Harmful algal blooms are spreading across lakes, rivers and coastal waters in the United States, threatening drinking-water supplies, wildlife, public health and economies built around fishing and tourism. Now, researchers at Florida Atlantic University are developing an artificial intelligence-guided system designed to attack one of the main causes of these ecological disasters: excess phosphorus.
FAU’s College of Engineering and Computer Science has received an $800,475 grant from the Gulf of America Division of the U.S. Environmental Protection Agency for a three-year project titled “AI-Guided Use of 3D-Printed Adsorbents for Phosphate Removal.” The research began July 1 and will focus on creating reusable structures capable of extracting phosphorus from freshwater systems before nutrient pollution triggers explosive algal growth.
The project is led by Masoud Jahandar Lashaki, an associate professor in FAU’s Department of Civil, Environmental and Geomatics Engineering. Yalan Liu and Mohammed Abdellatef, also assistant professors in the department, are serving as co-principal investigators. Huichun “Judy” Zhang of Case Western Reserve University will participate as the project’s sub-awardee.
Phosphorus reaches waterways through agricultural runoff, wastewater discharges, failing septic systems and urban stormwater. Once concentrated in a lake or river, it can stimulate rapid growth of algae and cyanobacteria. These harmful algal blooms may reduce water clarity, consume dissolved oxygen as they decay and produce toxins capable of endangering people, pets, fish and other wildlife. The resulting damage can extend beyond the water itself, affecting recreation, tourism, commercial fishing and municipal water treatment.
Lake Okeechobee will serve as the project’s principal field-testing site. The large Florida lake has experienced recurring harmful algal blooms associated with elevated nutrient levels. Because it lies at the headwaters of the Gulf of America watershed, phosphorus leaving the lake can move into downstream rivers, estuaries and coastal ecosystems. Reducing the nutrient load in Lake Okeechobee could therefore improve water quality across a much larger region.
The FAU team plans to manufacture durable, three-dimensional structures from sargassum, a naturally abundant seaweed. The material will be modified with lanthanum, an element that binds strongly with phosphate. In technical terms, the structures will function as adsorbents: phosphorus-containing compounds will attach to their surfaces rather than remaining dissolved in the water. Their three-dimensional architecture is intended to increase contact with contaminated water while allowing the units to be recovered after use.
That retrievability is central to the proposed technology. Lanthanum-based materials can remove phosphorus efficiently, but they are commonly deployed as fine powders that settle into sediments. Over time, those powders may release lanthanum back into the environment and are difficult to collect. The FAU researchers aim to avoid this problem by producing larger, reusable structures that can be placed in the water column or near lake sediments, removed, regenerated and redeployed, reducing waste and limiting uncontrolled dispersal.
Artificial intelligence and machine learning will guide nearly every stage of the work. Algorithms will analyze experimental results to identify the most effective combinations of sargassum, lanthanum and other material properties. The system will also evaluate where phosphorus-removal structures should be placed and predict which locations are most likely to produce meaningful reductions in bloom risk. Researchers plan to combine water-quality measurements with data on land use, weather, fertilizer application, livestock operations and septic systems to map nutrient movement more precisely.
The technology will be tested under real-world conditions in Lake Okeechobee. Researchers will track phosphorus concentrations, water clarity and indicators of harmful algal blooms through field sampling, publicly available environmental data and observations collected by unmanned aerial vehicles. The resulting information will be shared through the EPA’s Water Quality Exchange, creating a dataset that may help other communities evaluate similar interventions. If the system performs as expected, it could offer a scalable approach for lakes, reservoirs and watersheds worldwide where nutrient pollution is turning clean water into a recurring public-health and environmental crisis.
Subject of Research: Artificial intelligence-guided phosphorus removal from freshwater systems using reusable, 3D-printed sargassum-based adsorbents modified with lanthanum.
Article Title: AI-Guided 3D-Printed Structures Aim to Stop Harmful Algal Blooms at Their Source
Web References: Florida Atlantic University; FAU College of Engineering and Computer Science; Image and media resource: EurekAlert multimedia
References: U.S. Environmental Protection Agency Gulf of America Division grant; Florida Atlantic University project information.
Image Credits: Brian Lapointe, Ph.D.
Keywords
Harmful algal blooms, phosphorus pollution, Lake Okeechobee, artificial intelligence, machine learning, water quality, phosphate removal, sargassum, lanthanum, 3D-printed adsorbents, freshwater ecosystems, environmental engineering, watershed pollution, Florida Atlantic University
