Nutrient Recovery from Brackish Groundwater with Selective Electrodialysis & Nanofiltration

Overview

The Campo de Cartagena basin (SE Spain) faces stressed hydrology and eutrophication of the Mar Menor due to groundwater overuse and pollution. Local brackish groundwater is high in monovalent ions harmful to crops (Na⁺, Cl⁻) but also rich in nutrient divalents (Mg²⁺, Ca²⁺, SO₄²⁻), making it low-quality for direct irrigation and underutilized for economic activities.

Conventional reverse osmosis (RO) removes nearly all ions, forcing fertilizer re-addition downstream. We instead evaluate monovalent-selective electrodialysis (MSED) and nanofiltration (NF) to retain nutrients while rejecting Na⁺/Cl⁻, aiming to cut fertilizer demand and brine losses.

My goal was simple: show that we can produce irrigation-ready water that retains Mg²⁺/Ca²⁺/SO₄²⁻, cuts Na⁺/Cl⁻, and reduces fertilizer inputs using nanofiltration (NF) and monovalent-selective electrodialysis (MSED).

Work

I conducted a series of nanofiltration (NF) and monovalent-selective electrodialysis (MSED) experiments using synthetic brackish groundwater from the Campo de Cartagena region. My work combined hands-on experimentation with computational modeling to understand ion transport mechanisms and optimize nutrient recovery.

• • Designed and executed NF and MSED trials to assess ion selectivity and flux under variable feed salinities and pH
• • Measured and analyzed ion concentrations using conductivity meters to determine transport numbers and selectivity coefficients
• • Calibrated a semi-empirical multi-ion transport model in Python to simulate membrane performance and validate against experimental data
• • Compiled experimental datasets into a reproducible analysis pipeline for visualization

Results & Impact

The study successfully demonstrated that MSED with NF enables selective removal of harmful monovalent contaminants (Na⁺, Cl⁻) while preserving essential nutrient ions (Mg²⁺, Ca²⁺, SO₄²⁻). This approach produces irrigation-ready water that significantly reduces fertilizer demand and minimizes brine waste which addresses key sustainability challenges in water-stressed agricultural regions.

Additionally, the refined transport model accurately reproduced experimental trends, providing a valuable predictive tool for optimizing system design and operating conditions. This computational framework enables future researchers and engineers to scale the technology for broader agricultural applications.

This research experience was my first foray into mechanical engineering research on sustainability. I developed wet-lab skills and gained firsthand exposure to how graduate-level research is conducted. More specifically, I built skills in experimental design, lab documentation, and integrating experimental work with ion-transport modeling. Overall, it was a very rewarding experience.

Full Research Report

View the complete technical report with detailed methodology, results, and analysis.