Magnetic γ-Fe2O3-Loaded Attapulgite Sorbent for Hg0 Removal in Coal-Fired Flue Gas

A magnetically recoverable composite mercury removal sorbent was produced by introducing magnetic γ-Fe2O3 into attapulgite (ATT) (xFe1ATT) via the co-precipitation method and used to remove Hg0 in the simulated coal-fired power plant flue gas. The as-prepared 0.5Fe1ATT sorbent was characterized by X-ray diffraction, Brunauer–Emmett–Teller, transmission electron microscopy, vibrating sample magnetometer, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy analyses. The results showed that the Hg0 removal performance of the composite of γ-Fe2O3 and ATT was significantly promoted in comparison to pure γ-Fe2O3 and ATT individually. A relatively high magnetization value and good Hg0 removal performance were obtained by the sample of 0.5Fe1ATT. O2 could enhance Hg0 removal activity via the Mars–Maessen mechanism. NO displayed a significant promotion effect on Hg0 removal as a result of the formation of active species, such as NO2 and NO+. SO2 inhibited the removal of Hg0 as a result of its competition adsorption against Hg0 for the active sites and the sulfation of the sorbent. However, the introduction of NO could obviously alleviate the adverse effect of SO2 on the Hg0 removal capability. H2O showed a prohibitive effect on Hg0 removal as a result of its competition with Hg0 for the active sites. The findings of this study are of fundamental importance to the development of efficient and economic magnetic mercury sorbents for Hg0 removal from coal-fired boiler flue gases

Unsupervised Saliency Estimation based on Robust Hypotheses

Visual saliency estimation based on optimization models is gaining increasing popularity recently. In this paper, we formulate saliency estimation as a quadratic program (QP) problem based on robust hypotheses. First, we propose an adaptive center-based bias hypothesis to replace the most common image center-based center-bias. It calculates the weighted center by utilizing local contrast which is much more robust when the objects are far away from the image center. Second, we model smoothness term on saliency statistics of each color. It forces the pixels with similar colors to have similar saliency statistics. The proposed smoothness term is more robust than the smoothness term based on region dissimilarity when the image has complicated background or low contrast. The primal-dual interior point method is applied to optimize the proposed QP in polynomial time. Extensive experiments demonstrate that the proposed method can outperform 10 state-of-the-art methods on three public benchmark datasets

Microbial metabolism influences microplastic perturbation of dissolved organic matter in agricultural soils

An estimated 258 million tons of plastic enter the soil annually. Joining persistent types of microplastic (MP), there will be an increasing demand for biodegradable plastics. There are still many unknowns about plastic pollution by either type, and one large gap is the fate and composition of dissolved organic matter (DOM) released from MPs as well as how they interact with soil microbiomes in agricultural systems. In this study, polyethylene MPs, photoaged to different degrees, and virgin polylactic acid MPs were added to agricultural soil at different levels and incubated for 100 days to address this knowledge gap. We find that, upon MP addition, labile components of low aromaticity were degraded and transformed, resulting in increased aromaticity and oxidation degree, reduced molecular diversity, and changed nitrogen and sulfur contents of soil DOM. Terephthalate, acetate, oxalate, and L-lactate in DOM released by polylactic acid MPs and 4-nitrophenol, propanoate, and nitrate in DOM released by polyethylene MPs were the major molecules available to the soil microbiomes. The bacteria involved in the metabolism of DOM released by MPs are mainly concentrated in Proteobacteria, Actinobacteriota, and Bacteroidota, and fungi are mainly in Ascomycota and Basidiomycota. Our study provides an in-depth understanding of the microbial transformation of DOM released by MPs and its effects of DOM evolution in agricultural soils