## 5 Conclusions  
We optimised the detection of VOCs in urine using HS-SPME-GC-MS by altering pH, H\({}_{2}\)SO\({}_{4}\) concentration, and phase ratio. This is the first direct comparison of H\({}_{2}\)SO\({}_{4}\), HCl, and NaOH as treatment techniques prior to HS-SPME-GC-MS analysis. Altering urine sample pH indicates that H\({}_{2}\)SO\({}_{4}\) is more effective at optimising detection of VOCs than NaOH or HCl. H\({}_{2}\)SO\({}_{4}\) resulted in a significantly larger mean number of VOCs being identified per sample and more unique VOCs, produced more VOCs with significantly greater abundance than their counterparts, produced a more diverse range of classes of VOCs, and led to less HS-SPME-GC-MS degradation. We propose that adding 0.2 mL of 2.5 M H\({}_{2}\)SO\({}_{4}\) to 1 mL of urine within a 10 mL headspace vial is the optimal sample preparation prior to HS-SPME-GC-MS analysis. We hope the use of our optimised method for urinary HS-SPME-GC-MS analysis will enhance our understanding of human disease and bolster metabolic biomarker identification.  
The following are available online at [[http://www.mdpi.com/2218-1989/10/12/482/s1](http://www.mdpi.com/2218-1989/10/12/482/s1)]([http://www.mdpi.com/2218-1989/10/12/482/s1](http://www.mdpi.com/2218-1989/10/12/482/s1)), Figure S1: Number of VOCs detected when altering pH or ionic strength using saturated NaCl solution. Figure S2: Equipment stability of the HS-SPME-GC-MS over time using 5 M H\({}_{2}\)SO\({}_{4}\). Table S1: The final local library containing 173 unique VOCs. Please note this is an.MSL file. Table S2a: A full list of CV values for VOCs detected using urine plus HCl. Table S2c: A full list of CV values for VOCs detected using urine plus NaOH. Table S3: The full breakdown of classification of VOCs. Table S4: The full breakdown of classification of VOCs per treatment group.  
Conceptualization, E.A.C. and C.P.; methodology, E.A.C.; software, E.A.C., J.B., and P.A.; validation, E.A.C., J.B., and P.A.; formal analysis, J.B. and P.A.; investigation, J.B. and P.A.; resources, C.P.; data curation, J.B., P.A., and E.C.; writing--original draft preparation, J.B. and P.A.; writing--review and editing, E.A.C., C.P., S.C., M.T.B., J.B., and P.A.; visualization, J.B., P.A., and E.A.C.; supervision, C.P. and E.A.C.; project administration, E.A.C.; funding acquisition, C.P., S.C., M.T.B., and E.A.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Wellcome Trust and North West Cancer Research, grant numbers 202022/16/Z and SI2018.11 respectively. Both grants were held at The University of Liverpool. [PERSON] was funded by a Wellcome Trust Seed Award in Science, 'Biology of Dying' [202022/Z/16/Z] and North West Cancer Research [NNCR] grant, Title: Method optimisation of urine GC-MS analysis to predict dying in lung cancer patients [SI2018.11]. [PERSON] received funding from the Wolfson foundation intercalation award. Both [PERSON] and [PERSON] received a bursary from North West Cancer Research (NWCR). The APC was funded by Wellcome Trust Fund Block Grant, University of Liverpool.  
Authors would like to thank [PERSON] and [PERSON] for their support.  
The authors declare no conflict of interest.