The Nutrient App: Developing a smartphone application for on-site instantaneous community-based NO3 and PO4 monitoring. (November 2020)

• Record Type: Journal Article
• Authors: Costa, Diogo; Aziz, Uswah; Elliott, Jane; Baulch, Helen; Roy, Banani; Schneider, Kevin; Pomeroy, John
• Is Part Of: Environmental modelling & software. Volume 133(2020)
• Publication Date: 2020-11
• Subjects: Community-based monitoring -- Smartphone -- Mobile application -- Low cost -- Nitrate -- Phosphate; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104829
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Freshwater ecosystems, particularly those in agricultural areas, remain at risk of eutrophication due to anthropogenic inputs of nutrients. While community-based monitoring has helped improve awareness and spur action to mitigate nutrient loads, monitoring is challenging due to the reliance on expensive laboratory technology, poor data management, time lags between measurement and availability of results, and risk of sample degradation during transport or storage. In this study, an easy-to-use smartphone-based application (The Nutrient App) was developed to estimate NO 3 and PO 4 concentrations through the image-processing of on-site qualitative colorimetric-based results obtained via cheap commercially-available instantaneous test kits. The app was tested in rivers, wetlands, and lakes across Canada and relative errors between 30% (filtered samples) and 70% (unfiltered samples) were obtained for both NO 3 and PO 4 . The app can be used to identify sources and hotspots of contamination, which can empower communities to take immediate remedial action to reduce nutrient pollution. Highlights: A new mobile application was developed to support community-based monitoring of nutrient pollution. It aims at supporting the identification of hotspots of contamination to help reduce the frequency of algae blooms in lakes. The app was tested in field conditions for nitrate and phosphate. The accuracy of the results depends on the quality of the image and light conditions.