Maleic anhydride production from renewables: a life cycle assessment at pilot scale

Maleic anhydride (MA) represents one of the most intersting and diffused commodities worldwide, with a potential market volume of 3.40Mt in 2029. 1 Here we proposed the application of the E factor and the Life Cycle Assessment (LCA) methodology to two bio based pathways for the production of MA, by selecting 1000 kg as functional unit (FU). We investigated the production from bio butanol (bio ButOH MA) and from bio furfural (bio Furf MA). In both cases dedicated biomasses were used to feed the pilot plants, since it represents a more realistic scenario. In the bio ButOH MA pathway the system was modelled by assuming the usage of maize, sugarcane and switchgrass (Panicum virgatum) in equal amount. On the contrary, in the case bio Furf it is assumed the precur sor derive 100% from switchgrass. The study considers two levels of analysis for Ef and LCA. In the first case (Level I Ef) MA is considered the sole valuable output; during Level II Ef level other co products are included within the mass allocation. In th e case of LCA, first level (Level IEN) represents the simplest situation, in which no energy recovery is considered within the system boundaries. In second assessment level (Level IIEN) it is assumed that 100% of the heat released by the reaction (extremel y exothermic) is recovered to feed the plant and co produce steam (available for other commodities). In both cases the production of MA from bio Furf results more competitive. Life cycle impact assessment phase, evaluated in terms of carbon footprint (IPCC ), cumulative energy demand (CED) and following a multi impact approach (ReCiPe method), confirms the scores achieved from the application of the Ef. In fact, the higher selectivity of the catalytic system used to convert bio Furf into MA implies a lower a mount of raw materials per FU with a consequent minor potential impacts on the several impact categories considered. Results, also confirmed by Monte Carlo analysis, could be used to set future improvements and supporting the design or the retrofit of inno vative industrial plants able to enhance the whole efficiency.