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Economical and Novel Microplastic Detection Using a Arduino-Based Turbidity Sensor: A Comprehensive Investigation
Summary
Researchers developed a low-cost Arduino-based turbidity sensor system for microplastic detection as an accessible alternative to expensive FTIR and Raman spectroscopy methods. The sensor demonstrated the ability to detect microplastic-induced changes in water clarity, offering a practical monitoring tool for low-resource settings and smaller waterways that are typically undersampled.
Microplastics-generally defined as plastic particles ranging from 1 µm to 5 mmhave emerged as a critical environmental contaminant worldwide. Although they are ubiquitous in rivers, lakes, and oceans, their presence in smaller waterways is often undetected. Traditional analytical methods, such as Fourier Transform Infrared (FTIR) spectroscopy or Raman microscopy, provide specific identification of polymer types but are prohibitively expensive, technically demanding, and inaccessible to many communities, especially in low-resource regions. This paper presents a novel, low-cost solution for microplastic detection based on a custom-built turbidity sensor integrated with an Arduino microcontroller system. By exploiting the slower settling rates and unique scattering characteristics of microplastics relative to natural sediments, this sensor can accurately classify water samples into four categories: clear water, sediment-laden, microplastic-laden, and mixed (i.e., both sediment and microplastics). Laboratory tests spanned multiple microplastic polymers-polyethylene (PE), polypropylene (PP), and nylon-at concentrations ranging from 10 to 100 mg/L, as well as common sediments (river silt, decomposed leaf matter, and fine sand) in the 50 to 200 mg/L range. Using a rigorous experimental protocol (n=3 replicate samples per condition) and advanced data analysis (ANOVA, Principal Component Analysis, and Support Vector Machine classification), I demonstrated that the sensor can achieve up to 95% classification accuracy, with near 100% sensitivity to the presence of microplastics. This method, which costs under $50 to assemble, offers a significant advancement in making microplastic detection accessible to students, local communities, and resource-constrained regions worldwide. Furthermore, the device's reliance on turbidity decay over time-an otherwise overlooked metric-offers a powerful, distinctive fingerprint for identifying buoyant or slow-sinking plastic particles.