Image based analytical approaches for study of particulate matter (PM) in air

Abstract

Particulate matter (PM) stands as a predominant pollutant in developing countries, demanding effective source identification and remediation strategies. This review centers on the scanning electron microscopy (SEM) image-based methodology for PM analysis, particularly emphasizing the passive technique of utilizing plant leaves for PM capture. The SEM-image-based approach serves as a powerful tool for unraveling the morphological characteristics of PM, crucial for source identification. Additionally, SEM, when equipped with energy dispersive spectroscopy (EDS), enables chemical and mineralogical characterization, providing insights into the origin of PM. The first part of the review describes the plant as the best bio-sampler for PM. In this context, removal of PM from the environment through plant-based interventions is described. Subsequently, the application of SEM for size-based analysis using ImageJ and morphological analysis for source identification of PM is detailed. Following this, the PM chemical and mineralogical composition for source identification are described based on EDS analysis. Image-based techniques play a pivotal role in selecting the most effective plant species for PM removal from the air. The review comprehensively outlines the morphological, chemical, and mineralogical attributes utilized for PM source identification and their subsequent remediation by plants. Finally, the benefits of SEM-image-based techniques for PM analysis are elucidated. This review offers a holistic understanding of the SEM-EDS and plant-based approach, presenting a promising avenue for addressing PM pollution and enhancing environmental quality.