Sustainable technology has become increasingly important as a result of global environmental issues. Meanwhile, new technologies tend to be more expensive and have larger environmental impacts than established technologies. The reason is a first-time production process is less smooth than a production process that has been in operation for years. Biorefinery system requires a significant investment in terms of capital expenditures (CAPEX) as well as feedstock inputs. Therefore, R&D and experience are important in estimating the cost-saving potential of building a growing number of biorefinery plants which are comprised of a mix of established and innovative technologies. To the best of our knowledge, this study is the first to describe how superstructure-based biorefineries could grow in the future by integrating prospective LCA with scenario methodology and prospective economic analysis explained by learning effects. It can provide valuable information to stakeholders about the estimated economic investment and environmental assessment to achieve the European Commission's goals in 2050. In this study we employ a theoretical framework for prospective economic assessments based on the "learning curve theory" to estimate cost reduction due to technological implementation, measured in terms of numbers or capacities of units. In this framework learning theory is employed through a multi-component analysis approach. This approach involves systematically breaking down the complete production process. The aim is to pinpoint both established and innovative technological components. These components are then analysed in depth using the corresponding techno-economic data. Prospective LCA, which tries to analyse the environmental performance of technologies in the future, has recently received a lot of attention. The evolution of the future background scenarios that result from a combination of the ecoinvent database and the integrated assessment models (IAMs) has a significant impact on the outcome of LCA studies. IAMs, such as the shared socio-economic pathways (SSPs), often execute globally consistent future scenarios that span probable evolutions of society and ecosystems over a century timeline. Scenarios development is a systematic and documented approach that includes the steps of aim and scope determination as well as inventory analysis. An open source software Activity-Browser (AB) is used to conduct the prospective LCA. The core part of the applicable technique is scenario generation during the inventory analysis phase, which represents both descriptions of possible future states and descriptions of events influencing both the LCI's foreground and background data. GAMS software is used to solve the multi-objective optimization model in terms of economic and environmental perspective. These prospective strategies could lead in a clearer view on the environmental effect and cost structure of the new technology, as well as a more equitable comparison basis with traditional technologies, thus leading in faster acceptance and shorter time to market for sustainable solutions.