Putting biomonitors to work: native moss as a screening tool for solid waste incineration.

Solid waste incineration (SWI) can release numerous air pollutants although the geographic reach of emissions is not routinely monitored. While many studies use moss and lichens for biomonitoring trace elements, including around SWIs, few investigate the complex, multi-element footprint expected from SWI emissions. This study develops using native moss as a screening tool for SWI while also informing community concerns about an aging incinerator in rural Oregon, USA.

Spectrophotometric thermodynamic analysis of methylene blue aggregation in water by chemometrics; what comes in the presence of different cyclodextrins?

Spectrophotometry has been utilized to characterize the thermodynamic/dynamic properties of self-aggregation of methylene blue (MB) in water, particularly while interacting with a modulator like different cyclodextrins (α-, β-, hydroxypropyl-β- (HP-β-), and γ-CDs). These systems comprise many interactions that make such chemical systems sophisticated. We developed a mathematical modeling-fitting analysis for the simultaneous quantitative analysis of thermodynamic parameters of chemical reactions, relying on the fitting algorithm.

PLS and N-PLS based MIA-QSPR modeling of the photodegradation half-lives for polychlorinated biphenyl congeners.

Multivariate image analysis applied to quantitative structure-property relationships (MIA-QSPR) has been used to predict photodegradation half-lives of polychlorinated biphenyls in -hexane solution under UV irradiation. Owing to the high cost and laboriousness in experimental tests, developing a simple method to assess the photostability of the compounds is important in environmental risk assessment. The predictor block was built by superposition of the chemical structures (2D images), which was unfolded to a matrix, suitable for multilinear and classical partial least squares, N-PLS and PLS, respectively, as regression methods, demonstrating different predictive capability to each other.

Multivariate image analysis-quantitative structure-retention relationship study of polychlorinated biphenyls using partial least squares and radial basis function neural networks.

Polychlorinated biphenyls belong to a class of hazardous and environmental pollutants. Gas chromatography separation and experimental relative retention time evaluation of these compounds on a poly (94% methyl/5% phenyl) silicone-based capillary non-bonded and cross-linked column are time consuming and expensive. In this study, relative retention times were estimated using two-dimensional images of molecules based on a newly implemented rapid and simple quantitative structure retention relationship methodology.