Song T (PhD student), T Q, Chen J *. Multi task based sound localization model, in Proceedings of 148th Audio Engineering Society International Convention. Vienna, Austria; 2020:1-6.
Changing climate is one of the most challenging environment issues worldwide. The objective of this paper is to develop a Multi-Dimensional Hypothetical Fuzzy Risk Simulation Model to facilitate the Greenhouse Gases mitigation policy development and multi-dimensional risk simulation. In detail, the comprehensive performances of various industries are evaluated and analyzed through Hypothetical Extraction Method. The preferences of decision-makers are considered through Analytic Hierarchy Process and Fuzzy Technique for Order Preference by Similarities to Ideal Solution method to develop the optimized Greenhouse Gases mitigation policies. The multi-dimensional risks of optimized Greenhouse Gases mitigation policies are simulated through RAS method. A detailed case study of the Province of Saskatchewan, Canada, is conducted to illustrate the potential benefits of the proposed model and support the Greenhouse Gases mitigation policy development. It is found that Electric power generation, transmission and distribution sector is the key industry in Saskatchewan. The government supports are suggested to be allocated to the Electric power generation, transmission and distribution sector, since it will benefit the province from environmental, economic, and urban metabolic perspectives.
Surface heating membrane distillation overcomes several limitations inherent in conventional membrane distillation technology. Here we report a successful effort to grow in situ a hexagonal boron nitride (hBN) nanocoating on a stainless-steel wire cloth (hBN-SSWC), and its application as a scalable electrothermal heating material in surface heating membrane distillation. The novel hBN-SSWC provides superior vapour permeability, thermal conductivity, electrical insulation and anticorrosion properties, all of which are critical for the long-term surface heating membrane distillation performance, particularly with hypersaline solutions. By simply attaching hBN-SSWC to a commercial membrane and providing power with an a.c. supply at household frequency, we demonstrate that hBN-SSWC is able to support an ultrahigh power intensity (50 kW m−2) to desalinate hypersaline solutions with exceptionally high water flux (and throughput), single-pass water recovery and heat utilization efficiency while maintaining excellent material stability. We also demonstrate the exceptional performance of hBN-SSWC in a scalable and compact spiral-wound electrothermal membrane distillation module.
As has been the case in North America and western Europe, the SO2 emissions have substantially reduced in the North China Plain (NCP) in recent years. Differential rates of reduction in SO2 and NOx concentrations result in the frequent occurrence of particulate matter pollution dominated by nitrate (pNO(3)(-)) over the NCR. In this study, we observed a polluted episode with the particulate nitrate mass fraction in nonrefractory PM1 (NR-PM1) being up to 44 % during wintertime in Beijing. Based on this typical pNO(3)(-)-dominated haze event, the linkage between aerosol water uptake and pNO(3)(-) enhancement, further impacting on visibility degradation, has been investigated based on field observations and theoretical calculations. During haze development, as ambient relative humidity (RH) increased from similar to 10 % to 70 %, the aerosol particle liquid water increased from similar to 1 mu g m(-3) at the beginning to similar to 75 mu g m(-3) in the fully developed haze period. The aerosol liquid water further increased the aerosol surface area and volume, enhancing the condensational loss of N2O5 over particles. From the beginning to the fully developed haze, the condensational loss of N2O5 increased by a factor of 20 when only considering aerosol surface area and volume of dry particles, while increasing by a factor of 25 when considering extra surface area and volume due to water uptake. Furthermore, aerosol liquid water favored the thermodynamic equilibrium of HNO3 in the particle phase under the supersaturated HNO3 and NH3 in the atmosphere. All the above results demonstrated that pNO(3)(-) is enhanced by aerosol water uptake with elevated ambient RH during haze development, in turn facilitating the aerosol take-up of water due to the hygroscopicity of particulate nitrate salt. Such mutual promotion between aerosol particle liquid water and particulate nitrate enhancement can rapidly degrade air quality and halve visibility within 1 d. Reduction of nitrogen-containing gaseous precursors, e.g., by control of traffic emissions, is essential in mitigating severe haze events in the NCP.
Abstract Understanding nanoconfined water effect on CO2 utilization and storage has tremendous implications in academic research and practical applications, especially for extremely low-permeability shale reservoirs. Here, a new nanoscale-extended cubic-plus association equation of state is developed by including the confinement effects and intermolecular interactions, based on which the phase behavior and interfacial tension of the pure water and water-CO2 system are accurately calculated. Moreover, three important parameters, caprock-sealing pressure, maximum storage height, and storage capacity, are quantitatively determined for assessing the potential for the CO2 storage. On the basis of the results from this study, the negative effect of nanoconfiend water can be substantially reduced or even converted to be positive for the CO2 utilization and storage in the shale reservoirs due to the extremely small pore scale as well as the associated strong confinements and intermolecular interactions. Overall, this study supports the foundation of general practical applications pertaining to CO2 utilization and geological storage in unconventional low-permeability shale formations with existence of nanoconfined water.
The detection of ultra-low concentration of biomacromolecules remains the focus of research in micro-nanofluidic systems. Sample enrichment is primarily targeted at very low concentration of sample detection tasks. The use of ion concentration polarization principle is the most efficient means to solve the problem of electrokinetic ion enrichment. In this paper, numerical simulation of nano-electrokinetic ion enrichment in a micro-nanofluidic preconcentrator with nanochannel's Cantor fractal wall structure was performed based on Poisson-Nernst-Planck equation combined with the Navier-Stokes equation. The results show that reducing the initial length L-0, increasing the initial height h(0), increasing the fractal step n and using the unstaggered structure in the Cantor fractal principle can increase the ion enrichment concentration and peak voltage. The initial ion concentration is 0.1 mol/m(3). When the applied voltage is 30 V and the initial height h(0) increases from 35 to 45 nm, the ion enrichment concentration drastically increases from 1.007 to 1.410 mol/m(3) by 40%. This study provides a theoretical basis and a novel design method for improving the sensitivity of micro-nanofluidic chips and the design of ultra-low concentration sample testing equipment.
Anthropogenic emissions alter secondary organic aerosol (SOA) formation chemistry from naturally emitted isoprene. We use correlations of tracers and tracer ratios to provide new perspectives on sulfate, NOx, and particle acidity influencing isoprene-derived SOA in two isoprene-rich forested environments representing clean to polluted conditions—wet and dry seasons in central Amazonia and Southeastern U.S. summer. We used a semivolatile thermal desorption aerosol gas chromatograph (SV-TAG) and filter samplers to measure SOA tracers indicative of isoprene/HO2 (2-methyltetrols, C5-alkene triols, 2-methyltetrol organosulfates) and isoprene/NOx (2-methylglyceric acid, 2-methylglyceric acid organosulfate) pathways. Summed concentrations of these tracers correlated with particulate sulfate spanning three orders of magnitude, suggesting that 1 $μ$g m–3 reduction in sulfate corresponds with at least ∼0.5 $μ$g m–3 reduction in isoprene-derived SOA. We also find that isoprene/NOx pathway SOA mass primarily comprises organosulfates, ∼97% in the Amazon and ∼55% in Southeastern United States. We infer under natural conditions in high isoprene emission regions that preindustrial aerosol sulfate was almost exclusively isoprene-derived organosulfates, which are traditionally thought of as representative of an anthropogenic influence. We further report the first field observations showing that particle acidity correlates positively with 2-methylglyceric acid partitioning to the gas phase and negatively with the ratio of 2-methyltetrols to C5-alkene triols.
Li X, Hu S, Zou L. Natural Answer Generation via Graph Transformer, in Web and Big Data - 4th International Joint Conference, APWeb-WAIM 2020, Tianjin, China, September 18-20, 2020, Proceedings, Part I.Vol 12317. Springer; 2020:302–318.
Ferrihydrite nanoparticles (Fh NPs) are ubiquitous in natural environments. However, their colloidal stability, and fate and transport behavior are difficult to predict in the presence of heterogeneous natural organic matter (NOM) mixtures. Here, we investigated the adsorption and aggregation behavior of Fh NPs exposed to NOM fractions with different molecular weights (MW). The NOM fraction with MW < 3 kDa destabilized the NPs, resulting in accelerated aggregation even at high C/Fe mass ratios, whereas higher MW NOM fractions imparted better colloidal stability with increasing MW and C/Fe ratio. Despite differences in the functional group composition of the bulk (dissolved) NOM fractions, all NOM fractions produced similar adsorbed layer compositions on the NPs, suggesting minimal contribution of chemical properties to the distinctive aggregation behavior. Rather, the higher adsorbed mass and larger size of the higher MW fractions were key factors in stabilizing the NPs through steric repulsion, whereas the lowest MW fraction had low adsorbed mass and was unable to counter electrostatic patch-charge attraction when the NPs are positively charged. This mechanistic understanding helps us predict the transport and fate of Fh NPs and the associated contaminants in natural environments with varying NOM compositions.
Complex networks have been an effective paradigm to represent a variety of complex systems, such as social networks, collaborative networks, and biomolecular networks, where network topology is unkown in advance and has to be inferred with limited observed measurements. Compressive sensing (CS) theory is an efficient technique to achieve accurate network reconstruction in complex networks by formulating the problem as a series of convex optimization models and utilizing the sparsity of networks. However, previous CS-based works have to solve a large number of convex optimization models, which is time-consuming especially when the network scale becomes large. Further, since partial link information shared among multiple convex models, data conflict problem may incur when the derived common variables are inconsistent, which may badly degrade infer precision. To address the issues above, we propose a new model for network reconstruction based on compressive sensing. To be specific, a single convex optimization model is formulated for inferring global network structure by combing the series of convex optimization models, which can effectively improve computation efficiency. Further, we devise a vector to represent the connection states of all the nodes without redundant link information, which is used for representing the unkown topology variables in the proposed optimization model based a devised transformation method. In this way, the proposed model can eliminate data conflict problem and improve infer precision. The comprehensive simulation results shows the superiority of the proposed model compared with the competitive algorithms under a wide variety of scenarios.
