Water quality monitoring allows communities to achieve sustainable management of water resources, which is crucial for life-supporting processes. Water quality is determined by measuring chemical, physical, and biological parameters, requiring sophisticated meters and trained specialists to perform the measurement. However, in low-income communities, water quality is determined by using human senses-smell, color, and taste-since meter acquisition is limited by costs and most people do not know how to monitor water quality. Therefore, accessible technology is necessary to empower communities to have a sustainable lifestyle. In this paper, we present the design and implementation of PortAqua, a 2-parameter water quality meter (WQM), to promote training on water quality measurement. Using basic electronic components, PortAqua is capable of measuring pH with an error of 0.4, and conductivity with an error of 33% at 85 µS cm, and 8.7% at 1413 µS cm. To demonstrate its preliminary effectiveness as a WQM and its science communication capabilities, the meter has been used in a hands-on workshop with undergraduate and graduate students. During the workshop, attendees participated in a short lecture about water quality measurement techniques and local regulations. Then, they collected water samples from a local source, measured the samples using PortAqua, and discussed the results based on the concepts and regulations. The workshop's effectiveness was evaluated through pre- and post-assessments which revealed increased knowledge of water quality regulations, measurement, and parameters at the end of the activity.
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http://dx.doi.org/10.1007/s10661-022-10804-3 | DOI Listing |
Int Microbiol
December 2024
Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia.
The present research work is concerned with the production and optimization of the dopa-oxidase enzyme by using pre-grown mycelia of Aspergillus oryzae. Different strains of A. oryzae were collected and isolated from various soil samples.
View Article and Find Full Text PDFSci Rep
December 2024
Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, USA.
Groundwater monitoring is a crucial part of groundwater remediation that produces data from various strategically placed wells to maintain a water quality standard. Using the United States Department of Energy's Hanford 100-HRD area well data, recurrent neural networks are trained in the form of one-dimensional Convolutional Neural Networks (CNNs), Long Short Term Memory (LSTM) networks, and Dual-stage Attention-based LSTM (DA-LSTM) networks to reduce monitoring costs and increase data sampling responsiveness that is subject to laboratory analysis delays, with the best network being DA-LSTM achieving an R score of 0.82.
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December 2024
College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi, 832000, Xinjiang, China.
Heavy metal contamination of drinking water, primarily driven by industrial activities, represents a critical challenge, with implications for human health and environmental safety. Gujranwala is an industrial and thickly populated city. The current study aimed to assess and compare heavy metal contamination levels in drinking water from five industrial areas and evaluate their potential impacts on human health.
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December 2024
Department of Civil, Construction and Environmental Engineering (Dept 2470), North Dakota State University, PO Box 6050, Fargo, ND, 58108-6050, USA.
A precise streamflow forecast is crucial in hydrology for flood alerts, water quantity and quality management, and disaster preparedness. Machine learning (ML) techniques are commonly employed for hydrological prediction; however, they still face certain drawbacks, such as the need to optimize the appropriate predictors, the ability of the models to generalize across different time horizons, and the analysis of high-dimensional time series. This research aims to address these specific drawbacks by developing a novel framework for streamflow forecasting.
View Article and Find Full Text PDFJ Public Health Manag Pract
October 2024
Author Affiliations: Public Health - Seattle and King County, Washington.
Context: Most major urban areas in the US, including Seattle and King County, have a long-standing lack of public restrooms, handwashing stations, and drinking water, presenting public health risks.
Objective: To aid decision-makers in expanding access, we review available information regarding successful hygiene programs in urban settings to identify shared characteristics and costs.
Design: We reviewed 10 journal articles, 49 news articles, and 54 pieces of gray literature including reports, white papers, and online resources describing real-world hygiene, sanitation, and drinking water programs in US and global urban settings.
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