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Microplastics (MPs) (plastic particles < 5 mm in size) have become the most ubiquitous type of anthropogenic litter contaminating aquatic environments worldwide, and are capable of harming aquatic organisms and entering the food web. Microplastic research has rapidly evolved over several decades, with many studies sampling microplastic in surface waters. For sea surface sampling of MPs, different net devices have been used. But although there is an increasing number of studies using these devices to quantifying MPs in different aquatic environments, data comparison is difficult due to the lack of standardised, harmonised sampling methods and data reporting units. The Manta net device is actually the most commonly used method for sea surface sampling of MPs. The three main parts of this net are: the floating/stabilizing part, the opening mouth and the net bag, and each of them can have its own specifications. These specifications, along with the sampling methods, can be critical for the efficiency of the sampling accurate quantification of MPs in the aquatic environments. The use of different mesh sizes, inconsistency in trawling duration, speed and distance, and in the net opening dimensions, make it impossible to compare the studies between each other. This review analyzes the methodologies and characteristics of Manta nets used for MPs sampling, discussing factors that can impact the efficiency of the sampling and the quantification of MPs, and proposes recommendations in order to improve and standardize the sampling protocol.

Due to limitations of sampling methods, subsurface water is usually a less well-investigated compartment of the water column when scientists assess microplastic contamination. In this study, microplastic (MP) contamination was assessed in a freshwater river both in surface and subsurface using an innovative sampling method. Microplastic contamination in the lower part of the water column, i.e., near-bottom water and in sediments, was also studied. Three sampling campaigns were carried out during different weather conditions: stormy, rainy, and dry in order to observe their influence on the microplastics vertical distribution. No significant difference was observed between the abundance and types of MPs in surface and subsurface water. The proportion of polymer with theoretical density < 1 (polypropylene d = 0.9, polyethylene d = 0.91-0.95) and polystyrene (d = 0.1-1.06) in the surface and subsurface samples was 73.5%, and this proportion drops to 40.8% for the samples located in the near-bottom water and the sediments. Our results indicate that the MP concentration of the different compartments analyzed can be significantly influenced by rainfall during and prior to the sampling day. This study highlights that in shallow rivers, surface water sampling is representative of the water column MP contamination, but that sampling without taking environmental conditions into account may lead to erroneous estimation of MPs concentration and flux entering the marine environment.

The Arctic is one of the most rapidly warming regions of the globe. Low-level clouds and fog modify the energy transfer from and to space and play a key role in the observed strong Arctic surface warming, a phenomenon commonly termed “Arctic amplification”. The response of low-level clouds to changing aerosol characteristics throughout the year is therefore an important driver of Arctic change that currently lacks sufficient constraints. As such, during the NASCENT campaign (Ny-Ålesund AeroSol Cloud ExperimeNT) extending over a full year from October 2019 to October 2020, microphysical properties of aerosols and clouds were studied at the Zeppelin station (475 m a.s.l.), Ny-Ålesund, Svalbard, Norway. Particle number size distributions obtained from differential mobility particle sizers as well as chemical composition derived from filter samples and an aerosol chemical speciation monitor were analyzed together with meteorological data, in particular vertical wind velocity. The results were used as input to a state-of-the-art cloud droplet formation parameterization to investigate the particle sizes that can activate to cloud droplets, the levels of supersaturation that can develop, the droplet susceptibility to aerosol and the role of vertical velocity. We evaluate the parameterization and the droplet numbers calculated through a droplet closure with in-cloud in situ measurements taken during nine flights over 4 d. A remarkable finding is that, for the clouds sampled in situ, closure is successful in mixed-phase cloud conditions regardless of the cloud glaciation fraction. This suggests that ice production through ice–ice collisions or droplet shattering may have explained the high ice fraction, as opposed to rime splintering that would have significantly reduced the cloud droplet number below levels predicted by warm-cloud activation theory. We also show that pristine-like conditions during fall led to clouds that formed over an aerosol-limited regime, with high levels of supersaturation (generally around 1 %, although highly variable) that activate particles smaller than 20 nm in diameter. Clouds formed in the same regime in late spring and summer, but aerosol activation diameters were much larger due to lower cloud supersaturations (ca. 0.5 %) that develop because of higher aerosol concentrations and lower vertical velocities. The contribution of new particle formation to cloud formation was therefore strongly limited, at least until these newly formed particles started growing. However, clouds forming during the Arctic haze period (winter and early spring) can be limited by updraft velocity, although rarely, with supersaturation levels dropping below 0.1 % and generally activating larger particles (20 to 200 nm), including pollution transported over a long range. The relationship between updraft velocity and the limiting cloud droplet number agrees with previous observations of various types of clouds worldwide, which supports the universality of this relationship.

This study is the first to apply dilute acid pretreatment (DAP) under different severity conditions to poplar wood genetically modified for the cinnamyl alcohol dehydrogenase ( CAD1 ) gene, which is involved in the lignin biosynthesis pathway. The carefully selected pretreatment conditions resulted in glucose yields that were 15 points higher for the hpCAD poplar line than for the wild-type (WT) wood after 48 h of enzymatic hydrolysis. To explain this higher saccharification rate, the chemical, spectral and structural changes in WT and hpCAD wood were analyzed in relation to the severity of the pretreatment process. Although few differences were found at the chemical level, variations in autofluorescence and cell deformation were more significant: at high severity, the cells of hpCAD wood observed by nanotomography were more easily deformed, but their middle lamella was more resistant than those of WT wood. All these differences are possibly explained by changes in the molecular structure of lignin in hpCAD wood, leading to the formation of more hydrophobic shorter monomer chains with fewer lignin‒carbohydrate interactions. Graphical Abstract

The Arctic is warming at more than twice the rate of the global average. This warming is influenced by clouds, which modulate the solar and terrestrial radiative fluxes and, thus, determine the surface energy budget. However, the interactions among clouds, aerosols, and radiative fluxes in the Arctic are still poorly understood. To address these uncertainties, the Ny-Ålesund Aerosol Cloud Experiment (NASCENT) study was conducted from September 2019 to August 2020 in Ny-Ålesund, Svalbard. The campaign’s primary goal was to elucidate the life cycle of aerosols in the Arctic and to determine how they modulate cloud properties throughout the year. In situ and remote sensing observations were taken on the ground at sea level, at a mountaintop station, and with a tethered balloon system. An overview of the meteorological and the main aerosol seasonality encountered during the NASCENT year is introduced, followed by a presentation of first scientific highlights. In particular, we present new findings on aerosol physicochemical and molecular properties. Further, the role of cloud droplet activation and ice crystal nucleation in the formation and persistence of mixed-phase clouds, and the occurrence of secondary ice processes, are discussed and compared to the representation of cloud processes within the regional Weather Research and Forecasting Model. The paper concludes with research questions that are to be addressed in upcoming NASCENT publications.

The Arctic is one of the most rapidly warming regions of the globe. Low-level clouds and fog modify the energy transfer from and to space and play a key role in the observed strong Arctic surface warming, a phenomenon commonly termed “Arctic amplification”. The response of low-level clouds to changing aerosol characteristics throughout the year is therefore an important driver of Arctic change that currently lacks sufficient constraints. As such, during the NASCENT campaign (Ny-Ålesund AeroSol Cloud ExperimeNT) extending over a full year from October 2019 to October 2020, microphysical properties of aerosols and clouds were studied at the Zeppelin station (475 m a.s.l.), Ny-Ålesund, Svalbard, Norway. Particle number size distributions obtained from differential mobility particle sizers as well as chemical composition derived from filter samples and an aerosol chemical speciation monitor were analyzed together with meteorological data, in particular vertical wind velocity. The results were used as input to a state-of-the-art cloud droplet formation parameterization to investigate the particle sizes that can activate to cloud droplets, the levels of supersaturation that can develop, the droplet susceptibility to aerosol and the role of vertical velocity. We evaluate the parameterization and the droplet numbers calculated through a droplet closure with in-cloud in situ measurements taken during nine flights over 4 d. A remarkable finding is that, for the clouds sampled in situ, closure is successful in mixed-phase cloud conditions regardless of the cloud glaciation fraction. This suggests that ice production through ice–ice collisions or droplet shattering may have explained the high ice fraction, as opposed to rime splintering that would have significantly reduced the cloud droplet number below levels predicted by warm-cloud activation theory. We also show that pristine-like conditions during fall led to clouds that formed over an aerosol-limited regime, with high levels of supersaturation (generally around 1 %, although highly variable) that activate particles smaller than 20 nm in diameter. Clouds formed in the same regime in late spring and summer, but aerosol activation diameters were much larger due to lower cloud supersaturations (ca. 0.5 %) that develop because of higher aerosol concentrations and lower vertical velocities. The contribution of new particle formation to cloud formation was therefore strongly limited, at least until these newly formed particles started growing. However, clouds forming during the Arctic haze period (winter and early spring) can be limited by updraft velocity, although rarely, with supersaturation levels dropping below 0.1 % and generally activating larger particles (20 to 200 nm), including pollution transported over a long range. The relationship between updraft velocity and the limiting cloud droplet number agrees with previous observations of various types of clouds worldwide, which supports the universality of this relationship.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

High-dimensional quantum computing has generated significant interest due to its potential to address scalability and error correction challenges faced by traditional qubit-based systems. This paper investigates the Average Gate Fidelity (AGF) of single qudit systems under Markovian noise in the Lindblad formalism, extending previous work by developing a comprehensive theoretical framework for the calculation of higher-order correction terms. We derive general expressions for the perturbative expansion of the Average Gate Infidelity (AGI) in terms of the environmental coupling coefficient and validate these with extensive numerical simulations, emphasizing the transition from linear to nonlinear behaviour in the strong coupling regime. Our findings highlight the dependence of AGI on qudit dimensionality, quantum gate choice, and noise strength, providing critical insights for optimising quantum gate design and error correction protocols. Additionally, we utilise our framework to identify universal bounds for the AGI in the strong coupling regime and explore the practical implications for enhancing the performance of near-term qudit architectures. This study offers a robust foundation for future research and development in high-dimensional quantum computing, contributing to the advancement of robust, high-fidelity quantum operations.