亚硝酸盐
社会化媒体
计算机科学
环境科学
智能手机应用
作者
Shulu Zheng,Hangqian Li,Tengyue Fang,Guangyong Bo,Dongxing Yuan,Jian Ma
标识
DOI:10.1016/j.scitotenv.2021.152613
摘要
Citizen scientists-based water quality surveys are becoming popular because of their wide applications in environmental monitoring and public education. At present, many similar studies are reported on collecting samples for later laboratory analysis. For environmentally toxic analytes such as ammonium and nitrite, on-site detection is a promising choice. However, this approach is limited by the availability of suitable methods and instruments. Here, a simple on-site detection method for ammonium and nitrite is reported. The chemistry of this method is based on the classic Griess reaction and modified indophenol blue reaction. Digital image colorimetry is carried out using a smartphone with a custom-made WeChat mini-program or free built-in applications (APPs). Using a simple and low-cost analytical kit, the detection limit of 0.27 μmol/L and 0.84 μmol/L is achieved for nitrite and ammonium, respectively, which are comparable to those achieved with a benchtop spectrophotometer. Relative standard deviations (n = 7) for low and high concentrations of nitrite are 3.6% and 4.3% and for ammonium are 5.6% and 2.6%, respectively. Identical results with a relative error of less than 10% are obtained using different smartphones (n = 3), color extracting software (n = 6), and with multiple individual users (n = 5). These results show the robustness and applicability of the proposed method. The on-site application is carried out in an in-campus wastewater treatment plant and at a local river. A total of 40 samples are analyzed and the analytical results are compared with that obtained by a standard method and a spectrophotometer, followed by a paired t-test at a 95% confidence level. This proposed on-site analytical kit has the advantages of simplicity and portability and has the potential to be popular and useful for citizen science-based environmental monitoring.
科研通智能强力驱动
Strongly Powered by AbleSci AI