A self-adaptive model for sensing total phosphorus in natural water bodies using Fourier transform mid-infrared attenuated total reflectance spectroscopy

As the most economically developed area in China, the environmental water quality of Guangdong-Hong Kong-Macao Greater Bay Area has received extensive attention, and the spatial variations of total phosphorus (TP) in the Greater Bay were significant, conventional laboratory analysis is difficult to meet the requirements of TP monitoring due to time and cost consuming, and Fourier transform infrared attenuated total reflectance spectroscopy (FTIR-ATR) technology, combined with the self-adaptive partial least squares (SA-PLS) model, was used to determine the TP concentration. The results showed that P-O vibrations were observed in the wavenumber range of 1200–900 cm−1, and prediction models were established by using this range. For the conventional partial least squares (PLS) model, the R2, RMSE and RPD were 0.817, 0.022 mg L−1 and 2.335, respectively, while for the SA-PLS model the prediction was improved with the values of 0.965, 0.010 mg L−1, 5.296, respectively, and the SA-PLS mode prediction was satisfied when the TP content in water was more than 0.05 mg L−1. It was found that the TP determination was interfered by sulfate, when the sulfate content was < 100 mg L−1, both SA-PLS and the conventional PLS model could be used for quantitative analysis of TP; when sulfate content was > 100 mg L−1, PLS model could not be used while the SA-PLS model still achieved an excellent prediction. Therefore, FTIR-ATR combined with SA-PLS model can rapidly determine TP in water, providing an alternative strategy for monitoring TP in natural water bodies.