# LCA Practices of Plastics and Their Recycling: A Critical Review
## 2 The Methodological Foundations and Advances in Life Cycle Assessment
### Types of LCA
#### 2.2.4 Ex-ante LCA and Multi Method Approaches  
As interest in LCA related methods and applications has risen throughout the last decades, so have the number of publications and methodological advances in the field. Recently, [48] discussed an application referred to as 'ex-ante' LCA. Rather than performing an 'ex-post' LCA, the 'ex-ante' approach helps assess the projected future of emerging technologies. This can be an instrumental tool in aiding technology design and development, as early decisions in the design process often have far reaching consequences in the future. Therefore, early decision support through ex-ante LCA can be instrumental  
Figure 2: The effects of displacing coal with wood on changes in atmospheric CO\({}_{2}\) concentration. (**a**) Displacing coal with wood cut from south-central oak-hickory forest; (**b**) displacing coal with wood cut from south-central managed shortleaf loblolly. Figure taken from [44]. in minimizing important footprints. The authors define ex-ante LCA as being studies that compare scaled-up emerging technologies with evolved incumbent technologies and scaled-up emerging technologies based on likely scenarios in terms of their future performance when operational. In the context of bio-based chemicals, [49] found that when starting at the process design phase of a new production process, ex-ante LCA yielded good predictions of hotspots. This allows for an early identification of major contributions to the emissions pertaining to a product's life cycle. In another paper, [50] reviewed case studies pertaining to ex-ante LCA and proposed a framework wherein the emerging technology should be compared with an incumbent technology and interact with the background system at three different moments in time: the current situation, the time at which the emerging technology reaches maturity, and, finally, a point in time where the mature technology was implemented for a while already. In terms of categorizing modelled aspects in their reviewed articles, they used the categories 'Technology Development', 'Technological Learning', and 'Technology Diffusion'. The majority of studies in their review sample only partially modelled at most two of these aspects, while all are relevant in assessing the prospects of emerging technologies. Due to its forward looking nature and evaluation of an emerging technology, ex-ante LCA facilitates the practice of combining LCA with other methods such as technoeconomic analysis (TEA), life cycle costing (LCC), social life cycle assessment (sLCA), multi criteria decision analysis (MCDA), and others. Recently, [51] wrote a review on LCA of emerging technologies and discussed the use of such and other methods in conjunction with LCA, as well as the challenges that exist in performing LCA on emerging technologies at early development stages. They identified an opportunity in further integration of LCA with TEA. In other work, [24] systematically reviewed papers on prospective LCA for emerging technologies. Even though they did not refer to these LCA studies as 'ex-ante', many of them fit this terminology considering their scope and aim. They found that there was a marked increase in such applications in recent years, but point out that there exists a lot of uncertainty regarding transparency and justification of data quality in the applications they reviewed. The same goes for system boundaries and how uncertainty was handled. Figure 3: Greenhouse gas (GHG) emissions of wood displacing coal. (**a**) The net CO\({}_{2}\) savings per end-use energy under varying assumptions of key parameters; (**b**) equal to (**a**) but zoomed in. Figure taken from [45]. They call for a more standardized approach in order to improve comparability between such studies. In other LCA studies where the aim is not necessarily to perform an ex-ante study, there are ample opportunities to apply other methods to support or extend the analysis.