Tallinn University of Technology

Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) has emerged as a pivotal analytical technique for trace element determination in solid fuel wastes (e.g., coal fly ash, biomass-derived char, petroleum coke residues), owing to its high sensitivity (ng/g-level limits of detection), micron-scale spatial resolution (1-100 μm), and capability for simultaneous multi-element analysis. This technique enables in situ micro-area characterization without complex sample preparation, precisely mapping the spatial distribution of hazardous metals (Pb, Cd, Cr) and Rare Earth Elements (REEs) within heterogeneous matrices (e.g., silicate glass phases vs. porous carbon interfaces). Such insights are crucial for assessing environmental risks (e.g., ecotoxicity) and evaluating the potential for resource recovery (e.g., REE-enriched micro-domains with concentrations exceeding 500 μg/g in coal ash). However, challenges persist due to the compositional complexity of solid fuel wastes, including matrix-dependent fractionation, scarcity of calibration standards, and limitations in universal calibration strategies. Future research must prioritize: i) Optimizing sample preparation protocols; ii) Advancing calibration strategies; and iii) Integrating complementary analytical techniques. By harmonizing technological innovations with standardization, LA-ICP-MS shows promise in advancing precise environmental risk assessment and high-value resource recovery from solid fuel wastes, thereby contributing to sustainable waste management in line with carbon neutrality goals.

Individual chronotype may shape economic outcomes through alignment or misalignment with work and societal schedules. Genome-wide association studies suggest that morningness-eveningness has a partially genetic basis. This study examines how genetic predisposition to chronotype relates to economic disadvantage, using polygenic indices for morningness-eveningness both as predictors and as instruments for phenotypic chronotype.

Employing various regression and extended regression models, we studied data from 20,121 working-aged adults representative of Finnish regions, combining genetic, registry, and survey data from 1992 to 2017.

Genetic markers for morningness were monotonically negatively associated with educational attainment (p = 0.002)-a key determinant of economic success-particularly in males. Conversely, the same genetic markers were also monotonically negatively associated with the likelihood of belonging to the lowest income quintile in males (p = 0.012), suggesting differential valuation of chronotype traits in education versus the labour market. This pattern emerged in post-2000. Furthermore, among males with higher education, genetic predisposition to eveningness was linked to a higher likelihood of falling into the lowest income quintile (p < 0.001), indicating reduced economic returns to their education. No significant associations between chronotype-related genetic markers and income were observed in females across education levels.

This study reveals emerging, gender-specific inequalities in how genetically influenced chronotype traits relate to economic outcomes. Genetic predisposition to eveningness favoured education but hindered income-especially in highly educated males-via phenotypic chronotype pathways. Though modest, these effects highlight the need for workplace inclusion through recognition of chronotype diversity, public sleep health initiatives, and flexible work structures.

The complex matrix of oil shale and its solid wastes poses significant challenges for trace element quantification. This study compares the performance and challenges of seven analytical methods for quantifying 19 trace elements (V, Cr, Mn, Co, Ni, Cu, Zn, As, Zr, Mo, Sn, Sb, Ba, La, Ce, Pb, Bi, Th, and U) in oil shale and its solid wastes. These methods include matrix-matched and matrix-independent laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) method employing different internal standards, as well as traditional solution-based inductively coupled plasma mass spectrometry (ICP-MS) with three digestion protocols (HNO₃, HNO₃-HF, and HNO₃-HCl-HF-HClO₄). Validation with certified reference materials (SGR-1b, ACIRS-A1-2016) and practical samples (oil shale and related residues from laboratory and power plant combustion) showed that matrix-matched LA-ICP-MS using lithium borate glass standard effectively mitigated matrix effects and achieved superior analytical performance (recoveries within ±15% with coefficient of variation (CV) ≤ 5%) and |En| < 1 for 5/9 elements in ash matrices) compared to matrix-independent LA-ICP-MS and ICP-MS methods. While conventional ICP-MS methods performed well for certain elements (e.g., Ba, Mn, and Cr), but showed limited accuracy and consistency for others due to remaining matrix effects, even with internal standard correction, especially in complex ash matrices. These findings underscore the strengths and limitations of each technique and highlight the potential of matrix-matched LA-ICP-MS as a promising tool for rapid and accurate trace element quantification, offering promising applications in resource recovery and environmental risk assessment in the oil shale industry.