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Green Analytical Chemistry (GAC) aims at environmentally sustainable practices, minimizing the use of hazardous substances, waste and resource consumption, and improving energy efficiency. This review emphasizes the application of chemometric approaches in GAC for various industries focusing on process optimization, data reduction, experimental design, and advanced signal processing. Chemometrics uses mathematical and statistical methods, such as Principal Component Analysis (PCA), Partial Least Squares (PLS) and Design of Experiments (DoE), to effectively manage complex and high-dimensional data in chemistry. These techniques enable multivariate calibration, simultaneous determination of analytes and robust method development according to Quality by Design (QbD) principles, while reducing the solvent consumption up to 60% and significantly decreasing the analysis times. The application of greenness metrics, such as NEMI, Analytical Eco-Scale, GAPI, AGREE and AMVI, allows the quantification of environmental impacts and stimulates the development of sustainable analytical procedures. Chemometric approaches improve data quality through the use of signal processing tools such as wavelet transforms, filtering methods and Net Analyte Signal (NAS) which increase the signal to noise ratio and analytical accuracy. Chemometrics supports fast, nondestructive quality control, authentication and process monitoring in sectors such as food, pharmaceuticals, nutraceuticals and wine industries and helps in reducing resource consumption and waste. Proper validation and software tools can overcome the challenges of statistical expertise, complex data interpretation, and reproducibility. A future trend in the field of sustainable analytical science is the use of chemometric tools in combination with artificial intelligence, machine learning, Industry 4.0 and sensor technologies. In conclusion, chemometrics is an indispensable tool in GAC, providing efficient, accurate and environmentally friendly solutions in compliance with regulatory frameworks, and encouraging long-term sustainability.
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Saha et al. (2026) studied this question.
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