What Water quality sensors are used to check water quality?4 answersLow-cost, portable and efficient prototype sensor-based systems are used to monitor water quality in real-time. These systems consist of microcontrollers, temperature, turbidity, pH, and distance sensors, and applications for visual representation of the data. The Ph4502c sensor is used for pH measurement. The TSW30 sensor is used for turbidity measurement. Luminescent techniques such as fluorescence and phosphorescence are used to monitor the quality of waters, including dissolved gases, ions, organic pollutants, general toxicity, and pathogenic microorganisms. Low-cost sensors integrated with the Internet of Things are also used for water quality monitoring, providing valuable information to the public. However, further research is needed to determine the reliability and accuracy of low-cost sensors compared to professional devices.
How can IoT be used to monitor the quality of water?5 answersIoT can be used to monitor the quality of water by implementing a system of monitoring stations equipped with sensors to measure various parameters such as temperature, pH, turbidity, and dissolved oxygen in real-time. These sensors are connected to a central controller, such as Raspberry Pi or Arduino, which collects the data and transfers it to a cloud infrastructure for storage and visualization. The collected data can be accessed through presentation devices like computers or phones, allowing for instant information on water quality and the ability to detect possible contamination. Additionally, the data can be used for deeper analysis of water quality and to provide continuous monitoring, alerting authorities if the water quality falls below acceptable levels.
What are the key parameters for water quality monitoring?5 answersThe key parameters for water quality monitoring include dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP), chlorophyll-a concentration, turbidity, total suspended solids, colored dissolved organic matter, total dissolved solids, chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N), and pH. These parameters are important for assessing the quality of water and identifying potential pollution sources. Various techniques, such as Pearson's correlation analysis, band ratio, principal component analysis, and artificial intelligence models, are used to estimate and monitor these parameters. Remote sensing technologies, including satellite images and optical sensors, have proven effective in retrieving water quality parameters on a large scale. Additionally, the Internet of Things (IoT) enables real-time monitoring of water quality using physicochemical parameters. These monitoring methods provide valuable information for water resource management and decision-making.
Can localized surface plasmon resonance be used to detect pesticides in water samples?4 answersLocalized surface plasmon resonance (LSPR) can be used to detect pesticides in water samples. LSPR-based colorimetric sensors, such as thiol-capped gold nanoparticles (Au NPs), have been developed for the detection of pesticides like parathion. These sensors utilize the aggregation of thiol-capped Au NPs, which is influenced by the concentration of the pesticide. The degree of aggregation can be measured through changes in the LSPR absorbance ratio, allowing for the detection of pesticides at low concentrations. Additionally, LSPR has been combined with fluorescence in a dual-readout sensing system for the detection of acetamiprid and organophosphorus pesticides (OPs). In this system, DNA-functionalized Au NPs act as a nanoprobe, and the degree of polymerization of dopamine on the Au NPs surface is dependent on the concentration of OPs, leading to a significant LSPR spectral shift and color change. Therefore, LSPR-based techniques show promise for the rapid and sensitive detection of pesticides in water samples.
How does the plasmonic resonance work in photocatalysis of TiO2?4 answersPlasmonic resonance in photocatalysis of TiO2 involves the interaction between TiO2 and plasmonic nanoparticles, such as Au or Al, which leads to enhanced photocatalytic efficiency. The presence of plasmonic nanoparticles on the TiO2 surface results in the localized surface plasmon resonance (LSPR) effect, which is characterized by an absorption peak in the UV-Vis spectrum. This LSPR effect is responsible for the generation of reactive oxygen species (ROS), such as superoxide anion radicals (O2•) and hydroxyl radicals, under visible-light illumination. The LSPR effect is highly controllable and can be influenced by factors such as particle size, aspect ratio, and the presence of hot spots. The hot electron dynamics and interband transitions play a crucial role in plasmonic photocatalysis, depending on the specific plasmonic system. The LSPR effect of Al nanoparticles has also been shown to significantly enhance the photocatalytic efficiency of TiO2. Overall, plasmonic resonance in TiO2 photocatalysis enables efficient utilization of sunlight and enhances the performance of various chemical reactions.
How can cutting-edge technology such as underwater robots be used to monitor water quality?4 answersCutting-edge technology such as underwater robots can be used to monitor water quality in various ways. One approach is the use of industrial robots based on MATLAB simulation, which allows for wide-range data collection and autonomous monitoring. Another method involves the development of automatic navigation systems for underwater inspection robots, enabling them to navigate and inspect underwater structures autonomously. Additionally, piezoelectric driven underwater detection robots have been proposed, utilizing piezoelectric ceramics as actuators for their small size, high control accuracy, and low noise. These robots undergo static simulation and thickness optimization to enhance their pressure resistance and reduce costs. Furthermore, advancements in antifouling strategies, such as the use of wiper technologies, can be integrated into underwater monitoring systems to prevent biofouling and improve sensor performance.