Uncompensated claims to fair emission space risk putting Paris Agreement goals out of reach

Addressing questions of equitable contributions to emission reductions is important to facilitate ambitious global action on climate change within the ambit of the Paris Agreement. Several large developing regions with low historical contributions to global warming have a strong moral claim to a large proportion of the remaining carbon budget (RCB). However, this claim needs to be assessed in a context where the RCB consistent with the long-term temperature goal (LTTG) of the Paris Agreement is rapidly diminishing. Here we assess the potential tension between the moral claim to the remaining carbon space by large developing regions with low per capita emissions, and the collective obligation to achieve the goals of the Paris Agreement. Based on scenarios underlying the IPCC's 6th Assessment Report, we construct a suite of scenarios that combine the following elements: (a) two quantifications of a moral claim to the remaining carbon space by South Asia, and Africa, (b) a 'highest possible emission reduction' effort by developed regions (DRs), and (c) a corresponding range for other developing regions (ODR). We find that even the best effort by DRs cannot compensate for a unilateral claim to the remaining carbon space by South Asia and Africa. This would put the LTTG firmly out of reach unless ODRs cede their moral claim to emissions space and, like DRs, pursue highest possible emission reductions, which would also constitute an inequitable outcome. Furthermore, regions such as Latin America would need to provide large-scale negative emissions with potential risks and negative side effects. Our findings raise important questions of perspectives on equity in the context of the Paris Agreement including on the critical importance of climate finance. A failure to provide adequate levels of financial support to compensate large developing regions to emit less than their moral claim will put the Paris Agreement at risk

pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios [version 2; peer review: 3 approved]

The open-source Python package pyam provides a suite of features and methods for the analysis, validation and visualization of reference data and scenario results generated by integrated assessment models, macro-energy tools and other frameworks in the domain of energy transition, climate change mitigation and sustainable development. It bridges the gap between scenario processing and visualisation solutions that are "hard-wired" to specific modelling frameworks and generic data analysis or plotting packages. The package aims to facilitate reproducibility and reliability of scenario processing, validation and analysis by providing well-tested and documented methods for working with timeseries data in the context of climate policy and energy systems. It supports various data formats, including sub-annual resolution using continuous time representation and "representative timeslices". The pyam package can be useful for modelers generating scenario results using their own tools as well as researchers and analysts working with existing scenario ensembles such as those supporting the IPCC reports or produced in research projects. It is structured in a way that it can be applied irrespective of a user's domain expertise or level of Python knowledge, supporting experts as well as novice users. The code base is implemented following best practices of collaborative scientific-software development. This manuscript describes the design principles of the package and the types of data which can be handled. The usefulness of pyam is illustrated by highlighting several recent applications

Antimicrobial Nanoplexes meet Model Bacterial Membranes: the key role of Cardiolipin

Antimicrobial resistance to traditional antibiotics is a crucial challenge of medical research. Oligonucleotide therapeutics, such as antisense or Transcription Factor Decoys (TFDs), have the potential to circumvent current resistance mechanisms by acting on novel targets. However, their full translation into clinical application requires efficient delivery strategies and fundamental comprehension of their interaction with target bacterial cells. To address these points, we employed a novel cationic bolaamphiphile that binds TFDs with high affinity to form self-assembled complexes (nanoplexes). Confocal microscopy revealed that nanoplexes efficiently transfect bacterial cells, consistently with biological efficacy on animal models. To understand the factors affecting the delivery process, liposomes with varying compositions, taken as model synthetic bilayers, were challenged with nanoplexes and investigated with Scattering and Fluorescence techniques. Thanks to the combination of results on bacteria and synthetic membrane models we demonstrate for the first time that the prokaryotic-enriched anionic lipid Cardiolipin (CL) plays a key-role in the TFDs delivery to bacteria. Moreover, we can hypothesize an overall TFD delivery mechanism, where bacterial membrane reorganization with permeability increase and release of the TFD from the nanoplexes are the main factors. These results will be of great benefit to boost the development of oligonucleotides-based antimicrobials of superior efficacy

Structural studies of metal ligand complexes by ion mobility-mass spectrometry

The final publication is available at Springer via http://dx.doi.org/10.1007/s12127-013-0122-8Collision cross sections (CCS) have been measured for three salen ligands, and their complexes with copper and zinc using travelling-wave ion mobility-mass spectrometry (TWIMS) and drift tube ion mobility-mass spectrometry (DTIMS), allowing a comparative size evaluation of the ligands and complexes. CCS measurements using TWIMS were determined using peptide and TAAH calibration standards. TWIMS measurements gave significantly larger CCS than DTIMS in helium, by 9 % for TAAH standards and 3 % for peptide standards, indicating that the choice of calibration standards is important in ensuring the accuracy of TWIMS-derived CCS measurements. Repeatability data for TWIMS was obtained for inter- and intra-day studies with mean RSDs of 1. 1 % and 0. 7 %, respectively. The CCS data obtained from IM-MS measurements are compared to CCS values obtained via the projection approximation, the exact hard spheres method and the trajectory method from X-ray coordinates and modelled structures using density functional theory (DFT) based methods. © 2013 Springer-Verlag Berlin Heidelberg

COVID-19 recovery funds dwarf clean energy investment needs.

Governments around the globe are responding to the coronavirus disease 2019 (COVID-19)–related economic crisis with unprecedented economic recovery packages (1), which at the time of writing surpassed USD 12 trillion. Several influential voices, including the United Nations (UN) secretary-general, heads of state, companies, investors, and central banks, have called for post–COVID-19 economic recovery efforts to be used to catalyze the necessary longer-term transformation toward a more sustainable and resilient society. Here we shine a light on the opportunity for these investments to support a green recovery by inventorying and classifying the latest information on governments' fiscal stimulus plans (1) and comparing the size of these measures to estimates of low-carbon energy investment needs compatible with the 2015 UN Paris Agreement. We show that low-carbon investments to put the world on an ambitious track toward net zero carbon dioxide emissions by mid-century are dwarfed by currently announced COVID-19 stimulus funds. But marked differences across countries and regions at differing stages of development emphasize the role that international support and global partnership must play to create conditions that enable a global climate-positive recovery

climate-analytics/covid_recovery: Data and analysis scripts

This is the (final) version of the code for Andrijevic et al. 2020, "COVID-19 recovery funds dwarf clean energy investment needs" Built on v1.0 with a bit of spring cleaningThis is the (final) version of the code for Andrijevic et al. 2020, "COVID-19 recovery funds dwarf clean energy investment needs" Built on v1.0 with a bit of spring cleaningv1.

Institutional decarbonization scenarios evaluated against the Paris Agreement 1.5 °C goal

Scientifically rigorous guidance to policy makers on mitigation options for meeting the Paris Agreement long-term temperature goal requires an evaluation of long-term global-warming implications of greenhouse gas emissions pathways. Here we employ a uniform and transparent methodology to evaluate Paris Agreement compatibility of influential institutional emission scenarios from the grey literature, including those from Shell, BP, and the International Energy Agency. We compare a selection of these scenarios analysed with this methodology to the Integrated Assessment Model scenarios assessed by the Intergovernmental Panel on Climate Change. We harmonize emissions to a consistent base-year and account for all greenhouse gases and aerosol precursor emissions, ensuring a self-consistent comparison of climate variables. An evaluation of peak and end-of-century temperatures is made, with both being relevant to the Paris Agreement goal. Of the scenarios assessed, we find that only the IEA Net Zero 2050 scenario is aligned with the criteria for Paris Agreement consistency employed here. We investigate root causes for misalignment with these criteria based on the underlying energy system transformation

Current and future global climate impacts resulting from COVID-19

The global response to the COVID-19 pandemic has led to a sudden reduction of both GHG emissions and air pollutants. Here, using national mobility data, we estimate global emission reductions for ten species during the period February to June 2020. We estimate that global NOx emissions declined by as much as 30% in April, contributing a short-term cooling since the start of the year. This cooling trend is offset by ~20% reduction in global SO2 emissions that weakens the aerosol cooling effect, causing short-term warming. As a result, we estimate that the direct effect of the pandemic-driven response will be negligible, with a cooling of around 0.01 ± 0.005 °C by 2030 compared to a baseline scenario that follows current national policies. In contrast, with an economic recovery tilted towards green stimulus and reductions in fossil fuel investments, it is possible to avoid future warming of 0.3 °C by 2050