Performance and environmental accounting of nutrient cycling models to estimate nitrogen emissions in agriculture and their sensitivity in life cycle assessment

Purpose Several models are available in the literature to estimate agricultural emissions. From life cycle assessment (LCA) perspective, there is no standardized procedure for estimating emissions of nitrogen or other nutrients. This article aims to compare four agricultural models (PEF, SALCA, Daisy and Animo) with different complexity levels and test their suitability and sensitivity in LCA. Methods Required input data, obtained outputs, and main characteristics of the models are presented. Then, the performance of the models was evaluated according to their potential feasibility to be used in estimating nitrogen emissions in LCA using an adapted version of the criteria proposed by the United Nations Framework Convention on Climate Change (UNFCCC), and other relevant studies, to judge their suitability in LCA. Finally, nitrogen emissions from a case study of irrigated maize in Spain were estimated using the selected models and were tested in a full LCA to characterize the impacts. Results and discussion According to the set of criteria, the models scored, from best to worst: Daisy (77%), SALCA (74%), Animo (72%) and PEF (70%), being Daisy the most suitable model to LCA framework. Regarding the case study, the estimated emissions agreed to literature data for the irrigated corn crop in Spain and the Mediterranean, except N2O emissions. The impact characterization showed differences of up to 56% for the most relevant impact categories when considering nitrogen emissions. Additionally, an overview of the models used to estimate nitrogen emissions in LCA studies showed that many models have been used, but not always in a suitable or justified manner. Conclusions Although mechanistic models are more laborious, mainly due to the amount of input data required, this study shows that Daisy could be a suitable model to estimate emissions when fertilizer application is relevant for the environmental study. In addition, and due to LCA urgently needing a solid methodology to estimate nitrogen emissions, mechanistic models such as Daisy could be used to estimate default values for different archetype scenarios.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713679 and from the Universitat Rovira i Virgili (URV).Peer ReviewedPostprint (published version

Characterisation of emissions from a cow manure anaerobic codigestion plant

Postprint (published version

Integration of environment and nutrition in life cycle assessment of food items: opportunities and challenges

This report is the outcome of a consensus-building project to agree on best practices for environmental and nutritional Life Cycle Assessment (nLCA) methodology, and identify future research needs. The project involved 30 nutritional and environmental LCA researchers from 18 countries. It focused on the assessment of food items (as opposed to meals or diets).Best practice recommendations were developed to address the intended purpose of an LCA study and related modeling approach, choice of an appropriate functional unit, assessment of nutritional value, and reporting nLCA results. An nLCA study should report the quantities of as many essential nutrients as possible and aim to provide information on the nutritional quality and/or health impacts in addition to nutrient quantities. Outstanding issues requiring further research attention include: defining a minimum number of nutrients to be considered in an nLCA study; treatment of nutrients to limit; use of nutrient indexes; further development of Impact Assessment methods; representation of nutritional changes that may occur during subsequent distribution and food preparation in cradle-to-gate nLCA studies; and communication of data uncertainty and variability. More data are required for different regions (particularly developing countries); for the processing, distribution, retail, and consumption life cycle stages; and for food loss and waste. Finally, there is a need to extend nLCA methodology for the assessment of meals and diets, to consider further how to account for the multi-functionality of food in a sustainability framework, and to set nLCA studies within the context of environmental limits.These results provide a robust basis for improving nLCA methodology and applying it to identify solutions that minimize the trade-offs between nourishing populations and safeguarding the environment