Enhanced removal of perfluorooctanoic acid (PFOA) via microwave-fenton-reactive membrane filtration

Perfluorooctanoic Acid (PFOA), one of the common per- and poly fluorinated alkylated substances (PFASs), is increasingly detected in the environment due to the diverse industrial applications and high resistance to degradation processes. This study evaluated degradation of PFOA in microwave-assistant catalytic membrane filtration, a process that integrates microwave catalytic reactions into a ceramic membrane filtration. First, water permeation of the pristine and catalyst-coated membranes were examined under the influence of microwave irradiation to analyse the impacts of the coating layer and water temperature increase on permeate flux, which were well interpreted by three models. Then, the PFOA removal was first assessed in a continuous filtration model with and without microwave irradiation. Our results show that PFOA adsorbed on membrane and catalyst materials and fully penetrated the membrane filter after reaching adsorption equilibrium. Under microwave irradiation (7.2 watt·cm-2), approximate 65.9% of PFOA (25 μg·L-1) in the feed solution was degraded within a hydraulic time of 2 min (at the permeate flow rate of 43 LMH) due to the microwave-Fenton like reactions. In addition, low flow rates and moderate catalyst coating densities are critical for optimizing PFOA removal. Finally, potential degradation mechanisms of PFOA were proposed through the analysis of degradation by-products (e.g., PFPeA). The findings may provide new insight into the development of reactive membrane-enabled systems for destruction of refractory PFAS

Multi-scale analyses of granular flows for disaster resilience enhancement

A study that overlaps the fundamentals of granular flows with human responses to disasters at the community or regional scale is considered to be a strategic approach that advances existing methods in natural and human-induced hazard research in light of global-scale changes in earth systems. This study aims to improve the understanding: 1) on the mechanical behaviors of fluidized loess flowslide using centrifuge modeling as well as in-house designed laboratory testing and elastic wave characterization techniques (i.e. natural systems), and 2) on the cascading impacts of geohazards on local communities, assessing disaster resilience associated with reconstruction strategies and the performance of debris flow mitigation systems (i.e. natural-human systems interactions). The current work reveals the state-dependent effects of structure on flow behavior of loess and proposes modified criteria to predict the flow behavior. Laboratory tests show the changes in the mechanical behavior due to decementation of loess and indicate the needs to study loess within the scope of geotechnical analysis. The failure mechanism of loess flowslide is better understood from the study on the deformation process that shows the compounding effects of increasing pore-water pressure and reducing confining stresses on static liquefaction. The earthquake and post-earthquake impacts are documented after the 2008 Wenchuan earthquake, which permits a pilot study on quantifying the recovery processes of two communities of different reconstruction modes in light of Bayesian-based learning method. The design and performance of post-earthquake debris flow mitigation systems are reviewed; it offers a simple and robust data-driven approach to evaluate the effectiveness of debris flow mitigation systems at the regional scale.Ph.D

CityDreamer: Compositional Generative Model of Unbounded 3D Cities

In recent years, extensive research has focused on 3D natural scene generation, but the domain of 3D city generation has not received as much exploration. This is due to the greater challenges posed by 3D city generation, mainly because humans are more sensitive to structural distortions in urban environments. Additionally, generating 3D cities is more complex than 3D natural scenes since buildings, as objects of the same class, exhibit a wider range of appearances compared to the relatively consistent appearance of objects like trees in natural scenes. To address these challenges, we propose CityDreamer, a compositional generative model designed specifically for unbounded 3D cities, which separates the generation of building instances from other background objects, such as roads, green lands, and water areas, into distinct modules. Furthermore, we construct two datasets, OSM and GoogleEarth, containing a vast amount of real-world city imagery to enhance the realism of the generated 3D cities both in their layouts and appearances. Through extensive experiments, CityDreamer has proven its superiority over state-of-the-art methods in generating a wide range of lifelike 3D cities.Comment: Project page: https://haozhexie.com/project/city-dreame