Cement plays a dual role in the global carbon cycle like a sponge: its massive production contributes significantly to present-day global anthropogenic CO₂ emissions, yet its hydrated products gradually reabsorb substantial amounts of atmospheric CO₂ (carbonation) in the future. The role of this sponge effect along the cement cycle (including production, use, and demolition) in carbon emissions mitigation, however, remains hitherto unexplored. Here, we quantify the effects of demand- and supply-side mitigation measures considering this material-energy-emissions-uptake nexus, finding that climate goals would be imperiled if the growth of cement stocks continues. Future reabsorption of CO₂ will be significant (~30% of cumulative CO₂ emissions from 2015 to 2100), but climate goal compliant net CO₂ emissions reduction along the global cement cycle will require both radical technology advancements (e.g., carbon capture and storage) and widespread deployment of material efficiency measures, which go beyond those envisaged in current technology roadmaps.

This data includes two example databases from the paper "Hybrid Sankey diagrams: visual analysis of multidimensional data for understanding resource use": the made-up fruit flows, and real global steel flow data from Cullen et al. (2012). It also includes the Sankey Diagram Definitions to reproduce the diagrams in the paper. The code to reproduce the figures is written in Python in the form of Jupyter notebooks. A conda environment file is included to easily set up the necessary Python packages to run the notebooks. All files are included in the "examples.zip" file. The notebook files are also uploaded standalone so they can be linked to nbviewer.EPSRC [EP/N02351x/1

There is increasing concern that climate change poses an existential risk to humanity. Understanding these worst-case scenarios is essential for good risk management. However, our knowledge of the causal pathways through which climate change could cause societal collapse is underdeveloped. This paper aims to identify and structure an empirical evidence base of the climate change, food insecurity and societal collapse pathway. We first review the societal collapse and existential risk literature and define a set of determinants of societal collapse. We develop an original methodology, using these determinants as societal collapse proxies, to identify an empirical evidence base of climate change, food insecurity and societal collapse in contemporary society and then structure it using a novel-format causal loop diagram (CLD) defined at global scale and national granularity. The resulting evidence base varies in temporal and spatial distribution of study and in the type of data-driven methods used. The resulting CLD documents the spread of the evidence base, using line thickness and colour to depict density and type of data-driven method respectively. It enables exploration of how the effects of climate change may undermine agricultural systems and disrupt food supply, which can lead to economic shocks, socio-political instability as well as starvation, migration and conflict. Suggestions are made for future work that could build on this paper to further develop our qualitative understanding of, and quantitative complex systems modelling capabilities for analysing, the causal pathways between climate change and societal collapse.

Uncertainties in greenhouse gas emissions estimates for petrochemical production have lacked quantification globally, impacting emissions reporting and decarbonization policymaking. Here we analyze cradle-to-gate emissions of 81 chemicals at 37,000 facilities worldwide, assessing 6 uncertainty sources. The results estimate a 34% uncertainty in total global emissions of 1.9 ± 0.6 Gt of CO₂-equivalent emissions for 2020, and 15–40% uncertainties across most petrochemicals analyzed. The largest uncertainties stem from the inability to assign specific production processes to facilities owing to data limitations. Uncertain data on feedstock production and off-site energy generation contribute substantially, while on-site fuel combustion and chemical reactions have smaller roles. Allocation method choices for co-products are generally insignificant. Prioritizing facility-level process specification in data collection for just 20% of facilities could reduce global uncertainty by 80%. This underscores the necessity of quantifying uncertainty in petrochemical greenhouse gas emissions globally and outlines priorities for improved reporting. The dataset generated offers independent emissions factor estimates based on facility-specific information for 81 chemicals, supporting future analyses.

Passenger car carbon footprints are highly sensitive to future energy systems, a factor often overlooked in life cycle assessment. We use a time-dependent prospective life cycle assessment to enhance carbon footprints under four 1.5–3.0 °C decarbonisation pathways for electricity, fuel, and hydrogen from an energy-based integrated assessment model. Across 5000 comparative cases, battery electric vehicles consistently have the lowest carbon footprints compared to hybrid, plug-in hybrid, and fuel-cell vehicles. For example, battery electric vehicles show an average 32 to 47% lower footprint than hybrid combustion in 3.0 °C and 1.5 °C climate-compatible futures, respectively. This is driven by greater projected decarbonisation of electricity compared to fossil-dominated fuels and hydrogen. Battery electric vehicles meaningfully retain their advantage for mileages over 100,000 km, even in regions with carbon-intensive electricity since these are anticipated to decarbonise the most. Although our study supports battery electric vehicles as the most reliable climate-mitigation option for passenger cars, reducing their high manufacturing footprint remains important.