Traffic emitted semi-volatile organic compounds (SVOCs) and intermediate volatility organic compounds (IVOCs) analysed by GC×GC-ToF-MS

Many uncertainties exist regarding the chemical composition of semi-volatile and intermediate volatility organic compounds (S/IVOCs), as traditional gas chromatographic methods are unable to separate them adequately. Air samples were collected at four sites in central London and were analysed using thermal desorption coupled to comprehensive gas chromatography time-of-flight mass spectrometry (GC×GC-ToF-MS). Main S/IVOC groups identified and quantified include C13-C36 alkanes (linear and branched alkanes), C12-C25 monocyclic alkanes, C13-C27 bicyclic alkanes and C10-C24 monocyclic aromatics in the gas phase and particle phase. Diagnostic ratios of n-alkanes as well as correlation analysis of S/IVOCs and traffic tracers suggest traffic is a major contributor with a minor contribution from other sources. The distribution of hydrocarbons is similar in background and roadside air, indicating the importance of road traffic as a source of hydrocarbons in the urban atmosphere of London. Emission factors estimated in this study are broadly similar to those measured elsewhere in the world, despite differences in traffic fleet composition. Gas-particle partitioning of n-alkanes is discussed and compared between sites. The S/IVOC concentrations identified contribute to a small fraction of the total OH reactivity and SOA formation in background London

Detailed simulation of LOX/GCH4 flame-vortex interaction in supercritical Taylor-Green flows with machine learning

Accurate and affordable simulation of supercritical reacting flow is of practical importance for developing advanced engine systems for liquid rockets, heavy-duty powertrains, and next-generation gas turbines. In this work, we present detailed numerical simulations of LOX/GCH4 flame-vortex interaction under supercritical conditions. The well-established benchmark configuration of three-dimensional Taylor-Green vortex (TGV) embedded with a diffusion flame is modified for real fluid simulations. Both ideal gas and Peng-Robinson (PR) cubic equation of states are studied to reveal the real fluid effects on the TGV evolution and flame-vortex interaction. The results show intensified flame stretching and quenching arising from the intrinsic large density gradients of real gases, as compared to that for the idea gases. Furthermore, to reduce the computational cost associated with real fluid thermophysical property calculations, a machine learning-based strategy utilising deep neural networks (DNNs) is developed and then assessed using the three-dimensional reactive TGV. Generally good prediction accuracy is achieved by the DNN, meanwhile providing a computational speed-up of 13 times over the convectional approach. The profound physics involved in flame-vortex interaction under supercritical conditions demonstrated by this study provides a benchmark for future related studies, and the machine learning modelling approach proposed is promising for practical high-fidelity simulation of supercritical combustion

High-Throughput Screening of Transition Metal Single-Atom Catalysts for Nitrogen Reduction Reaction

The discovery of metals as catalytic centers for nitrogen reduction reactions has stimulated great enthusiasm for single-atom catalysts. However, the poor activity and low selectivity of available SACs are far away from the industrial requirement. Through the high throughout first principles calculations, the doping engineering can effectively regulate the NRR performance of b-Sb monolayer. Especially, the origin of activated N2 is revealed from the perspective of the electronic structure of the active center. Among the 24 transition metal dopants, Re@Sb and Tc@Sb showed the best NRR catalytic performance with a low limiting potential. The Re@Sb and Tc@Sb also could significantly inhibit HER and achieve a high theoretical Faradaic efficiency of 100%. Our findings not only accelerate discovery of catalysts for ammonia synthesis but also contribute to further elucidate the structure-performance correlations

Variable pitch approach for performance improving of straight-bladed VAWT at rated tip speed ratio

This paper presents a new variable pitch (VP) approach to increase the peak power coefficient of the straight-bladed vertical-axis wind turbine (VAWT), by widening the azimuthal angle band of the blade with the highest aerodynamic torque, instead of increasing the highest torque. The new VP-approach provides a curve of pitch angle designed for the blade operating at the rated tip speed ratio (TSR) corresponding to the peak power coefficient of the fixed pitch (FP)-VAWT. The effects of the new approach are exploited by using the double multiple stream tubes (DMST) model and Prandtl’s mathematics to evaluate the blade tip loss. The research describes the effects from six aspects, including the lift, drag, angle of attack (AoA), resultant velocity, torque, and power output, through a comparison between VP-VAWTs and FP-VAWTs working at four TSRs: 4, 4.5, 5, and 5.5. Compared with the FP-blade, the VP-blade has a wider azimuthal zone with the maximum AoA, lift, drag, and torque in the upwind half-cycle, and yields the two new larger maximum values in the downwind half-cycle. The power distribution in the swept area of the turbine changes from an arched shape of the FP-VAWT into the rectangular shape of the VP-VAWT. The new VP-approach markedly widens the highest-performance zone of the blade in a revolution, and ultimately achieves an 18.9% growth of the peak power coefficient of the VAWT at the optimum TSR. Besides achieving this growth, the new pitching method will enhance the performance at TSRs that are higher than current optimal values, and an increase of torque is also generated

Effects of Electroacupuncture on Chronic Unpredictable Mild Stress Rats Depression-Like Behavior and Expression of p-ERK/ERK and p-P38/P38

We investigate the antidepressant-like effect and mechanism of electroacupuncture (EA) on a chronic unpredictable mild stress rats depression-like behavior. In our study, depression in rats was induced by unpredictable chronic mild stress (UCMS) and isolation for four weeks. Male Sprague-Dawley rats were randomly divided into four groups: Normal, Model, EA, and Sham EA. EA treatment was administered for two weeks, once a day for five days a week. Two acupoints, Yintang (EX-HN3) and Baihui (GV20), were selected. For sham EA, acupuncture needles were inserted shallowly into the acupoints: EX-HN3 and GV20. No electrostimulator was connected. The antidepressant-like effect of the electroacupuncture treatment was measured by sucrose intake test, open field test, and forced swimming test in rats. The protein levels of phosphorylated extracellular regulated protein kinases (p-ERK1/2)/ERK1/2 and p-P38/P38 in the hippocampus (HP) were examined by Western blot analysis. Our data demonstrate that EA treatment decreased the immobility time of forced swimming test and improved the sucrose solution intake in comparison to unpredictable chronic mild stress and placebo sham control. Electroacupuncture may act on depression by enhancing p-ERK1/2 and p-p38 in the hippocampus

Efficacy of metformin targets on cardiometabolic health in the general population and non-diabetic individuals: a Mendelian randomization study

BACKGROUND: Metformin shows beneficial effects on cardiometabolic health in diabetic individuals. However, the beneficial effects in the general population, especially in non-diabetic individuals are unclear. We aim to estimate the effects of perturbation of seven metformin targets on cardiometabolic health using Mendelian randomization (MR). METHODS: Genetic variants close to metformin-targeted genes associated with expression of the corresponding genes and glycated haemoglobin (HbA1c) level were used to proxy therapeutic effects of seven metformin-related drug targets. Eight cardiometabolic phenotypes under metformin trials were selected as outcomes (average N = 466,947). MR estimates representing the weighted average effects of the seven effects of metformin targets on the eight outcomes were generated. One-sample MR was applied to estimate the averaged and target-specific effects in 338,425 non-diabetic individuals in UK Biobank. FINDINGS: Genetically proxied averaged effects of five metformin targets, equivalent to a 0.62% reduction of HbA1c level, was associated with 37.8% lower risk of coronary artery disease (CAD) (odds ratio [OR] = 0.62, 95% confidence interval [CI] = 0.46-0.84), lower levels of body mass index (BMI) (β = -0.22, 95% CI = -0.35 to -0.09), systolic blood pressure (SBP) (β = -0.19, 95% CI = -0.28 to -0.09) and diastolic blood pressure (DBP) levels (β = -0.29, 95% CI = -0.39 to -0.19). One-sample MR suggested that the seven metformin targets showed averaged and target-specific beneficial effects on BMI, SBP and DBP in non-diabetic individuals. INTERPRETATION: This study showed that perturbation of seven metformin targets has beneficial effects on BMI and blood pressure in non-diabetic individuals. Clinical trials are needed to investigate whether similar effects can be achieved with metformin medications. FUNDING: Funding information is provided in the Acknowledgements