AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Selective separation of cobalt versus nickel by split-phosphinate complexation using a phosphonium-based ionic liquid

Environmental Chemistry Letters - The rising demand of metals for batteries is calling for advanced methods to separate metallic mixtures in mineral ores and electronic waste. In particular, the...     

Novel Tough Crystalline Blends of Polylactide with Ethylene Glycol Derivative of POSS

Blending of polylactide (PLA) with low stereoregularity and polyhedral oligomeric silsesquioxane grafted with arms of poly(ethylene glycol) methyl ether, acting as a plasticizer, allowed us previously to obtain a novel stable elastomeric-like material. The present contribution focuses on the properties of semi-crystalline PLA plasticized with this compound. Melt blends of PLA with 5–15 wt% of the plasticizer, were compression molded, quenched and annealed, which enabled cold-crystallization. The glass transition temperature of the blends and their drawability depended on their crystallinity and plasticizer content. The best ductility was reached at the plasticizer content of 15 wt%; the achieved strain at break was 6.5 (650%) and 1.3 (130%), for the quenched and annealed material, respectively. The latter value exceeded 20 times the strain at break of neat crystalline PLA. The tensile toughness of the annealed 15 wt% blend was 12 times larger than that of crystalline PLA. Moreover, annealing of 15 wt% blend improved its yield strength by 40%. Despite the two peaks of the loss modulus, indicating the two glass transitions in this blend, no heterogeneities were found by scanning electron microscopy, indicating that the plasticizer enriched phase formed instead of distinct inclusions of the plasticizer.     

Supervisor expediency to employee expediency: The moderating role of leader–member exchange and the mediating role of employee unethical tolerance

We utilize social learning theory to test the role‐modeling effect of supervisor expediency (i.e., a supervisor's use of unethical practices to expedite work for self‐serving purposes). In particular, we examine the relationship between supervisor expediency and employee expediency, as moderated by leader–member exchange (LMX) and mediated by employee unethical tolerance. We predict that employees are more likely to model their supervisors' expedient behaviors when their relationship is characterized by high‐LMX (a high‐quality exchange relationship that is rich in socioemotional support). Furthermore, we argue that supervisor expediency, especially when LMX is high, influences employees' attitudes of unethical tolerance, which then affects employees' expedient behaviors. Across 2 multisource field studies and a third time‐lagged field study, we found general support for our theoretical predictions. Theoretical and practical implications are discussed.     

The quest for environmental justice in China: citizen participation and the rural–urban network against Panguanying’s waste incinerator

Environmental distribution conflicts (EDCs) related to the construction and operation of waste incinerators have become commonplace in China. This article presents a detailed case study of citizen opposition to an incinerator in the village of Panguanying, Hebei Province. Drawing on in-depth fieldwork, we show how this case was notable, because it transcended the local arena to raise bigger questions about environmental justice, particularly in relation to public participation in siting decisions, after villagers exposed fraudulent public consultation in the environmental impact assessment. An informal network between villagers and urban environmental activists formed, enabling the Panguanying case to exert influence far beyond the village locality. This network was critical in creating wider public debate about uneven power and substandard public participation in siting disputes, a central feature in many Chinese EDCs. By transcending local specificities and exposing broader, systemic inadequacies, this case became instrumental in supporting “strong sustainability”.     

Preparation of Viscose Fibres Stripped of Reactive Dyes and Wrinkle-Free Crosslinked Cotton Textile Finish

The chemical recycling of cellulosic fibres may represent a next-generation fibre–fibre recycling system for cotton textiles, though remaining challenges include how to accommodate fibre blends, dyes, wrinkle-free finishes, and other impurities from finishing. These challenges may disrupt the regeneration process steps and reduce the fibre quality. This study examines the impact on regenerated viscose fibre properties of a novel alkaline/acid bleaching sequence to strip reactive dyes and dimethyloldihydroxyethyleneureas (DMDHEU) wrinkle-free finish from cotton textiles. Potentially, such a bleaching sequence could advantageously be integrated into the viscose process, reducing the costs and environmental impact of the product. The study investigates the spinning performance and mechanical properties (e.g., tenacity and elongation) of the regenerated viscose fibres. The alkaline/acid bleaching sequence was found to strip the reactive dye and DMDHEU wrinkle-free finish from the cotton fabric, so the resulting pulp could successfully be spun into viscose fibres, though the mechanical properties of these fibres were worse than those of commercial viscose fibres. This study finds that reactive dyes and DMDHEU wrinkle-free finish affect the viscose dope quality and the regeneration performance. The results might lead to progress in overcoming quality challenges in cellulosic chemical recycling.