Greenhouse gas emissions from inorganic and organic fertilizer production and use: A review of emission factors and their variability.

Fertilizers have become an essential part of our global food supply chain and are necessary to sustain our growing population. However, fertilizers can also contribute to greenhouse gas (GHG) emissions, along with other potential nutrient losses in the environment, e.g. through leaching. To reduce this environmental impact, tools such as life cycle assessments and decision support systems are being used to aid in selecting sustainable fertilization scenarios. These scenarios often include organic waste-derived amendments, such as manures, composts and digestates. To produce an accurate assessment and comparison of potential fertilization scenarios, these tools require emission factors (EFs) that are used to estimate GHG emissions and that are an integral part of these analyses. However, such EFs seem to be very variable in nature, thereby often resulting in high uncertainty on the outcomes of the analyses. This review aims to identify ranges and sources of variability in EFs to provide a better understanding of the potential uncertainty on the outcomes, as well as to provide recommendations for selecting EFs for future studies. As such, an extensive review of the literature on GHG emissions from production, storage, transportation and application of synthetic fertilizers (N, P, K), composts, digestates and manures was performed. This paper highlights the high variability that is present in emissions data and confirms the great impact of this uncertainty on the quality and validity of GHG predictions related to fertilizers. Variability in EFs stem from the energy source used for production, operating conditions, storage systems, crop and soil type, soil nutrient content, amount and method of fertilizer application, soil bacterial community, irrigation method, among others. Furthermore, a knowledge gap exists related to EFs for potassium fertilizers and waste valorization (anaerobic digestion/composting) processes. Overall, based on this review, it is recommended to determine EFs on a case by case basis when possible and to use uncertainty analyses as a tool to better understand the impact of EF variability.