Heterogeneous ice nucleation on dust particles sourced from nine deserts worldwide - Part 1: Immersion freezing

Desert dust is one of the most abundant ice nucleating particle types in the atmosphere. Traditionally, clay minerals were assumed to determine the ice nucleation ability of desert dust and constituted the focus of ice nucleation studies over several decades. Recently some feldspar species were identified to be ice active at much higher temperatures than clay minerals, redirecting studies to investigate the contribution of feldspar to ice nucleation on desert dust. However, so far no study has shown the atmospheric relevance of this mineral phase. For this study four dust samples were collected after airborne transport in the troposphere from the Sahara to different locations (Crete, the Peloponnese, Canary Islands, and the Sinai Peninsula). Additionally, 11 dust samples were collected from the surface from nine of the biggest deserts worldwide. The samples were used to study the ice nucleation behavior specific to different desert dusts. Furthermore, we investigated how representative surface-collected dust is for the atmosphere by comparing to the ice nucleation activity of the airborne samples. We used the IMCA-ZINC setup to form droplets on single aerosol particles which were subsequently exposed to temperatures between 233 and 250 K. Dust particles were collected in parallel on filters for offline cold-stage ice nucleation experiments at 253–263 K. To help the interpretation of the ice nucleation experiments the mineralogical composition of the dusts was investigated. We find that a higher ice nucleation activity in a given sample at 253 K can be attributed to the K-feldspar content present in this sample, whereas at temperatures between 238 and 245 K it is attributed to the sum of feldspar and quartz content present. A high clay content, in contrast, is associated with lower ice nucleation activity. This confirms the importance of feldspar above 250 K and the role of quartz and feldspars determining the ice nucleation activities at lower temperatures as found by earlier studies for monomineral dusts. The airborne samples show on average a lower ice nucleation activity than the surface-collected ones. Furthermore, we find that under certain conditions milling can lead to a decrease in the ice nucleation ability of polymineral samples due to the different hardness and cleavage of individual mineral phases causing an increase of minerals with low ice nucleation ability in the atmospherically relevant size fraction. Comparison of our data set to an existing desert dust parameterization confirms its applicability for climate models. Our results suggest that for an improved prediction of the ice nucleation ability of desert dust in the atmosphere, the modeling of emission and atmospheric transport of the feldspar and quartz mineral phases would be key, while other minerals are only of minor importance

Studies of insect temporal trends must account for the complex sampling histories inherent to many long-term monitoring efforts

Crossley et al. (2020)1 examine patterns of change in insect abundance and diversity across US Long-Term Ecological Research (LTER) sites, concluding “a lack of overall increase or decline”. This is notable if true, given mixed conclusions in the literature regarding the nature and ubiquity of insect declines across regions and insect taxonomic groups2–6. The data analyzed, downloaded from and collected by US LTER sites, represent unique time series of arthropod abundances. These long-term datasets often provide critical insights, capturing both steady changes and responses to sudden unpredictable events. However, a number of the included datasets are not suitable for estimating long-term observational trends because they come from experiments or have methodological inconsistencies. Additionally, long-term ecological datasets are rarely uniform in sampling effort across their full duration as a result of the changing goals and abilities of a research site to collect data7. We suggest that Crossley et al.’s results rely upon a key, but flawed, assumption, that sampling was collected “in a consistent way over time within each dataset”. We document problems with data use prior to statistical analyses from eight LTER sites due to datasets not being suitable for long-term trend estimation and not accounting for sampling variation, using the Konza Prairie (KNZ) grasshopper dataset (CGR022) as an example

Evidence for non-exponential elastic proton proton differential cross-section at low vertical bar t vertical bar and √ s = 8 TeV by TOTEM

The TOTEM experiment has made a precise measurement of the elastic proton proton differential cross-section at the centre-of-mass energy root s = 8 TeV based on a high-statistics data sample obtained with the beta* = 90 m optics. Both the statistical and systematic uncertainties remain below 1%, except for the t-independent contribution from the overall normalisation. This unprecedented precision allows to exclude a purely exponential differential cross-section in the range of four-momentum transfer squared 0.027 <vertical bar t vertical bar <0.2 GeV2 with a significance greater than 7 sigma. Two extended parametrisations, with quadratic and cubic polynomials in the exponent, are shown to be well compatible with the data. Using them for the differential cross-section extrapolation to t = 0, and further applying the optical theorem, yields total cross-section estimates of (101.5 +/- 2.1) mb and (101.9 +/- 2.1) mb, respectively, in agreement with previous TOTEM measurements. (C) 2015 The Authors. Published by Elsevier B.V.Peer reviewe

Host specificity and species colouration mediate the regional decline of nocturnal moths in central European forests

The high diversity of insects has limited the volume of long-term community data with a high taxonomic resolution and considerable geographic replications, especially in forests. Therefore, trends and causes of changes are poorly understood. Here we analyse trends in species richness, abundance and biomass of nocturnal macro moths in three quantitative data sets collected over four decades in forests in southern Germany. Two local data sets, one from coppiced oak forests and one from high oak forests included 125K and 48K specimens from 559 and 532 species, respectively. A third regional data set, representing all forest types in the temperate zone of central Europe comprised 735K specimens from 848 species. Generalized additive mixed models revealed temporal declines in species richness (−38%), abundance (−53%) and biomass (−57%) at the regional scale. These were more pronounced in plant host specialists and in dark coloured species. In contrast, the local coppiced oak forests showed an increase, in species richness (+62%), while the high oak forests showed no clear trends. Left and right censoring as well as cross validation confirmed the robustness of the analyses, which led to four conclusions. First, the decline in insects appears in hyper diverse insect groups in forests and affects species richness, abundance and biomass. Second, the pronounced decline in host specialists suggests habitat loss as an important driver of the observed decline. Third, the more severe decline in dark species might be an indication of global warming as a potential driver. Fourth, the trends in coppiced oak forests indicate that maintaining complex and diverse forest ecosystems through active management may be a promising conservation strategy in order to counteract negative trends in biodiversity, alongside rewilding approaches

First measurement of elastic, inelastic and total cross-section at √s = 13TeV by TOTEM and overview of cross-section data at LHC energies : TOTEM Collaboration

The TOTEM collaboration has measured the proton- proton total cross section at v s = 13 TeV with a luminosity- independent method. Using dedicated ss * = 90m beam optics, the Roman Pots were inserted very close to the beam. The inelastic scattering rate has been measured by the T1 and T2 telescopes during the same LHC fill. After applying the optical theorem the total proton- proton cross section is stot = (110.6 +/- 3.4) mb, well in agreement with the extrapolation from lower energies. This method also allows one to derive the luminosity- independent elastic and inelastic cross sections: sel = (31.0 +/- 1.7) mband sinel = (79.5 +/- 1.8) mb.Peer reviewe

LipidomeDB Data Calculation Environment: Online Processing of Direct-Infusion Mass Spectral Data for Lipid Profiles

The final publication is available at Springer via http://dx.doi.org/10.1007/s11745-011-3575-8.LipidomeDB Data Calculation Environment (DCE) is a web application to quantify complex lipids by processing data acquired after direct infusion of a lipid-containing biological extract, to which a cocktail of internal standards has been added, into an electrospray source of a triple quadrupole mass spectrometer. LipidomeDB DCE is located on the public Internet at http://lipidome.bcf.ku.edu:9000/Lipidomics. LipidomeDB DCE supports targeted analyses; analyte information can be entered, or pre-formulated lists of typical plant or animal polar lipid analytes can be selected. LipidomeDB DCE performs isotopic deconvolution and quantification in comparison to internal standard spectral peaks. Multiple precursor or neutral loss spectra from up to 35 samples may be processed simultaneously with data input as Excel files and output as tables viewable on the web and exportable in Excel. The pre-formulated compound lists and web access, used with direct-infusion mass spectrometry, provide a simple approach to lipidomic analysis, particularly for new users

Coal fly ash: Linking immersion freezing behavior and physicochemical particle properties

To date, only a few studies have investigated the potential of coal fly ash particles to trigger heterogeneous ice nucleation in cloud droplets. The presented measurements aim at expanding the sparse dataset and improving process understanding of how physicochemical particle properties can influence the freezing behavior of coal fly ash particles immersed in water. Firstly, immersion freezing measurements were performed with two single particle techniques, i.e., the Leipzig Aerosol Cloud Interaction Simulator (LACIS) and the SPectrometer for Ice Nuclei (SPIN). The effect of suspension time on the efficiency of the coal fly ash particles when immersed in a cloud droplet is analyzed based on the different residence times of the two instruments and employing both dry and wet particle generation. Secondly, two cold-stage setups, one using microliter sized droplets (Leipzig Ice Nucleation Array) and one using nanoliter sized droplets (WeIzmann Supercooled Droplets Observation on Microarray setup) were applied. We found that coal fly ash particles are comparable to mineral dust in their immersion freezing behavior when being dry generated. However, a significant decrease in immersion freezing efficiency was observed during experiments with wet-generated particles in LACIS and SPIN. The efficiency of wet-generated particles is in agreement with the cold-stage measurements. In order to understand the reason behind the deactivation, a series of chemical composition, morphology, and crystallography analyses (single particle mass spectrometry, scanning electron microscopy coupled with energy dispersive X-ray microanalysis, X-ray diffraction analysis) were performed with dry- and wet-generated particles. From these investigations, we conclude that anhydrous CaSO4 and CaO - which, if investigated in pure form, show the same qualitative immersion freezing behavior as observed for dry-generated coal fly ash particles - contribute to triggering heterogeneous ice nucleation at the particle-water interface. The observed deactivation in contact with water is related to changes in the particle surface properties which are potentially caused by hydration of CaSO4 and CaO. The contribution of coal fly ash to the ambient population of ice-nucleating particles therefore depends on whether and for how long particles are immersed in cloud droplets

Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy

The chance of freezing – a conceptional study to parameterize temperature-dependent freezing by including randomness of ice-nucleating particle concentrations

Ice-nucleating particle concentrations (INPCs) can spread over several orders of magnitude at any given temperature. However, this variability is rarely accounted for in heterogeneous ice-nucleation parameterizations. In this paper, we present an approach to incorporate the random variation in the INPC into the parameterization of immersion freezing and analyze this novel concept with various sensitivity tests. In the new scheme, the INPC is drawn from a relative frequency distribution of cumulative INPCs. At each temperature, this distribution describing the INPCs is expressed as a lognormal frequency distribution. The new parameterization scheme does not require aerosol information from the driving model to represent the heterogeneity of INPCs. The scheme's performance is tested in a large-eddy simulation of a relatively warm Arctic mixed-phase stratocumulus. We find that it leads to reasonable ice masses in the cloud, especially when compared to immersion freezing schemes that yield one fixed INPC per temperature and lead to almost no ice production in the simulated cloud. The scheme is sensitive to the median of the frequency distribution and highly sensitive to the standard deviation of the distribution, as well as to the frequency of drawing a new INPC and the resolution of the model. Generally, a higher probability of drawing large INPCs leads to substantially more ice in the simulated cloud. We expose inherent challenges to introducing such a parameterization and explore possible solutions and potential developments.</p

Oseltamivir-Resistant Influenza Viruses A (H1N1), Norway, 2007–08

Resistance was not associated with oseltamivir use or more severe disease