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Spatial and technological variability in the carbon footprint of durum wheat production in Iran
- Heidari, Mohammad Davoud, Mobli, Hossein, Omid, Mahmoud, Rafiee, Shahin, Jamali Marbini, Vahid, Elshout, Pieter M. F., Van Zelm, Rosalie, Huijbregts, Mark A. J.
- The international journal of life cycle assessment 2017 v.22 no.12 pp. 1893-1900
- biomass, carbon, carbon footprint, carbon sinks, correlation, crop yield, durum wheat, farms, fertilizer application, fertilizers, fossils, greenhouse gas emissions, greenhouse gases, irrigation, life cycle assessment, losses from soil, mechanization, nitrous oxide, pesticides, seeds, soil, tillage, transportation, Iran
- PURPOSE: The purpose of this study was to quantify the spatial and technological variability in life cycle greenhouse gas (GHG) emissions, also called the carbon footprint, of durum wheat production in Iran. METHODS: The calculations were based on information gathered from 90 farms, each with an area ranging from 1 to 150 ha (average 16 ha). The carbon footprint of durum wheat was calculated by quantifying the biogenic GHG emissions of carbon loss from soil and biomass, as well as the GHG emissions from fertilizer application and machinery use, irrigation, transportation, and production of inputs (e.g., fertilizers, seeds, and pesticides). We used Spearman’s rank correlation to quantify the relative influence of technological variability (in crop yields, fossil GHG emissions, and N₂O emissions from fertilizer application) and spatial variability (in biogenic GHG emissions) on the variation of the carbon footprint of durum wheat. RESULTS AND DISCUSSION: The average carbon footprint of 1 kg of durum wheat produced was 1.6 kg CO₂-equivalents with a minimum of 0.8 kg and a maximum of 3.0 kg CO₂-equivalents. The correlation analysis showed that variation in crop yield and fertilizer application, representing technological variability, accounted for the majority of the variation in the carbon footprint, respectively 76 and 21%. Spatial variation in biogenic GHG emissions, mainly resulting from differences in natural soil carbon stocks, accounted for 3% of the variation in the carbon footprint. We also observed a non-linear relationship between the carbon footprint and the yield of durum wheat that featured a scaling factor of −2/3. This indicates that the carbon footprint of durum wheat production (in kg CO₂-eq kg⁻¹) typically decreases by 67% with a 100% increase in yield (in kg ha⁻¹ year⁻¹). CONCLUSIONS: Various sources of variability, including variation between locations and technologies, can influence the results of life cycle assessments. We demonstrated that technological variability exerts a relatively large influence on the carbon footprint of durum wheat produced in Iran with respect to spatial variability. To increase the durum wheat yield at farms with relatively large carbon footprints, technologies such as site-specific nutrient application, combined tillage, and mechanized irrigation techniques should be promoted.