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Greenhouse gas (GHG) emissions from direct land use change (LUC) in GHG footprint studies of crops are often estimated using national land use change statistics, as in many cases the exact location of crop cultivation and land use history is unknown. As such, these studies neglect spatial variability in land use change (amount and configuration) at the sub-national level as well as spatial variability in natural carbon stocks. For this reason, a spatial approach that enables consistent implementation of LUC emissions of crop production at different locations is developed and applied in this study. The dataset of crop production covers 69 crops cultivated on 1885 farms in 33 countries, spanning North and South America, Asia, Australia and Oceania, Europe and Africa, in the year 2014. Of the 1885 farms, 33% (619 farms) were identified to have LUC emissions when estimated at the local scale. LUC emissions of farms, derived using local scale location information, were found to have little correlation with those estimated at coarser spatial scales (such as the province or country level) using the spatial approach in this study or estimated using accounting approaches based on national statistics. Analysis at coarser spatial scales typically overestimated the LUC emissions of crops, as LUC in other regions can heavily influence these estimates. Therefore, it is concluded that local scale LUC emissions better represent local LUC dynamics, thereby improving the reliability of GHG footprint studies. Unlabelled Image • LUC of crops estimated with national statistics neglects intra-country variability. • Approximate farm locations were used to estimate LUC emissions of 1885 farms. • 33% of farms were identified to have LUC emissions at the local scale. • Analysis at coarser spatial scales typically overestimated LUC emissions of crops. • Local level farm location needs to be collected to better represent LUC dynamics. [ABSTRACT FROM AUTHOR]

Our study provides an integrated analysis of the variability of greenhouse gas (GHG) footprints of field-grown tomatoes for processing. The global farm-specific data set of 890 observations across 14 countries over a three-year period (2013-2015) was obtained from farms grown under Unilever's sustainable agricultural code. It represents on average 3% of the annual global production of processing tomatoes: insights can be used to help inform corporate sourcing strategies and certification schemes. The median GHG footprint ranged from 18 in Chile to 61 kg CO 2 -equiv per tonne of tomatoes in India, lower than results reported in other studies. We found that footprints are more consistent within countries than between them. Using linear mixed effect models, we quantified the relative influence of environmental conditions and farm management factors. Key variables were area of production and the method of fertilizer application. GHG footprints decreased with increasing area of production to a threshold of 17.4 ha. Farms using single fertilizer application methods in general had a larger GHG footprint than those using a combination of methods. We conclude that farm management factors should be prioritized for future data collection, and more stringent guidance on acceptable practices is required if greater comparability of outcomes is needed either within a scheme, such as the Unilever's sustainable agriculture code, or between schemes.