Understanding the drivers and dynamics of global ultra-processed food (UPF) consumption is essential, given the evidence linking these foods with adverse health outcomes. In this synthesis review, we take two steps. First, we quantify per capita volumes and trends in UPF sales, and ingredients (sweeteners, fats, sodium and cosmetic additives) supplied by these foods, in countries classified by income and region. Second, we review the literature on food systems and political economy factors that likely explain the observed changes. We find evidence for a substantial expansion in the types and quantities of UPFs sold worldwide, representing a transition towards a more processed global diet but with wide variations between regions and countries. As countries grow richer, higher volumes and a wider variety of UPFs are sold. Sales are highest in Australasia, North America, Europe and Latin America but growing rapidly in Asia, the Middle East and Africa. These developments are closely linked with the industrialization of food systems, technological change and globalization, including growth in the market and political activities of transnational food corporations and inadequate policies to protect nutrition in these new contexts. The scale of dietary change underway, especially in highly populated middle-income countries, raises serious concern for global health.

Compiling, deploying and utilising large-scale databases that integrate environmental and economic data have traditionally been labour- and cost-intensive processes, hindered by the large amount of disparate and misaligned data that must be collected and harmonised. The Australian Industrial Ecology Virtual Laboratory (IELab) is a novel, collaborative approach to compiling large-scale environmentally extended multi-region input-output (MRIO) models. The utility of the IELab product is greatly enhanced by avoiding the need to lock in an MRIO structure at the time the MRIO system is developed. The IELab advances the idea of the "mother-daughter" construction principle, whereby a regionally and sectorally very detailed "mother" table is set up, from which "daughter" tables are derived to suit specific research questions. By introducing a third tier - the "root classification" - IELab users are able to define their own mother-MRIO configuration, at no additional cost in terms of data handling. Customised mother-MRIOs can then be built, which maximise disaggregation in aspects that are useful to a family of research questions. The second innovation in the IELab system is to provide a highly automated collaborative research platform in a cloud-computing environment, greatly expediting workflows and making these computational benefits accessible to all users. Combining these two aspects realises many benefits. The collaborative nature of the IELab development project allows significant savings in resources. Timely deployment is possible by coupling automation procedures with the comprehensive input from multiple teams. User-defined MRIO tables, coupled with high performance computing, mean that MRIO analysis will be useful and accessible for a great many more research applications than would otherwise be possible. By ensuring that a common set of analytical tools such as for hybrid life-cycle assessment is adopted, the IELab will facilitate the harmonisation of fragmented, dispersed and misaligned raw data for the benefit of all interested parties.

[1] The likely effects of climate change on the water resources of the eastern Mediterranean and Middle East region are investigated using a high-resolution regional climate model (PRECIS) by comparing precipitation simulations of 2040-2069 and 2070-2099 with 1961-1990. The simulations show about a 10% decline in precipitation across the region by both the middle and the end of the century, with considerable variation between countries and international river basins. Results suggest that per capita water resources will not change particularly significantly in southeastern Europe, where they are relatively plentiful and population growth is minimal. However, in much of the Middle East, climate change coupled with population growth is likely to reduce per capita water resources considerably. This will inevitably result in major social, economic, and environmental change in the region. Countries where the required adaptation is likely to be particularly challenging include Turkey and Syria because of the large agricultural workforces, Iraq because of the magnitude of the change and its downstream location, and Jordan because of its meager per capita water resources coupled with limited options for desalination. If the internal water footprint of the region declines in line with precipitation but the total water footprint of the region increases in line with population, then by midcentury, as much as half the total water needs of the region may need to be provided through desalination and imported in the form of virtual water.

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Population dietary guidelines have started to include information about the environmental impacts of food choices, but more quantifiable evidence is needed, particularly about the impacts associated with discretionary foods. This paper utilised the 2011–2012 Australian Health Survey food intake data along with a highly disaggregated input–output model to estimate the greenhouse gas emissions (GHGe) of Australians’ dietary intake, and compare current patterns of eating which vary in diet quality and GHGe to the recommended diet. The average dietary GHGe were 18.72 ± 12.06 and 13.73 ± 8.72 kg CO2e/day for male and female adults, respectively. The correlation between total energy and GHGe was r = 0.54 (p < 0.001). Core foods contributed 68.4% and discretionary foods 29.4%. Within core foods, fresh meat and alternatives (33.9%) was the greatest contributor. The modelling of current dietary patterns showed the contribution of discretionary foods to GHGe was 121% greater in the average diet and 307% greater in the “lower quality, higher GHGe” diet compared to the recommended diet. Reducing discretionary food intake would allow for small increases in emissions from core foods (in particular vegetables, dairy and grains), thereby providing a nutritional benefit at little environmental expense. Public health messages that promote healthy eating, eating to one’s energy needs and improved diet quality will also contribute to lowering GHGe.