Near-Infrared Spectroscopy Combined with Multivariate Tools for Analysis of Trace Metals in Environmental Matrices

Abstract

Environmental contamination by trace elements is becoming increasingly important problem worldwide. Trace metals such as cadmium, copper, lead, chromium, and mercury are major environmental pollutants that are predominantly found in areas with high anthropogenic activities. Therefore, there is a need for rapid and reliable tools to assess and monitor the concentration of heavy metal in environmental matrices. A nondestructive, cost-effective, and environmentally friendly procedure based on near-infrared reflectance spectroscopy (NIRS) and chemometric tools has been used as alternative technique for the simultaneous estimation of various heavy metal concentrations in environmental sample. The metal content is estimated by assigning the absorption features of metals associated with molecular vibrations of organic and inorganic functional groups in organic matter, silicates, carbonates, and water at 780-2500 nm in the near-infrared region.This chapter, reviewed the application of NIRS combined with chemometric tools such as multiple linear regression (MLR), principal component regression (PCR), and partial least squares (PLS) regression. The disadvantages and advantages of each chemometric tool are discussed briefly.

Greening the waves: experimental and chemometric approaches in spectroscopic methods for organic pollutant determination in natural waters

“…Furthermore, reports also illustrated the use of IoT and wireless sensor networks for water quality monitoring, demonstrating the practical application of advanced technologies in real-time water quality assessment. [59][60][61] Moreover, the integration of spectroscopic techniques with chemometric analysis has further enhanced water quality monitoring. Reports demonstrated the use of chemometrics for the development of green analytical methods to determine the shelf-life of olive oils, highlighting the application of uorescence spectroscopy and multivariate analysis methods for quality control.…”

“…Furthermore, reports also illustrated the use of IoT and wireless sensor networks for water quality monitoring, demonstrating the practical application of advanced technologies in real-time water quality assessment. 59–61…”