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Major sources of greenhouse gas (GHG) emissions from agricultural crop production are nitrous oxide (N2O) emissions resulting from the application of mineral and organic fertilizer, and carbon dioxide (CO2) emissions from soil carbon losses. Consequently, choice of fertilizer type, optimizing fertilizer application rates and timing, reducing microbial denitrification and improving soil carbon management are focus areas for mitigation. We have integrated separate models derived from global data on fertilizer‐induced soil N2O emissions, soil nitrification inhibitors, and the effects of tillage and soil inputs of soil C stocks into a single model to determine optimal mitigation options as a function of soil type, climate, and fertilization rates. After Monte Carlo sampling of input variables, we aggregated the outputs according to climate, soil and fertilizer factors to consider the benefits of several possible emissions mitigation strategies, and identified the most beneficial option for each factor class on a per‐hectare basis. The optimal mitigation for each soil‐climate‐region was then mapped to propose geographically specific optimal GHG mitigation strategies for crops with varying N requirements. The use of empirical models reduces the requirements for validation (as they are calibrated on globally or continentally observed phenomena). However, as they are relatively simple in structure, they may not be applicable for accurate site‐specific prediction of GHG emissions. The value of this modelling approach is for initial screening and ranking of potential agricultural mitigation options and to explore the potential impact of regional agricultural GHG abatement policies. Given the clear association between management practice and crop productivity, it is essential to incorporate characterization of the yield effect on a given crop before recommending any mitigation practice.

Purpose Greenhouse gas (GHG) emissions have been identified as one of Unilever's priority environmental impact themes: this assessment was therefore conducted to help the Knorr brand measure and understand the GHG emissions related to its product portfolio, identify opportunities to manage GHG emissions in the Unilever-owned operations (manufacture) and influence managed reductions elsewhere in the Knorr product lifecycles, and assess the impact of the brand's innovation and portfolio strategies on its GHG footprint. Methods A bottom-up product-based life cycle assessment (LCA) approach was considered impractical to assess Knorr's portfolio's complexity. Thus, a meta-product-based accounting LCA approach was followed (Milà i Canals et al. 2009). Up to 16 product types or "meta-products" were assessed in each geographical region, with a total of 36 meta-products assessed globally. Then, the Knorr GHG footprint was derived by multiplying the impacts calculated per tonne of each product type with the sales volumes in 2007. Data for ingredients and processing technologies were gathered from the literature and suppliers; data from Knorr factories were used for the manufacturing stage. The variability in ingredients' production and processing and in manufacture was factored in and propagated through the calculations to assess the robustness of the results. Results The profiles of different meta-products within a product group (e.g. dry soups) follow similar patterns in terms of absolute GHG per tonne and distribution of such emissions along the life cycle. Variations are observed due to recipe composition and electricity mixes in the different regions. The range of variability around absolute results is significant and varies between meta-products. Aggregating the results for individual meta-products with their production volumes, the global Knorr brand GHG footprint in 2007 was estimated to be in the region of 3-5 million tonnes CO 2 e/ annum (95% confidence interval). In spite of the significant variability ranges found, the results are useful for target setting and identification of opportunities for improvement. Conclusions This is the world's first life cycle GHG assessment at brand's product portfolio level. The metaproduct approach simultaneously allows for the assessment and comparison of individual product types as well as for the estimation of a brand's total GHG. The variability assessment enhanced robustness of the results by identifying a confidence range; given the complexity of the studied supply chains and the current data quality translated in wide confidence ranges, single number on-pack carbon labels seem questionable and not robust enough to inform consumers.

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