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Increasing shares of microfibers are being detected in environmental samples and a closer look to identify the risk associated with them using ecologically relevant endpoints, especially at sensitive early life stages, is needed. To assess exposure hazards, we used rope samples representative of fiber types ubiquitous in coastal systems, where microfibers are often the most common debris type found in the water column. To compare responses to natural vs. synthetic microfibers, we used rinsed “natural” cotton, polyester, and polypropylene microfibers (80-150 µm length, 8-20 µm width) created from the rope. Larval and juvenile estuarine indicator species Inland Silverside (Menidia beryllina) and mysid shrimp (Americamysis bahia) , respectively, were exposed to these three microfiber types at three concentrations (3, 10, 30 particles/ml) along a 5-25 PSU salinity gradient to mimic estuarine conditions. Behavioral responses, growth, and ingestion were measured. The cotton microfibers were not detected in the digestive tracts of Silversides, however, both the polyester and polypropylene microfibers were detected in the Silversides’ stomach and gut lining. None of the fiber types were detected in mysid shrimps. Mysids exposed to cotton microfibers had fewer behavioral effects compared to Silversides, who responded more to cotton. Cotton exerted no effect on growth in Silversides but did cause reduced growth in the mysids at the two lower salinities. In contrast, polyester and polypropylene were identified to have a significant dose dependent effect on mysid and Silverside behavior as well as growth was affected in at least one of the three salinities at concentrations as low as 3 particles/ml. Cotton impacted both the organism’s behavior more at higher salinities, whereas polyester and polypropylene had more impacts at lower salinities. This raises concerns for microfiber impacts on estuarine ecosystems and the need for policies to limit microfiber production and outfall into the aquatic environment. 

We summarize the second radio synchrotron background workshop, which took place on 2022 June 15–17 in Barolo, Italy. This meeting was convened because available measurements of the diffuse radio zero level continue to suggest that it is several times higher than can be attributed to known Galactic and extragalactic sources and processes, rendering it the least well-understood electromagnetic background at present and a major outstanding question in astrophysics. The workshop agreed on the next priorities for investigations of this phenomenon, which include searching for evidence of the radio Sunyaev–Zel’dovich effect, carrying out cross-correlation analyses of radio emission with other tracers, and supporting the completion of the 310 MHz absolutely calibrated sky map project.

 

The C-Band All-Sky Survey (C-BASS) has observed the Galaxy at 4.76 GHz with an angular resolution of 0${_{.}^{\circ}}$73 full-width half-maximum, and detected Galactic synchrotron emission with high signal-to-noise ratio over the entire northern sky (δ > −15○). We present the results of a spatial correlation analysis of Galactic foregrounds at mid-to-high (b > 10○) Galactic latitudes using a preliminary version of the C-BASS intensity map. We jointly fit for synchrotron, dust, and free–free components between 20 and 1000 GHz and look for differences in the Galactic synchrotron spectrum, and the emissivity of anomalous microwave emission (AME) when using either the C-BASS map or the 408-MHz all-sky map to trace synchrotron emission. We find marginal evidence for a steepening (<Δβ> = −0.06 ± 0.02) of the Galactic synchrotron spectrum at high frequencies resulting in a mean spectral index of <β> = −3.10 ± 0.02 over 4.76–22.8 GHz. Further, we find that the synchrotron emission can be well modelled by a single power law up to a few tens of GHz. Due to this, we find that the AME emissivity is not sensitive to changing the synchrotron tracer from the 408-MHz map to the 4.76-GHz map. We interpret this as strong evidence for the origin of AME being spinning dust emission.

 

A description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015–2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared.