# Hyperspectral Imaging Sorting of Refurbishment Plasterboard Waste
## 5 Conclusions  
A laboratory-scale hyperspectral imaging classification system has been evaluated for the first time as an automatic sorting process for refurbishment plasterboard waste. The HSI classification system was trained with manually segregated components of a batch of refurbishment plasterboard waste. Then, another batch of refurbishment plasterboard waste was processed to validate the HSI classification process. The main conclusions of this study are:  
1. The chemical purity of gypsum obtained from HSI-sorted plasterboard and from manually sorted plasterboard was similar;
2. The plasterboard recovery yield attained with the HSI-based sorting system, relative to the plasterboard in the input material, was above 98 wt%;
3. The chemical purity of the gypsum in the refurbishment plasterboard waste particles <10 mm in size was similar to that of the gypsum obtained from the plasterboard in the sorted product (95.8 wt%). Therefore, the unprocessed refurbishment plasterboard waste with particles <10 mm could be combined with the HSI-sorted product material to be used as the feedstock of the sulfuric acid leaching purification process.  
Overall, the laboratory-scale HSI-based classification system has been proved to be an efficient sorting process for refurbishment plasterboard waste. The findings reveal the potential industrial application of the HSI-based sorting process for the segregation of refurbishment plasterboard waste, at a lower cost, lower exposure of workers to health risks (e.g., fines) and higher capacity than with manual segregation. Further research should focus on the scalability of the HSI-based sorting process for industrial applications. In this respect, the impact of process parameters, such as conveyor speed, amount of input material on the conveyor and particle size distribution, on plasterboard recovery yield should be determined. Furthermore, potential technical issues that could hinder the efficiency of the HSI-based sorting system, such as the deposition of gypsum dust on the HSI camera over time and operating costs, should be evaluated.  
**Author Contributions:** Conceptualization, M.O., S.C., I.C. and I.U.; methodology, M.C.-D., I.C. and I.U.; software, I.C. and I.U.; validation, M.C.-D., I.C. and I.U.; formal analysis, M.C.-D., I.C. and I.U.; investigation, M.C.-D., I.C. and I.U.; resources, I.C., I.U., P.N., J.T., B.P. and T.L.; data curation, I.C. and I.U.; writing--original draft preparation, M.C.-D., I.C. and I.U.; writing--review and editing, M.C.-D., M.O., S.C., I.C., I.U., P.N. and B.P.; supervision, M.O., S.C. and I.C.; project administration, M.O., S.C. and I.C.; funding acquisition, M.O., S.C. and I.C. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the European Union's Horizon 2020 research and innovation program under grant agreement No. 869336.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Acknowledgments:** The authors would like to acknowledge the use of XRF facilities within the Loughborough Materials Characterization Centre at Loughborough University.  
**Conflicts of Interest:** The authors declare no conflict of interest.