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Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx (NOx = NO + NO2) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s−1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s−1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory. Weekly variations in NO2 emission are highly related to anthropogenic activities, such as the transport sector. The NO2 emissions were reduced by 16 % at weekends in Riyadh, and high reductions were found near the city center and in areas along the highway. An average weekend reduction estimate of 28 % was found in Madrid. The regions with dominant sources are located in the east of Madrid, where residential areas and the Madrid-Barajas airport are located. Additionally, due to the COVID-19 lockdowns, the NO2 emissions decreased by 21 % in March–June 2020 in Riyadh compared with the same period in 2019. A much higher reduction (62 %) is estimated for Madrid, where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas, and they cover smaller areas on weekdays compared with weekends. The spatial patterns of NO2 emission strengths during lockdown are similar to those observed at weekends in both cities. Although our analysis is limited to two cities as test examples, the method has proven to provide reliable and consistent results. It is expected to be suitable for other trace gases and other target regions. However, it might become challenging in some areas with complicated emission sources and topography, and specific NO2 decay times in different regions and seasons should be taken into account. These impacting factors should be considered in the future model to further reduce the uncertainty budget.

Possibilities of applying automated content analysis in journalism studies include, for example, machine learning to identify topics in journalistic coverage or measuring news diffusion via automated approaches. But how have computational methods been applied thus far? And what are consequences of the “computational turn” in communication science, especially concerning interdisciplinarity? Based on a systematic literature review, this article summarizes the use of automated content analysis in journalism studies. Results illustrate an increasing use of the method by communication scientists, as yet another indicator of methodological interdisciplinarity in communication science. However, there is little evidence of an increase in theoretical interdisciplinarity: Studies relying on computational methods do not increasingly refer to theories from other disciplines. With respect to practical interdisciplinarity, for instance collaborations, our discipline is by no means becoming more interdisciplinary. Instead, we find a shift in favor of technical disciplines. At least up to now, the “computational turn” in communication science should thus not be equated with an “interdisciplinary turn.”

Dam construction affects freshwater ecosystems worldwide. While there is much focus on large impoundments, farm ponds are overlooked despite their near-ubiquity across human-altered landscapes. Within the Great Plains of North America, there are millions of farm ponds, yet little is known about the fish communities and factors structuring them. We propose a conceptual model where fish, amphibian, and crayfish abundances differ along a pond size and water permanency gradient and are further influenced by interactions among species. In the summer of 2021, we sampled 100 farm ponds across central Kansas, primarily on private land. Pond size and permanency explained community structure with smaller and less permanent ponds being dominated by amphibians and crayfish while larger ponds were dominated by stocked sportfish. Distribution modeling revealed a negative correlation between stocked fish and other community components indicating potential interactions. If we are to conserve headwater stream species, especially those that are threatened or endangered, strategies that integrate farm ponds seem necessary given their prevalence on the landscape.

Data donations represent a user-centered approach to data collection where researchers ask EU participants to exercise their right of access (GDPR) vis-à-vis intermediaries and to donate the digital trace data they receive to academic research. These data donations are often combined with survey data to gain deeper insights into the questions under investigation. Although initially promising, this process is complex for respondents and involves serious methodological, ethical, and legal challenges for researchers. A series of recently developed software solutions facilitate and streamline data donation studies. However, these stand-alone systems work separately from survey software. As a result, respondents typically face two platforms, one for the survey and one for the data donation. To facilitate their combination, we integrated two existing software solutions for online surveys (SoSci Survey) and data donations (OSD2F). We present our integrated solution and report on experiences with the approach from two exemplary studies.

Cu2ZnSnS4 (CZTS) thin films have attracted considerable attention as potential candidates for photovoltaic absorber materials.

Urban areas are home to many people on the globe, and centres of industry. Emissions from cities contribute to atmospheric concentrations of greenhouse gases like CO2 and CH4, which influence the Earth’s energy budget. The Ruisdael Observatory is a Dutch research infrastructure to investigate the atmosphere over the Netherlands by bringing together measurements and high resolution modelling. One part of it is a semi-mobile trailer to be flexibly deployed as measurement station for targeted field measurements. Mounted on the roof of this trailer are a Bruker EM27/SUN (EM27) for columnar trace gas measurements and a Cimel for columnar aerosol measurements. A targeted field campaign was conducted in August and September 2022 to study Rotterdam, one of the biggest city in the Netherlands and the biggest harbour in Europe. Three EM27s were set up around Rotterdam in an upwind-downwind configuration. To ensure the comparability of the data, the instruments measured in parallel for three days before and after the measurement period, which showed good agreement between the instruments. Four different configurations of instrument locations were used during the three week campaign to account for changes in wind direction and investigate specific targets as well as separate between the influence of the harbour area and the city itself. Enhancements in the CO2 column were around 1-3 ppm across the harbour and about 1 ppm across the city. CH4 columnar concentrations were not significantly enhanced across the city, but increased by several ppb across the harbour area. The CO columnar concentrations increased across the harbour by up to 10 ppb and 5 ppb across the city area.

A field experiment was carried out on the black cotton soil in the years 2018 and 2019 in the district of Sangli, Maharashtra, India to evaluate the sustainable agricultural practices for improving the growth and yield of the soybean (Glycine max L.) variety JS-335 along with the soil improvement. Twelve treatments were evaluated in a randomized block design with three replications. The results revealed that combined applications of chemical fertilizer (RDF-30:80:20:40) and organic manures (FYM and VCM) improved the growth attributes and seed yield as compared to control and other treatments along with a significant improvement in the soil health parameters. This agricultural practice emerged as a promising method for sustainable cultivation of soybean (C.V. JS-335) which improved the economic yield (kg.ha-1), agronomic efficiency (kg.ha-1), physiological efficiency (kg.ha-1), partial factor productivity (kg.ha-1), apparent recovery efficiency (kg.ha-1) and sustainable yield index (0.80) with maximum return having cost: benefit ratio (1:3.8). The results found statistically significant and correlated having a positive relationship between yield and sustainability parameters.

In this paper, we compare Orbiting Carbon Observatory 2 (OCO-2) measurements of column-averaged dry-air mole fractions (DMF) of CO2 (XCO2) and its urban–rural differences against ground-based remote sensing data measured by the Munich Urban Carbon Column network (MUCCnet). Since April 2020, OCO-2 has regularly conducted target observations in Munich, Germany. Its target-mode data provide high-resolution XCO2 within a 15 km × 20 km target field of view that is greatly suited for carbon emission studies from space in cities and agglomerated areas. OCO-2 detects urban XCO2 with a root mean square different (RMSD) of less than 1 ppm when compared to the MUCCnet reference site. OCO-2 target XCO2 is biased high against the ground-based measurements. The close proximity of MUCCnet's five fully automated remote sensing sites enables us to compare spaceborne and ground-based XCO2 in three urban areas of Munich separately (center, north, and west) by dividing the target field into three smaller comparison domains. Due to this more constrained collocation, we observe improved agreement between spaceborne and ground-based XCO2 in all three comparison domains. For the first time, XCO2 gradients within one OCO-2 target field of view are evaluated against ground-based measurements. We compare XCO2 gradients in the OCO-2 target observations to gradients captured by collocated MUCCnet sites. Generally, OCO-2 detects elevated XCO2 in the same regions as the ground-based monitoring network. More than 90 % of the observed spaceborne gradients have the same orientation as the XCO2 gradients measured by MUCCnet. During our study, urban–rural enhancements are found to be in the range of 0.1 to 1 ppm. The low urban–rural gradients of typically well below 1 ppm in Munich during our study allow us to test OCO-2's lower detection limits for intra-urban XCO2 gradients. Urban XCO2 gradients recorded by the OCO-2 instruments and MUCCnet are strongly correlated (R2=0.68) with each other and have an RMSD of 0.32 ppm. A case study, which includes a comparison of one OCO-2 target overpass to WRF-GHG modeled XCO2, reveals a similar distribution of enhanced CO2 column abundances in Munich. In this study, we address OCO-2's capability to detect small-scale spatial XCO2 differences within one target observation. Our results suggest OCO-2's potential to assess anthropogenic emissions from space.

Immune-related liver injury (liver-irAE) is a clinical problem with a potentially poor prognosis.We retrospectively collected clinical data from patients treated with immune checkpoint inhibitors between September 2014 and December 2021 at the Nagoya University Hospital. Using an unsupervised machine learning method, the Gaussian mixture model, to divide the cohort into clusters based on inflammatory markers, we investigated the cumulative incidence of liver-irAEs in these clusters.This study included a total of 702 patients. Among them, 492 (70.1%) patients were male, and the mean age was 66.6 years. During the mean follow-up period of 423 days, severe liver-irAEs (Common Terminology Criteria for Adverse Events grade ≥ 3) occurred in 43 patients. Patients were divided into five clusters (a, b, c, d, and e). The cumulative incidence of liver-irAE was higher in cluster c than in cluster a (hazard ratio [HR]: 13.59, 95% confidence interval [CI]: 1.70-108.76, P = 0.014), and overall survival was worse in clusters c and d than in cluster a (HR: 2.83, 95% CI: 1.77-4.50, P 0.001; HR: 2.87, 95% CI: 1.47-5.60, P = 0.002, respectively). Clusters c and d were characterized by high temperature, C-reactive protein, platelets, and low albumin. However, there were differences in the prevalence of neutrophil count, neutrophil-to-lymphocyte ratio, and liver metastases between both clusters.The combined assessment of multiple markers and body temperature may help stratify high-risk groups for developing liver-irAE.

Ammonia (NH3) is the most abundant alkaline compound in the atmosphere, with consequences for the environment, human health, and radiative forcing. In urban environments, it is known to play a key role in the formation of secondary aerosols through its reactions with nitric and sulfuric acids. However, there are only a few studies about NH3 in Mexico City. In this work, atmospheric NH3 was measured over Mexico City between 2012 and 2020 by means of ground-based solar absorption spectroscopy using Fourier transform infrared (FTIR) spectrometers at two sites (urban and remote). Total columns of NH3 were retrieved from the FTIR spectra and compared with data obtained from the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument. The diurnal variability of NH3 differs between the two FTIR stations and is strongly influenced by the urban sources. Most of the NH3 measured at the urban station is from local sources, while the NH3 observed at the remote site is most likely transported from the city and surrounding areas. The evolution of the boundary layer and the temperature play a significant role in the recorded seasonal and diurnal patterns of NH3. Although the vertical columns of NH3 are much larger at the urban station, the observed annual cycles are similar for both stations, with the largest values in the warm months, such as April and May. The IASI measurements underestimate the FTIR NH3 total columns by an average of 32.2±27.5 % but exhibit similar temporal variability. The NH3 spatial distribution from IASI shows the largest columns in the northeast part of the city. In general, NH3 total columns over Mexico City measured at the FTIR stations exhibited an average annual increase of 92±3.9×1013 molecules cm−2 yr−1 (urban, from 2012 to 2019) and 8.4±1.4×1013 molecules cm−2 yr−1 (remote, from 2012 to 2020), while IASI data within 20 km of the urban station exhibited an average annual increase of 38±7.6×1013 molecules cm−2 yr−1 from 2008 to 2018.

The use of robotics in hepatobiliary and pancreatic surgery has increased. With this increased collaboration, there has also been a push toward improving the transparency of conflicts of interest in terms of funding provided by robotics companies.Studies with ≥1 American author published between 2016 and 2020 discussing robotic hepatobiliary and pancreatic surgery were included in the analysis. The Centers for Medicare and Medicaid Services Open Payments Program was used to evaluate the accuracy of industry payment disclosures. Conflict of interest was defined as a lack of disclosure of ≥$100 funding from any robotics company in the United States. The primary outcome of this study was to determine the efficacy of the current standard conflict of interest reporting in surgery.A total of 355 studies (2,413 authors) were included. Of the studies that received robotics funding (n = 133), 20.3% did not disclose their conflicts of interest, whereas 79.7% had a conflict of interest disclosure. However, most of the disclosures (76.5%) were inaccurate.The findings of this study require an update in journal policies to ensure the accurate disclosure of conflicts of interest in robotic hepatobiliary and pancreatic surgery studies. Similarly, the investigators should ensure that their disclosures are accurate. Finally, surgeons must be more on top of their relationships with these companies and consider their vulnerability to bias.

To capture audiences’ attention on social media, news outlets may disseminate journalistic content in line with platform instead of mass media logics, indicating a platformization of news. Taking a cross-platform, multi-modal approach, we analyze how German outlets select and adapt existing stories for Facebook, Instagram, TikTok, and Twitter. We combine a computational and a manual content analysis of articles and social media posts (N = 4,412), including related images/videos (N = 6,850). Overall, evidence for outlets following platform logics on social media is limited: News outlets select and adapt news on a technical level, for instance by distributing more content on news-centered platforms like Twitter or by fostering on-platform engagement by excluding external links on Instagram. However, they do not systematically select or adapt news on a more communicative level, for instance by preferring specific topics for social media or by using more engaging language on platforms.

Using the reliable change index (RCI), we aimed to examine the effect of a multicomponent exercise program on the individual level.Overall, 270 adults (mean age, 78 years) completed a multicomponent physical exercise program (strength, aerobic, gait, and balance) for 40 min, 1-2 times per week, continued up to 1 year at a daycare center. Effectiveness was assessed using grip, ankle, knee, and hip strength; Timed UpGo (TUG); Berg Balance Scale (BBS); gait speed; and 6-min walking distance. These were measured at baseline and every 3 months thereafter. We calculated the RCI using the data between two-time points (baseline and at 3, 6, 9, or 12 months) in each participant and then calculated the mean RCI value across the participants. A paired t-test was also employed to evaluate the effect of the intervention as an average-based statistics.The highest mean RCI values were on ankle plantar-flexion strength, followed by gait speed, hip abduction strength, BBS, knee extensor strength, 6-min walk distance, grip strength, and finally TUG. Paired t-test also revealed significant improvement with moderate effect sizes for ankle plantar-flexion strength (0.504), gait speed (0.413), hip abduction strength (0.374), BBS (0.334), knee extensor strength (0.264), and 6-min walk distance (0.248). Significant but small effect size was seen on TUG (0.183).The RCI is a convenient method of comparing the effect between different assessments, especially at an individual level. This index can be applied to the use of personal feedback.

Rheumatoid arthritis (RA) is systemic autoimmune arthritis that causes joint inflammation and destruction. Accumulating evidence has shown that inhibitors of class I histone deacetylases (HDACs) (i.e., HDAC1, 2, 3, and 8) are potential therapeutic candidates as targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs). Nevertheless, the inhibition of class I HDACs has severe adverse effects because of their broad spectrum. We evaluated the therapeutic effect of a novel selective HDAC1 inhibitor TTA03-107 for collagen-induced arthritis (CIA) and collagen antibody-induced arthritis (CAIA) models in mice. We also examined the effect of TTA03-107 in bone marrow-derived macrophages (BMDMs) and T helper 17 (Th17) cells in vitro. Here, we delineate that TTA03-107 reduced the severity of autoimmune arthritis without obvious adverse effects in CIA and CAIA models. Moreover, TTA03-107 suppressed the production of inflammatory cytokines, such as interleukin (IL)-1β, tumor necrosis factor (TNF)-α, and IL-17A, in serum and joint tissue. In vitro treatment of BMDMs with TTA03-107 dampened the M1 differentiation and inflammatory cytokine production. TTA03-107 also suppressed the differentiation of Th17 cells. These results demonstrate that TTA03-107 can attenuate the development of arthritis in experimental RA models by inhibiting the differentiation and activation of macrophages and Th17 cells. Therefore, TTA03-107 is a potential tsDMARD candidate.

Background Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD), but currently available treatments do not improve kidney function or prevent the initiation of dialysis/kidney replacement therapy. A previous study demonstrated that bardoxolone methyl improves the estimated glomerular filtration rate (eGFR), but the study was prematurely terminated because of an imbalance in heart failure between treatment groups. The subsequent phase 2 TSUBAKI study demonstrated no incidence of heart failure and an improved eGFR and GFR as determined by inulin clearance in DKD patients. Methods This randomized, double-blind, placebo-controlled multicentre phase 3 study was designed to assess the efficacy and safety of bardoxolone methyl in DKD patients with an eGFR ≥15.0– Results The mean age of the 1013 patients is 65.9 years, 21.5% are female, the mean eGFR is 37.84 ml/min/1.73 m2 and the median UACR is 351.80 mg/g. Conclusions Appropriate patients are enrolled in this study. This study will investigate the long-term efficacy and safety of bardoxolone methyl in DKD patients covering a wider range of eGFR (≥15.0–

Science-related crowdfunding enables public engagement with science. However, we know little about citizens engaging with science this way: Who are the people engaging with and donating to science through crowdfunding – and how do they decide how much to give? This study analyses behavioural and survey data from the Swiss crowdfunding platform wemakeit ( N = 576). Results illustrate that a small, non-representative segment of the public engages with science through crowdfunding. Compared to the general public in Switzerland, these backers have an above-average education and income. Science-related crowdfunding mainly reaches citizens with an existing interest in science, personal ties to project initiators or the scientific community. The size of backers’ donations correlates with perceived personal appeals in campaigns or connections to initiators rather than projects’ scientific merit. While science-related crowdfunding thus opens up new avenues for public outreach by the scientific community, its potential for broader public engagement with science seems limited.

Total column H2O is measured by two remote sensing techniques at the Altzomoni Atmospheric Observatory (19°12′N, 98°65′W, 4000 m above sea level), a high-altitude, tropical background site in central Mexico. A ground-based solar absorption FTIR spectrometer that is part of the Network for Detection of Atmospheric Composition Change (NDACC) is used to retrieve water vapor in three spectral regions (6074–6471, 2925–2941, and 1110–1253 cm−1) and is compared to data obtained from a global positioning system (GPS) receiver that is part of the TLALOCNet GPS-meteorological network. Strong correlations are obtained between the coincident hourly means from the three FTIR products and small relative bias and correction factors could be determined for each when compared to the more consistent GPS data. Retrievals from the 2925–2941 cm−1 spectral region have the highest correlation with GPS [coefficient of determination (R2) = 0.998, standard deviation (STD) = 0.18 cm (78.39%), mean difference = 0.04 cm (8.33%)], although the other products are also highly correlated [R2 ≥ 0.99, STD ≤ 0.20 cm (

Nanoparticles are readily coated by proteins in biological systems. The protein layers on the nanoparticles, which are called the protein corona, influence the biological impacts of the nanoparticles, including internalization into cells and cytotoxicity. This study expands the scope of the nanoparticle's protein corona for exogenous artificial nanoparticles to that for exogenous proteinaceous nanoparticles. Specifically, this study addresses the formation of protein coronas on nanoscale human antibody aggregates with a radius of approximately 20-40 nm, where the antibody aggregates were induced by a pH shift from low to neutral pH. The size of the human immunoglobulin G (hIgG) aggregates grew to approximately 25 times the original size in the presence of human serum albumin (HSA). This size evolution was ascribed to the association of the hIgG aggregates, which was triggered by the formation of the hIgG aggregate's protein corona

For COVID-19 survivors, defeating the virus is just the beginning of a long road to recovery. The inducibility and catastrophic effects of the virus are distributed across multiple organs. The induction of cytokine storms in COVID-19 patients is due to the interaction of the SARS-CoV-2 virus and the host receptor, leading to various immunopathological consequences that may eventually lead to death. So far, COVID-19 has affected tons of people across the world, but there is still no effective treatment. Patients facing complications of COVID-19 after recovery have shown extensive clinical symptoms similar to that of patients recovering from previously circulating coronaviruses. Previous knowledge and literature have opened up ways to treat this disease and manage post-COVID-19 complications, which pose a severe challenge to the health system globally and may exacerbate the fragmentation of diseases. The use of steroids as a treatment has resulted in various health problems and side-effects in COVID-19 patients. This review discusses various post-COVID-19 complications observed and adjunctive therapies used along with common COVID-19 treatment and spotlights their side effects and consequences. This review provides the latest literature on COVID-19, which emphasizes the subsequent complications in various organs, side effects of drugs, and alternative regimens used to treat COVID-19.

In global geodesy co-location of geodetic space techniques are required for mutual control of the measurements. The ground-based active transmitters of the DORIS system are in conflict to VLBI-observations. The VLBI systems are designed to receive extremely faint cosmic signals down to -110 dBm , whereas the DORIS beacon emits signals at a frequency of 2,036 MHz with 40 dBm output power . There is a potential for coupling between DORIS emissions and the VLBI receiving chain generating spurious signals. The selection of possible sites for DORIS next to a VLBI radio telescope have been studied with pycraf. The study results coincide well with real measurements at the site of Wettzell. DORIS can´t be installed in the line of sight with a radio telescope., The complete study is available as living document at https://www.craf.eu/wp-content/uploads/2023/05/DORIS_VGOS_compatibility_study.pdf

Carbapenem-resistant Citrobacter freundii CF20-4P-1 and Escherichia coli EC20-4B-2 were isolated from edible Mastacembelidae in Vietnam. We present the draft genome sequences, and the complete plasmid genome sequencing was also performed by hybrid assembly sequencing of Oxford Nanopore and Illumina. The 137-kbp plasmid encoding the assembled bla NDM-1 was detected in both strains.

In this study, we conduct a multi-disciplinary study, including geophysics, geochemistry, and geology, in an attempt to reconstruct geothermal geological model(s) at the shallow 3 km, for a project of potential geothermal power generation at the Hongchailin site in the Ilan plain of northeastern Taiwan. Our geophysical techniques include seismic imaging from natural earthquakes as well as ambient noise. Three seismic arrays deployed at different time periods in the past decade were used. We also incorporate geophysical imaging results from previous studies, in particular a series of seismic reflection profiles. For the magnetotelluric (MT) technique, two major surveys have been conducted, including 2015-2018 AMT by National Central University and 2021-2022 MT by GERD and Academia Sinica. Three test holes were drilled around the Hongchailin site in 2016-2019. Logging and on-site measurements were conducted at increment depths, including stratigraphy and rock types, P/T measurements, fractures analyses, geochemical analyses (e.g., hydrogen/oxygen/helium isotope, fluid inclusion, etc.), and so on. Based on regional geology and structures, and incorporating geophysical subsurface imaging, we reconstruct geothermal geological models in line with detailed geological cross sections at the shallow 3 km level. We interpret that there exits a shallow geothermal reservoir within the massive quartz sandstone layers (Szeleng sandstone) at 1-2 km depth with the downhole temperature of 80-100 C. Geologically, the reservoir is located at the regional Songlo syncline and its south limb; and geophysically, it corresponds to a relatively low resistivity area. Isotope results show that the cool meteoric water came from nearby higher altitude mountain area, then flew through the Szeleng sandstone, which plunges 1-2 km depth below the Ilan plain. Hot fluid is interpreted to be derived from deeper heat source and to be upflowed along a N-S trending vertical faults system near the Hongchailin area. In addition, two E-W trending major faults, identified by the seismic reflection profiles, seem to be acted as hydrothermal fluid barriers to confine the hot fluid within the reservoir area.

The reduction of carbon emissions is required to limit global warming. Thus, measurement-based methods to monitor the progress in reducing emissions are essential. A significant part of the global emissions is produced in urban areas where also industry is located. Here, we investigate the urban area of Thessaloniki to better understand the distribution of local greenhouse gas sources during October 2021 and the summer of 2022.We present results of a measurement campaign using a pair of Fourier-Transform Infrared (FTIR) Spectrometers of the type EM27/SUN developed by Bruker and KIT.The measurement campaign took part in the framework of the Collaborative Carbon Column Observing Network (COCCON). During the campaign the spectrometers were used in an up- downwind setup. One spectrometer was located in a central position of the city while the second instrument was transported to various locations at the boundaries of the city, selected according to the prevailing wind direction. Additionally, measurements to characterize the advected background variability were performed. Here, the spectrometers were arranged orthogonal to the prevailing wind direction to estimate the variability of the background concentrations of carbon dioxide and methane.In total, 30 days of measurements were collected, giving a comprehensive dataset to study the emissions of the city area. The measurements are interpreted using a box model to estimate the averaged emission area fluxes. We present results for both, carbon dioxide and methane, and discuss the temporal and spatial variability we encountered.In a next step, we aim to confront these measurements with simulation results with idealized tracer emission patterns using the ICON-ART modeling framework, a numerical weather forecast model developed and used operationally by the German Weather Service (DWD). The results from the box model introduced above will be used as a starting point to combine measurements and simulations. First simulations produced for this purpose will be shown.

Precise knowledge of sources and sinks in the carbon cycle is desired to understand its sensitivity to climate change and to account and verify man-made emissions. In this context, extended sources like urban areas play an important role. While in-situ measurements of carbon dioxide (CO2) and methane (CH4) are highly accurate but localized, satellites measure column-integrated concentrations over an extended footprint. The CLARS-FTS [1, 2] stationed at the Mt. Wilson observatory looking downward into the Los Angeles basin has pioneered an innovative measurement technique that fills the sensitivity gap between in-situ and satellite measurements. The technique enables mapping the urban greenhouse gas concentration fields by collecting spectra of ground scattered sunlight and scanning through the region. We develop a similar but portable instrument using a CLARS-FTS-like measurement geometry. It is based on the EM27/SUN FTS with a modified pointing system, increased throughput and a more sensitive detector than the standard type. The compact setup enables campaign-based observations in various source regions of interest, utilizing the increased sensitivity to boundary layer concentration by the horizontal light path component. Here, we present the portable instrument setup and its performance. Throughout April 2022, we observed the Los Angeles basin with both the portable setup and the CLARS-FTS simultaneously. The retrieval algorithm is based on the RemoTeC software, previously employed for solar backscatter satellite measurements. From this, we evaluate the XCO2 and XCH4 precision of our setup under field conditions, and compare our instrument to the concurrent CLARS-FTS measurements. References:[1] Fu, D. et al., 2014: Near-infrared remote sensing of Los Angeles trace gas distributions from a mountaintop site, Atmos. Meas. Tech., 7, 713–729, https://doi.org/10.5194/amt-7-713-2014[2] Wong, K. W. et al., 2015: Mapping CH4 : CO2 ratios in Los Angeles with CLARS-FTS from Mount Wilson, California, Atmos. Chem. Phys., 15, 241–252, https://doi.org/10.5194/acp-15-241-2015

Greenhouse gases (GHGs) play a crucial role regarding global warming. Therefore, precise and accurate observations of anthropogenic GHGs, especially carbon dioxide and methane, are of utmost importance for the estimation of their emission strengths, flux changes and long-term monitoring. Satellite observations are well suited for this task as they provide global coverage. However, like all measurements these need to be validated.The COllaborative Carbon Column Observing Network (COCCON) performs ground-based observations to retrieve column-averaged dry air mole fractions of GHGs (XGAS) with reference precision. The instrument used by the network is the EM27/SUN, a solar-viewing Fourier Transform infrared (FTIR) spectrometer. COCCON data are of high accuracy as COCCON uses species dependent airmass-independent and airmass-dependent adjustments for tying the XGAS products to TCCCON (Total Carbon Column Observing Network) and thereby to the World Meteorological Organization (WMO) reference scale. Moreover, instrument specific characteristics are measured for each COCCON spectrometer, and taken into account in the data analysis.Here we first introduce the COCCON network in general and summarize its capabilities for various challenges including satellite and model validation, long-term observation of GHGs, and local and regional GHG source emission strength estimations. By example of the COCCON Tsukuba station we highlight in detail its usefulness for the above-mentioned applications.

Quantifying sources and sinks, as well as chemical activity of trace gases in the lower troposphere, requires accurate measurements of the concentrations of the species of interest. While there exist in-situ measurement techniques, which are highly accurate, point-like measurements are only sufficiently representative in the spatial domain for a small area. This holds true in particular in high-gradient environments, e.g., urban settings. Hence, measuring those concentrations averaged on the length scale of a few kilometers is desirable. Furthermore, quantifying emissions requires combining concentration measurements with regional transport models, which cover a comparable spatial resolution.We present a long open-path setup that measures average concentrations on the kilometer-scale in the urban boundary layer. Our setup, which is operational since March 2022, is based on a Bruker IFS 125 HR Fourier transform spectrometer, a commercially available spectrometer, which offers high resolution and throughput. The instrument choice provides flexible and explorative experimental setups such as variable and high spectral resolution and the extension of spectral coverage from the shortwave-infrared to the near ultra-violet spectral range. Here, we present the results on CO2 and CH4 from our 2022 measurement campaign as well as analysis of the diurnal variability in comparison to the prediction of local and regional transport models.

The E-TEST project (Einstein Telescope EMR Site & Technology) investigates the feasibility of constructing a large Laser Interferometer (Einstein Telescope) in the Euregio Rhine Meuse. The aim of this instrument is to detect gravitational waves. To reach a sufficient noise attenuation the telescope will be built deep underground (more than 200 meters depth). The infrastructure consists of multiple tunnels and caverns spanning several kilometers. As with any large-scale infrastructure, the geological model, especially the existence and orientation of faults, is of large importance for hydrogeophysical and geotechnical characterization. At such depths, few near-surface geophysical methods are able to provide information with enough details. The application of large 3D Deep ERT surveys helps understanding the local geological settings and to identify important geological features but suffers from ambiguous interpretation. However, such imaging requires measuring dipoles independent of the injection system (such as the Fullwaver System by IRIS Instruments) in contrast to conventional ERT Systems, and due to the large covered area, coarsely spaced. This results in a drastic decrease in resolution when compared to classical ERT measurements.Here, we present a sensitivity analysis on a dataset based on the geologic setting in Plombières, Belgium to identify the impact of geology and survey setup on Deep 3D ERT surveys. The utilized geologic model was created with the Open-Source 3D structural geomodelling software GemPy and used as an input for forward modelling using the Open-Source modelling and inversion library pyGIMLi.

The time-domain (TD) induced polarization (IP) method is used as an extension to classical DC resistivity measurements to capture information on the ability of the subsurface to develop electrical polarization, which is closely coupled to petrophysical parameters of relevance in hydrogeophysical characterization. In a TD IP measurement, the transient voltage decay between two electrodes is measured after the termination of an injected current between two other electrodes. TD IP measurements are typically analyzed in terms of chargeabilities, while in the frequency domain (FD) polarization responses are measured as complex-valued impedances. The latter can be inverted into a subsurface model of complex electrical resistivity by means of existing tomographic inversion algorithms. In order to apply these FD inversion algorithms to TD IP measurements, the necessity of TD to FD data conversion arises. A suitable conversion approach must transform the measured decay curve into a FD impedance and, preferably, also propagate the corresponding measurement uncertainty from TD into FD. Here we present such an approach based on a Debye decomposition (DD) of the decay curve into a relaxation-time distribution (RTD). Since equivalent formulations of the DD exist in TD and FD, it is possible to compute the FD response from the RTD inverted from the TD response. The corresponding FD data error can be obtained by applying error propagation through all these steps, assuming that the errors on the underlying parameters are normally distributed. To accomplish the DD we implemented a non-linear Gauss-Newton inversion scheme which automatically tunes the regularization strength to achieve a stable FD estimate and FD uncertainty. We test the performance of the inversion scheme in a synthetic study and demonstrate its application to field data on a tomographic TD IP data set measured on the Maletoyvaemskoie field of altered rocks (Kamchatka, Russia), which features epithermal gold deposits of high sulfidation type. The converted tomographic TD IP data set is inverted into subsurface models of complex electrical resistivity at frequencies of 1 Hz and 20 Hz. The proposed conversion approach yields accurate impedance data for relaxation processes which are resolved by the TD measurements. The error propagation scheme provides a reasonable FD uncertainty estimate, as revealed by a Monte-Carlo analysis of the underlying parameter distributions. Propagated FD errors are in agreement with previously established FD error models. The presented methodology to convert TD to FD IP data allows to invert and analyze field data collected with widely used TD instruments in the frequency domain, where the diagnostic potential of electrical impedance spectroscopy can be fully exploited for an improved interpretation.

Campylobacter spp. is a gram-negative bacillus that causes infectious enteritis and consists of several species, including Campylobacter jejuni, Campylobacter coli, and Campylobacter fetus. Although C. jejuni and C. coli cause infectious enteritis primarily in immunocompetent hosts, C. fetus causes extraintestinal infections such as septicemia, meningitis, and perinatal infections in immunocompromised hosts, as well as myopericarditis in rare cases. Only a few cases of infectious myo(peri)carditis associated with C. coli in immunocompetent hosts have been reported. These studies concentrated on antecedent C. coli enterocolitis and never demonstrated a positive culture in the pericardial fluid.A 72-year-old Japanese man presented with a 2-week fever, cough, and vomiting lasting. He was on hemodialysis for polycystic kidney disease, as well as medication for diabetes and hypertension. A chest computed tomography (CT) scan and a transthoracic echocardiogram revealed bilateral pleural fluid and large pericardial fluid at the time of admission. C. coli was identified from blood culture samples and blood-tinged pericardial fluid. He was successfully treated with antibacterial chemotherapy as well as pericardial fluid drainage and was discharged from the hospital with no complications.In this case, the presence of C. coli in the pericardial fluid confirmed the diagnosis of C. coli pericarditis. C. coli may cause septic pericarditis in immunocompromised hosts, despite typically causing only enteritis.