Global glass production grew to 150 million tonnes (Mt) in 2014, equating to approximately 21 kg per person. Producing this glass is energy intensive and contributes annual CO2 emissions of some 86Mt. An accurate map of the global glass supply chain is needed to help identify emissions mitigation options from across the supply chain, including process energy efficiency and material efficiency options. This map does not yet exist, so we address this knowledge gap by tracing the production chain from raw materials to end of life and producing a global Sankey diagram of container and flat glass making for 2014. To understand future demand for flat glass we also model the stocks of glass in vehicles and buildings. The analysis shows the relative scale of glass flows and stocks worldwide and provides a baseline for future study of the emission mitigation potential of energy and material efficiency of manufacturing with glass.

Fuel economy standards are a key measure to increase the rate of efficiency improvements in passenger cars. The fuel consumption of vehicles can be improved in three ways: incremental technical efficiency improvements within powertrain technologies, market shifts to more efficient types of powertrains and by limiting increases in the size and performance of vehicles. This study quantifies the effect of each of these three drivers on the fuel consumption of British vehicles between 2001 and 2018 using driver-reported data on real-world fuel consumption. Analysis shows the introduction of EU fuel economy standards in 2008/09 had little effect on the rate of real technical efficiency improvements in British vehicles. Instead of adopting technical improvements at a higher rate or limiting the size and power of vehicles, these results suggest vehicle manufacturers met emissions standards by increasing the divergence between laboratory tests and real-world fuel consumption. This study adds to the growing literature calling for official test procedures to be representative of real-world driving.

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Increased recycling and reuse rates are a central part of the objectives laid out by the COP21. Nonetheless, the practical implementation of what has been called the circular economy, as well as its true potential, are not easily established. This is because the impact and implementation time scales of any intervention depend on knowing the lifetime of products, which is frequently unknown. This is particularly true in construction, responsible for 39% of worldwide emissions, 11% of which are embodied. Most material flow analysis (MFA) models will simply assume a range of plausible life expectancies when bottom‐up data are lacking. In this work, we propose a novel method of identification using the high quality but highly aggregated trade data available and use it to establish a “mortality curve” for buildings and other long‐lasting products. This identification method is intended to provide more reliable inputs to existing MFA models. It is widely applicable because of the general availability of the underlying data. Using it on United Kingdom trade data, we identify product classes at 1 year for packaging/home scrap, 1 to around 10 years for vehicles/equipment, and around 50 years for construction. The identification approach was then validated by using classical approaches using bottom‐up data for vehicles.

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