Aligning climate scenarios to emissions inventories shifts global benchmarks.

Taking stock of global progress towards achieving the Paris Agreement requires consistently measuring aggregate national actions and pledges against modelled mitigation pathways1. However, national greenhouse gas inventories (NGHGIs) and scientific assessments of anthropogenic emissions follow different accounting conventions for land-based carbon fluxes resulting in a large difference in the present emission estimates2,3, a gap that will evolve over time. Using state-of-the-art methodologies4 and a land carbon-cycle emulator5, we align the Intergovernmental Panel on Climate Change (IPCC)-assessed mitigation pathways with the NGHGIs to make a comparison. We find that the key global mitigation benchmarks become harder to achieve when calculated using the NGHGI conventions, requiring both earlier net-zero CO2 timing and lower cumulative emissions. Furthermore, weakening natural carbon removal processes such as carbon fertilization can mask anthropogenic land-based removal efforts, with the result that land-based carbon fluxes in NGHGIs may ultimately become sources of emissions by 2100. Our results are important for the Global Stocktake6, suggesting that nations will need to increase the collective ambition of their climate targets to remain consistent with the global temperature goals.

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.

Can updated climate pledges limit warming well below 2°C?

Increased ambition and implementation are essential.

pyam: Analysis and visualisation of integrated assessment and macro-energy scenarios.

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.

Erratum: Publisher Correction: Current and future global climate impacts resulting from COVID-19.

[This corrects the article DOI: 10.1038/s41558-020-0883-0.].

Taking stock of national climate policies to evaluate implementation of the Paris Agreement.

Many countries have implemented national climate policies to accomplish pledged Nationally Determined Contributions and to contribute to the temperature objectives of the Paris Agreement on climate change. In 2023, the global stocktake will assess the combined effort of countries. Here, based on a public policy database and a multi-model scenario analysis, we show that implementation of current policies leaves a median emission gap of 22.4 to 28.2 GtCO2eq by 2030 with the optimal pathways to implement the well below 2 °C and 1.5 °C Paris goals. If Nationally Determined Contributions would be fully implemented, this gap would be reduced by a third. Interestingly, the countries evaluated were found to not achieve their pledged contributions with implemented policies (implementation gap), or to have an ambition gap with optimal pathways towards well below 2 °C. This shows that all countries would need to accelerate the implementation of policies for renewable technologies, while efficiency improvements are especially important in emerging countries and fossil-fuel-dependent countries.

A new scenario logic for the Paris Agreement long-term temperature goal.

To understand how global warming can be kept well below 2 degrees Celsius and even 1.5 degrees Celsius, climate policy uses scenarios that describe how society could reduce its greenhouse gas emissions. However, current scenarios have a key weakness: they typically focus on reaching specific climate goals in 2100. This choice may encourage risky pathways that delay action, reach higher-than-acceptable mid-century warming, and rely on net removal of carbon dioxide thereafter to undo their initial shortfall in reductions of emissions. Here we draw on insights from physical science to propose a scenario framework that focuses on capping global warming at a specific maximum level with either temperature stabilization or reversal thereafter. The ambition of climate action until carbon neutrality determines peak warming, and can be followed by a variety of long-term states with different sustainability implications. The approach proposed here closely mirrors the intentions of the United Nations Paris Agreement, and makes questions of intergenerational equity into explicit design choices.

Dynamic control of extracellular environment in in vitro neural recording systems.

A technique is presented for rapid fabrication of microfluidic channels on top of multichannel in vitro neural recording electrode arrays. The channels allow dynamic control of both stable and transient flow patterns over localized areas of the array, over biologically relevant timescales. A cellular model consisting of thermally sensitive dorsal root ganglion neurons was integrated into the devices. The device was used to demonstrate precise control of the extracellular microenvironment of individual cells on the array. Since the methods presented here are not specific to a particular cell type or neural recording system, the technique is amenable to a wide range of applications within the neuroscience field.