Ammonia and nitrous oxide emission factors for excreta deposited by livestock and land-applied manure

Manure application to land and deposition of urine and dung by grazing animals are major sources of ammonia (NH3) and nitrous oxide (N2O) emissions. Utilizing data on NH3 and N2O emissions following land-applied manures and excreta deposited during grazing, emission factors (EFs) disaggregated by climate zone were developed and effects of mitigation strategies evaluated. The NH3 data represents emissions from cattle and swine manures in temperate wet climates, while the N2O data includes cattle, sheep and swine manure emissions in temperate wet/dry and tropical wet/dry climates. The NH3 EFs for broadcast cattle solid manure and slurry were 0.03 and 0.24 kg NH3-N kg-1 total N (TN), respectively, while broadcast swine slurry was 0.29. Emissions from both cattle and swine slurry were reduced between 46 and 62% with low emissions application methods. Land application of cattle and swine manure in wet climates had EFs of 0.005 and 0.011 kg N2O-N kg-1 TN, respectively, while in dry climates the EF for cattle manure was 0.0031. The N2O EF for cattle urine and dung in wet climates was 0.0095 and 0.002 kg N2O-N kg-1 TN, respectively, which were three times greater than for dry climates. The N2O EFs for sheep urine and dung in wet climates were 0.0043 and 0.0005, respectively. The use of nitrification inhibitors reduced emissions in swine manure, cattle urine/dung and sheep urine by 45 to 63%. These enhanced EFs can improve national inventories; however, more data is needed across multiple livestock species and climates

DataMan: A global dataset of nitrous oxide and ammonia emission factors for excreta deposited by livestock and land-applied manure

Nitrous oxide (N2O), ammonia (NH3) and methane (CH4) emissions from the manure management chain of livestock production systems are important contributors to greenhouse gases (GHG) and NH3 emitted by human activities. Several studies have evaluated manure-related emissions and associated key variables at regional, national or continental scales. However, there have been few studies focusing on these emissions using a global dataset. An international project was created (DataMan) to develop a global database on GHG and NH3 emissions from the manure management chain (housing, storage and field), to identify key variables influencing emissions, and ultimately to refine EFs for future national GHG inventories and NH3 emission reporting. This paper describes the “field” database that focuses on N2O and NH3 EFs from land-applied manure and excreta deposited by grazing livestock. We collated relevant information (EFs, manure characteristics, soil properties and climatic conditions) from published peer-reviewed research, theses, conference papers and existing databases. The database, containing 5,632 observations compiled from 184 studies, was relatively evenly split between N2O and NH3 (56% and 44% of the EF values, respectively). The N2O data were derived from studies conducted in 21 countries on five continents, with New Zealand, the UK, Kenya and Brazil representing 86% of the data. The NH3 data originated from studies conducted in 17 countries on four continents, with the UK, Denmark, Canada and the Netherlands representing 79% of the data. Wet temperate climates represented 90% of the total database. The DataMan field database is available online at http:// dataman.azurewebsites.net

DEXi-Dairy: an ex post multicriteria tool to assess the sustainability of dairy production systems in various European regions

Growing awareness of global challenges and increasing pressures on the farming sector, including the urgent requirement to rapidly cut greenhouse gases (GHG) emissions, emphasize the need for sustainable production, which is particularly relevant for dairy production systems. Comparing dairy production systems across the three sustainability dimensions is a considerable challenge, notably due to the heterogeneity of production conditions in Europe. To overcome this, we developed an ex post multicriteria assessment tool that adopts a holistic approach across the three sustainability dimensions. This tool is based on the DEXi framework, which associates a hierarchical decision model with an expert perspective and follows a tree shaped structure; thus, we called it the DEXi-Dairy tool. For each dimension of sustainability, qualitative attributes were defined and organized in themes, sub-themes, and indicators. Their choice was guided by three objectives: (i) better describe main challenges faced by European dairy production systems, (ii) point out synergies and trade-offs across sustainability dimensions, and (iii) contribute to the identification of GHG mitigation strategies at the farm level. Qualitative scales for each theme, sub-theme, and indicator were defined together with weighting factors used to aggregate each level of the tree. Based on selected indicators, a list of farm data requirements was developed to populate the sustainability tree. The model was then tested on seven case study farms distributed across Europe. DEXi-Dairy presents a qualitative method that allows for the comparison of different inputs and the evaluation of the three sustainability dimensions in an integrated manner. By assessing synergies and trade-offs across sustainability dimensions, DEXi-Dairy is able to reflect the heterogeneity of dairy production systems. Results indicate that, while trade-offs occasionally exist among respective selected sub-themes, certain farming systems tend to achieve a higher sustainability score than others and hence could serve as benchmarks for further analyses

A global horizon scan of issues impacting marine and coastal biodiversity conservation

The biodiversity of marine and coastal habitats is experiencing unprecedented change. While there are well-known drivers of these changes, such as overexploitation, climate change and pollution, there are also relatively unknown emerging issues that are poorly understood or recognized that have potentially positive or negative impacts on marine and coastal ecosystems. In this inaugural Marine and Coastal Horizon Scan, we brought together 30 scientists, policymakers and practitioners with transdisciplinary expertise in marine and coastal systems to identify new issues that are likely to have a significant impact on the functioning and conservation of marine and coastal biodiversity over the next 5–10 years. Based on a modified Delphi voting process, the final 15 issues presented were distilled from a list of 75 submitted by participants at the start of the process. These issues are grouped into three categories: ecosystem impacts, for example the impact of wildfires and the effect of poleward migration on equatorial biodiversity; resource exploitation, including an increase in the trade of fish swim bladders and increased exploitation of marine collagens; and new technologies, such as soft robotics and new biodegradable products. Our early identification of these issues and their potential impacts on marine and coastal biodiversity will support scientists, conservationists, resource managers and policymakers to address the challenges facing marine ecosystems

The Atacama Cosmology Telescope: A Catalog of >4000 Sunyaev–Zel’dovich Galaxy Clusters

We present a catalog of 4195 optically confirmed Sunyaev–Zel'dovich (SZ) selected galaxy clusters detected with signal-to-noise ratio >4 in 13,211 deg2 of sky surveyed by the Atacama Cosmology Telescope (ACT). Cluster candidates were selected by applying a multifrequency matched filter to 98 and 150 GHz maps constructed from ACT observations obtained from 2008 to 2018 and confirmed using deep, wide-area optical surveys. The clusters span the redshift range 0.04 1 clusters, and a total of 868 systems are new discoveries. Assuming an SZ signal versus mass-scaling relation calibrated from X-ray observations, the sample has a 90% completeness mass limit of M500c > 3.8 × 1014 M⊙, evaluated at z = 0.5, for clusters detected at signal-to-noise ratio >5 in maps filtered at an angular scale of 2farcm4. The survey has a large overlap with deep optical weak-lensing surveys that are being used to calibrate the SZ signal mass-scaling relation, such as the Dark Energy Survey (4566 deg2), the Hyper Suprime-Cam Subaru Strategic Program (469 deg2), and the Kilo Degree Survey (825 deg2). We highlight some noteworthy objects in the sample, including potentially projected systems, clusters with strong lensing features, clusters with active central galaxies or star formation, and systems of multiple clusters that may be physically associated. The cluster catalog will be a useful resource for future cosmological analyses and studying the evolution of the intracluster medium and galaxies in massive clusters over the past 10 Gyr

DES Y3 + KiDS-1000: Consistent cosmology combining cosmic shear surveys

We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter $S_8 = \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$ with a mean value of $0.790^{+0.018}_{-0.014}$. The mean marginal is lower than the maximum a posteriori estimate, $S_8=0.801$, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with $S_8$ constraints from observations of the cosmic microwave background by Planck, with agreement at the $1.7\sigma$ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum.Comment: 38 pages, 21 figures, 15 tables, submitted to the Open Journal of Astrophysics. Watch the core team discuss this analysis at https://cosmologytalks.com/2023/05/26/des-kid

Epstein-Barr virus: clinical and epidemiological revisits and genetic basis of oncogenesis

Epstein-Barr virus (EBV) is classified as a member in the order herpesvirales, family herpesviridae, subfamily gammaherpesvirinae and the genus lymphocytovirus. The virus is an exclusively human pathogen and thus also termed as human herpesvirus 4 (HHV4). It was the first oncogenic virus recognized and has been incriminated in the causation of tumors of both lymphatic and epithelial nature. It was reported in some previous studies that 95% of the population worldwide are serologically positive to the virus. Clinically, EBV primary infection is almost silent, persisting as a life-long asymptomatic latent infection in B cells although it may be responsible for a transient clinical syndrome called infectious mononucleosis. Following reactivation of the virus from latency due to immunocompromised status, EBV was found to be associated with several tumors. EBV linked to oncogenesis as detected in lymphoid tumors such as Burkitt's lymphoma (BL), Hodgkin's disease (HD), post-transplant lymphoproliferative disorders (PTLD) and T-cell lymphomas (e.g. Peripheral T-cell lymphomas; PTCL and Anaplastic large cell lymphomas; ALCL). It is also linked to epithelial tumors such as nasopharyngeal carcinoma (NPC), gastric carcinomas and oral hairy leukoplakia (OHL). In vitro, EBV many studies have demonstrated its ability to transform B cells into lymphoblastoid cell lines (LCLs). Despite these malignancies showing different clinical and epidemiological patterns when studied, genetic studies have suggested that these EBV- associated transformations were characterized generally by low level of virus gene expression with only the latent virus proteins (LVPs) upregulated in both tumors and LCLs. In this review, we summarize some clinical and epidemiological features of EBV- associated tumors. We also discuss how EBV latent genes may lead to oncogenesis in the different clinical malignancie

Joint analysis of Dark Energy Survey Year 3 data and CMB lensing from SPT and Planck . I. Construction of CMB lensing maps and modeling choices

Joint analyses of cross-correlations between measurements of galaxy positions, galaxy lensing, and lensing of the cosmic microwave background (CMB) offer powerful constraints on the large-scale structure of the Universe. In a forthcoming analysis, we will present cosmological constraints from the analysis of such cross-correlations measured using Year 3 data from the Dark Energy Survey (DES), and CMB data from the South Pole Telescope (SPT) and Planck. Here we present two key ingredients of this analysis: (1) an improved CMB lensing map in the SPT-SZ survey footprint and (2) the analysis methodology that will be used to extract cosmological information from the cross-correlation measurements. Relative to previous lensing maps made from the same CMB observations, we have implemented techniques to remove contamination from the thermal Sunyaev Zel’dovich effect, enabling the extraction of cosmological information from smaller angular scales of the cross-correlation measurements than in previous analyses with DES Year 1 data. We describe our model for the cross-correlations between these maps and DES data, and validate our modeling choices to demonstrate the robustness of our analysis. We then forecast the expected cosmological constraints from the galaxy survey-CMB lensing auto and cross-correlations. We find that the galaxy-CMB lensing and galaxy shear-CMB lensing correlations will on their own provide a constraint on S 8 = σ 8 √ Ω m / 0.3 at the few percent level, providing a powerful consistency check for the DES-only constraints. We explore scenarios where external priors on shear calibration are removed, finding that the joint analysis of CMB lensing cross-correlations can provide constraints on the shear calibration amplitude at the 5% to 10% level

Joint analysis of Dark Energy Survey Year 3 data and CMB lensing from SPT and Planck . II. Cross-correlation measurements and cosmological constraints

Cross-correlations of galaxy positions and galaxy shears with maps of gravitational lensing of the cosmic microwave background (CMB) are sensitive to the distribution of large-scale structure in the Universe. Such cross-correlations are also expected to be immune to some of the systematic effects that complicate correlation measurements internal to galaxy surveys. We present measurements and modeling of the cross-correlations between galaxy positions and galaxy lensing measured in the first three years of data from the Dark Energy Survey with CMB lensing maps derived from a combination of data from the 2500     deg 2 SPT-SZ survey conducted with the South Pole Telescope and full-sky data from the Planck satellite. The CMB lensing maps used in this analysis have been constructed in a way that minimizes biases from the thermal Sunyaev Zel’dovich effect, making them well suited for cross-correlation studies. The total signal-to-noise of the cross-correlation measurements is 23.9 (25.7) when using a choice of angular scales optimized for a linear (nonlinear) galaxy bias model. We use the cross-correlation measurements to obtain constraints on cosmological parameters. For our fiducial galaxy sample, which consist of four bins of magnitude-selected galaxies, we find constraints of Ω m = 0.272 + 0.032 − 0.052 and S 8 ≡ σ 8 √ Ω m / 0.3 = 0.736 + 0.032 − 0.028 ( Ω m = 0.245 + 0.026 − 0.044 and S 8 = 0.734 + 0.035 − 0.028 ) when assuming linear (nonlinear) galaxy bias in our modeling. Considering only the cross-correlation of galaxy shear with CMB lensing, we find Ω m = 0.270 + 0.043 − 0.061 and S 8 = 0.740 + 0.034 − 0.029 . Our constraints on S 8 are consistent with recent cosmic shear measurements, but lower than the values preferred by primary CMB measurements from Planck