Microwave-Assisted Rapid Substitution of Ti for Zr to Produce Bimetallic (Zr/Ti)UiO-66-NH2 with Congenetic "Shell-Core" Structure for Enhancing Photocatalytic Removal of Nitric Oxide.

Efficient nitric oxide (NO) removal without nitrogen dioxide (NO2 ) emission is desired for the control of air pollution. Herein, a series of (Zr/Ti)UiO-66-NH2 with congenetic shell-core structure, denoted as Ti-UION, are rapidly synthesized by microwave-assisted post-synthetic modification for NO removal. The optimal Ti-UION (i.e., 2.5Ti-UION) exhibits the highest activity of 80.74% without NO2 emission with moisture, which is 21.65% greater than that of the UiO-66-NH2 . The NO removal efficiency of 2.5Ti-UION further increases to 95.92% without photocatalyst deactivation under an anhydrous condition. This is because selectively produced NO2 in photocatalysis is completely adsorbed into micropores, refreshing active sites for subsequent reaction. In addition, the enhanced photocatalytic activity after Ti substitution is due to the presence of Ti electron acceptor, the potential difference between the shell and core of Ti-UION crystal, and the high conductivity of TiO units. Additionally, the improved adsorption of gas molecules not only favors NO oxidation, but also avoids the emission of NO2 . This work provides a feasible strategy for rapid metal substitution in metal-organic frameworks and insights into enhanced NO photodegradation.

Atomic Fe/Zn anchored N, S co-doped nano-porous carbon for boosting oxygen reduction reaction.

Dual-single-atom catalysts are well-known due to their excellent catalytic performance of oxygen reduction reaction (ORR) and the tunable coordination environment of the active sites. However, it is still challengable to finely modulate the electronic states of the metal atoms and facilely fabricate a catalyst with dual-single atoms homogeneously dispersed on conductive skeletons with good mass transport. Herein, atomic FeNx/ZnNx sites anchored N, S co-doped nano-porous carbon plates/nanotubes material (Fe0.10ZnNSC) is rationally prepared via a facile room-temperature reaction and high-temperature pyrolysis. The as-prepared Fe0.10ZnNSC catalyst exhibits a positive onset potential of 0.956 V, an impressive half-wave potential of 0.875 V, excellent long-term durability, and a high methanol resistance, outperforming the benchmark Pt/C. The outstanding ORR performance of Fe0.10ZnNSC is due to its unique nanoarchitecture: a large specific surface area (1092.8 cm2 g-1) and well-developed nanopore structure ensure the high accessibility of active sites; the high conductivity of the carbon matrix guarantees a strong ability to transport electrons to the active sites; and the optimized electronic states of FeNx and ZnNx sites possess good oxygen intermediate adsorption/desorption capacity. This strategy can be extended to design and fabricate other non-precious dual-single-atom ORR catalysts.

Multi-step forecast of PM2.5 and PM10 concentrations using convolutional neural network integrated with spatial-temporal attention and residual learning.

Accurate and reliable forecasting of PM2.5 and PM10 concentrations is important to the public to reasonably avoid air pollution and for the governmental policy responses. However, the prediction of PM2.5 and PM10 concentrations has great uncertainty and instability because of the dynamics of atmospheric flows, making it difficult for a single model to efficiently extract the spatial-temporal dependences. This paper reports a robust forecasting system to achieve accurate multi-step ahead forecasting of PM2.5 and PM10 concentrations. First, correlation analysis is adopted to screen the spatial information on pollution and meteorology that may facilitate the prediction of concentrations in a target city. Then, a spatial-temporal attention mechanism is used to assign weights to original inputs from both space and time dimensions to enhance the essential information. Subsequently, the residual-based convolutional neural network with feature extraction capabilities is employed to model the refined inputs. Finally, five accuracy metrics and two additional statistical tests are applied to comprehensively assess the performance of the proposed forecasting system. In addition, experimental studies of three major cities in the Yangtze River Delta urban agglomeration region indicate that the forecasting system outperforms various prevalent baseline models in terms of accuracy and stability. Quantitatively, the proposed STA-ResCNN model reduces root mean square error by 5.595 %-15.247 % and 6.827 %-16.906 % for the average of 1-4 h ahead predictions in three major cities of PM2.5 and PM10, respectively, compared to baseline models. The applicability and generalization of the proposed forecasting system are further verified by the extended applications in the other 23 cities in the entire region. The results prove that the forecasting system is promising in the early warning, regional prevention, and control of air pollution.

Insights into the impurities of Bi2WO6 synthesized using the hydrothermal method.

Bismuth tungstate (Bi2WO6) nanomaterials are widely used as visible-light driven photocatalysts. However, limited attention has been paid to the purity of prepared Bi2WO6 nanoparticles, which may affect the photocatalytic performance and hinder in-depth study of Bi2WO6. In this work, the impurities of Bi2WO6 formed during the hydrothermal process under a wide range of acid-base conditions (from 1.5 M HNO3 to 0.5 M NaOH) were qualitatively analyzed and accurately quantified for the first time. After confirmation of Bi2WO6 stability, the impurities were dissolved using acid or base treatment, followed by measurements of the ion concentrations using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Furthermore, various characterization techniques including XRD, FE-SEM, TEM, UV-Vis DRS, XPS and FTIR were implemented to explore the change in morphology and optical properties of Bi2WO6 prepared in different acid-base environments, and to facilitate qualitative analysis of impurities. The hydrolytic properties of raw materials used for the synthesis of Bi2WO6 were also analyzed with UV-Vis transmittance observation. Following these analyses, the types and contents of impurities in Bi2WO6 prepared by the hydrothermal method under different acid-base conditions were determined. Results show that the primary impurity is WO3·0.33H2O (41.09%) for the precursor prepared in 1.5 M nitric acid solution. When the pH of the precursor was in the range of 0.97-7.01, the synthesized Bi2WO6 has relatively high purity, and the impure products were identified as BiONO3. Bi2O3 began to appear when pH reached 9.01 and it reached 18.88% when pH was 12.98. The final product was Bi2O3 exclusively for the precursor conditioned in 0.5 M NaOH solution. In addition, the accuracy of the proposed quantitative method using ICP-MS was validated for several scenarios by weight difference experiments.

Simulation of gaseous pollutant dispersion around an isolated building using the k-ω SST (shear stress transport) turbulence model.

The dispersion of gaseous pollutant around buildings is complex due to complex turbulence features such as flow detachment and zones of high shear. Computational fluid dynamics (CFD) models are one of the most promising tools to describe the pollutant distribution in the near field of buildings. Reynolds-averaged Navier-Stokes (RANS) models are the most commonly used CFD techniques to address turbulence transport of the pollutant. This research work studies the use of [Formula: see text] closure model for the gas dispersion around a building by fully resolving the viscous sublayer for the first time. The performance of standard [Formula: see text] model is also included for comparison, along with results of an extensively validated Gaussian dispersion model, the U.S. Environmental Protection Agency (EPA) AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model). This study's CFD models apply the standard [Formula: see text] and the [Formula: see text] turbulence models to obtain wind flow field. A passive concentration transport equation is then calculated based on the resolved flow field to simulate the distribution of pollutant concentrations. The resultant simulation of both wind flow and concentration fields are validated rigorously by extensive data using multiple validation metrics. The wind flow field can be acceptably modeled by the [Formula: see text] model. However, the [Formula: see text] model fails to simulate the gas dispersion. The [Formula: see text] model outperforms [Formula: see text] in both flow and dispersion simulations, with higher hit rates for dimensionless velocity components and higher "factor of 2" of observations (FAC2) for normalized concentration. All these validation metrics of [Formula: see text] model pass the quality assurance criteria recommended by The Association of German Engineers (Verein Deutscher Ingenieure, VDI) guideline. Furthermore, these metrics are better than or the same as those in the literature. Comparison between the performances of [Formula: see text] and AERMOD shows that the CFD simulation is superior to Gaussian-type model for pollutant dispersion in the near wake of obstacles. AERMOD can perform as a screening tool for near-field gas dispersion due to its expeditious calculation and the ability to handle complicated cases. The utilization of [Formula: see text] to simulate gaseous pollutant dispersion around an isolated building is appropriate and is expected to be suitable for complex urban environment. IMPLICATIONS: Multiple validation metrics of [Formula: see text] turbulence model in CFD quantitatively indicated that this turbulence model was appropriate for the simulation of gas dispersion around buildings. CFD is, therefore, an attractive alternative to wind tunnel for modeling gas dispersion in urban environment due to its excellent performance, and lower cost.

On the kinetics of the absorption of nitric oxide into ammoniacal cobalt(II) solutions.

Experiments were conducted using a custom double-stirred tank reactor to determine the rate constants of reactions between nitric oxide (NO) and both pentaaminecobalt(II) and hexaaminecobalt(II) at temperatures of 298.2 and 303.2 K and pH levels between 8.50 and 9.87 under atmospheric pressure. The NO concentration of simulated flue gas stream ranged from 400 to 1400 ppmv. Ammoniacal cobalt(II) solutions were prepared by adding aqueous ammonia into a cobalt(II) nitrate solution in the presence of concentrated ammonium nitrate. The reaction rate constants were calculated with an enhancement factor for gas absorption associated with parallel chemical reactions. The results showed that the reaction between NO and pentaaminecobalt(II) was first order with respect to both the NO and the pentaamminecobalt(II) ion. Similarly, the reaction between NO and hexaamminecobalt(II) was first order with respect to both the NO and the hexaamminecobalt(II) ion. The forward reaction rate constants of these two reactions were 6.43 × 10(6) and 1.00 × 10(7) L · mol(-1) · s(-1) at 298.2 K, respectively, and increased to 7.57 × 10(6) and 1.12 × 10(7) L · mol(-1) · s(-1) at 303.2 K, respectively. Ammoniacal cobalt(II) solutions also have the potential to simultaneously remove CO2, SO2, and NOx from postcombustion flue gas.

The a3 isoform of the 100-kDa V-ATPase subunit is highly but differentially expressed in large (>or=10 nuclei) and small (

Osteoclasts dissolve bone through acidification of an extracellular compartment by means of a multimeric vacuolar type H+-ATPase (V-ATPase). In mammals, there are four isoforms of the 100-kDa V-ATPase "a" subunit. Mutations in the a3 isoform result in deficient bone resorption and osteopetrosis, suggesting that a3 has a unique function in osteoclasts. It is thus surprising that several studies show a basal level of a3 expression in most tissues. To address this issue, we have compared a3 expression in bone with expression in other tissues. RNA blots revealed that the a3 isoform was expressed highest in bone and confirmed its expression (in decreasing order) in liver, kidney, brain, lung, spleen, and muscle. In situ hybridization on bone tissue sections revealed that the a3 isoform was highly expressed in multinucleated osteoclasts but not in mononuclear stromal cells, whereas the a1 isoform was expressed in both cell types at about the same level. We also found that a3 expression was greater in osteoclasts with 10 or more nuclei as compared with osteoclasts with five or fewer nuclei. We hypothesize that these differences in a3 expression may be associated with previously demonstrated differences between large and small osteoclasts with reference to their resorptive activity.