Three ambient PM2.5 filters extracts were measured in the DTT assay, alongside mixtures of analytical standards prepared to match PAH concentrations in the filter extracts to test if the OP follows an additive model of toxicity. The additive prediction model did not accurately predict the DTT consumption in the assay for any of the prepared standard mixtures or ambient PM2.5 filter extracts, indicating a much more complex model of toxicity for the OP of PAHs in ambient PM2.5. This study combined computed molecular properties with toxicologically relevant assay results to probe the OP of anthropogenically driven portions of ambient PM2.5, and results in a better understanding of the complexity of ambient PM2.5 OP.Methylmercury accumulated at the top of aquatic food chains constitutes a toxicological risk to humans and other top predators. Biomagnification of methylmercury takes place among vertebrates at the higher trophic levels, but this process is less elucidated in benthic invertebrates at the lower trophic levels. Therefore, we investigated the accumulation from food and elimination of methylmercury and inorganic mercury in the benthic sea star Asterias rubens (L.) - a representative of trophic level ~3 - in laboratory experiments. Sea stars fed over 49 days with contaminated mussels (Mytilus edulis) accumulate methylmercury and inorganic mercury to the highest concentrations in the digestive glands, the pyloric caeca, less in stomach, gonad, tube feet, aboral body wall and not to detectable levels in the coelomic fluid. Concerning whole body contents, steady states were reached for both methylmercury and inorganic mercury during the 7-week feeding period and the sea stars reached approximately ½ and ¼ of the concentrations in the mussel food for the two mercury forms, respectively. Half-lives for the elimination of the two mercury forms varied between 45 and 173 days in a 140-d elimination period following the feeding period; inorganic mercury was eliminated faster than methylmercury. Examination of total mercury concentrations in field-collected sea stars confirmed this lack of trophic magnification in relation to the major food items, soft parts of molluscs. We suggest that mercury is not trophically magnified in sea stars 1) because they eliminate methylmercury faster than larger fish and decapod crustaceans and 2) maybe more importantly, because inorganic mercury with its faster elimination constitutes a larger fraction of the total mercury in the food at the lower trophic levels - as opposed to methylmercury which dominates at the higher trophic levels.The use of agro-biowaste compost fertilizers in agriculture is beneficial from technical, financial, and environmental perspectives. Nevertheless, the physical, mechanical, and agronomical attributes of agro-biowaste compost fertilizers should be engineered to reduce their storage, handling, and utilization costs and environmental impacts. Pelletizing and drying are promising techniques to achieve these goals. In the present work, the effects of process parameters, including compost particle size/moisture content, pelletizing compression ratio, and drying air temperature/velocity, were investigated on the density, specific crushing energy, and moisture diffusion of agro-biowaste compost pellet. The Taguchi technique was applied to understand the effects of independent parameters on the output responses, while the optimal pellet properties were found using the iterative thresholding method.  https://www.selleckchem.com/products/pds-0330.html  The soil and plant (sweet basil) response to the optimal biocompost pellet was experimentally evaluated. The farm applica collectively mitigate the weighted environmental impact of farm application of the agro-biowaste compost by more than 63%. This reduction could be attributed to the fact that the pelletizing-drying processes could avoid methane emissions from the untreated agro-biowaste compost during the farm application. Overall, pelletizing-drying of the agro-biowaste compost could be regarded as a promising strategy to improve the environmental and agronomical performance of farm application of organic biofertilizers.The high density and viscosity of fuel oil leads to its prolonged persistence in the environment and causes widespread contamination. Dispersants with a low environmental impact are necessary for fuel oil spill remediation. This study aimed to formulate bio-based dispersants by mixing anionic biosurfactant (lipopeptides from Bacillus subtilis GY19) with nonionic oleochemical surfactant (Dehydol LS7TH). The synergistic effect of the anionic-nonionic surfactant mixture produced a Winsor Type III microemulsion, which promoted petroleum mobilization. The hydrophilic-lipophilic deviation (HLD) equations for ionic and nonionic surfactant mixtures were compared, and it was found that the ionic equation was applicable for the calculation of lipopeptides and Dehydol LS7TH concentrations. The best formula contained 6.6% w/v lipopeptides and 11.9% w/v Dehydol LS7TH in seawater, and its dispersion effectiveness for bunker fuels A and C was 92% and 78%, respectively. The application of bio-based dispersants in water sources was optimized by Box-Behnken design. The efficiency of the bio-based dispersant was affected by the dispersant-to-oil ratios (DORs) but not by the water salinity. A suitable range of DORs for different oil contamination levels could be identified from the response surface plot. The dispersed fuel oil was further degraded by adding an oil-degrading bacterial consortium to the chemically enhanced water accommodated fractions (CEWAFs). After 7 days of incubation, the concentration of fuel oil was reduced from 3692 mg/L to 356 mg/L (88% removal efficiency). On the other hand, the abiotic control removed less than 40% fuel oil from the CEWAFs. This bio-based dispersant had an efficiency comparable to that of a commercial dispersant. The process of dispersant formulation and optimization could be applied to other surfactant mixtures.Outdoor concentrations of particulate matter with an aerodynamic diameter of less then 2.5 μm (PM2.5) are often used as a surrogate for population exposure to PM2.5 in epidemiological studies. However, people spend most of their daily activities indoors; therefore, the relationship between indoor and outdoor PM2.5 concentrations should be considered in the estimation of population exposure to PM2.5. In this study, a population exposure model was developed to predict seasonal population exposure to PM2.5 in Seoul, Korea. The input data for the population exposure model comprised 3984 time-location patterns, outdoor PM2.5 concentrations, and the microenvironment-to-outdoor PM2.5 concentrations in seven microenvironments. A probabilistic approach was used to develop the Korea simulation exposure model. The determinants for the population exposure group were identified using a multinomial logistic regression analysis. Population exposure to PM2.5 varied significantly among the three seasons (p less then 0.01).