A harmonised systems-wide re-analysis of greenhouse gas emissions from sunflower oil production

Sunflower (Helianthus annuus L.) is the largest source of vegetable oil in Europe and the fourth largest globally. Intensive cultivation and post-harvest steps contribute to global food-systems’ greenhouse gas (GHG) emissions. However, variation between production systems and reporting disparity have resulted in discordance in previous emissions estimates. To assess systems-wide GHG implications of meeting increasing edible oil demand using sunflower, we performed a unified re-analysis of primary life cycle inventory data, representing 995 farms in 11 countries, from a saturating search of published literature. Total GHG emissions varied from 1.1 to 4.2 kg CO2-equivalent per kg oil across systems, 62% of which originated from cultivation. Major emissions sources included diesel- and fertiliser-use, with irrigation electricity contributing most to between-systems variation. Our harmonised, cross-study re-analysis not only enabled robust comparisons and identification of mitigation opportunities across sunflower oil production systems, but also lays the groundwork for comparisons between alternative oil crops.

Toward Standards-Based Generation of Reusable Life Cycle Inventory Data Models for Manufacturing Processes

The production stage of a product's life cycle can significantly contribute to its overall environmental impact. Estimates of environmental impact for a product are typically produced using life cycle assessment (LCA) methods. These methods rely on life cycle inventory (LCI) data containing impact estimates of manufacturing processes and other operations that contribute to a product's creation. The accuracy of LCI data is critical for quality assessments; however, these data are often insufficient in the types and varieties of manufacturing processes covered and are often only a coarse estimate of actual impacts. At the same time, much manufacturing research focuses on how to model, measure, assess, and reduce the environmental impacts of manufacturing processes. Recent standards emerging from ASTM International define a structured format for presenting these studies in a reusable way. In this paper, we investigate the potential for using the ASTM E3012-16 format to generate LCI datasets suitable to perform LCA by mapping from the ASTM standard into the widely adopted ecoSpold2 format. A process is presented for generating LCI datasets from ASTM models, and overlaps and gaps between the two standards are identified.

Environmental sustainability assessment of HMF and FDCA production from lignocellulosic biomass through life cycle assessment (LCA)

2,5-Furandicarboxylic acid (FDCA) and 5-hydroxymethylfurfural (HMF) are top biomass-based platform chemicals with promising potential and an essential part of the future of green chemistry. HMF can be obtained mainly from fructose or glucose. Lignocellulosic glucose has a high production potential from not edible biomass. In the present paper life cycle assessment (LCA) was performed aiming at a better understanding of the environmental performance of the production of FDCA and HMF from lignocellulosic feedstock. Two case studies from the literature were modeled to obtain the life cycle inventory data. The production routes to FDCA comprise seven different process sections: hydrolysis, HMF synthesis, HMF recovery, FDCA synthesis, FDCA flash separation, FDCA purification and HMF boiler. By means of the LCA methodology, solvents such as dimethyl sulfoxide (DMSO) and dichloromethane (DCM), together with the energy demand, were found to be clear critical points in the process. Two scenarios were in focus: Scenario 1 considered the purification of FDCA through crystallization, whereas in Scenario 2 purification was performed through distillation.