In-line diffuse reflectance spectroscopy with partial least-squares regression was piloted at a full-scale municipal anaerobic codigestion facility to evaluate rapid monitoring of heterogeneous feedstocks and digestate. Models developed from 42 high-strength waste samples and 146 digestate samples yielded operationally useful predictions (root-mean-square error 10–27%) for total solids, volatile solids, fats, chemical oxygen demand, volatile acids, and alkalinity. Protein and carbohydrate predictions were less accurate due to limitations in reference data. Importantly, predicted volatile acid:alkalinity ratios provided rapid indicators of digester stability. Downsampling analysis demonstrated that effective models could be developed with fewer than 50 training samples for several parameters, highlighting opportunities to reduce analytical costs. Field deployment during periods of digester instability, including foaming and failure, further validated the robustness of diffuse reflectance spectroscopy models under dynamic operating conditions. These results establish diffuse reflectance spectroscopy as a potentially cost-effective tool for improving process stability, biogas yield, and decision-making at full-scale anaerobic codigestion facilities.
In-Line Diffuse Reflectance Spectroscopy Enables Rapid Monitoring of Full-Scale Anaerobic Co-Digestion
Zoe A. M. Kramin,M. K. Putney,Craig L. Just
Published 2025 in Energy & Fuels
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- Publication year
2025
- Venue
Energy & Fuels
- Publication date
2025-11-20
- Fields of study
Medicine, Engineering, Environmental Science
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Semantic Scholar, PubMed
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