Abstract
Identifying drivers of farm-level greenhouse gas (GHG) footprints of crop production can reveal opportunities to improve farming practices and enable more targeted GHG mitigation strategies. Although many studies evaluated the GHG footprints of crop production, differences between and within crops have not been systematically evaluated for a large number of farms so far. Here, we evaluated possible sources of variability in GHG footprints (in terms of kg CO2-eq/kg crop produced) of 26 crops, grown in compliance with Unilever's Sustainable Agriculture Code, using data from 4565 farms in 36 countries from 2013 through 2016. We quantified crop-farm-specific GHG footprints based on four components: (i) emissions from electricity use, (ii) emissions from fossil fuel (petrol and diesel) use, (iii) emissions from crop and pruning residue application, and (iv) emissions from fertilizer use. On average, fertilizer use contributed most to the GHG footprint for 23 out of the 26 crops in our dataset. We further found that variability in GHG footprints was smaller between crops (45%) than within crops (55%). Regression modelling revealed that on average 44% of the GHG footprint variability within crops could be attributed to (a selection of) three explanatory variables, i.e., yield, area of production, and year of production. Of these, yield was the most important explanatory variable. Lower GHG footprints were associated with higher yields for 24 out of the 26 crops. Relationships with area and year of production were less clear, and directions of the relationships were more variable between crops. Strategies to improve fertilizer use efficiencies while maintaining or increasing yields are preferable in a GHG reduction programme.
Highlights
Climate change is one of the most pressing issues of our time (Pachauri et al, 2014)
Results of the one-way ANOVA revealed that differences be tween crops explained 45% of the variance of crop greenhouse gas (GHG) footprints, while the remaining variance was explained by the variability within crops (55%)
The negative relationship between GHG footprints of crops and yield, combined with the large contribution of fertilizer use emissions to GHG footprints, suggest that GHG footprints can be effectively reduced by closing yield gaps without increasing fertilizer use
Summary
Climate change is one of the most pressing issues of our time (Pachauri et al, 2014). For example, has developed a Sustainable Agriculture Code (SAC) (Smith et al, 2017), which requires suppliers and farmers to adopt a set of sustainable farming and sourcing practices based on 12 social, economic and envi ronmental themes, including: crop and pasture nutrient (fertilization) management, pest, disease and weed management, soil management, water management, biodiversity and ecosystem services, energy and GHG emissions, waste management, social aspects, animal husbandry, value chain, continuous improvement, and responsible sourcing. Under the energy and GHG emissions as well as the continuous improvement themes of the SAC, farmers are required to submit infor mation for calculating GHG footprints of crops using the Cool Farm Tool (Hillier et al, 2011). The Cool Farm Tool is a farm-level GHG calculator for estimating GHG emissions from agricultural
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