The clustering of merging star-forming haloes: dust emission as high frequency arcminute CMB foreground

Future observations of CMB anisotropies will be able to probe high multipole regions of the angular power spectrum, corresponding to a resolution of a few arcminutes. Dust emission from merging haloes is one of the foregrounds that will affect such very small scales. We estimate the contribution to CMB angular fluctuations from objects that are bright in the sub-millimeter band due to intense star formation bursts following merging episodes. We base our approach on the Lacey-Cole merger model and on the Kennicutt relation which connects the star formation rate in galaxies with their infrared luminosity. We set the free parameters of the model in order to not exceed the SCUBA source counts, the Madau plot of star formation rate in the universe and COBE/FIRAS data on the intensity of the sub-millimeter cosmic background radiation. We show that the angular power spectrum arising from the distribution of such star-forming haloes will be one of the most significant foregrounds in the high frequency channels of future CMB experiments, such as PLANCK, ACT and SPT. The correlation term, due to the clustering of multiple haloes at redshift z~2-6, is dominant in the broad range of angular scales 200<l<3000. Poisson fluctuations due to bright sub-millimeter sources are more important at higher l, but since they are generated from the bright sources, such contribution could be strongly reduced if bright sources are excised from the sky maps. The contribution of the correlation term to the angular power spectrum depends strongly on the redshift evolution of the escape fraction of UV photons and the resulting temperature of the dust. The measurement of this signal will therefore give important information about galaxies in the early stage of their evolution.Comment: 18 pages, 16 figures. Accepted by Astronomy & Astrophysic

The global impact of the transport sectors on the atmospheric aerosol and the resulting climate effects under the Shared Socioeconomic Pathways (SSPs)

A global aerosol–climate model is applied to quantify the impact of the transport sectors (land transport, shipping, and aviation) on aerosol and climate. Global simulations are performed for the present day (2015), based on the emission inventory of the Climate Model Intercomparison Project Phase 6 (CMIP6), and for near-term (2030) and mid-term (2050) future projections, under the Shared Socioeconomic Pathways (SSPs). The results for the present day show that land transport emissions have a large impact on near-surface concentrations of black carbon and aerosol nitrate over the most populated areas of the globe, but with contrasting patterns in terms of relative contributions between developed and developing countries. In spite of the recently introduced regulations to limit the fuel sulfur content in the shipping sector, shipping emissions are still responsible for a considerable impact on aerosol sulfate near-surface concentrations, about 0.5 to 1 µg m−3 in the most travelled regions, with significant effects on continental air pollution and in the northern polar regions as well. Aviation impacts on aerosol mass are found to be quite small, of the order of a few nanograms per cubic metre, while this sector considerably affects particle number concentrations, contributing up to 20 %–30 % of the upper-tropospheric particle number concentration at the northern mid-latitudes. The transport-induced impacts on aerosol mass and number concentrations result in a present-day radiative forcing of −164, −145, and −64 mW m−2 for land transport, shipping, and aviation, respectively, with a dominating contribution by aerosol–cloud interactions. These forcings represent a marked offset to the CO2 warming from the transport sectors and are therefore very relevant for climate policy. The projections under the SSPs show that the impact of the transport sectors on aerosol and climate are generally consistent with the narratives underlying these scenarios: the lowest impacts of transport on both aerosol and climate are simulated under SSP1, especially for the land transport sector, while SSP3 is generally characterized by the largest effects. Notable exceptions to this picture, however, exist, as the emissions of other anthropogenic sectors also contribute to the overall aerosol concentrations and thus modulate the relevance of the transport sectors in the different scenarios, not always consistently with their underlying storyline. On a qualitative level, the results for the present day mostly confirm the findings of our previous assessment for the year 2000, which used a predecessor version of the same model and the CMIP5 emission data. Some important quantitative differences are found, which can mostly be ascribed to the improved representation of aerosol background concentrations in the present study.</p

A new class of variable capacitance generators based on the dielectric fluid transducer

This paper introduces the novel concept of dielectric fluid transducer (DFT), which is an electrostatic variable capacitance transducer made by compliant electrodes, solid dielectrics and a dielectric fluid with variable volume and/or shape. The DFT can be employed in actuator mode and generator mode. In this work, DFTs are studied as electromechanical generators able to convert oscillating mechanical energy into direct current electricity. Beside illustrating the working principle of dielectric fluid generators (DFGs), we introduce different architectural implementations and provide considerations on limitations and best practices for their design. Additionally, the proposed concept is demonstrated in a preliminary experimental test campaign conducted on a first DFG prototype. During experimental tests a maximum energy per cycle of and maximum power of has been converted, with a conversion efficiency up to 30%. These figures correspond to converted energy densities of with respect to the displaced dielectric fluid and with respect to the mass of the solid dielectric. This promising performance can be largely improved through the optimization of device topology and dimensions, as well as by the adoption of more performing conductive and dielectric materials

Revealing dominant patterns of aerosol regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations

Aerosols play an important role in the Earth system, but their impact on cloud properties and the resulting radiative forcing of climate remains highly uncertain. The large temporal and spatial variability of a number of aerosol properties and the choice of different “preindustrial” reference years prevent a concise understanding of their impacts on clouds and radiation. In this study, we characterize the spatial patterns and long-term evolution of lower tropospheric aerosols (in terms of regimes) by clustering multiple instead of single aerosol properties from preindustrial times to the year 2050 under three different Shared Socioeconomic Pathway (SSP) scenarios. The clustering is based on a combination of statistic-based machine learning algorithms and output from emissions-driven global aerosol model simulations, which do not consider the effects of climate change. Our analysis suggests that in comparison with the present-day case, lower tropospheric aerosol regimes during preindustrial times are mostly represented by regimes of comparatively clean conditions, where marked differences between the years 1750 and 1850 emerge due to the growing influence of agriculture and other anthropogenic activities in 1850. Key aspects of the spatial distribution and extent of the aerosol regimes identified in year 2050 differ compared to preindustrial and present-day conditions, with significant variations resulting from the emission scenario investigated. In 2050, the low-emission SSP1-1.9 scenario is the only scenario where the spatial distribution and extent of the aerosol regimes very closely resemble preindustrial conditions, where the similarity is greater compared to 1850 than 1750. The aerosol regimes for 2050 under SSP3-7.0 closely resemble present-day conditions, but there are some notable regional differences: developed countries tend to shift towards cleaner conditions in future, while the opposite is the case for developing countries. The aerosol regimes for 2050 under SSP2-4.5 represent an intermediate stage between preindustrial times and present-day conditions. Further analysis indicates a north–south difference in the clean background regime during preindustrial times and close resemblance of preindustrial aerosol conditions in the marine regime to present-day conditions in the Southern Hemispheric ocean. Not considering the effects of climate change is expected to cause uncertainties in the size and extent of the identified aerosol regimes but not the general regime patterns. This is due to a dominating influence of emissions rather than climate change in most cases. The approach and findings of this study can be used for designing targeted measurements of different preindustrial-like conditions and for tailored air pollution mitigation measures in specific regions.</p

A global climatology of ice-nucleating particles under cirrus conditions derived from model simulations with MADE3 in EMAC

Ice-nucleating particles (INPs) have important influences on cirrus clouds and the climate system; however, their global atmospheric distribution in the cirrus regime is still very uncertain. We present a global climatology of INPs under cirrus conditions derived from model simulations, considering the mineral dust, soot, crystalline ammonium sulfate, and glassy organics INP types. The comparison of respective INP concentrations indicates the large importance of ammonium sulfate particles

Exploring the uncertainties in the aviation soot-cirrus effect

A global aerosol–climate model, including a twomoment cloud microphysical scheme and a parametrization for aerosol-induced ice formation in cirrus clouds, is applied in order to quantify the impact of aviation soot on natural cirrus clouds. Several sensitivity experiments are performed to assess the uncertainties in this effect related to (i) the assumptions on the ice nucleation abilities of aviation soot, (ii) the representation of vertical updrafts in the model, and (iii) the use of reanalysis data to relax the model dynamics (the socalled nudging technique)

Microstrip Resonators and Broadband Lines for X-band EPR Spectroscopy of Molecular Nanomagnets

We present a practical setup to perform continuous-wave X-band electron paramagnetic resonance spectroscopy by using planar microstrip lines and general purpose instrumentation. We fabricated Ag/alumina and Nb/sapphire microstrip resonators and transmission lines and compared their performance down to 2 K and under applied magnetic field. We used these devices to study single crystals of molecular Cr3 nanomagnets. By means of X-band planar resonators we measured angle-dependent spectra at fixed frequency, while broadband transmission lines were used to measure continuous wave spectra with varying frequency in the range 2–25 GHz. The spectra acquired at low temperatures allowed to extract the essential parameters of the low-lying energy levels of Cr3 and demonstrate that this method is particularly suitable to study small crystals of molecular nanomagnets

An aerosol classification scheme for global simulations using the K-means machine learning method

The K-means machine learning algorithm is applied to climatological data of seven aerosol properties from a global aerosol simulation using EMAC-MADE3. The aim is to partition the aerosol properties across the global atmosphere in specific aerosol regimes; this is done mainly for evaluation purposes. K-means is an unsupervised machine learning method with the advantage that an a priori definition of the aerosol classes is not required. Using K-means, we are able to quantitatively define global aerosol regimes, so-called aerosol clusters, and explain their internal properties and their location and extension. This analysis shows that aerosol regimes in the lower troposphere are strongly influenced by emissions. Key drivers of the clusters' internal properties and spatial distribution are, for instance, pollutants from biomass burning and biogenic sources, mineral dust, anthropogenic pollution, and corresponding mixtures. Several continental clusters propagate into oceanic regions as a result of long-range transport of air masses. The identified oceanic regimes show a higher degree of pollution in the Northern Hemisphere than over the southern oceans. With increasing altitude, the aerosol regimes propagate from emission-induced clusters in the lower troposphere to roughly zonally distributed regimes in the middle troposphere and in the tropopause region. Notably, three polluted clusters identified over Africa, India, and eastern China cover the whole atmospheric column from the lower troposphere to the tropopause region. The results of this analysis need to be interpreted taking the limitations and strengths of global aerosol models into consideration. On the one hand, global aerosol simulations cannot estimate small-scale and localized processes due to the coarse resolution. On the other hand, they capture the spatial pattern of aerosol properties on the global scale, implying that the clustering results could provide useful insights for aerosol research. To estimate the uncertainties inherent in the applied clustering method, two sensitivity tests have been conducted (i) to investigate how various data scaling procedures could affect the K-means classification and (ii) to compare K-means with another unsupervised classification algorithm (HAC, i.e. hierarchical agglomerative clustering). The results show that the standardization based on sample mean and standard deviation is the most appropriate standardization method for this study, as it keeps the underlying distribution of the raw data set and retains the information of outliers. The two clustering algorithms provide similar classification results, supporting the robustness of our conclusions. The classification procedures presented in this study have a markedly wide application potential for future model-based aerosol studies