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Applications of machine learning in chemistry are many and varied, from prediction of structure-property relationships, to modeling of potential energy surfaces for large scale atomistic simulations. We describe a generalized approach for the application of machine learning to the classification of spectra which can be used as the basis for a wide variety of undergraduate projects. While our examples use FTIR and mass spectra, the approach could equally well be used with UV-visible, Raman, NMR, or indeed any other type of spectra. We summarize a number of different unsupervised and supervised machine learning algorithms that can be used to classify spectra into groups, and illustrate their application using data from three different projects carried out by fourth year chemistry undergraduates. The three projects investigated the ability of the various machine learning approaches to correctly classify spectra of a variety of fruits, whiskies, and teas, respectively. In all cases the algorithms were able to differentiate between the various samples used in each study, and the trained machine learning models could then be used to classify unknown samples with a high degree of accuracy (>98% in many cases). Depending on the extent to which students are expected to write their own code to perform the data analysis, the general model adopted in this work can be adapted for a variety of purposes, from short (one to two day) practical exercises and workshops, to much longer independent student projects.

Teaching practical chemistry skills remotely is not a task that would have been high on the agenda only a few months ago. However, in light of the COVID-19 pandemic, students around the world are having to work from home, and the chemistry education community has been forced to adapt to the new circumstances. In response, we discuss the use of simulations in place of practical laboratory work, with emphasis on the development of students' experimental design skills. The simulation of Michaelis-Menten enzyme kinetics is given as an example exercise, which other instructors could implement with immediate effect.

The COVID-19 pandemic has resulted in a need for social distancing measures in public spaces and will have an important impact on university level teaching going forward. Remote methods to complete laboratory related activities are a potential means of students achieving practical credit while still isolating or social distancing. We outline the implementation of two novel remote exercises, based on coding in Mathematica, and the methods used to provide ongoing help to students. These exercises are used as a case study to identify potential problems with remote exercises based on student feedback. Suggestions for how these problems might be overcome in further iterations of these remote exercises are explored.

Earth's field nuclear magnetic resonance (EFNMR) spectroscopy offers students a unique opportunity to consolidate their understanding of NMR spectroscopic theory through hands-on practice with a simple spectrometer. A comprehensive, 6 h experiment is presented for the introduction of low-field NMR techniques, covering spectroscopy, relaxivity, and imaging experiments in the Earth's magnetic field. This multifaceted practical session explores the concepts of free induction decay, pulse sequences, field homogeneity, relaxation times, J-coupling, and magnetic resonance imaging (MRI), which are reinforced through a series of experiments carried out within an undergraduate teaching laboratory. Students are required to alter parameters as they see fit in order to obtain data, ensuring their understanding of the theory behind NMR spectroscopy. The challenges overcome for the implementation of EFNMR spectroscopy in a modern undergraduate laboratory are also discussed, and detailed instructions are included for spectrometer setup.

Time-resolved luminescence lifetime measurements are an important photophysical technique. However, access to this technique at the undergraduate level is limited by the expense of the instrumentation needed to create the well-defined light pulses required to measure the luminescence decay of an excited state molecule. We present here an inexpensive, improved light emitting diode (LED) circuit that is capable of supplying bright light pulses. Our circuit is designed to overdrive the LED resulting in a bright excitation light source with a well-defined square wave pulse shape. This allows for the facile measurement of luminescent molecules with decay lifetimes in the hundreds of nanoseconds to microsecond range. Data are presented for five UV, violet, and blue LEDs as driven by the improved circuit that can be used as a guide for selecting the best excitation light source for a particular molecule of interest. Our students have studied the quenching of aqueous tris(bipyridine)ruthenium(II) chloride with ferric ion using an overdriven blue LED as an excitation source. While ferric ion is not an efficient quencher compared to molecular oxygen, it is much easier to handle, allowing for the preparation of accurate standard solutions free of dissolved oxygen.

Many instrumental analysis students develop limited skills as the course rushes through different instruments to ensure familiarity with as many methodologies as possible. This broad coverage comes at the expense of superficiality of learning and a lack of student confidence and engagement. To mitigate these issues, a peer-led team learning model was developed to give each student in-depth experiences operating and troubleshooting six common instruments. Electronic cigarette solutions were chosen for all work because of their current relevance. Small groups became "class experts" on their assigned instrument. Students were responsible for teaching their peers how to utilize their instrument for experimentation. Each student rotated through their peer's instruments, learned to apply the knowledge they gained from one instrument to others, while they answered questions from peers. The students developed troubleshooting and communication skills--foundational tools for chemists. This model proved successful in promoting cognitive flexibility and critical thinking about experimental design, as reflected by oral quizzes and peer teaching. This adaptation of peer-led team learning helped engage students, promote confidence, and a facilitate a deeper understanding of instrumentation.

Abstract Neuromorphic computing has emphasized the need for memristors with non-volatile, multiple conductance levels. This paper demonstrates the potential of hexagonal boron nitride (hBN)/graphene heterostructures to act as memristors with multiple resistance states that can be optically tuned using visible light. The number of resistance levels in graphene can be controlled by modulating doping levels, achieved by varying the electric field strength or adjusting the duration of optical illumination. Our measurements show that this photodoping of graphene results from the optical excitation of charge carriers from the nitrogen-vacancy levels of hBN to its conduction band, with these carriers then being transferred to graphene by the gate-induced electric field. We develop a qualitative model to describe our observations. Additionally, utilizing our device architecture, we propose a memristive crossbar array for vector-matrix multiplications.

Many small-molecule antioxidants found in whole fruits and vegetables are analyzed and identified in this laboratory module for upper-division biochemistry courses. During this experiment, students develop their knowledge of the bioactivity of fruit and vegetable products while learning techniques to identify vitamins and nutritionally derived secondary metabolites. Students first develop skills by analyzing wellstudied fruit and vegetable juice products prior to development of a multicomponent fruit and vegetable superjuice displaying maximal antioxidant capacity. Antioxidant capacity is measured using ascorbic acid standardized ferric reducing antioxidant power (FRAP) assay, and both aqueous and lipophilic small molecules are identified using reversephase, high-performance liquid chromatography. Final analyses include correlation of whole fruit and vegetable products with antioxidant capacity and vitamin content using basic statistical analysis, and identification and characterization of antioxidant compounds derived from whole produce. This laboratory experiment is designed to be performed by groups of three or four students in three, 4 h laboratory periods; however, the modular nature of the experiment allows for completion of the components separately. This laboratory is easily adapted for use with thin layer chromatography to allow maximum resource flexibility.

​​​​​​​The 21 June 2019 Raikoke eruption (48° N, 153° E) generated one of the largest amounts of sulfur emission to the stratosphere since the 1991 Mt. Pinatubo eruption. Satellite measurements indicate a consensus best estimate of 1.5 Tg for the sulfur dioxide (SO2) injected at an altitude of around 14–15 km. The peak Northern Hemisphere (NH) mean 525 nm stratospheric aerosol optical depth (SAOD) increased to 0.025, a factor of 3 higher than background levels. The Volcano Response (VolRes) initiative provided a platform for the community to share information about this eruption which significantly enhanced coordination efforts in the days after the eruption. A multi-platform satellite observation subgroup formed to prepare an initial report to present eruption parameters including SO2 emissions and their vertical distribution for the modeling community. It allowed us to make the first estimate of what would be the peak in SAOD 1 week after the eruption using a simple volcanic aerosol model. In this retrospective analysis, we show that revised volcanic SO2 injection profiles yield a higher peak injection of the SO2 mass. This highlights difficulties in accurately representing the vertical distribution for moderate SO2 explosive eruptions in the lowermost stratosphere due to limited vertical sensitivity of the current satellite sensors (±2 km accuracy) and low horizontal resolution of lidar observations. We also show that the SO2 lifetime initially assumed in the simple aerosol model was overestimated by 66 %, pointing to challenges for simple models to capture how the life cycle of volcanic gases and aerosols depends on the SO2 injection magnitude, latitude, and height. Using a revised injection profile, modeling results indicate a peak NH monthly mean SAOD at 525 nm of 0.024, in excellent agreement with observations, associated with a global monthly mean radiative forcing of −0.17 W m−2 resulting in an annual global mean surface temperature anomaly of −0.028 K. Given the relatively small magnitude of the forcing, it is unlikely that the surface response can be dissociated from surface temperature variability.

A growing number of general circulation models are adapting interactive sulfur and aerosol schemes to improve the representation of relevant physical and chemical processes and associated feedbacks. They are motivated by investigations of climate response to major volcanic eruptions and potential solar geoengineering scenarios. However, uncertainties in these schemes are not well constrained. Stratospheric sulfate is modulated by emissions of sulfur-containing species of anthropogenic and natural origin, including volcanic activity. While the effects of volcanic eruptions have been studied in the framework of global model intercomparisons, the background conditions of the sulfur cycle have not been addressed in such a way. Here, we fill this gap by analyzing the distribution of the main sulfur species in nine global atmospheric aerosol models for a volcanically quiescent period. We use observational data to evaluate model results. Overall, models agree that the three dominant sulfur species in terms of burdens (sulfate aerosol, OCS, and SO2) make up about 98 % stratospheric sulfur and 95 % tropospheric sulfur. However, models vary considerably in the partitioning between these species. Models agree that anthropogenic emission of SO2 strongly affects the sulfate aerosol burden in the northern hemispheric troposphere, while its importance is very uncertain in other regions, where emissions are much lower. Sulfate aerosol is the main deposited species in all models, but the values deviate by a factor of 2. Additionally, the partitioning between wet and dry deposition fluxes is highly model dependent. Inter-model variability in the sulfur species is low in the tropics and increases towards the poles. Differences are largest in the dynamically active northern hemispheric extratropical region and could be attributed to the representation of the stratospheric circulation. The differences in the atmospheric sulfur budget among the models arise from the representation of both chemical and dynamical processes, whose interplay complicates the bias attribution. Several problematic points identified for individual models are related to the specifics of the chemistry schemes, model resolution, and representation of cross-tropopause transport in the extratropics. Further model intercomparison research is needed with a focus on the clarification of the reasons for biases, given the importance of this topic for the stratospheric aerosol injection studies.

Abstract Dynamic microscale droplets produced by liquid–liquid phase separation (LLPS) have emerged as appealing biomaterials due to their remarkable features. However, the instability of droplets limits the construction of population-level structures with collective behaviors. Here we first provide a brief background of droplets in the context of materials properties. Subsequently, we discuss current strategies for stabilizing droplets including physical separation and chemical modulation. We also discuss the recent development of LLPS droplets for various applications such as synthetic cells and biomedical materials. Finally, we give insights on how stabilized droplets can self-assemble into higher-order structures displaying coordinated functions to fully exploit their potentials in bottom-up synthetic biology and biomedical applications.

The crystal formation of nitric acid trihydrate (NAT) in the absence of water ice is important for a subset of polar stratospheric clouds (PSCs) and thereby ozone depletion. It has been suggested that either fragmented meteoroids or meteoric smoke particles (MSPs), or possibly both, are important as heterogeneous nuclei of these crystals. Previous work has focused on the nucleating ability of meteoric material in nitric acid in the absence of sulfuric acid. However, it is known that when immersed in stratospheric sulfuric acid droplets, metal-containing meteoric material particles partially dissolve and components can reprecipitate as silica and alumina that have different morphologies to the original meteoric material. Hence, in this study, we experimentally and theoretically explore the relative role that sulfuric acid-processed MSPs and meteoric fragments may play in NAT nucleation in PSCs. We compared meteoric fragments that had recently been prepared (by milling a meteorite sample) to a sample annealed under conditions designed to simulate heating during entry into the Earth's atmosphere. Whilst the addition of sulfuric acid decreased the nucleating ability of the recently milled meteoric material relative to nucleation in binary nitric acid-water solutions (at similar NAT saturation ratio), the annealed meteoric fragments nucleated NAT with a similar effectiveness in both solutions. However, combining our results with measured fluxes of meteoric material to the Earth, sedimentation modelling and recent experiments on fragmentation of incoming meteoroids suggests that it is unlikely for there to be sufficient fragments to contribute to the nucleation of crystalline NAT particles. We then considered silica formed from sulfuric acid-processed MSPs. Our previous work showed that nanoparticulate silica (radius ∼6 nm) is a relatively poor promoter of nucleation compared with micron-scaled silica particles, which were more effective. Both materials have similar chemical and structural (crystallographically amorphous) properties, indicating that size is critical. Here, we account for surface curvature of primary grains using the Classical Nucleation Theory (CNT) to explore this size dependence. This model is able to explain the discrepancy in nucleation effectiveness of fumed silica and fused quartz by treating their nucleating activity (contact angle) as equal but with differing particle size (or surface curvature), assuming interfacial energies that are physically reasonable. Here, we use this CNT model to present evidence that nucleation of NAT on acid-processed MSPs, where the primary grain size is tens of nanometres, is also effective enough to contribute to NAT crystals in early season PSCs where there is an absence of ice. This study demonstrates that the modelling of crystal nucleation in PSCs and resulting ozone depletion relies on an accurate understanding of the transport and chemical processing of MSPs. This will affect estimated sensitivity of stratospheric chemistry to rare events such as large volcanic eruptions and long-term forecasting of ozone recovery in a changing climate.

A previous model intercomparison of the Tambora aerosol cloud has highlighted substantial differences among simulated volcanic aerosol properties in the pre-industrial stratosphere and has led to questions about the applicability of global aerosol models for large-magnitude explosive eruptions prior to the observational period. Here, we compare the evolution of the stratospheric aerosol cloud following the well-observed June 1991 Mt. Pinatubo eruption simulated with six interactive stratospheric aerosol microphysics models to a range of observational data sets. Our primary focus is on the uncertainties regarding initial SO2 emission following the Pinatubo eruption, as prescribed in the Historical Eruptions SO2 Emission Assessment experiments (HErSEA), in the framework of the Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP). Six global models with interactive aerosol microphysics took part in this study: ECHAM6-SALSA, EMAC, ECHAM5-HAM, SOCOL-AERv2, ULAQ-CCM, and UM-UKCA. Model simulations are performed by varying the SO2 injection amount (ranging between 5 and 10 Tg S) and the altitude of injection (between 18–25 km). The comparisons show that all models consistently demonstrate faster reduction from the peak in sulfate mass burden in the tropical stratosphere. Most models also show a stronger transport towards the extratropics in the Northern Hemisphere, at the expense of the observed tropical confinement, suggesting a much weaker subtropical barrier in all the models, which results in a shorter e-folding time compared to the observations. Furthermore, simulations in which more than 5 Tg S in the form of SO2 is injected show an initial overestimation of the sulfate burden in the tropics and, in some models, in the Northern Hemisphere and a large surface area density a few months after the eruption compared to the values measured in the tropics and the in situ measurements over Laramie. This draws attention to the importance of including processes such as the ash injection for the removal of the initial SO2 and aerosol lofting through local heating.

Teaching practical laboratory skills is a key component of preparing undergraduate students for future careers in chemistry and elsewhere. In this paper, we present our new strategy to teach practical skills to undergraduate chemistry students. We report a Skills Inventory, a list of the suggested practical skills a graduate chemist should possess; this list was compiled by chemists across the UK. In our new practical course we begin by decoupling the practical skill from the theoretical background, compelling students to first master the basic processes needed to carry out a specific technique. In what we have termed a ‘spiral curriculum’ approach, skills are revisited on multiple occasions, with increasing complexity and greater emphasis on underlying theory. The new course makes links across traditional subdisciplines of chemistry to avoid compartmentalisation of ideas.

Observations of polar mesospheric clouds have revealed the presence of solid ice particles in the upper mesosphere at high latitudes; however, their formation mechanism remains uncertain. In this study, we investigated the formation process of ice particles through nucleation from small amounts of water vapor at low temperatures. Previous studies that used classical nucleation theory have shown that amorphous solid water particles can nucleate homogeneously at conditions that are present in the mesosphere. However, the rate predictions for water in classical nucleation theory disagree with experimental measurements by several orders of magnitude. We adopted a semi-phenomenological model for the nucleation process, which corrects the evaluation of the molecular cluster formation energy using the second virial coefficient, which agrees with both experiments and molecular dynamics simulations. To calculate the nucleation process, we applied atmospheric conditions for the temperature, pressure, numerical density of dust grains, and cooling rate. The results indicate that homogeneous water nucleation is extremely unlikely to occur in the mesosphere, while heterogeneous nucleation occurs effectively. Dust grains generated by meteor ablation can serve as nuclei for heterogeneous nucleation. We also showed that the ice can form directly in a crystalline state, rather than an amorphous state.

Solitary trees are natural land surface elements found in almost all climates, yet their influence on the surrounding airflow is poorly known. Here we use state-of-the-art, laser-based, remote sensing instruments to study the turbulent wind field in the near-wake region of a mature, open-grown oak tree. Our measurements provide for the first time a full picture of the mixing layer of high turbulence that surrounds the mean wind speed deficit. In this layer, we investigate the validity of a two-dimensional vectorial relation derived from the eddy-viscosity hypothesis, a hypothesis commonly used in modelling the turbulence transport of momentum and scalars in the atmosphere. We find that the momentum fluxes of the streamwise wind component can be adequately predicted by the transverse gradient of the mean flow. Using the mixing-length hypothesis we find that for this tree the corresponding turbulence length scale in the mixing layer can be approximated by one height-independent value. Further, the laser-based scanning technology used here was able to accurately reveal three-dimensional turbulent and spatially varying atmospheric flows over a large plane without seeding or intruding the atmospheric flow. This capability points to a new and more exact way of exploring the complex earth–atmosphere interactions.

Until now our understanding of the 11-year solar cycle signal (SCS) in stratospheric ozone has been largely based on high-quality but sparse ozone profiles from the Stratospheric Aerosol and Gas Experiment (SAGE) II or coarsely resolved ozone profiles from the nadir-viewing Solar Backscatter Ultraviolet Radiometer (SBUV) satellite instruments. Here, we analyse 16 years (2005–2020) of ozone profile measurements from the Microwave Limb Sounder (MLS) instrument on the Aura satellite to estimate the 11-year SCS in stratospheric ozone. Our analysis of Aura-MLS data suggests a single-peak-structured SCS profile (about 3 % near 4 hPa or 40 km) in tropical stratospheric ozone, which is significantly different to the SAGE II and SBUV-based double-peak-structured SCS. We also find that MLS-observed ozone variations are more consistent with ozone from our control model simulation that uses Naval Research Laboratory (NRL) v2 solar fluxes. However, in the lowermost stratosphere modelled ozone shows a negligible SCS compared to about 1 % in Aura-MLS data. An ensemble of ordinary least squares (OLS) and three regularised (lasso, ridge and elastic net) linear regression models confirms the robustness of the estimated SCS. In addition, our analysis of MLS and model simulations shows a large SCS in the Antarctic lower stratosphere that was not seen in earlier studies. We also analyse chemical transport model simulations with alternative solar flux data. We find that in the upper (and middle) stratosphere the model simulation with Solar Radiation and Climate Experiment (SORCE) satellite solar fluxes is also consistent with the MLS-derived SCS and agrees well with the control simulation and one which uses Spectral and Total Irradiance Reconstructions (SATIRE) solar fluxes. Hence, our model simulation suggests that with recent adjustments and corrections, SORCE data can be used to analyse effects of solar flux variations. Furthermore, analysis of a simulation with fixed solar fluxes and one with fixed (annually repeating) meteorology confirms that the implicit dynamical SCS in the (re)analysis data used to force the model is not enough to simulate the observed SCS in the middle and upper stratospheric ozone. Finally, we argue that the overall significantly different SCS compared to previous estimates might be due to a combination of different factors such as much denser MLS measurements, almost linear stratospheric chlorine loading changes over the analysis period, variations in the stratospheric dynamics as well as relatively unperturbed stratospheric aerosol layer that might have influenced earlier analyses.

Synthetic models of cells are becoming increasingly sophisticated, but engineering communication between these and living cells remains challenging. Here the authors review modes of communication and signal processing between living cells and synthetic analogs, such as giant unilamellar vesicles, proteinosomes, and coacervates.

Agglomeration of charged ice and dust particles in the mesosphere and lower thermosphere is studied using a classical electrostatic approach, which is extended to capture the induced polarisation of surface charge. Collision outcomes are predicted whilst varying the particle size, charge, dielectric constant, relative kinetic energy, collision geometry and the coefficient of restitution. In addition to Coulomb forces acting on particles of opposite charge, instances of attraction between particles of the same sign of charge are discussed. These attractive forces are governed by the polarisation of surface charge and can be strong at very small separation distances. In the mesosphere and lower thermosphere, these interactions could also contribute to the formation of stable aggregates and contamination of ice particles through collisions with meteoric smoke particles.

Abstract Inverse vulcanization is a process in which highly abundant and low-cost elemental sulfur is copolymerized with an unsaturated organic molecule such as a polyene. This process has provided a variety of useful materials with high sulfur content—typically 50% or greater in sulfur by mass. These materials have garnered increasing interest in research as sorbents for mercury, due to the high affinity of sulfur for mercury. In this review, the features of mercury sorbents made by inverse vulcanization are presented. Additionally, case studies are provided to illustrate the variety of polymer architectures accessible with this chemistry, the versatility of these materials in mercury remediation, and prospects for industrial use. 1 Introduction 2 Sulfur Polymers by Inverse Vulcanization 3 Sulfur Polymers as Mercury Sorbents 4 Increasing Surface Area to Improve Mercury Uptake 5 Crosslinker Considerations 6 Sorption of Different Forms of Mercury 7 Life-Cycle Management 8 Conclusions and Outlook

As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), several climate modeling centers performed a coordinated pre-study experiment with interactive stratospheric aerosol models simulating the volcanic aerosol cloud from an eruption resembling the 1815 Mt. Tambora eruption (VolMIP-Tambora ISA ensemble). The pre-study provided the ancillary ability to assess intermodel diversity in the radiative forcing for a large stratospheric-injecting equatorial eruption when the volcanic aerosol cloud is simulated interactively. An initial analysis of the VolMIP-Tambora ISA ensemble showed large disparities between models in the stratospheric global mean aerosol optical depth (AOD). In this study, we now show that stratospheric global mean AOD differences among the participating models are primarily due to differences in aerosol size, which we track here by effective radius. We identify specific physical and chemical processes that are missing in some models and/or parameterized differently between models, which are together causing the differences in effective radius. In particular, our analysis indicates that interactively tracking hydroxyl radical (OH) chemistry following a large volcanic injection of sulfur dioxide (SO2) is an important factor in allowing for the timescale for sulfate formation to be properly simulated. In addition, depending on the timescale of sulfate formation, there can be a large difference in effective radius and subsequently AOD that results from whether the SO2 is injected in a single model grid cell near the location of the volcanic eruption, or whether it is injected as a longitudinally averaged band around the Earth.

We present a detailed investigation of the formation of an additional sodium density peak at altitudes of 79–85 km below the main peak of the sodium layer based on sodium lidar and airglow imager measurements made at Ramfjordmoen near Tromsø, Norway, on the night of 19 December 2014. The airglow imager observations of OH emissions revealed four passing frontal systems that resembled mesospheric bores, which typically occur in ducting regions of the upper mesosphere. For about 1.5 h, the lower-altitude sodium peak had densities similar to that of the main peak of the layer around 90 km. The lower-altitude sodium peak weakened and disappeared soon after the fourth front had passed. The fourth front had weakened in intensity by the time it approached the region of lidar beams and disappeared soon afterwards. The column-integrated sodium densities increased gradually during the formation of the lower-altitude sodium peak. Temperatures measured with the lidar indicate that there was a strong thermal duct structure between 87 and 93 km. Furthermore, the temperature was enhanced below 85 km. Horizontal wind magnitudes estimated from the lidar showed strong wind shears above 93 km. We conclude that the combination of an enhanced stability region due to the temperature profile and intense wind shears have provided ideal conditions for evolution of multiple mesospheric bores revealed as frontal systems in the OH images. The downward motion associated with the fronts appeared to have brought air rich in H and O from higher altitudes into the region below 85 km, wherein the temperature was also higher. Both factors would have liberated sodium atoms from the reservoir species and suppressed the reconversion of atomic sodium into reservoir species so that the lower-altitude sodium peak could form and the column abundance could increase. The presented observations also reveal the importance of mesospheric frontal systems in bringing about significant variation of minor species over shorter temporal intervals.

Accurately quantifying volcanic impacts on climate is a key requirement for robust attribution of anthropogenic climate change. Here we use the Unified Model – United Kingdom Chemistry and Aerosol (UM-UKCA) composition–climate model to simulate the global dispersion of the volcanic aerosol clouds from the three largest eruptions of the 20th century: 1963 Mt Agung, 1982 El Chichón, and 1991 Mt Pinatubo. The model has interactive stratospheric chemistry and aerosol microphysics, with coupled aerosol–radiation interactions for realistic composition–dynamics feedbacks. Our simulations align with the design of the Interactive Stratospheric Aerosol Model Intercomparison (ISA-MIP) “Historical Eruption SO2 Emissions Assessment”. For each eruption, we perform three-member ensemble model experiments for upper, mid-point, and lower estimates of SO2 emission, each re-initialised from a control run to approximately match the observed transition in the phase of the quasi-biennial oscillation (QBO) in the 6 months after the eruptions. With this experimental design, we assess how each eruption's emitted SO2 translates into a tropical reservoir of volcanic aerosol and analyse the subsequent dispersion to mid-latitudes. We compare the simulations to the volcanic forcing datasets (e.g. Space-based Stratospheric Aerosol Climatology (GloSSAC); Sato et al., 1993, and Ammann et al., 2003) that are used in historical integrations for the two most recent Coupled Model Intercomparison Project (CMIP) assessments. For Pinatubo and El Chichón, we assess the vertical extent of the simulated volcanic clouds by comparing modelled extinction to the Stratospheric Aerosol and Gas Experiment (SAGE-II) v7.0 satellite measurements and to 1964–1965 Northern Hemisphere ground-based lidar measurements for Agung. As an independent test for the simulated volcanic forcing after Pinatubo, we also compare simulated shortwave (SW) and longwave (LW) top-of-the-atmosphere radiative forcings to the flux anomalies measured by the Earth Radiation Budget Experiment (ERBE) satellite instrument. For the Pinatubo simulations, an injection of 10 to 14 Tg SO2 gives the best match to the High Resolution Infrared Sounder (HIRS) satellite-derived global stratospheric sulfur burden, with good agreement also with SAGE-II mid-visible and near-infra-red extinction measurements. This 10–14 Tg range of emission also generates a heating of the tropical stratosphere that is consistent with the temperature anomaly present in the ERA-Interim reanalysis. For El Chichón, the simulations with 5 and 7 Tg SO2 emission give best agreement with the observations. However, these simulations predict a much deeper volcanic cloud than represented in the GloSSAC dataset, which is largely based on an interpolation between Stratospheric Aerosol Measurements (SAM-II) satellite and aircraft measurements. In contrast, these simulations show much better agreement during the SAGE-II period after October 1984. For 1963 Agung, the 9 Tg simulation compares best to the forcing datasets with the model capturing the lidar-observed signature of the altitude of peak extinction descending from 20 km in 1964 to 16 km in 1965. Overall, our results indicate that the downward adjustment to SO2 emission found to be required by several interactive modelling studies when simulating Pinatubo is also needed when simulating the Agung and El Chichón aerosol clouds. This strengthens the hypothesis that interactive stratospheric aerosol models may be missing an important removal or re-distribution process (e.g. effects of co-emitted ash) which changes how the tropical reservoir of volcanic aerosol evolves in the initial months after an eruption. Our model comparisons also identify potentially important inhomogeneities in the CMIP6 dataset for all three eruption periods that are hard to reconcile with variations predicted in the interactive stratospheric aerosol simulations. We also highlight large differences between the CMIP5 and CMIP6 volcanic aerosol datasets for the Agung and El Chichón periods. Future research should aim to reduce this uncertainty by reconciling the datasets with additional stratospheric aerosol observations.

Enzymes have the potential to catalyse complex chemical reactions with unprecedented selectivity, under mild conditions in aqueous media. Accordingly, there is serious interest from the pharmaceutical industry to utilize enzymes as biocatalysts to produce medicines in an environmentally sustainable and economic manner. Prominent advances in the field of biotechnology have transformed this potential into a reality. Using modern protein engineering techniques, in a matter of months it is possible to evolve an enzyme, which fits the demands of a chemical process, or even to catalyse entirely novel chemistry. Consequently, biocatalysis is routinely applied throughout the pharmaceutical industry for a variety of applications, ranging from the manufacture of large volumes of high value blockbuster drugs to expanding the chemical space available for drug discovery.

Direct non-oxidative methane conversion (DNMC) converts methane (CH4) in one step to olefin and aromatic hydrocarbons and hydrogen (H2) co-product. Membrane reactors comprising methane activation catalysts and H2-permeable membranes can enhance methane conversion by in situ H2 removal via Le Chatelier's principle. Rigorous description of H2 kinetic effects on both membrane and catalyst materials in the membrane reactor, however, has been rarely studied. In this work, we report the impact of hydrogen activation by hydrogen-permeable SrCe0.8Zr0.2O3−δ (SCZO) perovskite oxide material on DNMC over an iron/silica catalyst. The SCZO oxide has mixed ionic and electronic conductivity and is capable of H2 activation into protons and electrons for H2 permeation. In the fixed-bed reactor packed with a mixture of SCZO oxide and iron/silica catalyst, stable and high methane conversion and low coke selectivity in DNMC was achieved by co-feeding of H2 in methane stream. The characterizations show that SCZO activates H2 to favor “soft coke” formation on the catalyst. The SCZO could absorb H2in situ to lower its local concentration to mitigate the reverse reaction of DNMC in the tested conditions. The co-existence of H2 co-feed, SCZO oxide, and DNMC catalyst in the present study mimics the conditions of DNMC in the H2-permeable SCZO membrane reactor. The findings in this work offer the mechanistic understanding of and guidance for the design of H2-permeable membrane reactors for DNMC and other alkane dehydrogenation reactions.

The synthesis of methanol and dimethyl ether (DME) from carbon dioxide (CO2) and green hydrogen (H2) offers a sustainable pathway to convert CO2 emissions into value-added products. This heterogeneous catalytic reaction often uses copper (Cu) catalysts due to their low cost compared with their noble metal analogs. Nevertheless, improving the activity and selectivity of these Cu catalysts for these products is highly desirable. In the present study, a new architecture of Cu- and Cu/Zn-based catalysts supported on electrospun alumina nanofibers were synthesized. The catalysts were tested under various reaction conditions using high-throughput equipment to highlight the role of the hierarchical fibrous structure on the reaction activity and selectivity. The Cu or Cu/ZnO formed a unique structure of nanosheets, covering the alumina fiber surface. This exceptional morphology provides a large surface area, up to ~300 m2/g, accessible for reaction. Maximal production of methanol (~1106 gmethanolKgCu−1∙h−1) and DME (760 gDMEKgCu−1∙h−1) were obtained for catalysts containing 7% wt. Cu/Zn with a weight ratio of 2.3 Zn to Cu (at 300 °C, 50 bar). The promising results in CO2 hydrogenation to methanol and DME obtained here point out the significant advantage of nanofiber-based catalysts in heterogeneous catalysis.

Xanthones are secondary metabolites isolated from the peel of mangosteen showing medicinal potencies. Alpha-mangostin (α-MG) is the most plentiful xanthone, which has been reported to possess anti-inflammatory, anti-oxidant, and anti-bacterial activities. We aimed to investigate the anti-inflammatory effects of xanthones on LPS-treated hDPCs. Cell viability was determined using the WST-1 assay. The mRNA and protein expression profiles of inflammatory mediators were evaluated using quantitative real-time polymerase chain reaction (qPCR) and Western blot analysis. Anti-inflammatory effects were assessed using the Western blot analysis to examine underlying mechanisms. A one-way analysis of variance followed by Tukey’s post hoc test was used to determine statistically significant differences (p < 0.05). The study found no significant differences between the cytotoxic effects in the α-MG-treated groups and controls. The mRNA and protein expression levels of inflammatory markers in the α-MG treated groups decreased. α-MG significantly inhibited LPS-induced phosphorylation of proteins associated with the MAPK and NF-κB pathways. This study suggests that α-MG exerts anti-inflammatory effects by suppressing the MAPK and NF-κB signaling pathways in LPS-treated hDPCs.

The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) programme is an international collaborative project focusing on understanding the sources, processes and health effects of air pollution in the Beijing megacity. APHH-Beijing brings together leading China and UK research groups, state-of-the-art infrastructure and air quality models to work on four research themes: (1) sources and emissions of air pollutants; (2) atmospheric processes affecting urban air pollution; (3) air pollution exposure and health impacts; and (4) interventions and solutions. Themes 1 and 2 are closely integrated and support Theme 3, while Themes 1–3 provide scientific data for Theme 4 to develop cost-effective air pollution mitigation solutions. This paper provides an introduction to (i) the rationale of the APHH-Beijing programme and (ii) the measurement and modelling activities performed as part of it. In addition, this paper introduces the meteorology and air quality conditions during two joint intensive field campaigns – a core integration activity in APHH-Beijing. The coordinated campaigns provided observations of the atmospheric chemistry and physics at two sites: (i) the Institute of Atmospheric Physics in central Beijing and (ii) Pinggu in rural Beijing during 10 November–10 December 2016 (winter) and 21 May–22 June 2017 (summer). The campaigns were complemented by numerical modelling and automatic air quality and low-cost sensor observations in the Beijing megacity. In summary, the paper provides background information on the APHH-Beijing programme and sets the scene for more focused papers addressing specific aspects, processes and effects of air pollution in Beijing.

Because flow recirculation can generate significant amounts of turbulence, it can impact the success of wind energy projects. This study uses unique Doppler lidar observations to quantify occurrences of flow recirculation on lee sides of ridges. An extensive dataset of observations of flow over complex terrain is available from the Perdigão 2017 field campaign over a period of 3 months. The campaign site was selected because of the unique terrain feature of two nearly parallel ridges with a valley-to-ridge-top height difference of about 200 m and a ridge-to-ridge distance of 1.4 km. Six scanning Doppler lidars probed the flow field in several vertical planes orthogonal to the ridges using range–height indicator scans. With this lidar setup, we achieved vertical scans of the recirculation zone at three positions along two parallel ridges. We construct a method to identify flow recirculation zones in the scans, as well as define characteristics of these zones. According to our data analysis, flow recirculation, with reverse flow wind speeds greater than 0.5 m s−1, occurs over 50 % of the time when the wind direction is perpendicular to the direction of the ridges. Atmospheric conditions, such as atmospheric stability and wind speed, affect the occurrence of flow recirculation. Flow recirculation occurs more frequently during periods with wind speeds above 8 m s−1. Recirculation within the valley affects the mean wind and turbulence fields at turbine heights on the downwind ridge in magnitudes significant for wind resource assessment.

The global secondary organic aerosol (SOA) budget is highly uncertain, with global annual SOA production rates, estimated from global models, ranging over an order of magnitude and simulated SOA concentrations underestimated compared to observations. In this study, we use a global composition-climate model (UKCA) with interactive chemistry and aerosol microphysics to provide an in-depth analysis of the impact of each VOC source on the global SOA budget and its seasonality. We further quantify the role of each source on SOA spatial distributions, and evaluate simulated seasonal SOA concentrations against a comprehensive set of observations. The annual global SOA production rates from monoterpene, isoprene, biomass burning, and anthropogenic precursor sources is 19.9, 19.6, 9.5, and 24.6 Tg (SOA) a−1, respectively. When all sources are included, the SOA production rate from all sources is 73.6 Tg (SOA) a−1, which lies within the range of estimates from previous modelling studies. SOA production rates and SOA burdens from biogenic and biomass burning SOA sources peak during Northern Hemisphere (NH) summer. In contrast, the anthropogenic SOA production rate is fairly constant all year round. However, the global anthropogenic SOA burden does have a seasonal cycle which is lowest during NH summer, which is probably due to enhanced wet removal. Inclusion of the new SOA sources also accelerates the ageing by condensation of primary organic aerosol (POA), making it more hydrophilic, leading to a reduction in the POA lifetime. With monoterpene as the only source of SOA, simulated SOA and total organic aerosol (OA) concentrations are underestimated by the model when compared to surface and aircraft measurements. Model agreement with observations improves with all new sources added, primarily due to the inclusion of the anthropogenic source of SOA, although a negative bias remains. A further sensitivity simulation was performed with an increased anthropogenic SOA reaction yield, corresponding to an annual global SOA production rate of 70.0 Tg (SOA) a−1. Whilst simulated SOA concentrations improved relative to observations, they were still underestimated in urban environments and overestimated further downwind and in remote environments. In contrast, the inclusion of SOA from isoprene and biomass burning did not improve model–observations biases substantially except at one out of two tropical locations. However, these findings may reflect the very limited availability of observations to evaluate the model, which are primarily located in the NH mid-latitudes where anthropogenic emissions are high. Our results highlight that, within the current uncertainty limits in SOA sources and reaction yields, over the NH mid-latitudes, a large anthropogenic SOA source results in good agreement with observations. However, more observations are needed to establish the importance of biomass burning and biogenic sources of SOA in model agreement with observations.

The eruption of Mt. Tambora in 1815 was the largest volcanic eruption of the past 500 years. The eruption had significant climatic impacts, leading to the 1816 year without a summer, and remains a valuable event from which to understand the climatic effects of large stratospheric volcanic sulfur dioxide injections. The eruption also resulted in one of the strongest and most easily identifiable volcanic sulfate signals in polar ice cores, which are widely used to reconstruct the timing and atmospheric sulfate loading of past eruptions. As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), five state-of-the-art global aerosol models simulated this eruption. We analyse both simulated background (no Tambora) and volcanic (with Tambora) sulfate deposition to polar regions and compare to ice core records. The models simulate overall similar patterns of background sulfate deposition, although there are differences in regional details and magnitude. However, the volcanic sulfate deposition varies considerably between the models with differences in timing, spatial pattern and magnitude. Mean simulated deposited sulfate on Antarctica ranges from 19 to 264 kg km−2 and on Greenland from 31 to 194 kg km−2, as compared to the mean ice-core-derived estimates of roughly 50 kg km−2 for both Greenland and Antarctica. The ratio of the hemispheric atmospheric sulfate aerosol burden after the eruption to the average ice sheet deposited sulfate varies between models by up to a factor of 15. Sources of this inter-model variability include differences in both the formation and the transport of sulfate aerosol. Our results suggest that deriving relationships between sulfate deposited on ice sheets and atmospheric sulfate burdens from model simulations may be associated with greater uncertainties than previously thought.

The ability to assemble chemically different gelator molecules into complex supramolecular hydrogels provides excellent opportunities to construct functional soft materials. Herein, we demonstrate the formation of hybrid nucleotide–amino acid supramolecular hydrogels. These are generated by the silver ion (Ag+)-triggered formation of silver–guanosine monophosphate (GMP) dimers, which undergo self-assembly through non-covalent interactions to produce nanofilaments. This process results in a concomitant pH reduction due to the abstraction of a proton from the guanine residue, which triggers the in situ gelation of a pH-sensitive amino acid, N-fluorenylmethyloxycarbonyl tyrosine (FY), to form nucleotide–amino acid hybrid hydrogels. Alterations in the supramolecular structures due to changes in the assembly process are observed, with the molar ratio of Ag:GMP:FY affecting the assembly kinetics, and the resulting supramolecular organisation and mechanical properties of the hydrogels. Higher Ag:GMP stoichiometries result in almost instantaneous gelation with non-orthogonal assembly of the gelators, while at lower molar ratios, orthogonal assembly is observed. Significantly, by increasing the pH as an external stimulus, nanofilaments comprising FY can be selectively disassembled from the hybrid hydrogels. Our results demonstrate a simple approach for the construction of multicomponent stimuli-responsive supramolecular hydrogels with adaptable network and mechanical properties.

Most food waste is incinerated and reclaimed in Korea. Due to the development of industry, soil and groundwater pollution are serious. The purpose of this study was to study recycled materials and eco-friendly remediation methods to prevent secondary pollution after remediation. In this study, recycled food waste ash was filled in a permeable reactive barrier (PRB) and used as a heavy metal adsorption material. In situ remediation electrokinetic techniques (EK) and acetic acid were used. Electrokinetic remediation is a technology that can remove various polluted soils and pollutants, and is an economical and highly useful remediation technique. Thereafter, the current density increased constantly over time, and it was confirmed that it increased after electrode exchange and then decreased. Based on this result, the acetic acid was constantly injected and it was reconfirmed through the water content after the end of the experiment. In the case of both heavy metals, the removal efficiency was good after 10 days of operation and 8 days after electrode exchange, but, in the case of lead, it was confirmed that experiments are needed by increasing the operation date before electrode exchange. It was confirmed that the copper removal rate was about 74% to 87%, and the lead removal rate was about 11% to 43%. After the end of the experiment, a low pH was confirmed at x/L = 0.9, and it was also confirmed that there was no precipitation of heavy metals and there was a smooth movement by the enhancer and electrolysis after electrode exchange.

Roadside collisions are a significant problem faced by all countries. Urbanisation has led to an increase in traffic congestion and roadside vehicle collisions. According to the UK Government’s Department for Transport, most vehicle collisions occur on urban roads, with empirical evidence showing drivers are more likely to break local and fixed speed limits in urban environments. Analysis conducted by the Department for Transport found that the UK’s accident prevention measure’s cost is estimated to be £33bn per year. Therefore, there is a strong motivation to investigate the causes of roadside collisions in urban environments to better prepare traffic management, support local council policies, and ultimately reduce collision rates. This study utilises agent-based modelling as a tool to plan, experiment and investigate the relationship between speeding and vehicle density with collisions. The study found that higher traffic density results in more vehicles travelling at a slower speed, regardless of the degree to which drivers comply with speed restrictions. Secondly, collisions increase linearly as speed compliance is reduced for all densities. Collisions are lowest when all vehicles comply with speed limits for all densities. Lastly, higher global traffic densities result in higher local traffic densities near-collision sites across all adherence levels, increasing the likelihood of congestion around these sites. This work, when extended to real-world applications using empirical data, can support effective road safety policies.

Previous algorithms for slicing, path planning or trajectory planning of additive manufacturing cannot be used consistently for multidirectional additive manufacturing with pure object manipulation in wire-arc additive manufacturing. This work presents a novel path planning approach that directly takes robot kinematics into account and thus ensures the reachability of all critical path poses. In an additional step, the planned path segments are smoothed so that joint velocity limits are respected. It is shown that the implemented path planner generates executable robot paths and at the same time maintains the process quality (in this case, sufficient coverage of the slice area). While the introduced method enables the generation of reachable printing paths, the smoothing algorithm allows for the execution of the path with respect to the robot’s velocity limits and at the same time improves the slice coverage. Future experiments will show the realization of the real robot setup presented.

A convection-permitting limited area model with periodic lateral boundary conditions and prognostic aerosol microphysics is applied to investigate how concentrations of cloud condensation nuclei (CCN) in the marine boundary layer are affected by high-resolution dynamical and thermodynamic fields. The high-resolution aerosol microphysics–dynamics model, which resolves differential particle growth and aerosol composition across the particle size range, is applied to a domain designed to match approximately a single grid square of a climate model. We find that, during strongly convective conditions with high wind-speed conditions, CCN concentrations vary by more than a factor of 8 across the domain (5–95th percentile range), and a factor of ∼ 3 at more moderate wind speed. One reason for these large sub-climate-grid-scale variations in CCN is that emissions of sea salt and dimethyl sulfide (DMS) are much higher when spatial and temporal wind-speed fluctuations become resolved at this convection-permitting resolution (making peak wind speeds higher). By analysing how the model evolves during spin-up, we gain new insight into the way primary sea salt and secondary sulfate particles contribute to the overall CCN variance in these realistic conditions, and find a marked difference in the variability of super-micron and sub-micron CCN. Whereas the super-micron CCN are highly variable, dominated by strongly fluctuating sea spray emitted, the sub-micron CCN tend to be steadier, mainly produced on longer timescales following growth after new particle formation in the free troposphere, with fluctuations inherently buffered by the fact that coagulation is faster at higher particle concentrations. We also find that sub-micron CCN are less variable in particle size, the accumulation-mode mean size varying by ∼ 20 % (0.101 to 0.123 µm diameter) compared to ∼ 35 % (0.75 to 1.10 µm diameter) for coarse-mode particles at this resolution. We explore how the CCN variability changes in the vertical and at different points in the spin-up, showing how CCN concentrations are introduced both by the emissions close to the surface and at higher altitudes during strong wind-speed conditions associated to the intense convective period. We also explore how the non-linear variation of sea-salt emissions with wind speed propagates into variations in sea-salt mass mixing ratio and CCN concentrations, finding less variation in the latter two quantities due to the longer transport timescales inherent with finer CCN, which sediment more slowly. The complex mix of sources and diverse community of processes involved makes sub-grid parameterisation of CCN variations difficult. However, the results presented here illustrate the limitations of predictions with large-scale models and the high-resolution aerosol microphysics–dynamics modelling system shows promise for future studies where the aerosol variations will propagate through to modified cloud microphysical evolution.

We present observations of biomass burning aerosol from the South American Biomass Burning Analysis (SAMBBA) and other measurement campaigns, and use these to evaluate the representation of biomass burning aerosol properties and processes in a state-of-the-art climate model. The evaluation includes detailed comparisons with aircraft and ground data, along with remote sensing observations from MODIS and AERONET. We demonstrate several improvements to aerosol properties following the implementation of the Global Model for Aerosol Processes (GLOMAP-mode) modal aerosol scheme in the HadGEM3 climate model. This predicts the particle size distribution, composition, and optical properties, giving increased accuracy in the representation of aerosol properties and physical–chemical processes over the Coupled Large-scale Aerosol Scheme for Simulations in Climate Models (CLASSIC) bulk aerosol scheme previously used in HadGEM2. Although both models give similar regional distributions of carbonaceous aerosol mass and aerosol optical depth (AOD), GLOMAP-mode is better able to capture the observed size distribution, single scattering albedo, and Ångström exponent across different tropical biomass burning source regions. Both aerosol schemes overestimate the uptake of water compared to recent observations, CLASSIC more so than GLOMAP-mode, leading to a likely overestimation of aerosol scattering, AOD, and single scattering albedo at high relative humidity. Observed aerosol vertical distributions were well captured when biomass burning aerosol emissions were injected uniformly from the surface to 3 km. Finally, good agreement between observed and modelled AOD was gained only after scaling up GFED3 emissions by a factor of 1.6 for CLASSIC and 2.0 for GLOMAP-mode. We attribute this difference in scaling factor mainly to different assumptions for the water uptake and growth of aerosol mass during ageing via oxidation and condensation of organics. We also note that similar agreement with observed AOD could have been achieved with lower scaling factors if the ratio of organic carbon to primary organic matter was increased in the models toward the upper range of observed values. Improved knowledge from measurements is required to reduce uncertainties in emission ratios for black carbon and organic carbon, and the ratio of organic carbon to primary organic matter for primary emissions from biomass burning.