The origin, supply chain, and deforestation risk of Brazil's beef exports.

Though the international trade in agricultural commodities is worth more than $1.6 trillion/year, we still have a poor understanding of the supply chains connecting places of production and consumption and the socioeconomic and environmental impacts of this trade. In this study, we provide a wall-to-wall subnational map of the origin and supply chain of Brazilian meat, offal, and live cattle exports from 2015 to 2017, a trade worth more than $5.4 billion/year. Brazil is the world's largest beef exporter, exporting approximately one-fifth of its production, and the sector has a notable environmental footprint, linked to one-fifth of all commodity-driven deforestation across the tropics. By combining official per-shipment trade records, slaughterhouse export licenses, subnational agricultural statistics, and data on the origin of cattle per slaughterhouse, we mapped the flow of cattle from more than 2,800 municipalities where cattle were raised to 152 exporting slaughterhouses where they were slaughtered, via the 204 exporting and 3,383 importing companies handling that trade, and finally to 152 importing countries. We find stark differences in the subnational origin of the sourcing of different actors and link this supply chain mapping to spatially explicit data on cattle-associated deforestation, to estimate the "deforestation risk" (in hectares/year) of each supply chain actor over time. Our results provide an unprecedented insight into the global trade of a deforestation-risk commodity and demonstrate the potential for improved supply chain transparency based on currently available data.

A Commodity Supply Mix for More Regionalized Life Cycle Assessments.

Supply chain information is invaluable to further regionalize product life cycle assessments (LCAs), but detailed information linking production and consumption centers is not always available. We introduce the commodity supply mix (CSM) defined as the trade-volume-weighted average representing the combined geographic areas for the production of a commodity exported to a given market with the goal of (1) enhancing the relevance of inventory and impact regionalization and (2) allocating these impacts to specific markets. We apply the CSM to the Brazilian soybean supply chain mapped by Trase to obtain the mix of ecoregions and river basins linked to domestic consumption and exports to China, EU, France, and the rest of the world, before quantifying damage to biodiversity, and water scarcity footprints. The EU had the lowest potential biodiversity damage but the largest water scarcity footprint following respective sourcing patterns in 12 ecoregions and 18 river basins. These results differed from the average impact scores obtained from Brazilian soybean production information alone. The CSM can be derived at different scales (subnationally, internationally) using existing supply chain information and constitutes an additional step toward greater regionalization in LCAs, particularly for impacts with greater spatial variability such as biodiversity and water scarcity.