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Fossil CO2 emissions in the post-COVID-19 era

Five years after the adoption of the Paris Climate Agreement, growth in global CO2 emissions has begun to falter. The pervasive disruptions from the COVID-19 pandemic have radically altered the trajectory of global CO2 emissions. Contradictory effects of the post-COVID-19 investments in fossil fuel-based infrastructure and the recent strengthening of climate targets must be addressed with new policy choices to sustain a decline in global emissions in the post-COVID-19 era

European anthropogenic AFOLU emissions and their uncertainties: a review and benchmark data

Emission of greenhouse gases (GHG) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, along with estimates of their inherent uncertainties, in order 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 Europe. The data integrates recent AFOLU emission inventories with ecosystem data and land carbon models, covering the European Union (EU28) and summarizes GHG emissions and removals over the period 1990–2016, of relevance for UNFCCC. 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. Particular effort is devoted to the estimation of uncertainty, 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 will need to account for both within model uncertainty and the spread from different model results. At EU28 level, the largest inconsistencies between estimates are mainly due to different sources of data related to human activity which result in emissions or removals taking place during a given period of time (IPCC 2006) referred here as activity data (AD) and methodologies (Tiers) used for calculating emissions/removals from AFOLU sectors. The referenced datasets related to figures are visualised at https://doi.org/10.5281/zenodo.3460311, Petrescu et al., 2019

Gridded fossil CO2 emissions and related O2 combustion consistent with national inventories 1959-2018

Quantification of CO2 fluxes at the Earth’s surface is required to evaluate the causes and drivers of observed increases in atmospheric CO2 concentrations. Atmospheric inversion models disaggregate observed variations in atmospheric CO2 concentration to variability in CO2 emissions and sinks. They require prior constraints fossil CO2 emissions. Here we describe GCP-GridFED (version 2019.1), a gridded fossil emissions dataset that is consistent with the national CO2 emissions reported by the Global Carbon Project (GCP). GCP-GridFEDv2019.1 provides monthly fossil CO2 emissions estimates for the period 1959-2018 at a spatial resolution of 0.1°. Estimates are provided separately for oil, coal and natural gas, for mixed international bunker fuels, and for the calcination of limestone during cement production. GCP-GridFED also includes gridded estimates of O2 uptake based on oxidative ratios for oil, coal and natural gas. It will be updated annually and made available for atmospheric inversions contributing to GCP global carbon budget assessments, thus aligning the prior constraints on top-down fossil CO2 emissions with the bottom-up estimates compiled by the GCP

Identification of a small molecule yeast TORC1 inhibitor with a flow cytometry-based multiplex screen

TOR (target of rapamycin) is a serine/threonine kinase, evolutionarily conserved from yeast to human, which functions as a fundamental controller of cell growth. The moderate clinical benefit of rapamycin in mTOR-based therapy of many cancers favors the development of new TOR inhibitors. Here we report a high throughput flow cytometry multiplexed screen using five GFPtagged yeast clones that represent the readouts of four branches of the TORC1 signaling pathway in budding yeast. Each GFP-tagged clone was differentially color-coded and the GFP signal of each clone was measured simultaneously by flow cytometry, which allows rapid prioritization of compounds that likely act through direct modulation of TORC1 or proximal signaling components. A total of 255 compounds were confirmed in dose-response analysis to alter GFP expression in one or more clones. To validate the concept of the high throughput screen, we have characterized CID 3528206, a small molecule most likely to act on TORC1 as it alters GFP expression in all five GFP clones in an analogous manner to rapamycin. We have shown that CID 3528206 inhibited yeast cell growth, and that CID 3528206 inhibited TORC1 activity both in vitro and in vivo with EC50s of 150 nM and 3.9 μM, respectively. The results of microarray analysis and yeast GFP collection screen further support the notion that CID 3528206 and rapamycin modulate similar cellular pathways. Together, these results indicate that the HTS has identified a potentially useful small molecule for further development of TOR inhibitors

To what extent can behaviour change techniques be identified within an adaptable implementation package for primary care? A prospective directed content analysis

Interpreting evaluations of complex interventions can be difficult without sufficient description of key intervention content. We aimed to develop an implementation package for primary care which could be delivered using typically available resources and could be adapted to target determinants of behaviour for each of four quality indicators: diabetes control, blood pressure control, anticoagulation for atrial fibrillation and risky prescribing. We describe the development and prospective verification of behaviour change techniques (BCTs) embedded within the adaptable implementation packages

The barley immune receptor Mla recognizes multiple pathogens and contributes to host range dynamics.

Funder: Gatsby Charitable Foundation; doi: https://doi.org/10.13039/501100000324Crop losses caused by plant pathogens are a primary threat to stable food production. Stripe rust (Puccinia striiformis) is a fungal pathogen of cereal crops that causes significant, persistent yield loss. Stripe rust exhibits host species specificity, with lineages that have adapted to infect wheat and barley. While wheat stripe rust and barley stripe rust are commonly restricted to their corresponding hosts, the genes underlying this host specificity remain unknown. Here, we show that three resistance genes, Rps6, Rps7, and Rps8, contribute to immunity in barley to wheat stripe rust. Rps7 cosegregates with barley powdery mildew resistance at the Mla locus. Using transgenic complementation of different Mla alleles, we confirm allele-specific recognition of wheat stripe rust by Mla. Our results show that major resistance genes contribute to the host species specificity of wheat stripe rust on barley and that a shared genetic architecture underlies resistance to the adapted pathogen barley powdery mildew and non-adapted pathogen wheat stripe rust

The consolidated European synthesis of CO2emissions and removals for the European Union and United Kingdom : 1990-2018

Acknowledgements FAOSTAT statistics are produced and disseminated with the support of its member countries to the FAO regular budget. Philippe Ciais acknowledges the support of the European Research Council Synergy project SyG-2013-610028 IMBALANCE-P and from the ANR CLAND Convergence Institute. We acknowledge the work of the entire EDGAR group (Marilena Muntean, Diego Guizzardi, Edwin Schaaf and Jos Olivier). We acknowledge Stephen Sitch and the authors of the DGVMs TRENDY v7 ensemble models for providing us with the data. Financial support This research has been supported by the H2020 European Research Council (grant no. 776810).Peer reviewedPublisher PD