ORIGINAL RESEARCH article
Front. Water
Sec. Environmental Water Quality
Volume 7 - 2025 | doi: 10.3389/frwa.2025.1629179
This article is part of the Research TopicInnovative Approaches for Resource Recovery from Wastewater and SludgeView all articles
Struvite as a Sustainable Fertilizer: Nutrient Recovery from Corn Starch Wastewater with Minimal Sludge Production
Provisionally accepted
- 1Changchun Institute of Technology, Changchun, China
- 2China Northeast Municipal Engineering Design and Research Institute Co., Ltd., Changchun, China
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The deep-processing corn industry produces nutrient-rich wastewater that exacerbates eutrophication in water bodies, necessitating the development of sustainable nutrient-recovery methods. This study introduces a sensor-integrated struvite crystallization method for nitrogen (N) and phosphorus (P) recovery from cornstarch wastewater through struvite crystallization. Using real-time pH and ion sensors, the conditions were optimized (pH 10.50, Mg/P ratio 2.0, 30°C, 35 min, 180 rpm), which recovered 98.52% of P and high N rates. Single-factor and orthogonal experiments identified pH and Mg: P ratio as the primary factors that influenced recovery, with aquatic temperature, reaction time, and stirring rate as secondary factors. X-ray diffraction, scanning electron microscopy, and energy-dispersive X-ray spectroscopy were used to confirm the rod-shaped struvite morphology and purity magnitude. Compared to biochar (89% N recovery) and algal systems, our approach reduced chemical inputs by 30% and sludge inputs by 40%, supporting circular economic principles. Pot experiments validated the efficacy of struvite as a slow-release fertilizer and its ability to enhance vegetable growth. This sensor-driven method offers an innovative and eco-friendly solution for managing agro-industrial wastewater. This mitigates eutrophication and promotes resource recovery in the corn-processing industry.
Keywords: Struvite crystallization, Nutrient recovery, Corn starch wastewater, Eutrophication mitigation, Sensor-based monitoring
Received: 15 May 2025; Accepted: 29 Aug 2025.
Copyright: © 2025 Li, He, Long, Li, Tian, Li and Ma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Hongyan Li, lihongyan@ccit.edu.cn
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