Researchers developed a low-cost, field-ready protocol using the water fern Azolla pinnata to detect heavy metal pollution in wastewater. By observing visible stress signs like yellowing and die-off, communities in developing countries can screen water quality without expensive lab equipment.
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Azolla pinnata showed measurable decline in green cover and increased tissue death when exposed to industrial effluents over 15-20 days, directly correlating with heavy metal concentrations.
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Maximum detected metal levels were cadmium at 0.01 mg/L in blackwater, lead at 0.030 mg/L in graywater, and zinc at 0.50 mg/L in industrial effluents.
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Statistical clustering (PCA and HCA) successfully separated domestic wastewater from industrial effluent types, validating the protocol's ability to differentiate pollution sources.
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