File:Net food sector GHG emissions from technology adoption scenarios.png

English: "Net food sector GHG emissions from technology adoption scenarios (0%, 25%, 50%, 75% and 100% adoption) across global dietary transitions from business as usual (top) to 50% (middle) to 100% flexitarian adoption (bottom) with (right) and without (left) reductions in food loss and waste in 2050. All scenarios assume full closure of yield gaps by 2050. Technological adoption rate is based on the global additive effects of all technologies in Fig 1. BAU caloric consumption. Values provided in Supplemental Material (Table C in S1 Text)." "Here, we use a global food system model used in the EAT-Lancet analyses (see Methods; [11]) to examine an array of conditions and scenarios for which gross GHG reductions, gross CDR and net negative GHG emissions can be achieved in the 2050 food system. These scenarios include changes in dietary choice, land use changes, technology deployment levels, and food loss and waste reductions, thus alternating the land, fertilizer, and energy GHG emissions that are tied to the food demands of 10 billion people by 2050 (see Methods). We combine a ‘business as usual’ (BAU) scenario with a global food system model to ascribe GHG emissions to the production of different foods [11]. We focus on agro-industrial technologies representative of food system emissions sourcing, spanning cradle-to-grave and land-to-sea, including hydro-powered fertilizer production, improved livestock feed, anaerobic digesters, soil amendments, agroforestry, seaweed farming, and reduced trawling (Table 1, Fig 1). Our analyses include both discrete categories (Fig 2) and a continuous spectrum (Fig 3) of dietary, technological, and food loss and waste reduction scenarios, and include both global and country-wide scenarios (Figs 4 and 5). We aim to explore which levers offer the most potential for achieving food system emission targets. We argue that systematic investigation of the technologies we selected to explore, in combination with dietary change and food waste scenarios, will provide immediate policy-relevant foresight and help prioritize research and practice."