Water Monitoring Applications Research Articles

Real-time cationic sensing using plasmonic fiber optic sensor based phosphoryl-carrageenan

We report Fiber Optic-Localized Surface Plasmon Resonance (FO-LSPR) spectroscopy sensors comprising a coating of spherical silver nanoparticles (AgNPs) embedded in phosphoryl-carrageenan. This is a novel report on modified carrageenan namely phosphoryl-carrageenan as sensing materials for cations specifically ammonium ions (NH4+). The morphology of carrageenan and phosphoryl-carrageenan coatings on the fiber optic probe was uneven and wavelike topography, indicating the successful coating on the fiber optic probe surface. The FO-LSPR showed a distinct dip in reflectivity in the region of 370–400 nm due to the resonance frequency of spherical AgNPs. The response and recovery times of FO-LSPR sensors for 1 ppm NH4+ and deionized water were <20 s and ∼1.2 minutes, respectively, with five times stable repeatability. The sensitivity of the FO-LSPR phosphoryl-carrageenan was 3.441 nm/ppm. Equally, the limits of detection and quantitation of fiber optic FO-LSPR were 0.336 and 1.018 ppm, respectively. Meanwhile, the dynamic range of the FO-LSPR was 0.3 – 2.0 ppm. The proposed sensor demonstrated strong selectivity towards NH4+ over common cationic interferents. Furthermore, the reported FO-LPSR sensor offered a comparable measurement performance to current methods, while being low cost and portable, and allowing in-situ real-time monitoring of cation ammonium. Thus, reported FO-LPSR sensors are highly promising for water monitoring applications.

Research on high-power and high-efficiency emission of crosswell electromagnetic logging

Crosswell electromagnetic (EM) logging has useful applications in oil, gas, and water monitoring as well as carbon sequestration estimation. Difficulties in the efficient propagation of EM waves through a steel casing inhibit crosswell EM logging at distances greater than 300 m. This study investigates whether high-power transmission and high-efficiency transmitting antennas can resolve the challenges of long-distance crosswell EM logging through steel casings. Theoretical analysis indicates that the emission moment should be at least 12,000 A·m2. By calculating the equivalent relative permeability and selecting the appropriate coil materials and magnetic cores, the maximum emission magnetic moment can create a high-power transmission. Based on series and parallel resonant circuits and the alternating current/direct current cable core multiplexing power supply method, the effective transmission bandwidth is broadened and the transmission efficiency increases by three times. The emission unit is fabricated and tested using single, double, and fiberglass casing. We observe that the crosswell EM technology performs better for nonmetal casing wells than that for metal casing wells. The amplitude and phase curves between two fiberglass casing wells in the range of 425 m are quite smooth. However, the receiving signals in the double-layer steel casing decrease to only a few tenths of the value in the fiberglass casing wells, highlighting the difficulty of long-distance EM wave transmission when using steel casings. Thus, studies on EM transmission through four or more layers of steel casings should be conducted in the future.

A low-cost and portable fluorometer based on an optical pick-up unit for chlorophyll-a detection

Chlorophyll-a (Chl-a) fluorescence detection is an important technique for monitoring water quality. In this work, we proposed an approach that employs the mass-produced low-cost optical pick-up unit (OPU) extracted from the high-definition digital versatile disc (HD-DVD) drive as the key optical component for our chlorophyll-a fluorometer. The built-in blue-violet 405 nm laser diode of the OPU acts as the excitation light to perform laser-induced fluorescence (LIF). The laser driver and a series of intrinsic lenses within the OPU, such as an objective lens with a numerical aperture (NA) of 0.65 and a collimating lens, help reduce the size, cost, and system complexity of the fluorometer. By integrating off-the-shelf electronic components, miniaturized optical setups, and 3D-printed assemblies, we have developed a low-cost, easy-to-make, standalone, and portable fluorometer. Finally, we validated the performance of the device for chlorophyll-a fluorescence detection under laboratory and on-site conditions, which demonstrated its great potential in water monitoring applications. The limit of detection (LOD) for chlorophyll-a is 0.35 μg/L, the size of the device is 151 × 100 × 80 mm3, and the total cost of the proposed fluorometer is as low as 137.5 USD.© 2023 Elsevier Science. All rights reserved.

An evaluation of a spectral fluorometer for monitoring chlorophyll a in New York State lakes

Prestigiacomo AR, June SG, Gorney RM, Smith AJ, Clinkhammer AC. 2022. An evaluation of a spectral fluorometer for monitoring chlorophyll a in New York State lakes. Lake Reserv Manage. 38:318–333. The quantification of chlorophyll a in surface waters through sampling and laboratory extraction methods has limitations, including the lack of phytoplankton composition analysis and delayed analysis time. Recently, automated instruments have been developed to quickly provide estimation of total chlorophyll a and characterize phytoplankton composition into functional groups. Here, we analyzed a dataset of paired, laboratory-extracted chlorophyll a samples (Chl-a) and chlorophyll a estimated from a spectrofluorometer (FluoroProbe, bbe Moldaenke; FPChl-a) for comparability at several time scales. We found that FPChl-a was highly correlated to Chl-a (r > 0.8) but overestimated Chl-a by 1.5–2 times on average. Summer average FPChl-a was higher than summer average Chl-a, resulting in incorrect lake evaluations against selected thresholds. Linear least squares regression of Chl-a/FPChl-a was highly significant (P < 0.01) and demonstrated a good fit (r2 > 0.75) but had high variability, consistent with FPChl-a performance values reported in the scientific literature. Factors such as FPChl-a magnitude and algal dominance were statistically important factors affecting the Chl-a/FPChl-a relationship. We developed a multiple linear regression method for postcalibrating FPChl-a to equivalent Chl-a values (adjusted FPChl-a) and applied it to the FPChl-a dataset. Adjusted FPChl-a values were unbiased and compared well with Chl-a (mean residual equal to 0 µg/L). Adjusted FPChl-a summer averages resulted in correct waterbody evaluation in more than 90% of lakes. We propose that the FluoroProbe, properly postcalibrated to adjusted FPChl-a, can be used as a surrogate of Chl-a in open water monitoring applications, reducing the need for traditional laboratory Chl-a samples for lake monitoring and management.

IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water.

The in-line determination of chemical parameters in water is of capital importance for environmental reasons. It must be carried out frequently and at a multitude of points; thus, the ideal method is to utilize automated monitoring systems, which use sensors based on many transducers, such as Ion Selective Electrodes (ISE). These devices have multiple advantages, but their management via traditional methods (i.e., manual sampling and measurements) is rather complex. Wireless Sensor Networks have been used in these environments, but there is no standard way to take advantage of the benefits of new Internet of Things (IoT) environments. To deal with this, an IoT-based generic architecture for chemical parameter monitoring systems is proposed and applied to the development of an intelligent potassium sensing system, and this is described in detail in this paper. This sensing system provides fast and simple deployment, interference rejection, increased reliability, and easy application development. Therefore, in this paper, we propose a method that takes advantage of Cloud services by applying them to the development of a potassium smart sensing system, which is integrated into an IoT environment for use in water monitoring applications. The results obtained are in good agreement (correlation coefficient = 0.9942) with those of reference methods.

Multitemporal Water Extraction of Dongting Lake and Poyang Lake Based on an Automatic Water Extraction and Dynamic Monitoring Framework

Timely and accurate large-scale water body mapping and dynamic monitoring are of great significance for water resource planning, flood control, and disaster reduction applications. Synthetic aperture radar (SAR) systems have the characteristics of strong operability, wide coverage, and all-weather data availability, and play a key role in large-scale water monitoring applications. However, there are still some challenges in the application of highly efficient, high-precision water extraction and dynamic monitoring methods. In this paper, a framework for the automatic extraction and long-term change monitoring of water bodies is proposed. First, a multitemporal water sample dataset is produced based on the bimodal threshold segmentation method. Second, attention block and pyramid module are introduced into the UNet (encoder-decoder) model to construct a robust water extraction network (PA-UNet). Then, GIS modeling is used for the automatic postprocessing of the water extraction results. Finally, the results are mapped and statistically analyzed. The whole process realizes end-to-end input and output. Sentinel-1 data covering Dongting Lake and Poyang Lake are selected for water extraction and dynamic monitoring analysis from 2017 to 2020, and Sentinel-2 images from a similar time frame are selected for verification. The results show that the proposed framework can realize high-precision (the extraction accuracy is higher than 95%), highly efficient automatic water extraction. Multitemporal monitoring results show that Dongting Lake and Poyang Lake fluctuate most in April, July, and November in 2017, 2019, and 2020, and the change trends of the two lakes are the same.

RETRACTED: Monitoring Air Pada Water Torn Berbasis Android dan Mikrokontroller

Kendali dan monitoring air dalam sebuah tangki merupakan satu intrumentasi komputer yang diperlukan di industri. Tugas Akhir ini membahas tentang aplikasi monitoring air pada water torn secara otomatis berbasis android dan didukung oleh mikrokontroller. Salah satu bidang teknologi yang berkembang ialah teknologi mikrokontroller, dalam perancangan alat ini, menggunakan mikrokontroller NodeMCU sebagai pengolah data dan sensor ultrasonik sebagai input data serta buzzer, dan servo. Sensor ultrasonik merupakan suatu perangkat yang dapat mengukur jarak suatu objek dengan memanfaatkan pantulan gelombang ultrasonik. Monitoring air ini menggunakan firebase sebagai database untuk menyimpan data. Untuk menampilkan data pengukuran, perangkat antar muka dirancang pula dengan menggunakan perangkat lunak aplikasi android studio dalam bentuk grafik, status pompa, dan notifikasi air. Hasil pengujian menunjukan bahwa sensor ultrasonik yang digunakan mampu mengukur ketinggian air dari 2 cm sampai 20 cm dengan rata-rata kesalahan pengukuran 4,93%. Monitoring air yang dirancang mampu menghasilkan respon keluaran sistem sesuai dengan nilai referensi yang diberikan. Sebagai tambahan, monitoring ketinggian muka air dapat ditampilkan pada perangkat lunak android secara interaktif

Aplikasi Monitoring Air Pada Water Torn Secara Otomatis Berbasis Android dan Di Dukung Oleh Mikrokontroller

Control and monitoring of water in a tank is a computer instrumentation needed in industry. This research discusses a water monitoring application in water torn automatically based on android and supported by a microcontroller. One of the developing technology fields is microcontroller technology. In designing this device, it uses a NodeMCU microcontroller as a data processor and an ultrasonic sensor as data input as well as a buzzer and servo. An ultrasonic sensor is a device that can measure the distance of an object by utilizing reflected ultrasonic waves. This water monitoring uses firebase as a database to store data. To display measurement data, the interface is also designed using the Android Studio application software in the form of graphs, pump status, and water notifications. The test results show that the ultrasonic sensor used is able to measure water levels from 2 cm to 20 cm with an average measurement error of 4.93%. Water monitoring is designed to be able to produce a system output response according to the reference value given. In addition, water level monitoring can be displayed on the Android software interactively

Electrochemical Sensing of Arsenic Using Physically Vapor Deposited Au Nanofilm Electrodes: Flow Cell Configuration

There is a current need for an inline arsenic sensing system that can continuously sample aquifer water quality for well drilling and ground water monitoring applications. Concentrations of arsenic oxyanions above 10 μg/L in drinking water are considered dangerous by the World Health Organization [1]. Levels above this in daily consumption can lead to renal toxicity and a condition known as Arsenicosis, which produces lesions on the skin. We are currently developing an Au thin film, As stripping voltammetry flow cell sensing to meet this challenging need. Our findings show that use of gold (Au) nanofilm electrodes physically vapor deposited (PVD) onto porous carbon papers can detect concentrations below 10 μg/L of arsenite, As (III), in water. The nanofilms were characterized by SEM, X-ray diffraction and with X-ray fluorescence with a measured loading of approximately 13 μg of Au per 1 cm2 of carbon paper in each electrode. The PVD method increases the manufacturability of aqueous arsenic sensors because it is facile, scalable, and uses much less Au than screen printing methods. Linear stripping voltammetry (LSV) was used in a three-electrode configuration to create a calibration curve for standard additions of 5, 10, 25, 50 and 75 μg/L As (III). The resulting plot of peak area versus concentration resulted in a linear correlation. The capacitance of PVD deposited Au nano films was significantly less than that of Au nanoparticles on XC72 carbon, produced via solution precipitation methods. The lower capacitance enables the detection of low concentrations of As without the need for the application of more complex pulse voltammetry methods.

Wireless Underground Communications in Sewer and Stormwater Overflow Monitoring: Radio Waves through Soil and Asphalt Medium

Storm drains and sanitary sewers are prone to backups and overflows due to extra amount wastewater entering the pipes. To prevent that, it is imperative to efficiently monitor the urban underground infrastructure. The combination of sensors system and wireless underground communication system can be used to realize urban underground IoT applications, e.g., storm water and wastewater overflow monitoring systems. The aim of this article is to establish a feasibility of the use of wireless underground communications techniques, and wave propagation through the subsurface soil and asphalt layers, in an underground pavement system for storm water and sewer overflow monitoring application. In this paper, the path loss analysis of wireless underground communications in urban underground IoT for wastewater monitoring has been presented. The dielectric properties of asphalt, sub-grade aggregates, and soil are considered in the path loss analysis for the path loss prediction in an underground sewer overflow and wastewater monitoring system design. It has been shown that underground transmitter was able to communicate through thick asphalt (10 cm) and soil layers (20 cm) for a long range of up to 4 km.

A Frequency-domain optofluidic dissolved oxygen sensor with total internal reflection design for in situ monitoring

Continuous measurement of dissolved oxygen (DO) variation is important in water monitoring and biomedical applications, which require low-cost and low-maintenance sensors capable of automated operation. A frequency-domain optofluidic DO sensor with total internal reflection (TIR) design has been developed based on fluorescence quenching of Ruthenium complex (Ru(dpp) <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Cl <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ). To minimize artifacts causing drift in fluorescence measurements such as background autofluorescence, photobleaching, optical alignment variation, a low-cost frequency-domain approach is implemented in an optofluidic platform to measure the phase shift between the excitation and emission light. We show that the frequency domain optofluidic DO sensor provides absolute DO concentrations in repeated measurements. TIR design can enhance fluorescence signal in the integrated device and minimize background autofluorescence in the sample, which can subsequently improve overall sensitivity. Furthermore, photobleaching in the samples would be mitigated as the incident light does not enter the microfluidic channel. Our results demonstrate a measurement resolution of 0.2 ppm and response times of less than one minute. In accelerated photobleaching conditions, the long-term drift is shown to be less than ±0.4 ppm. These results suggest the potential of this optofluidic DO sensor as an in situ platform for water monitoring and biomedical applications.

Modeling of Smart Water Control Mechanism using IoT

The unexpected water demand has become a serious concern in the last few years. The increasing demand for water supply has posed a significant challenge for many countries around the world. Various factors, such as population growth, urbanization, and climate changes, have further exhausted water resources. Therefore, water conservation and natural resource management have become crucial factors for human survival. The proposed study presents the modeling of smart water control system based on IoT technology. The implementation of the proposed water control model is carried out using an analytical approach with cost-effective, functional modules using sensors and wireless communication system. The proposed smart water control mechanism is mainly designed for water distribution and monitoring application.

Integrated SPE-Self assembled MEPS platform for ultrasensitive determination of mononitrophenols in water: Experimental, computational and applicability studies

Integrated analytical approaches can be used to determine the trace concentrations of analytes in water matrices. Here we designed and compared two novel and facile, integrated polysaccharide adsorbent SPE-Self assembled MEPS (solid phase extraction and self-assembled microextraction by packed sorbent) protocols based on chitin, and cellulose acetate respectively, for simultaneously determining the ultralow concentrations of three mononitrophenols (MNPs) in water. In addition, we reported computational, and empirical, interaction profiling, for providing insights into the possible interactions among chitin-MNP, and cellulose acetate-MNP, respectively. The integrated SPE-MEPS analytical platform enhances the MNPs detection limits, scalability and recoveries from individual water matrices with the additional ease of use. Aside from offering improved control over lower scalability range (0.05–5 ng/mL) with both adsorbents Chitin and CA as compared to previous analogues reported methods, limits of detection (LODs) were as low as 0.01–0.03 ng/mL with Chitin and 0.008–0.025 ng/mL with CA, in quality control samples. By integrating SPE with MEPS, and chromatographic separations with high performance liquid chromatography-ultra violet detector (HPLC-UV), we were able to determine three MNPs at ppt (pg/mL) levels in different water matrices. This approach may find diverse applications in water monitoring at trace levels. Finally, and most importantly, to the best of authors knowledge, this study marks the first time that integrated SPE-MEPS analytical platform has been used for the efficient trace analysis in analytical chemistry.

Monitoring Application for Clean Water Access and Clustering using K-Means Algorithm

The purpose of this research is to develop a monitoring application of clean water access for the community and determining areas that need to improve access to clean water. Data collection was done by examining documents which were related to clean water management and conducting interviews with the Department of Housing and Settlement of West Java Province. The results of data collection are used to develop a clean water monitoring application system based on Android and Web. Data from the application will be used for clustering with the K-Means algorithm. For example, in the city of Bandung, 12 urban village areas were recommended for increasing access to clean water. The area has a percentage of ownership of clean water access approaching the value of 29.96% of the ownership of clean water sources for food and drink, 28.96% for ownership of other sources of clean water and 14.48% for ownership of reserves of clean water. The optimal number of clusters of clean water access in the city of Bandung is three clusters because it has the lowest Davies-Bouldin Index (DBI) value of 0.439.

Water monitoring using polymer inclusion membranes: a review

Water monitoring by conventional analytical methods is often complicated, time-consuming and laborious, requiring highly skilled personnel, thus calling for simpler, rapid and cost-effective methods. Polymer inclusion membranes (PIM) are of interest in environmental analysis due to their selectivity and sensitivity for the detection of a wide range of analytes such as metals. PIM have been used in the development of passive sampling, analyte separation and preconcentration, and sensing. PIM are also suitable for the automation of chemical analysis. Here we review PIM applications in environmental water monitoring.

Water quality prediction based on recurrent neural network and improved evidence theory: a case study of Qiantang River, China

Water quality prediction is an effective method for managing and protecting water resources by providing an early warning against water quality deterioration. In general, the existing water quality prediction methods are based on a single shallow model which fails to capture the long-term dependence in historical time series and is more likely to cause a high rate of false alarms and false negatives in practical water monitoring application. To resolve these problems, a new model combining recurrent neural network (RNN) with improved Dempster/Shafer (D-S) evidence theory (RNNs-DS) is proposed in this paper. Among them, the RNNs which can handle the long-term dependence in historical time series effectively are used to realize the preliminary prediction of water quality. And the improved D-S evidence theory is used to synthesize the prediction results of RNNs. In addition, an improved strategy based on correlation analysis method is presented for evidence theory to obtain the number of evidence, which reduces uncertainty in evidence selection effectively. Besides, a new basic probability assignment function which based on modified softmax function is proposed. The new function can effectively solve the problems of weight allocation failure in the traditional function. Then, data about permanganate index, pH, total phosphorus, and dissolved oxygen from Jiuxishuichang monitoring station near Qiantang River, Zhejiang Province, China is used to verify the proposed model. Compared with support vector regression (SVR) and backpropagation neural network (BPNN) and three RNN models, the new model shows higher accuracy and better stability as indicated by four indices. Finally, the engineering application of the RNNs-DS algorithm has been realized on the self-developed water environmental monitoring and forecasting system, which can provide effective support for early risk assessment and prevention in water environment.

Efficient Approach for Monitoring and Controlling Water Parameters Utilizing Integrated Treatment Based on WSNs

Research works of Wireless Sensor Networks (WSNs) applications and its constraints solutions occupy wide area around the world and attract many researchers. In this paper, an important one of environmental WSN applications is presented that is the water monitoring applications. An efficient approach for monitoring and controlling water parameters in real-time is implemented utilizing merging between WSN and designed simple workstation. For implementation simplicity, two water parameters (pH and temperature) are monitored and controlled in the proposed approach. Most of past work of water monitoring presented different proposed monitoring scenarios for different water parameters only. This research work utilizes the concept of interactive WSN nodes. The interactive nodes interact with the monitored water parameters to control its value. In the base station, the collected data is analyzed and the real-time value of the monitored parameters appears on the designed Graphic User Interface (GUI). The GUI is designed using the Matlab program. Through the GUI, the operator can switch the control between automatic and manual. ZigBee module is used for implementing the wireless communications between the nodes and the workstation. Due to the cost and simplicity, two sensors only are used in the proposed approach. Different real-time experiments are performed to test and measure the effectiveness and performance of the presented approach. These experiments reveal that the presented approach is effective for water treatment and efficient more than the past proposed water monitoring scenarios.

A fluorimetric nitrite biosensor with polythienothiophene-fullerene thin film detectors for on-site water monitoring.

A novel fluorimetric sensor for highly sensitive nitrite detection on the site is presented in this study. The proposed on-chip approach comprises the use of integrated polymer photodetectors to detect light from fluorescence reactions with a diaminofluorescein probe. The detectors were prepared with a heterostructured nanofilm of polythieno[3,4-b]thiophene/benzodithiophene and (6,6)-phenyl-C71-butyric-acid methyl-ester as a photoactive layer. Prior to fluorimetric detection, the quality of the spin-coated photoactive layer was characterized via nano-morphology and current-density measurements. Nitrite assays were conducted on a poly(methyl methacrylate) microchannel chip, to which polythienothiophene-C71 based detectors were aligned. Results of signal-to-noise ratio determination have indicated a detection limit below 0.55 μM, lower than the 0.1 mg L-1 maximum limit of operation in recirculating aquaculture systems for farming Atlantic salmon Salmo salar. An increase of the nitrite concentration to toxic levels may therefore be possible to detect. The fluorimetric sensor exhibited good linearity over three orders of magnitude and acceptable detection reproducibility, which confirmed its analytical value. Further tests revealed great promise of the integrated biosensor device for detecting nitrite in aquaculture-relevant samples with high precision. The approach reported hereby may provide impetus to in situ analytical tools for monitoring water quality at aquaculture facilities, the food industries or water monitoring stations.

Biofilm early stage development in two nutrient‐rich streams with different urban impacts

AbstractThe aim of this study was to describe the colonization of the biofilm during its early stages under different concentrations of nutrients and organic matter, specifically in urban streams influenced by agriculture and urbanization. We hypothesized that in a stream with higher concentrations of nutrients and organic matter, the initial biomass growth would be faster, and the changes in the structure of the community would be greater. Sterile glass substrates were placed in 2 urban streams that differed in nutrient and organic matter concentrations; samples were collected during their first week of colonization to measure total biomass, bacterial biomass, chlorophyll a, activity of the electron transfer system, and the community composition. Results show that biofilm development in both streams began within a few hours and differed under different conditions of nutrients; in the stream with a better water quality, the colonization dynamics consisted of 2 increments of bacterial biomass linked with an increase of algal biomass. In the urban stream with higher nutrient and organic matter concentrations, biofilm development was slower and consisted of a simultaneous increase of bacteria and algae, consistent with a lower electron transfer system activity. Therefore, the dynamics of the colonization process in addition to those characteristics of the fully developed biofilm could have potential applications in water monitoring of urban streams.

Planar Is Better: Monodisperse Three-Layered MoS2 Quantum Dots as Fluorescent Reporters for 2,4,6-Trinitrotoluene Sensing in Environmental Water and Luggage Cases.

In this study, we present a simple but effective fluorescent system for highly sensitive and versatile sensing of 2,4,6-trinitrotoluene (TNT) using few layered planar MoS2 quantum dots (QDs) as reporters. Excitation-independent emitting MoS2 QDs were first fabricated by using the proposed ultrasonic-hydrothermal-based top-down method assisted by carbon-free hydroxylamine hydrochloride. The obtained pristine MoS2 QDs were then modified with cysteine for introducing amino groups as TNT binding sites. The as-prepared MoS2 QDs possess a planar structure, which can more adequately interact with flat aromatic TNT molecules due to π-π attraction and decreased steric effects, compared with traditional spherical/quasi-spherical QDs. As a result, they exhibit extremely high sensitivity for TNT sensing (1 nM and 2 ng for solution and substrate assay, respectively). The common ions containing in environmental water samples do not interfere with the sensing. Furthermore, the QDs-decorated test paper shows an instantaneous (within 1 min) response to trace amounts of deposited TNT, and the fluorescence quenching can even be well-visualized by the naked eye. Because of favorable analytical performances, the proposed MoS2 QDs-based TNT sensing system has potential applications in both environmental water monitoring and security screening.