scholarly journals Real-Time Identification of Irrigation Water Pollution Sources and Pathways with a Wireless Sensor Network and Blockchain Framework

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3634 ◽  
Author(s):  
Yu-Pin Lin ◽  
Hussnain Mukhtar ◽  
Kuan-Ting Huang ◽  
Joy R. Petway ◽  
Chiao-Ming Lin ◽  
...  
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Real Time ◽  
Irrigation Water ◽  
Pollution Source ◽  
Pollution Sources ◽  
Blockchain Technology ◽  
Gis Tools ◽  
Source Tracing ◽  
Real Time Identification

Real-time identification of irrigation water pollution sources and pathways (PSP) is crucial to ensure both environmental and food safety. This study uses an integrated framework based on the Internet of Things (IoT) and the blockchain technology that incorporates a directed acyclic graph (DAG)-configured wireless sensor network (WSN), and GIS tools for real-time water pollution source tracing. Water quality sensors were installed at monitoring stations in irrigation channel systems within the study area. Irrigation water quality data were delivered to databases via the WSN and IoT technologies. Blockchain and GIS tools were used to trace pollution at mapped irrigation units and to spatially identify upstream polluted units at irrigation intakes. A Water Quality Analysis Simulation Program (WASP) model was then used to simulate water quality by using backward propagation and identify potential pollution sources. We applied a “backward pollution source tracing” (BPST) process to successfully and rapidly identify electrical conductivity (EC) and copper (Cu2+) polluted sources and pathways in upstream irrigation water. With the BPST process, the WASP model effectively simulated EC and Cu2+ concentration data to identify likely EC and Cu2+ pollution sources. The study framework is the first application of blockchain technology for effective real-time water quality monitoring and rapid multiple PSPs identification. The pollution event data associated with the PSP are immutable.

Design of Real-Time Monitoring System for Surface Water Pollution Based on GPRS

2011 ◽  
Vol 383-390 ◽  
pp. 213-217 ◽  
Author(s):  
Guang Jian Chen ◽  
Jin Ling Jia
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Surface Water ◽  
Real Time ◽  
Remote Monitoring ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Wireless Transmission ◽  
Surface Water Pollution ◽  
Monitoring Center

To implement the remote and real-time monitoring of surface water pollution, a design scheme of water quality monitoring system based on GPRS technology is put forward, which is composed of monitoring terminal, monitoring center and communication network. The various parameters of surface water are acquired using water quality detection sensor terminal and uploaded to the remote monitoring center via GPRS module by monitoring, and then the water quality parameters acquisition, processing and wireless transmission are realized. Water quality parameters are received through the internet network by the monitoring center, to realize its remote monitoring and management. According to the practice result, the system has materialized functions on GPRS service platform, such as real-time water quality parameters acquisition, procession, wireless transmission, remote monitoring and management, which is suitable for surface water pollution continuous monitoring and has the good application in the future.

scholarly journals Establishment of an Automatic Real-Time Monitoring System for Irrigation Water Quality Management

2020 ◽  
Vol 17 (3) ◽  
pp. 737 ◽  
Author(s):  
Wei-Jhan Syu ◽  
Tsun-Kuo Chang ◽  
Shu-Yuan Pan
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Quality Management ◽  
Real Time ◽  
Monitoring System ◽  
Irrigation Water ◽  
Water Quality Management ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Irrigation Water Quality

In order to provide the real-time monitoring for identifying the sources of pollution and improving the irrigation water quality management, the integration of continuous automatic sampling techniques and cloud technologies is essential. In this study, we have established an automatic real-time monitoring system for improving the irrigation water quality management, especially for heavy metals such as Cd, Pb, Cu, Ni, Zn, and Cr. As a part of this work, we have first provided several examples on the basic water quality parameters (e.g., pH and electrical conductance) to demonstrate the capacity of data correction by the smart monitoring system, and then evaluated the trend and variance of water quality parameters for different types of monitoring stations. By doing so, the threshold (to initiate early warming) of different water quality parameters could be dynamically determined by the system, and the authorities could be immediately notified for follow-up actions. We have also provided and discussed the representative results from the real-time automatic monitoring system of heavy metals from different monitoring stations. Finally, we have illustrated the implications of the developed smart monitoring system for ensuring the safety of irrigation water in the near future, including integration with automatic sampling for establishing information exchange platform, estimating fluxes of heavy metals to paddy fields, and combining with green technologies for nonpoint source pollution control.

scholarly journals Long-term of River Water Quality and Pollution Source Apportionment in Taiwan

2018 ◽  
Author(s):  
Marsha Savira Agatha Putri ◽  
Chao-Hsun Lou ◽  
Mat Syai'in ◽  
Shang-Hsin Ou ◽  
Yu-Chun Wang
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Heavy Metal ◽  
Cluster Analysis ◽  
Anthropogenic Activities ◽  
Pollution Source ◽  
Pollution Level ◽  
Analysis Model ◽  
Metal Levels ◽  
Metal Monitoring

This study reports multivariate statistical techniques applied including cluster analysis to evaluate and classify the river pollution level in Taiwan, and principal component analysis-multiple linear regression (PCA-MLR) to identify the possible pollution source. Water quality and heavy metal monitoring data from Taiwan Environmental Protection Administration (EPA) was evaluated for 14 rivers in the four regions of Taiwan. The Erren River was classified as the most polluted River in Taiwan. Biochemical oxygen demand, ammonia, and total phosphate concentration in this river were the highest of the 14 rivers evaluated. In addition, heavy metal levels of the following rivers exceeded the Taiwan EPA standard limit: lead - in the Dongshan, Jhuoshuei, and Xinhuwei Rivers; copper - in the Dahan, Laojie, and Erren Rivers; and manganese - in all rivers. Water pollution in the Erren River was estimated to originate 72% from industrial sources, 16% from domestic black water, and 12% from natural sources and runoff from other tributaries. Our research showed that PCA-MLR and the cluster analysis model accomplished our study objectives and will be helpful tools to evaluate water quality in rivers and we suggest that the continuous monitoring should be conducted to monitor water pollution from anthropogenic activities.

The Design of Online Water Pollution Monitoring System for Poultry Rearing

2014 ◽  
Vol 898 ◽  
pp. 730-733
Author(s):  
Xiang Jie Niu ◽  
Yan E Duan ◽  
Hua Li
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Real Time ◽  
Monitoring System ◽  
Management Control ◽  
Pollution Monitoring ◽  
Wireless Sensor ◽  
Long Distance ◽  
Parameter Configuration ◽  
Long Time

This paper proposes the construction of real-time online water pollution monitoring system for poultry rearing which applies network nodes in the Wireless Sensor Network to monitor the water quality in the poultry rearing areas. The wireless packet communications technology and broadband services are used to transmit the data in long distance. The system can fulfill the functions of online real-time water quality inquire via Web, management control, data collection, and alert. The system software designs the Web network optimization protocols, system monitoring platform, long-distance parameter configuration, and driver programs. The simulation and experiment illustrate the system can achieve 100% successful communication rates. The access speeds in the networks are 5~8 times of those in traditional network. The wireless sensor networks and the long-time monitoring can work normally and reliably in which the speeds can meet the requirements for real-time monitoring. Its suitable for the online real-time water pollution monitoring in the poultry rearing areas.

scholarly journals Water Level Decline in a Reservoir: Implications for Water Quality Variation and Pollution Source Identification

2020 ◽  
Vol 17 (7) ◽  
pp. 2400
Author(s):  
Zixiong Wang ◽  
Tianxiang Wang ◽  
Xiaoli Liu ◽  
Suduan Hu ◽  
Lingxiao Ma ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Level ◽  
Principal Component ◽  
Ammonia Nitrogen ◽  
Pollution Source ◽  
Biological Action ◽  
Pollution Sources ◽  
Reservoir Water ◽  
Reservoir Water Level ◽  
Water Level Decline

Continuous water-level decline makes the changes of water quality in reservoirs more complicated. This paper uses trend analyses, wavelet analysis and principal component analysis-multiple linear regression to explore the changes and pollution sources affecting water quality during a period of continuous reservoir water level decline (from 65.37 m to 54.15 m), taking the Biliuhe reservoir as an example. The results showed that the change of water level of Biliuhe reservoir has a significant 13-year periodicity. The unusual water quality changes during the low water level period were as follows: total nitrogen continued to decrease. And iron was lower than its historical level. pH, total phosphorus, and ammonia nitrogen were higher than historical levels and fluctuated seasonally. Permanganate index increased as water level decreased after initial fluctuations. Dissolved oxygen was characterized by high content in winter and relatively low content in summer. The pollutant sources of non-point source pollution (PC1), sediment and groundwater pollution (PC2), atmospheric and production & domestic sewage (PC3), other sources of pollution (PC4) were identified. The main source of DO, pH, TP, TN, NH4-N, Fe and CODMn were respectively PC3 (42.13%), PC1 (47.67%), PC3 (47.62%), PC1 (29.75%), PC2 (47.01%), PC1 (56.97%) and PC2 (50%). It is concluded that the continuous decline of water level has a significant impact on the changes and pollution sources affecting water quality. Detailed experiments focusing on sediment pollution release flux, and biological action will be explored next.

scholarly journals Planar Interdigitated Aptasensor for Flow-Through Detection of Listeria spp. in Hydroponic Lettuce Growth Media

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5773
Author(s):  
Raminderdeep K. Sidhu ◽  
Nicholas D. Cavallaro ◽  
Cicero C. Pola ◽  
Michelle D. Danyluk ◽  
Eric S. McLamore ◽  
...  
Keyword(s):  
Water Quality ◽  
Real Time ◽  
Irrigation Water ◽  
Primary Source ◽  
Growth Media ◽  
Basic Solution ◽  
Real Time Analysis ◽  
Piranha Solution ◽  
Regulatory Standards ◽  
Produce Contamination

Irrigation water is a primary source of fresh produce contamination by bacteria during the preharvest, particularly in hydroponic systems where the control of pests and pathogens is a major challenge. In this work, we demonstrate the development of a Listeria biosensor using platinum interdigitated microelectrodes (Pt-IME). The sensor is incorporated into a particle/sediment trap for the real-time analysis of irrigation water in a hydroponic lettuce system. We demonstrate the application of this system using a smartphone-based potentiostat for rapid on-site analysis of water quality. A detailed characterization of the electrochemical behavior was conducted in the presence/absence of DNA and Listeria spp., which was followed by calibration in various solutions with and without flow. In flow conditions (100 mL samples), the aptasensor had a sensitivity of 3.37 ± 0.21 kΩ log-CFU−1 mL, and the LOD was 48 ± 12 CFU mL−1 with a linear range of 102 to 104 CFU mL−1. In stagnant solution with no flow, the aptasensor performance was significantly improved in buffer, vegetable broth, and hydroponic media. Sensor hysteresis ranged from 2 to 16% after rinsing in a strong basic solution (direct reuse) and was insignificant after removing the aptamer via washing in Piranha solution (reuse after adsorption with fresh aptamer). This is the first demonstration of an aptasensor used to monitor microbial water quality for hydroponic lettuce in real time using a smartphone-based acquisition system for volumes that conform with the regulatory standards. The aptasensor demonstrated a recovery of 90% and may be reused a limited number of times with minor washing steps.

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