In-Situ (United States)

In this work, the effect of different atomic layer deposition (ALD) settings on the interface formation between ALD-grown (Zn1-xSnx)Oy (ZTO) buffers with varying [Sn]/([Sn]+[Zn]) composition and wide-band gap silver-alloyed CuGaSe2 (ACGSe) absorbers is investigated using X-ray fluorescence, transmission electron microscopy, and synchrotron-based soft and hard X-ray photoelectron spectroscopy. For buffer layers prepared in an industry-scale ALD reactor, we discover the formation of an interlayer best described by a mixture of ZnO with a minor (<10%) amount of Ga2O3, which is not present in similar layer stacks prepared in a lab-scale R&D-type ALD reactor. In addition, we show that ZTO/ACGSe-based solar cells containing such an interlayer have significantly lower fill factors compared to their counterparts without this interlayer, suggesting the presence of an electron transport barrier at the front contact.

<strong class="journal-contentHeaderColor">Abstract.</strong> From autumn 2021 through summer 2023, scientists from the National Oceanic and Atmospheric Administration (NOAA) and partners conducted the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign in the East River Watershed of Colorado. One objective of SPLASH was to observe the transfer of energy between the atmosphere and the surface, which was done at several locations. Two remote sites were chosen that did not have access to power utilities. These were along the valley floor near the East River in the vicinity of the unincorporated town of Gothic, Colorado. Energy balance measurements were made at these locations using autonomous, single-level flux towers referred to as Atmospheric Surface Flux Stations (ASFS). The ASFS were deployed on 28 September 2021 at the &ldquo;Kettle Ponds Annex&rdquo; site and on 12 October 2021 at the &ldquo;Avery Picnic&rdquo; site and operated until 19 July and 21 June 2023, respectively. Measurements included basic meteorology; upward and downward longwave and shortwave radiative fluxes, and subsurface conductive flux, each at 1-minute resolution; 3-d winds from a sonic anemometer and H₂O/CO₂ from an open-path gas analyser, both at 20 Hz from which sensible, latent heat, and CO₂ fluxes were derived; and profiles of soil properties in the upper 0.5 m (both sites) and temperature profiles through the snow (at Avery Picnic), each reported between 10 min and 6 hours. For most measurements, uptime was 96 % (Kettle Ponds) and 89 % (Avery Picnic), and collectively 1,184 days of data were obtained between the stations. The purpose of this manuscript is to document the ASFS deployment at SPLASH, the data acquisition and post-processing of measurements, and to serve as a guide for interested users of the data sets, which are archived under the Creative Commons 4.0 Public Domain licensing at Zenodo.

Abstract. The main goal of the TRacking Aerosol Convection interactions ExpeRiment (TRACER) project was to further understand the role that regional circulations and aerosol loading play in the convective cloud life cycle across the greater Houston, Texas area. To accomplish this goal, the United States Department of Energy and research partners collaborated to deploy atmospheric observing systems across the region. Cloud and precipitation radars, radiosondes, and air quality sensors captured atmospheric and cloud characteristics. A dense lower atmospheric dataset was developed using ground-based remote sensors, a tethersonde, and uncrewed aerial systems (UAS). TRACER-UAS is a subproject that deployed two UAS platforms to gather high-resolution observations in the lower atmosphere between 1 June and 30 September 2022. The University of Oklahoma CopterSonde and the University of Colorado Boulder RAAVEN (Robust Autonomous Aerial Vehicle – Endurant Nimble) were flown at two coastal locations between the Gulf of Mexico and Houston. The University of Colorado RAAVEN gathered measurements of atmospheric thermodynamic state, winds and turbulence, and aerosol size distribution. Meanwhile, the University of Oklahoma CopterSonde system operated on a regular basis to resolve the vertical structure of the thermodynamic and kinematic state. Together, a complementary dataset of over 200 flight hours across 61 days was generated, and data from each platform proved to be in strong agreement. In this paper, the platforms and respective data collection and processing are described. The dataset described herein provides information on boundary layer evolution, the sea breeze circulation, conditions prior to and nearby deep convection, and the vertical structure and evolution of aerosols.

Abstract. Atmospheric measurements taken over the span of an entire year between October 2019 and September 2020 during the icebreaker-based Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provide insight into processes acting in the Arctic atmosphere. Through the merging of disparate, yet complementary in situ observations, we can derive information about these thermodynamic and kinematic processes with great detail. This paper describes methods used to create a lower atmospheric properties dataset containing information on several key features relating to the central Arctic atmospheric boundary layer, including properties of temperature inversions, low-level jets, near-surface meteorological conditions, cloud cover, and the surface radiation budget. The lower atmospheric properties dataset was developed using observations from radiosondes launched at least four times per day, a 10 m meteorological tower and radiation station deployed on the sea ice near the Research Vessel Polarstern, and a ceilometer located on the deck of the Polarstern. This lower atmospheric properties dataset, which can be found at *insert DOI when published*, contains metrics which fall into the overarching categories of temperature, wind, stability, clouds, and radiation at the time of each radiosonde launch. The purpose of the lower atmospheric properties dataset is to provide a consistent description of general atmospheric boundary layer conditions throughout the MOSAiC year which can aid in research applications with the overall goal of gaining a greater understanding of the atmospheric processes governing the central Arctic and how they may contribute to future climate change.

As part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), the HELiX uncrewed aircraft system (UAS) was deployed over the sea ice in the central Arctic Ocean during summer 2020. Albedo measurements were obtained with stabilized pyranometers, and melt pond fraction was calculated from orthomosaic imagery from a surface-imaging multispectral camera. This study analyzed HELiX flight data to provide insights on the temporal and spatial evolution of albedo and melt pond fraction of the MOSAiC floe during the melt season as it drifted south through Fram Strait. The surface albedo distributions showed peak values changing from high albedo (0.55–0.6) to lower values (0.3) as the season advanced. Inspired by methods developed for satellite data, an algorithm was established to retrieve melt pond fraction from the orthomosaic images. We demonstrate that the near-surface observations of melt pond fraction were highly dependent on sample area, offering insight into the influence of subgrid scale features and spatial heterogeneity in satellite observations. Vertical observations conducted with the HELiX were used to quantify the influence of melt pond scales on observed surface albedo as a function of sensor footprint. These scaling results were used to link surface-based measurements collected during MOSAiC to broader-scale satellite data to investigate the influence of surface features on observed albedo. Albedo values blend underlying features within the sensor footprint, as determined by the melt pond size and concentration. This study framed the downscaling (upscaling) problem related to the airborne (surface) observations of surface albedo across a variety of spatial scales.

Determination of trace gas emissions from sources is critical for understanding and regulating air quality and climate change. Here, we demonstrate a method for rapid quantification of the emission rate of multiple gases from simple and complex sources using a mass-balance approach with a spatially scannable open-path sensor -in this case, an open-path dual-comb spectrometer. The open-path spectrometer measures the total column density of gases between the spectrometer and a retroreflector mounted on an unmanned aerial vehicle (UAV). By measuring slant columns at multiple UAV altitudes downwind of a source (or sink), the total emission rate can be rapidly determined without the need for an atmospheric dispersion model. Here, we demonstrate this technique using controlled releases of CH4 and C2H2. We show an emission rate determination to within 50% of the known flux with a single 10-minute flight and within 10% of the known flux after 10 flights. Furthermore, we estimate a detection limit for CH4 emissions to be 0.03 g CH4/s. This detection limit is approximately the same as the emissions from 25 head of beef cattle and is less than the average emissions from a small oil field pneumatic controller. Other gases including CO2, NH3, HDO, ethane, formaldehyde (HCHO), CO, and N2O can be measured by simply changing the dual-comb spectrometer. Measurements of the emission rate of a gas or gases from point and area sources are important in a range of monitoring applications. Several examples include measurement of emissions of CH4 and volatile organic compounds (VOCs) from oil and gas facilities (well pads, compressor stations, processing plants, etc.), from landfills and from composting facilities, CH4 and N2O (as well as VOCs) from waste-water treatment plants, CH4, NH3, and N2O from agricultural sites, and VOCs from industrial facilities. In all these examples, there are several important challenges for a measurement system. First, it is desirable to be able to measure emissions of multiple gases simultaneously. Second, the measurement system should be able to handle complex sources such as distributed sources or collocated sources. Finally, it is often desirable to be able to rapidly survey different sources to determine if emissions are present and then to quantify the emissions.

Mass spectrometry imaging (MSI) has been shown to be a valuable tool through nearly every stage of the preclinical drug research and development (R&amp;D) pipeline, and even to the early phase of clinical pharmaceutical evaluation. MSI can specifically resolve distributions of a parent drug and its metabolic products across dosed specimens without loss of spatial information, thus facilitating the direct observation of a drug’s pharmacokinetic processes, such as absorption, distribution, metabolism, and excretion. MSI can simultaneously visualize hundreds of phenotype molecules, including proteins, glycans, metabolites, and lipids, which have unique distribution patterns and biofunctions across different physiologic regions. This featured specificity in the chemical and physical spaces empowers MSI as an ideal analytical technique in exploring a drug’s pharmacodynamic properties, including in vitro/in vivo efficacy, safety, potential toxicity, and possible molecular mechanism. The application of MSI in pharmaceutical research has also been expanded from the conventional dosed tissue analysis to the front end of the preclinical drug R&amp;D pipeline, such as investigating the structure-activity relationship, high-throughput in vitro screening, and ex vivo studies on single cells, organoids, or tumor spheroids. This review summarizes MSI application in pharmaceutical research accompanied by its technical and methodologic advances serving this central demand.

Abstract. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 (DH2) fixed wing uncrewed aircraft system (UAS). Of particular interest is the atmospheric boundary layer (ABL) height, as ABL structure can be closely coupled to cloud properties, surface fluxes, and the atmospheric radiation budget. The high temporal resolution of the UAS observations allows us to subjectively identify ABL height for 65 out of the total 89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potential temperature, humidity, and bulk Richardson number. Comparing this subjective ABL height with the ABL heights identified by various previously published objective methods allows us to determine which objective methods are most successful at accurately identifying ABL height in the central Arctic environment. The objective methods we use are the Liu-Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objective methods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust across different measurement platforms, the subjective and objective ABL height determination processes were repeated using the radiosonde profile closest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the most successful at identifying ABL height, while the Liu-Liang method is least successful.

<strong class="journal-contentHeaderColor">Abstract.</strong> The mesoscale meteorology of lake breezes along Lake Michigan impacts local observations of high-ozone events. Previous manned aircraft and UAS observations have demonstrated non-uniform ozone concentrations within and above the marine layer over water and within shoreline environments. During the 2021 Wisconsin's Dynamic Influence of Shoreline Circulations on Ozone (WiscoDISCO-21) campaign, two UAS platforms, a fixed-wing (University of Colorado RAAVEN) and a multirotor (Purdue University DJI M210), were used simultaneously to capture lake breeze during forecasted high-ozone events at Chiwaukee Prairie State Natural Area in southeastern Wisconsin from 21–26 May 2021​​​​​​​. The RAAVEN platform (data DOI: <a href="https://doi.org/10.5281/zenodo.5142491">https://doi.org/10.5281/zenodo.5142491</a>, de Boer et al., 2021) measured temperature, humidity, and 3-D winds during 2 h flights following two separate flight patterns up to three times per day at altitudes reaching 500 m above ground level (a.g.l.). The M210 platform (data DOI: <a href="https://doi.org/10.5281/zenodo.5160346">https://doi.org/10.5281/zenodo.5160346</a>, Cleary et al., 2021a) measured vertical profiles of temperature, humidity, and ozone during 15 min flights up to six times per day at altitudes reaching 120 ma.g.l. near a Wisconsin DNR ground monitoring station (AIRS ID: 55-059-0019). This campaign was conducted in conjunction with the Enhanced Ozone Monitoring plan from the Wisconsin DNR that included Doppler lidar wind profiler observations at the site (data DOI: <a href="https://doi.org/10.5281/zenodo.5213039">https://doi.org/10.5281/zenodo.5213039</a>, Cleary et al., 2021b).