Smartphone Based Sensors For The Detection Of Typical Inorganic Pollutants In Water

In the field of environmental monitoring,traditional water quality monitoring has a complicated processes of sampling,sending sample and detection.With the increasingly serious environmental pollution,there is urgent need for new rapid on-site monitoring methods.POC technology,which is portable,simple and low-cost has been attracted more and more attention by researchers.This paper presents a smartphone-based detection method,which can provide real-time detection for many inorganic pollutants in water to meet the requirements of fast and on-site detection.First,two smartphone-based detection methods?smartphone colorimetric method and smartphone spectroscopic analysis?and two color processing methods?RGB color space and grayscale space?were proposed.The two devices were designed and customized for connecting to a smartphone.The device of smartphone spectroscopy was considered as a simple spectrophotometer.Then six kinds of dye solutions were tested by two smartphone-based detection methods and calculated by two color processing methods to select the highest sensitivity detection system.The sensitivity was determined by the limit of detection?LOD?.The result was that the detection system combined by smartphone spectroscopy and RGB color space has the highest sensitivity.Then,several typical inorganic pollutants(Cu²⁺,Ni²⁺,Ammonia and Orthophosphate)were tested by the above detection system.The LOD of four pollutants were 0.02 mg/L,0.27 mg/L,0.024 mg/L and 0.018 mg/L,respectively.The linear calibration curves of them were obtained in the range of 0?4.8mg/L,0?6mg/L,0?3.3mg/L and 0?4.5mg/L,respectively.The relative standard deviation of them were?1.8%,?2.5%,?2.6%and?2.9%,respectively.The results for the detection of Cu²⁺,Ni²⁺,Ammonia and Orthophosphate obtained with smartphone spectroscopy and UV-vis spectrophotometry has a highly linear correlation.The relative errors were?5.4%,?8.9%,?11.8%and?6.6%,respectively.Therefore,the smartphone-based detection method suggested in this work has strong feasibility and accuracy,and has great application prospect in the field of rapid on site detection.