A search for debris disks in the Herschel -ATLAS

Aims. We aim to demonstrate that the Herschel-ATLAS (H-ATLAS) is suitable for a blind and unbiased survey for debris disks by identifying candidate debris disks associated with main sequence stars in the initial science demonstration field of the survey. We show that H-ATLAS reveals a population of far-infrared/sub-mm sources that are associated with stars or star-like objects on the SDSS main-sequence locus. We validate our approach by comparing the properties of the most likely candidate disks to those of the known population. Methods. We use a photometric selection technique to identify main sequence stars in the SDSS DR7 catalogue and a Bayesian Likelihood Ratio method to identify H-ATLAS catalogue sources associated with these main sequence stars. Following this photometric selection we apply distance cuts to identify the most likely candidate debris disks and rule out the presence of contaminating galaxies using UKIDSS LAS K-band images. Results. We identify 78 H-ATLAS sources associated with SDSS point sources on the main-sequence locus, of which two are the most likely debris disk candidates: H-ATLAS J090315.8 and H-ATLAS J090240.2. We show that they are plausible candidates by comparing their properties to the known population of debris disks. Our initial results indicate that bright debris disks are rare, with only 2 candidates identified in a search sample of 851 stars. We also show that H-ATLAS can derive useful upper limits for debris disks associated with Hipparcos stars in the field and outline the future prospects for our debris disk search programme.Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the U.S. Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The UKIDSS project is defined in Lawrence et al. (2007). UKIDSS uses the UKIRT Wide Field Camera (WFCAM; Casali et al. 2007). The photometric system is described in Hambly et al. (2008), and the calibration is described in Hodgkin et al. (2009). The pipeline processing and science archive are described in Hambly et al. (2008). M.A.T. would like to thank two of our undergraduate project students, Sam Richards and Max Podger, who carried out initial database searches and also David Pinfield and Ralf Napiwotski for discussions on low mass stars

First report on reconciliation of bottom-up and top-down methods at sub-national scales (M9), STICHTING VU : deliverable D5.2

European greenhouse gas (GHG) emission reduction policies require accurate and robust estimates of anthropogenic emissions. Internationally recognized methods are needed to produce, and regularly update, these emission estimates, following TACCC (transparency, accuracy, comparability, consistency, completeness) UNFCCC requirements. New research is required to more accurately quantify carbon stocks and fluxes of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). The development and improvement of methodologies for a GHG verification system will address its applicability in Europe, and, whenever needed, the upscaling from Europe to other GHG emitting countries and regions, through international cooperation mechanisms promoted by the WMO, the IPCC and the UNFCCC in the context of the Paris Agreement on Climate.The EU funded project VERIFY aims to develop a framework for the synthesis of different data streams to produce harmonized European country-scale GHG budgets, with uncertainties and to provide scientific and observation-based evidence on the estimates. By reconciliation of data from different sources (e.g. bottom-up, top-down, regional emission estimates and national emission inventory reports) we aim to reduce overall uncertainty and identify and categorize key differences that are related to specific methods.This first report is intended as a ‘proof of concept’, and our preliminary analysis is based on total EU28 and sector totals from UNFCCC and EDGAR with a focus on a) Agriculture (UNFCCC, CAPRI, EDGAR, FAO, GAINS) and b) LULUCF biogenic fluxes - carbon stocks and sinks (UNFCCC, EFISCEN, CBM and TRENDY.v6). We analyzed as well inverse C fluxes from four inversions of the global carbon project (GCP) and N2O fluxes from the InGOS project. Together with CH4 fluxes from GCP we also mention the CH4 fluxes from natural wetlands. For the sector totals, we find a relatively good match between UNFCCC and the other sources with differences pertaining mostly to sectoral aggregation and/or expert judgment emission factors (EFs). We find large differences in the LULUCF carbon stocks and fluxes when comparing modelled results to UNFCCC reports. Differences in method (Tier 1 or Tier 2) and model set-up, might be the underlying cause of these discrepancies

On the trajectory of discrimination:a meta-analysis and forecasting survey capturing 44 years of field experiments on gender and hiring decisions

Funding: Michael Schaerer benefitted from a Tier 1 Research Grant (MSS22B011) awarded by the Ministry of Education, Singapore. Michael Schaerer, Christilene du Plessis, and Eric Uhlmann further benefitted from a Tier 2 Research Grant (MM22B03) awarded by the Ministry of Education, Singapore. Daniel Lakens was supported by the Netherlands Organization for Scientific Research (NWO) VIDI Grant 452-17-013. Anna Dreber benefitted from the Jan Wallander and Tom Hedelius Foundation (grants P21-0091 and P23-0098), Knut and Alice Wallenberg Foundation and Marianne and Marcus Wallenberg Foundation (Wallenberg Scholar grant to A.D.). Cory Clark was supported by a grant from the Searle Freedom Trust. The research also benefitted from a grant by the Wharton-INSEAD Centre for Global Research awarded to Eric Uhlmann and Cory Clark, among others. Finally, Eric L. Uhlmann also received an R&D grant from INSEAD that supported this research.A preregistered meta-analysis, including 244 effect sizes from 85 field audits and 361,645 individual job applications, tested for gender bias in hiring practices in female-stereotypical and gender-balanced as well as male-stereotypical jobs from 1976 to 2020. A “red team” of independent experts was recruited to increase the rigor and robustness of our meta-analytic approach. A forecasting survey further examined whether laypeople (n = 499 nationally representative adults) and scientists (n = 312) could predict the results. Forecasters correctly anticipated reductions in discrimination against female candidates over time. However, both scientists and laypeople overestimated the continuation of bias against female candidates. Instead, selection bias in favor of male over female candidates was eliminated and, if anything, slightly reversed in sign starting in 2009 for mixed-gender and male-stereotypical jobs in our sample. Forecasters further failed to anticipate that discrimination against male candidates for stereotypically female jobs would remain stable across the decades.Publisher PDFPeer reviewe

First scientific review article on multi-gas GHG budgets : Delivarable D5.9

European anthropogenic AFOLU greenhouse gas emissions: a review and benchmark data (Petrescu et al, 2020, published in ESSD)Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthropogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU281). The data integrates recent AFOLU emission inventories with ecosystem data and land carbon models and summarizes GHG emissions and removals over the period 1990-2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGI) with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for EU28 provides consistent quantification of uncertainty following the established IPCC guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred here as activity data (AD) and methodologies (Tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualised at http://doi.org/doi:10.5281/zenodo.3662371 (Petrescu et al., 2020)

Erratum:A review of trends and drivers of greenhouse gas emissions by sector from 1990 to 2018 (Environmental Research Letters (2021) 16 (073005) DOI: 10.1088/1748-9326/abee4e)

This corrigendum resolves an error in figure 17 and clarifies the scope of the cement sector in figure 2. Figure 17 in the original published manuscript depicts a Kaya identity for the agriculture, forestry and other land uses (AFOLU) sector. We unintentionally excluded land-use CO2 emissions from total greenhouse gas (GHG) emissions in this identity, and depicted only agricultural GHG emissions

The consolidated European synthesis of CO2 emissions and removals for EU27 and UK: 1990-2018

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results, and inverse modelling estimates, over the period 1990–2018. BU and TD products are compared with European national GHG inventories (NGHGI) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGI, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGI with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from Land Use, Land Use Change and Forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGI and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), well in line with the national inventories. Over 2011–2015, the CO2 land sources/sinks from NGHGI estimates report −90 Tg C yr−1 ± 30 Tg C while all other BU approaches report a mean sink of −98 Tg yr−1 (± 362 Tg C from DGVMs only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr−1 ± 400 T g C yr−1). This concludes that a) current independent approaches are consistent with NGHGI b) their uncertainty is too large to allow a "verification" because of model differences and probably also because of the definition of "CO2 flux" obtained from different approache

Non-natives: 141 scientists object [Letter]

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