In this study, the reliability of NDIR-based sensors was explored by evaluatingthe comparability between measurement systems in the near real-time analysis of CO₂. Forthis purpose, replicate analyses were performed using sensors of two different model types(H-550 and B-530, ELT Company, Korea). Three replicate data of each sensor typecollected continuously by side-by-side analysis in three second intervals (a duration of 304hour) were evaluated for the relative performance of NDIR sensors. The reproducibility ofsensors, when assessed by relative standard error (RSE %) values of all sensor units,showed moderate changes with time with the overall mean of 2.33%. When CO₂measurements from all NDIR sensor units were evaluated by correlation analysis, theresults showed strong comparability, regardless of the model type. The overall results ofthis study suggest that NDIR sensors are reliable enough to produce highly comparabledata at least in a relative sense.

Monoterpenes are volatile organic compounds that play important roles in atmospheric chemistry, plant physiology, communication, and defense. This review compiles the monoterpene emission flux data reported for different regions and plant species and highlights the role of abiotic environmental factors in controlling the emissions of biogenic monoterpenes and their emission fluxes for terrestrial plant species (including seasonal variations). Previous studies have demonstrated the role and importance of ambient air temperature and light in controlling monoterpene emissions, likely contributing to higher monoterpene emissions during the summer season in temperate regions. In addition to light and temperature dependence, other important environmental variables such as carbon dioxide (CO₂), ozone (O₃), soil moisture, and nutrient availability are also known to influence monoterpene emissions rates, but the information available is still limited. Throughout the paper, we identify knowledge gaps and provide recommendations for future studies.

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.