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Incorporating denitrification-decomposition method to estimate field emissions for Life Cycle Assessment
- Deng, Yelin, Paraskevas, Dimos, Cao, Shi-Jie
- The Science of the total environment 2017 v.593-594 pp. 65-74
- Monte Carlo method, acidification, climate, climate change, emissions factor, eutrophication, flax, greenhouse gas emissions, greenhouse gases, inventories, life cycle inventory, models, nitrogen, nitrous oxide, particulates, soil types, straw, uncertainty, France
- This study focuses on a detailed Life Cycle Assessment (LCA) for flax cultivation in Northern France. Nitrogen related field emissions are derived both from a process-oriented DeNitrification-DeComposition (DNDC) method and the generic Intergovernmental Panel on Climate Change (IPCC) method. Since the IPCC method is synthesised from field measurements at sites with various soil types, climate conditions, and crops, it contains significant uncertainties. In contrast, the outputs from the DNDC method are considered as more site specific as it is built according to complex models of soil science. As it is demonstrated in this paper the emission factors from the DNDC method and the recommended values from the IPCC method exhibit significant variations for the case of flax cultivation. The DNDC based emission factor for direct N2O emission, which is a strong greenhouse gas, is 0.25–0.5%, significantly lower than the recommend 1% level derived from the IPCC method. The DNDC method leads to a reduction of 17% in the impact category of climate change per kg retted flax straw production from the level obtained from the IPCC method. Much higher reductions are recorded for particulate matter formation, terrestrial acidification, and marine eutrophication impact categories. Meanwhile, based on the DNDC and IPCC methods, a comparative LCA per kg flax straw is presented. For both methods sensitivity analysis as well as comparison of uncertainties parameterisation of the N2O estimates via Monte-Carlo analysis are performed. The DNDC method incorporates more relevant field emissions from the agricultural life cycle phase, which can also improve the quality of the Life Cycle Inventory as well as allow more precise uncertainty calibration in the LCA inventory.