flow reactor provides a simple shear flow with uniform residence time. In both reactors, less than 1 part per hundred of dicumyl peroxide (dissolved in xylene) is added to a preblended single phase mixture of polymer melt and dibutyl maleate. The relative extent of maleation is much higher in the continuous flow reactor than in the batch reactor with comparable shear strain rates and mean residence times. As the feed rate and the rotation speed are varied at a fixed temperature in the continuous flow reactor, the highest degree of maleation is obtained under conditions where fluid dynamics computations show the stretching of a fluid element to be the greatest. Hence, increasing shear alone leads to rather limited increases in extent of maleation. These results emphasize the importance of the detailed deformation field for carrying out functionalization reactions on polymer melts.

One of the obstacles preventing the commercialization of colloidal nanoparticle catalysts is the difficulty in fabricating these materials at scale while maintaining a high level of control over their resulting morphologies, and ultimately, their properties. Translation of batch-scale solution nanoparticle syntheses to continuous flow reactors has been identified as one method to address the scaling issue. The superior heat and mass transport afforded by the high surface-area-to-volume ratios of micro- and millifluidic channels allows for high control over reaction conditions and oftentimes results in decreased reaction times, higher yields, and/or more monodisperse size distributions compared to an analogous batch reaction. Furthermore, continuous flow reactors are automatable and have environmental health and safety benefits, making them practical for commercialization. Herein, a discussion of continuous flow methods, reactor design, and potential challenges is presented. A thorough account of the implementation of these technologies for the fabrication of catalytically active metal nanoparticles is reviewed for hydrogenation, electrocatalysis, and oxidation reactions.

Innovative determination of the specific anammox activity for anammox sludge from continuous flow reactors: A comparison between continuous flow test and batch test

Introduction: This work was carried out to understand if a heterogeneous biocatalytic hydrogenation system could be implemented in a slurry mode continuous flow reactor, as a “slot-in” alternative to a metal/carbon catalyst with minimal process or chemical engineering development.Method: Biocatalytic hydrogenation was compared to metal (Pd/C) catalysed hydrogenation for ketone to chiral alcohol conversion in both a continuous flow reactor (Coflore ACR, AM Technology) and analogous scaled down batch reactions.Results and discussion: Initial results demonstrated that batch reactions can achieve high conversions in 30 min, with relatively low biocatalyst loadings, meeting critical criteria for operation as continuous slurry mode process. Further results demonstrated full conversion of quinuclidinone to (3R)-quinuclidinol in continuous flow under mild conditions (35°C, 2 bar H2). On intensification of the process to higher substrate loading (50 mM), conversion was similar to with Pd/C, however the biocatalytic system achieved far higher turnover frequency and total turnover number (65 min−1 and 20,000, respectively) than the metal system (0.16 min−1, 37). Comparison to an analogous batch reaction highlights that the biocatalytic system has promise for further optimisation and intensification in the scalable Coflore ACR. Overall, biocatalytic hydrogenation is shown to offer a decarbonised biocatalytic route and a “slot-in” replacement to metal catalysts for hydrogenation reactions in continuous flow reactors.

Design of continuous-flow microwave reactor based on a leaky waveguide

Improving treatment efficiency and reducing investment and operating costs make aerobic granular sludge technology (AGS) a promising technology for treating aquaculture wastewater. The development of continuous flow reactors (CFRs) has become a new direction in the research of AGS. This study clarifies the granulation effect, hydrodynamic behavior and particle separation of three different CFRs (R1 to R3). The established CFD model was able to explain the hydrodynamic behavior in all three CFRs; in particular, R3 performed the best from the perspective of hydrodynamic behavior due to its abundant turbulence. In addition, the optimal baffle distance and baffle angle of R3 were simulated to be 40 mm and 60°, respectively, due to them providing the best turbulent flow and particle separation effect. However, an overlarge baffle angle could weaken the turbulent pattern in the reactor. The retention time distribution further confirmed the reasonability of these optimal parameters with the highest effective volume ratio of 0.82. In short, this study gives an instruction for exploring the rapid formation mechanism of AGS in a CFR to promote its engineering application.

Fatty acid methyl esters derived from renewable sources such as vegetable oils has gained importance nowadays as an alternative fuel for diesel engines. The present study is aimed to produce biodiesel from non-edible oil (Karanja oil of Indian origin) both in batch and continuous reactors. The purpose of the study is the comparison of Karanja biodiesel production with different reactor types under variable reaction characteristics. Therefore, two types of continuous reactors were used: helical tube reactor and reactive distillation (RD) column. Experiments were carried out to obtain suitable operating parameters in batch- and continuous-flow reactors. For batch reactor, suitable operating conditions obtained are: 7:1 methanol-to-oil molar ratio, 0.8% (by weight of oil) catalyst (KOH), 65°C reaction temperature, and 1-h reaction time, at which the maximum yield obtained is 96%. In continuous helical tube reactor, maximum yield of 92.6% was obtained at 6.6 mL/min of flow rate at the same operating conditions of batch reactor. In continuous RD column, maximum yield of biodiesel 96.6% was obtained at the same operating conditions except methanol-to-oil molar ratio (5:1) because of recycling of methanol into the column. The residence times in the helical tube reactor and RD column were 4 and 8 min, respectively, as compared to 1 h in the batch reactor for almost the same yield.

The predominant working hypothesis of Alzheimer's disease is that the proximate pathologic agents are oligomers of the amyloid β-protein (Aβ). "Oligomer" is an ill-defined term. Many different types of oligomers have been reported, and they often exist in rapid equilibrium with monomers and higher-order assemblies. This has made formal structure-activity determinations difficult. Recently, Ono et al. [Ono, K., et al. (2009) Proc. Natl. Acad. Sci. U.S.A. 106, 14745-14750] used rapid, zero-length, in situ chemical cross-linking to stabilize the oligomer state, allowing the isolation and study of pure populations of oligomers of a specific order (number of Aβ monomers per assembly). This approach was successful but highly laborious and time-consuming, precluding general application of the method. To overcome these difficulties, we developed a "continuous flow reactor" with the ability to produce theoretically unlimited quantities of chemically stabilized Aβ oligomers. We show, in addition to its utility for Aβ, that this method can be applied to a wide range of other amyloid-forming proteins.

Synthesis of biodiesel fuel by enzymatic methanolysis of vegetable oil is promising because of the indifference of such a process to the quality of the feedstock. In order to reduce costs, it is convenient to use as the catalyst immobilized cells of lipolytic microorganisms, without separation of pure lipases. We studied methanolysis of sunflower oil in a continuous flow reactor and a stirred tank reactor when using immobilized Aspergillus niger mycelium and Yarrowia lipolytica cells, both free and immobilized, as the catalyst. In the continuous flow reactor, up to 62.2% yield of fatty acid methyl esters is achieved when using Aspergillus niger cells.

The importance of a compound that helps fight against influenza is, in times of a pandemic, self-evident. In order to produce these compounds in vast quantities, many researchers consider continuous flow reactors in chemical industry as next stepping stone for large scale production. For these reasons, the synthesis of N-acetylneuraminic acid (Neu5Ac) in a continuous fixed-bed reactor by an immobilized epimerase and aldolase was investigated in detail. The immobilized enzymes showed high stability, with half-life times > 173 days under storage conditions (6 °C in buffer) and reusability over 50 recycling steps, and were characterized regarding the reaction kinetics (initial rate) and scalability (different lab scales) in a batch reactor. The reaction kinetics were studied in a continuous flow reactor. A high-pressure circular reactor (up to 130 MPa) was applied for the investigation of changes in the position of the reaction equilibrium. By this, equilibrium conversion, selectivity, and yield were increased from 57.9% to 63.9%, 81.9% to 84.7%, and 47.5% to 54.1%, respectively. This indicates a reduction in molar volume from N-acetyl-ᴅ-glucosamine (GlcNAc) and pyruvate (Pyr) to Neu5Ac. In particular, the circular reactor showed great potential to study reactions at high pressure while allowing for easy sampling. Additionally, an increase in affinity of pyruvate towards both tested enzymes was observed when high pressure was applied, as evidenced by a decrease of KI for the epimerase and KM for the aldolase from 108 to 42 mM and 91 to 37 mM, respectively.

Reductive amination of levulinic acid or its derivatives to pyrrolidones over heterogeneous catalysts in the batch and continuous flow reactors: A review

Scenedesmus species, immobilized on alginate gel, was found effective in removing nitrate, atrazine, magnesium, phosphorus, zinc, oxadiazon, and triallate from groundwater in a continuous flow reactor. The laboratory-scale experiments with synthetic groundwater, made of 8.8mg/L NO3 -N and 90µg/L atrazine, were performed at a hydraulic retention time of 7days and the temperatures of 20 and 35°C. The highest uptake of nitrate and atrazine was observed at 20°C (97% and 70%, respectively). When tested in actual groundwater, 92% of nitrate, 100% of magnesium, 99.9% of phosphorus, and 92% of zinc were successfully removed at the end of 29days' treatment operations. The algal beads removed 100% of oxadiazon and triallate in the first 10days, but some of the herbicides diffused back into the solution toward the end of the treatment process. PRACTITIONER POINTS: Immobilized algae-alginate beads can remove nitrate, atrazine, oxadiazon, and triallate from groundwater in continuous flow reactor. The uptake rate of nitrate and atrazine is higher in room temperature (20°C). Same algae beads could be reused for herbicide uptake for the average of 10days. The immobilized system is a natural sustainable alternative that can be used in groundwater pump and treat.

The present paper involves a detailed study of the selective catalytic reduction of nitrates in aqueous mediums by the use of H2 in the presence of O2 over monometallic and bimetallic supported catalysts. In this study, an attempt has been made to improve the denitrification efficiency (XNO3(-), SN2) of several catalysts by regulating some experimental parameters that are involved in the process. Therefore, the effects of the type of reactor (semi-batch reactor vs continuous flow reactor), the nature of the active phase (Pd, Cu, and Pd-Cu) and the particle size of γ-Al2O3 spheres (particle diameter = 1.8 mm and 3 mm) on catalytic activity and reaction selectivity, as well as the adsorption capacity of γ-Al2O3 spheres for nitrates, were examined. As the review indicates, most of the research has so far been conducted on batch or semi-batch reactors. This study successfully demonstrates the benefits of using a continuous flow reactor in terms of catalytic activity (XNO3(-), %) and reaction selectivity (SN2, %). Another important aspect of this study is the crucial role of bimetallic Pd-Cu clusters for the prevention of NH4(+) formation. Moreover, the use of 1.8 mm diameter γ-Al2O3 spheres as a support was proved to significantly enhance the catalytic performance of bimetallic Pd-Cu catalysts towards nitrate reduction compared to 3 mm diameter γ-Al2O3 spheres. This difference may be attributed to mass (NO3(-), OH(-)) transfer effects (external mass transfer phenomena).