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Abstract Increasing production and use of chemicals and awareness of their impact on ecosystems and humans has led to large interest for broadening the knowledge on the chemical status of the environment and human health by suspect and non-target screening (NTS). To facilitate effective implementation of NTS in scientific, commercial and governmental laboratories, as well as acceptance by managers, regulators and risk assessors, more harmonisation in NTS is required. To address this, NORMAN Association members involved in NTS activities have prepared this guidance document, based on the current state of knowledge. The document is intended to provide guidance on performing high quality NTS studies and data interpretation while increasing awareness of the promise but also pitfalls and challenges associated with these techniques. Guidance is provided for all steps; from sampling and sample preparation to analysis by chromatography (liquid and gas—LC and GC) coupled via various ionisation techniques to high-resolution tandem mass spectrometry (HRMS/MS), through to data evaluation and reporting in the context of NTS. Although most experience within the NORMAN network still involves water analysis of polar compounds using LC–HRMS/MS, other matrices (sediment, soil, biota, dust, air) and instrumentation (GC, ion mobility) are covered, reflecting the rapid development and extension of the field. Due to the ongoing developments, the different questions addressed with NTS and manifold techniques in use, NORMAN members feel that no standard operation process can be provided at this stage. However, appropriate analytical methods, data processing techniques and databases commonly compiled in NTS workflows are introduced, their limitations are discussed and recommendations for different cases are provided. Proper quality assurance, quantification without reference standards and reporting results with clear confidence of identification assignment complete the guidance together with a glossary of definitions. The NORMAN community greatly supports the sharing of experiences and data via open science and hopes that this guideline supports this effort.

The increasing use of chemicals requires a better understanding of their presence and dynamics in the environment, as well as their impact on ecosystems. The aim of this study was to validate the first steps of an innovative multi-omics approach based on metabolomics and 16S metabarcoding data for analyses of the fate and impact of contaminants in Mediterranean lagoons. Semi-targeted analytical procedures for water and sediment matrices were implemented to assess chemical contamination of the lagoon: forty-six compounds were detected, 28 of which could be quantified in water (between 0.09 and 47.4 ng/L) and sediment (between 0.008 and 26.3 ng/g) samples using the UHPLC-MS/MS instrument. In addition, a non-targeted approach (UHPLC-HRMS) using four different sample preparation protocols based on solid/liquid extractions or an automated pressurized fluid extraction system (EDGE®) was carried out to determine the protocol with the best metabolome coverage, efficiency and reproducibility. Solid/liquid extraction using the solvent mixture acetonitrile/methanol (50/50) was evaluated as the best protocol. Microbial diversity in lagoon sediment was also measured after DNA extraction using five commercial extraction kits. Our study showed that the DNeasy PowerSoil Pro Qiagen kit (Promega, USA) was the most suitable for assessing microbial diversity in fresh sediment.

We investigate how mesoscale circulations associated with convective aggregation can modulate the sensitivity of the hydrologic cycle to warming. We quantify changes in the full distribution of rain across radiative-convective equilibrium states in a cloud-resolving model. For a given Sea Surface Temperature (SST), the shift in mean rainfall between disorganized and organized states is associated with a shift in atmospheric radiative cooling, and is roughly analogous to the effect of a 4K SST increase. With rising temperatures, the increase in mean rain rate is insensitive to the presence of organization, while extremes can intensify faster in the aggregated state, leading to a faster amplification in the sporadic nature of rain. When convection aggregates, heavy rain is enhanced by 20%-30% and nonlinear behaviors are observed as a function of SST and strength of aggregation feedbacks. First, radiative- and surface-flux aggregation feedbacks have multiplicative effects on extremes, illustrating a non-trivial sensitivity to the degree of organization. Second, alternating Clausius-Clapeyron and super-Clausius-Clapeyron regimes in extreme rainfall are found as a function of SST, corresponding to varying thermodynamic and dynamic contributions, and a large sensitivity to precipitation efficiency variations in some SST ranges. The potential for mesoscale circulations in amplifying the hydrologic cycle is established. However, these nonlinear distortions question the quantitative relevance of idealized self-aggregation. This calls for a deeper investigation of relationships which capture the coupling between global energetics, aggregation feedbacks and local convection, and for systematic tests of their sensitivity to domain configurations, surface boundary conditions, microphysics, and turbulence schemes.

Abstract Radiative cooling of the lowest atmospheric levels is of strong importance for modulating atmospheric circulations and organizing convection, but detailed observations and a robust theoretical understanding are lacking. Here we use unprecedented observational constraints from subsidence regimes in the tropical Atlantic to develop a theory for the shape and magnitude of low‐level longwave radiative cooling in clear‐sky, showing peaks larger than 5–10 K/day at the top of the boundary layer. A suite of novel scaling approximations is first developed from simplified spectral theory, in close agreement with the measurements. The radiative cooling peak height is set by the maximum lapse rate in water vapor path, and its magnitude is mainly controlled by the ratio of column relative humidity above and below the peak. We emphasize how elevated intrusions of moist air can reduce low‐level cooling, by sporadically shading the spectral range which effectively cools to space. The efficiency of this spectral shading depends both on water content and altitude of moist intrusions; its height dependence cannot be explained by the temperature difference between the emitting and absorbing layers, but by the decrease of water vapor extinction with altitude. This analytical work can help to narrow the search for low‐level cloud patterns sensitive to radiative‐convective feedbacks: the most organized patterns with largest cloud fractions occur in atmospheres below 10% relative humidity and feel the strongest low‐level cooling. This motivates further assessment of favorable conditions for radiative‐convective feedbacks and a robust quantification of corresponding shallow cloud dynamics in current and warmer climates.

Some studies documenting changes in extreme precipitation use scaling formulas to approximate the large percentiles of the rainfall distribution from average dynamical and thermodynamical variables, called predictors. Here we instead assess the performance of these formulas as approximations to the rain rates in individual events. We evaluate the accuracies of the scaling relationships as functions of spatial and temporal scales by analyzing tropical rainfall in a superparameterized model. Relationships using full vertical profiles of the predictors are more accurate than those using their values at specific vertical levels because they better characterize the specific dynamics of each event. Both types of scaling relationships perform well over a range of length scales from 200 to 2,000 km and time scales from an hour to a week, and their precision is higher in the case of simulations with superparameterization than with parameterized convection. Uncertainties emerging from the local use of the scaling relationships suggest that they may only characterize the intensification of individual extremes for a warming of 4–5 K or larger. Finally, we argue that these formulas can be used to reconstruct the tail of the rainfall distribution directly from its predictors without prior information on P. While scalings have been used as diagnostic equations conditioned on the occurrence of extreme rainfall, they are actually able to mimic the prognostic behavior of climate model parameterizations on a variety of scales when estimating the intensity, frequency, and spatial patterns of extremes.

As part of the EUREC4A (Elucidating the role of cloud–circulation coupling in climate) field campaign, which took place in January and February 2020 over the western tropical Atlantic near Barbados, the French SAFIRE ATR42 research aircraft (ATR) conducted 19 flights in the lower troposphere. Each flight followed a common flight pattern that sampled the atmosphere around the cloud base level, at different heights of the subcloud layer, near the sea surface and in the lower free troposphere. The aircraft's payload included a backscatter lidar and a Doppler cloud radar that were both horizontally oriented; a Doppler cloud radar looking upward; microphysical probes; a cavity ring-down spectrometer for water isotopes; a multiwavelength radiometer; a visible camera; and multiple meteorological sensors, including fast rate sensors for turbulence measurements. With this instrumentation, the ATR characterized the macrophysical and microphysical properties of trade-wind clouds together with their thermodynamical, turbulent and radiative environment. This paper presents the airborne operations, the flight segmentation, the instrumentation, the data processing and the EUREC4A datasets produced from the ATR measurements. It shows that the ATR measurements of humidity, wind and cloud base cloud fraction measured with different techniques and samplings are internally consistent; that meteorological measurements are consistent with estimates from dropsondes launched from an overflying aircraft (the High Altitude and LOng Range Research Aircraft, HALO); and that water-isotopic measurements are well correlated with data from the Barbados Cloud Observatory. This consistency demonstrates the robustness of the ATR measurements of humidity, wind, cloud base cloud fraction and water-isotopic composition during EUREC4A. It also confirms that through their repeated flight patterns, the ATR and HALO measurements provided a statistically consistent sampling of trade-wind clouds and of their environment. The ATR datasets are freely available at the locations specified in Table 11.

The science guiding the EUREC4A campaign and its measurements is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. Through its ability to characterize processes operating across a wide range of scales, EUREC4A marked a turning point in our ability to observationally study factors influencing clouds in the trades, how they will respond to warming, and their link to other components of the earth system, such as upper-ocean processes or the life cycle of particulate matter. This characterization was made possible by thousands (2500) of sondes distributed to measure circulations on meso- (200 km) and larger (500 km) scales, roughly 400 h of flight time by four heavily instrumented research aircraft; four global-class research vessels; an advanced ground-based cloud observatory; scores of autonomous observing platforms operating in the upper ocean (nearly 10 000 profiles), lower atmosphere (continuous profiling), and along the air–sea interface; a network of water stable isotopologue measurements; targeted tasking of satellite remote sensing; and modeling with a new generation of weather and climate models. In addition to providing an outline of the novel measurements and their composition into a unified and coordinated campaign, the six distinct scientific facets that EUREC4A explored – from North Brazil Current rings to turbulence-induced clustering of cloud droplets and its influence on warm-rain formation – are presented along with an overview of EUREC4A's outreach activities, environmental impact, and guidelines for scientific practice. Track data for all platforms are standardized and accessible at https://doi.org/10.25326/165 (Stevens, 2021), and a film documenting the campaign is provided as a video supplement.

Measurement(s) chemical • drinking water Technology Type(s) high resolution mass spectrometry • non-target analysis • Interlaboratory Factor Type(s) method Sample Characteristic - Environment laboratory environment Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.15028665

The Superparameterized Community Atmosphere Model (SPCAM) is used to identify the dynamical and organizational properties of tropical extreme rainfall events on two scales. We compare the mesoscales resolved by General Circulation Models (GCMs) and the convective scales resolved by Cloud-Resolving Models (CRMs) to reassess and extend on previous results from GCMs and CRMs in radiative-convective equilibrium. We first show that the improved representation of subgridscale dynamics in SPCAM allows for a close agreement with the 7%/K Clausius-Clapeyron rate of increase in mesoscale extremes rainfall rates. Three contributions to changes in extremes are quantified and appear consistent in sign and relative magnitude with previous results. On mesoscales, the thermodynamic contribution (5.8%/K) and the contribution from mass flux increases (2%/K) enhance precipitation rates, while the upward displacement of the mass flux profile (-1.1%/K) offsets this increase. Convective-scale extremes behave similarly except that changes in mass flux are negligible due to a balance between greater numbers of strong updrafts and downdrafts and lesser numbers of weak updrafts. Extremes defined on these two scales behave as two independent sets of rainfall events, with different dynamics, geometries, and responses to climate change. In particular, dynamic changes in mesoscale extremes appear primarily sensitive to changes in the large-scale mass flux, while the intensity of convective-scale extremes is not. In particular, the increases in mesoscale mass flux directly contribute to the intensification of mesoscale extreme rain, but do not seem to affect the increase in convective-scale rainfall intensities. These results motivate the need for better understanding the role of the large-scale forcing on the formation and intensification of heavy convective rainfall.

The increasing use of chemicals requires a better understanding of their presence and dynamics in the environment, as well as their impact on ecosystems. The aim of this study was to validate the first steps of an innovative multi-omics approach based on metabolomics and 16S metabarcoding data for analyses of the fate and impact of contaminants in Mediterranean lagoons. Semi-targeted analytical procedures for water and sediment matrices were implemented to assess chemical contamination of the lagoon: forty-six compounds were detected, 28 of which could be quantified in water (between 0.09 and 47.4 ng/L) and sediment (between 0.008 and 26.3 ng/g) samples using the UHPLC-MS/MS instrument. In addition, a non-targeted approach (UHPLC-HRMS) using four different sample preparation protocols based on solid/liquid extractions or an automated pressurized fluid extraction system (EDGE®) was carried out to determine the protocol with the best metabolome coverage, efficiency and reproducibility. Solid/liquid extraction using the solvent mixture acetonitrile/methanol (50/50) was evaluated as the best protocol. Microbial diversity in lagoon sediment was also measured after DNA extraction using five commercial extraction kits. Our study showed that the DNeasy PowerSoil Pro Qiagen kit (Promega, USA) was the most suitable for assessing microbial diversity in fresh sediment. [ABSTRACT FROM AUTHOR]

The couplings among clouds, convection, and circulation in trade-wind regimes remain a fundamental puzzle that limits our ability to constrain future climate change. Radiative heating plays an important role in these couplings. Here we calculate clear-sky radiative profiles from 2580 in situ soundings (1068 dropsondes and 1512 radiosondes) collected during the field campaign EUREC4A (Elucidating the role of clouds–circulation coupling in climate). EUREC4A took place in the downstream trades of the western tropical Atlantic in January–February 2020. We describe the method used to calculate these cloud-free, aerosol-free radiative profiles. We then present preliminary results sampling variability at multiple scales, from the variability across all soundings to groupings by diurnal cycle and mesoscale organization, as well as individual soundings associated with elevated moisture layers. We also perform an uncertainty assessment and find that the errors resulting from uncertainties in observed sounding profiles and ERA5 reanalysis employed as upper and lower boundary conditions are small. The present radiative profile data set can provide important additional details missing from calculations based on passive remote sensing and aid in understanding the interplay of radiative heating with dynamic and thermodynamic variability in the trades. The data set can also be used to investigate the role of low-level radiative cooling gradients in generating shallow circulations. All data are archived and freely available for public access on AERIS (Albright et al., 2020a, https://doi.org/https://doi.org/10.25326/78).

Projected increases in mean precipitation are constrained by the atmospheric energy budget through radiative-convective equilibrium. However, significant differences persist between climate models on the rate of increase in precipitation per unit warming, mostly arising from the clear-sky radiative response. While the intermodel spread in clear-sky longwave cooling has been explained by climate feedbacks, the sources of spread in clear-sky shortwave heating are still unclear. This article focuses on the latter. Since water vapor contributes most of the atmospheric shortwave absorption, both intermodel differences in its spatial distribution and in radiative transfer parameterizations are plausible hypotheses for the spread. This work reestablishes the primary contribution from water vapor relative to other shortwave-absorbing species and evaluates the validity of both hypotheses. It is found that the intermodel spread in shortwave absorption change most likely originates from the radiation schemes, possibly because of simplifications induced by their low spectral resolutions. Key Points Water vapor appears as the main cause of intermodel differences in atmospheric shortwave absorption Such discrepancies seem to come from the shortwave radiative transfer formulation for water vapor Errors arising from the coarse spectral resolution in radiation schemes could explain this spread

Abstract This work explores the effect of convective self‐aggregation on extreme rainfall intensities through an analysis at several stages of the cloud lifecycle. In addition to increases in 3‐hourly extremes consistent with previous studies, we find that instantaneous rainrates increase significantly (+30%). We mainly focus on instantaneous extremes and, using a recent framework, relate their increase to increased precipitation efficiency: the local increase in relative humidity drives larger accretion efficiency and lower re‐evaporation. An in‐depth analysis based on an adapted scaling for precipitation extremes reveals that the dynamic contribution decreases (−25%) while the thermodynamic is slightly enhanced (+5%) with convective self‐aggregation, leading to lower condensation rates. When the atmosphere is more organized into a moist convecting region and a dry convection‐free region, deep convective updrafts are surrounded by a warmer environment which reduces convective instability and thus the dynamic contribution. The moister boundary‐layer explains the positive thermodynamic contribution. The microphysic contribution is increased by +50% with aggregation. The latter is partly due to reduced evaporation of rain falling through a moister near‐cloud environment, but also to the associated larger accretion efficiency. Thus, a potential change in convective organization regimes in a warming climate could lead to an evolution of tropical precipitation extremes significantly different than that expected from thermodynamical considerations. The relevance of self‐aggregation to the real tropics is still debated. Improved fundamental understanding of self‐aggregation, its sensitivity to warming and connection to precipitation extremes, is hence crucial to achieve accurate rainfall projections in a warming climate.

Abstract We investigate how mesoscale circulations associated with convective aggregation can modulate the sensitivity of the hydrologic cycle to warming. We quantify changes in the full distribution of rain across radiative‐convective equilibrium states in a cloud‐resolving model. For a given Sea Surface Temperature (SST), the shift in mean rainfall between disorganized and organized states is associated with a shift in atmospheric radiative cooling, and is roughly analogous to the effect of a 4K SST increase. With rising temperatures, the increase in mean rain rate is insensitive to the presence of organization, while extremes can intensify faster in the aggregated state, leading to a faster amplification in the sporadic nature of rain. When convection aggregates, heavy rain is enhanced by 20%–30% and nonlinear behaviors are observed as a function of SST and strength of aggregation feedbacks. First, radiative‐ and surface‐flux aggregation feedbacks have multiplicative effects on extremes, illustrating a non‐trivial sensitivity to the degree of organization. Second, alternating Clausius‐Clapeyron and super‐Clausius‐Clapeyron regimes in extreme rainfall are found as a function of SST, corresponding to varying thermodynamic and dynamic contributions, and a large sensitivity to precipitation efficiency variations in some SST ranges. The potential for mesoscale circulations in amplifying the hydrologic cycle is established. However, these nonlinear distortions question the quantitative relevance of idealized self‐aggregation. This calls for a deeper investigation of relationships which capture the coupling between global energetics, aggregation feedbacks and local convection, and for systematic tests of their sensitivity to domain configurations, surface boundary conditions, microphysics, and turbulence schemes.

Environmental metabolomics has become a growing research field to understand biological and biochemical perturbations of organisms in response to various abiotic or biotic stresses. It focuses on the comprehensive and systematic analysis of a biologic system's metabolome. This allows the recognition of biochemical pathways impacted by a stressor, and the identification of some metabolites as biomarkers of potential perturbations occurring in a body. In this work, we describe the development and optimization of a complete reliable methodology based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) for untargeted metabolomics studies within a fish model species, the three-spined stickleback (Gasterosteus aculeatus). We evaluated the differences and also the complementarities between four different matrices (brain, gills, liver and whole fish) to obtain metabolome information. To this end, we optimized and compared sample preparation and the analytical method, since the type and number of metabolites detected in any matrix are closely related to these latter. For the sample preparation, a solid-liquid extraction was performed on a low quantity of whole fish, liver, brain, or gills tissues using combinations of methanol/water/heptane. Based on the numbers of features observed in LC-HRMS and on the responses of analytical standards representative of different metabolites groups (amino acids, sugars…), we discuss the influence of the nature, volume, and ratio of extraction solvents, the sample weight, and the reconstitution solvent. Moreover, the analytical conditions (LC columns, pH and additive of mobile phases and ionization modes) were also optimized so as to ensure the maximum metabolome coverages. Thus, two complementary chromatographic procedures were combined in order to cover a broader range of metabolites: a reversed phase separation (RPLC) on a C18 column followed by detection with positive ionization mode (ESI+) and a hydrophilic interaction chromatography (HILIC) on a zwitterionic column followed by detection with negative ionization mode (ESI-). This work provides information on brain, gills, liver, vs the whole body contribution to the stickleback metabolome. These information would help to guide ecotoxicological and biomonitoring studies.

Background: Aryl phosphate esters (APEs) are widely used and commonly present in the environment. Health hazards associated with these compounds remain largely unknown and the effects of diphenyl phosphate (DPhP), one of their most frequent derivatives, are poorly characterized. Objective: Our aim was to investigate whether DPhP per se may represent a more relevant marker of exposure to APEs than direct assessment of their concentration and determine its potential deleterious biological effects in chronically exposed mice. Methods: Conventional animals (FVB mice) were acutely or chronically exposed to relevant doses of DPhP or to triphenyl phosphate (TPhP), one of its main precursors. Both molecules were measured in blood and other tissues by liquid chromatography-mass spectrometry (LC-MS). Effects of chronic DPhP exposure were addressed through liver multi-omics analysis to determine the corresponding metabolic profile. Deep statistical exploration was performed to extract correlated information, guiding further physiological analyses. Results: Multi-omics analysis confirmed the existence of biological effects of DPhP, even at a very low dose of 0.1mg/mL in drinking water. Chemical structural homology and pathway mapping demonstrated a clear reduction of the fatty acid catabolic processes centered on acylcarnitine and mitochondrial [beta]-oxidation in mice exposed to DPhP in comparison with those treated with vehicle. An interesting finding was that in mice exposed to DPhP, mRNA, expression of genes involved in lipid catabolic processes and regulated by peroxisome proliferator-activated receptor alpha (PPAR[alpha]) was lower than that in vehicle-treated mice. Immunohistochemistry analysis showed a specific down- regulation of HMGCS2, a kernel target gene of PPAR[alpha]. Overall, DPhP absorption disrupted body weight-gain processes. Conclusions: Our results suggest that in mice, the effects of chronic exposure to DPhP, even at a low dose, are not negligible. Fatty acid metabolism in the liver is essential for controlling fast and feast periods, with adverse consequences on the overall physiology. Therefore, the impact of DPhP on circulating fat, cardiovascular pathologies and metabolic disease incidence deserves, in light of our results, further investigations. https://doi.org/10.1289/EHP6826, Introduction Diphenyl phosphate (DPhP) has been used as a main biomarker for assessing exposure to aryl phosphate esters (APEs), especially triphenyl phosphate (TPhP), a molecule suspected of presenting human health [...]

A phytochemical investigation of Diplotaxis virgata D.C. and D. erucoides (L.) D.C. (Brassicaceae) offered to the isolation of two new flavonoids isorhamnetin-3-O-α-l-glucopyranoside (1) and rhamnetin-3,3ʹ-di-O-β-d-glucopyranoside (2), respectively. Their structures have been elucidated from the extended spectroscopic methods, including 1D- and 2D-NMR, UV and mass spectrometry analysis and by comparison with literature data. The fatty acid composition of the hexane extracts of the two species was also investigated by using GC-MS. The antioxidant activity of ethanol, ethyl acetate, n-butanol extracts and the isolated compounds from the two species was evaluated using DPPH and ABTS+ scavenging assays. All the tested samples showed an efficient radical scavenging ability, with IC50 values ranging from 16–40 µg/mL for the DPPH and from 17–44 µg/mL for the ABTS+ assays. In addition, the antibacterial activity of the prepared extracts and compounds 1 and 2, determined by well diffusion agar method against two Gram positive and five Gram negative bacteria, was evaluated and the results showed significant effects against all strains used.