Multi-criteria decision analysis: technique for order of preference by similarity to ideal solution for selecting greener analytical method in the determination of mifepristone in environmental water samples.
Tlou A MakwakwaDineo E MoemaTitus Alfred Makudali MsagatiPublished in: Environmental science and pollution research international (2024)
This work proposes the use of multi-criteria decision analysis (MCDA) to select a more environmentally friendly analytical procedure. TOPSIS, which stands for Technique for Order of Preference by Similarity to Ideal Solution, is an example of a MCDA method that may be used to rank or select best alternative based on various criteria. Thirteen analytical procedures were used in this study as TOPSIS input choices for mifepristone determination in water samples. The input data, which consisted of these choices, was described using assessment criteria based on 12 principles of green analytical chemistry (GAC). Based on the objective mean weighting (MW), the weights for each criterion were assigned equally. The most preferred analytical method according to the ranking was solid phase extraction with micellar electrokinetic chromatography (SPE-MEKC), while solid phase extraction combined with ultra-high performance liquid chromatography tandem mass spectrometry (SPE-UHPLC-MS/MS) was ranked last. TOPSIS ranking results were also compared to the green metrics NEMI, Eco-Scale, GAPI, AGREE, and AGREEprep that were used to assess the greenness of thirteen analytical methods for mifepristone determination. The results demonstrated that only the AGREE metric tool correlated with TOPSIS; however, there was no correlation with other metric tools. The analysis results suggest that TOPSIS is a very useful tool for ranking or selecting the analytical procedure in terms of its greenness and that it can be easily integrated with other green metrics tools for method greenness assessment.
Keyphrases
- solid phase extraction
- liquid chromatography
- liquid chromatography tandem mass spectrometry
- high performance liquid chromatography
- tandem mass spectrometry
- molecularly imprinted
- mass spectrometry
- simultaneous determination
- high resolution mass spectrometry
- ms ms
- ultra high performance liquid chromatography
- gas chromatography mass spectrometry
- gas chromatography
- machine learning
- risk assessment
- electronic health record
- deep learning
- minimally invasive
- human health
- high speed