Spatially-explicit footprints of agricultural commodities: Mapping carbon emissions embodied in Brazil's soy exports
Spatially-explicit footprints of agricultural commodities: Mapping carbon emissions embodied in Brazil's soy exports
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DOI：
10.1016/j.gloenvcha.2020.102067
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发表时间：
2020-05-01
影响因子：
8.9
通讯作者：
Godar, Javier
中科院分区：
文献类型：
--
作者：
Escobar, Neus;Tizado, E. Jorge;Godar, Javier
要对农产品的碳足迹和其他环境足迹进行可靠的估计，就需要掌握沿着全球供应链的各种条件。生命周期评估（LCA）在解决生产、运输和制造系统的时空变异性方面面临着局限性。我们提出了一个自下而上的方法来量化的温室气体（GHG）排放嵌入在农产品的生产和贸易具有高的空间分辨率，通过整合LCA原则与增强的物理贸易流分析。我们的方法估计了2010 - 2015年期间巴西大豆出口的碳足迹（以每吨产品的二氧化碳当量吨计算），基于从原产地通过国际市场确定的豆类，油和蛋白质蛋糕的90，000个单独交易流量。大豆是世界上交易量最大的农产品，也是巴西的主要农作物出口，对环境造成重大影响。我们发现，在整个供应链的采购地区、进口国和子阶段，碳排放存在极大的空间变异性。最大的碳足迹与马托皮巴州和Path的市政当局有关，在那里大豆与自然植被损失直接相关。来自上述各州的大豆每单位产品的排放量比巴西平均水平（0.69吨）高出六倍。欧洲联盟（欧盟）的碳足迹最大（0.77吨吨-1），因为森林砍伐所产生的排放量比例大于中国（0.67吨-1），中国是最大的大豆进口国。2010 - 2015年，巴西大豆出口的温室气体排放总量估计为2.2346亿吨，其中一半以上是中国进口的，尽管从绝对值来看，欧盟进口的毁林排放量更大。我们的方法为加强地方、区域、国家和国际各级供应链的环境管理提供数据，同时为关于农业生产和贸易影响的全球责任的辩论提供信息。
Reliable estimates of carbon and other environmental footprints of agricultural commodities require capturing a large diversity of conditions along global supply chains. Life Cycle Assessment (LCA) faces limitations when it comes to addressing spatial and temporal variability in production, transportation and manufacturing systems. We present a bottom-up approach for quantifying the greenhouse gas (GHG) emissions embedded in the production and trade of agricultural products with a high spatial resolution, by means of the integration of LCA principles with enhanced physical trade flow analysis. Our approach estimates the carbon footprint (as tonnes of carbon dioxide equivalents per tonne of product) of Brazilian soy exports over the period 2010-2015 based on similar to 90,000 individual traded flows of beans, oil and protein cake identified from the municipality of origin through international markets. Soy is the most traded agricultural commodity in the world and the main agricultural export crop in Brazil, where it is associated with significant environmental impacts. We detect an extremely large spatial variability in carbon emissions across sourcing areas, countries of import, and sub-stages throughout the supply chain. The largest carbon footprints are associated with municipalities across the MATOPIBA states and Path, where soy is directly linked to natural vegetation loss. Importing soy from the aforementioned states entailed up to six times greater emissions per unit of product than the Brazilian average (0.69 t t(-1)). The European Union (EU) had the largest carbon footprint (0.77 t t(-1)) due to a larger share of emissions from embodied deforestation than for instance in China (0.67 t t(-1)), the largest soy importer. Total GHG emissions from Brazilian soy exports in 2010-2015 are estimated at 223.46 Mt, of which more than half were imported by China although the EU imported greater emissions from deforestation in absolute terms. Our approach contributes data for enhanced environmental stewardship across supply chains at the local, regional, national and international scales, while informing the debate on global responsibility for the impacts of agricultural production and trade.