Achieving Electrochemical-Sustainable-Based Solutions for Monitoring and Treating Hydroxychloroquine in Real Water Matrix

Hydroxychloroquine (HCQ) has been extensively consumed due to the Coronavirus (COVID-19) pandemic. Therefore, it is increasingly found in different water matrices. For this reason, the concentration of HCQ in water should be monitored and the treatment of contaminated water matrices with HCQ is a key issue to overcome immediately. Thus, in this study, the development of technologies and smart water solutions to reach the Sustainable Development Goal 6 (SDG6) is the main objective. To do that, the integration of electrochemical technologies for their environmental application on HCQ detection, quantification and degradation was performed. Firstly, an electrochemical cork-graphite sensor was prepared to identify/quantify HCQ in river water matrices by differential pulse voltammetric (DPV) method. Subsequently, an HCQ-polluted river water sample was electrochemically treated with BDD electrode by applying 15, 30 and 45 mA cm−2. The HCQ decay and organic matter removal was monitored by DPV with composite sensor and chemical oxygen demand (COD) measurements, respectively. Results clearly confirmed that, on the one hand, the cork-graphite sensor exhibited good current response to quantify of HCQ in the river water matrix, with limit of detection and quantification of 1.46 mg L−1 (≈3.36 µM) and 4.42 mg L−1 (≈10.19 µM), respectively. On the other hand, the electrochemical oxidation (EO) efficiently removed HCQ from real river water sample using BDD electrodes. Complete HCQ removal was achieved at all applied current densities; whereas in terms of COD, significant removals (68%, 71% and 84% at 15, 30 and 45 mA cm−2, respectively) were achieved. Based on the achieved results, the offline integration of electrochemical SDG6 technologies in order to monitor and remove HCQ is an efficient and effective strategy.

SMART WATER NETWORK MONITORING: A CASE STUDY AT UNIVERSITI TEKNOLOGI MALAYSIA

Water uses need to be measured, which is critical for evaluating water stress. The Industry 4.0 via the Internet of Things (IoT) and usage of water measurement sensor can provide real-time information on the water flow rate and water pressure, that is crucial for water monitoring and analysis. There is a need for online smart water monitoring that gives out more efficient and sustainable water uses at Universiti Teknologi Malaysia (UTM) campus. A prototype of an online smart water monitoring for UTM, which was developed based on the integration of IoT and Geographical Information System (GIS), consist of four layers; (1) physical layer; (2) network layer; (3) processing layer and, (4) application layer. The findings show that when the water flow increases, the water pressure decreases. When there is no water flow, the lowest value is 52.214 Psi, and the highest value is 60.916 Psi. The latest technology integrating the IoT-GIS for smart water monitoring has shown a very efficient way of providing real-time water parameters information, cost and time effective, and allowing for continuous water consumption analysis via the cloud computing service.

Smart water meter for automatic meter reading

Clean water is one of the main sectors in smart city that need well management. One of the clean water management is utilization of water meters. The smart meter is more suitable applied for smart city. Recent Smart Water Meter allows water authorities to obtain water consumption data remotely. It also provides ability to collect and record the data in real time that can be utilised for multipurpose. However, in Indonesia, the water meters are used only to measure the total volume of clean water consumption for billing purpose only using mechanical water meter and requires labour intensive manual. Currently, many researches on smart meter design have been developed. However, the smart meter only measure and record the water consumption, without ability in which customer can determine the amount of water as needed. This paper describes design and development of smart water metering with Internet of Things. Flow meter is used as a sensor of water flowing through the pipe. The ability of the proposed smart meter is not only to measure and to record the volume water consumed, but also the customer can determine the water desired and required. The volume of water measured by the smart meter is compared with the manual measurement. The result shows that the water measured manually differs slightly from smart meter measurement using water flow sensor. The maximum difference, error, is 0.03 litres. The proposed smart meter has ability to close the main valve once the determined amount of water is reached.

Open-Source, Low-Cost, In-Situ Turbidity Sensor for River Network Monitoring

Fine sediment transport in rivers is important for catchment nutrient fluxes, global biogeochemical cycles, water quality and pollution in riverine, coastal and marine ecosystems. Monitoring of suspended sediment in rivers with current sensors is challenging and expensive and most monitoring setups are restricted to few single site measurements. To better understand the spatial heterogeneity of fine sediment sources and transport in river networks there is a need for new smart water turbidity sensing that is multi-site, accurate and affordable. In this work, we have created such a sensor, which detects scattered light from an LED source using two detectors in a control volume, and can be placed in a river. We compare several replicates of our sensor to different commercial turbidity probes in a mixing tank experiment using two sediment types over a wide range of typical concentrations observed in rivers. Our results show that we can achieve precise and reproducible turbidity measurements in the 0-4000 NTU or 0-16g/L range. Our sensor can also be used directly as a suspended sediment sensor and bypass an unnecessary calibration to Formazin. The developed turbidity sensor is much cheaper than existing options of comparable quality and is especially intended for distributed sensing across river networks.