## 4 Conclusions  
A low-cost method for quantitation of multiple VOCs in ambient air using SPME-GC-MS was developed. It was proven that 65 \(\upmu\)m PDMS/DVB fiber provides a better combination of detection limits, accuracy and precision compared to 85 \(\upmu\)m Car/PDMS, 100 \(\upmu\)m PDMS and 50/30 \(\upmu\)m DVB/Car/PDMS. The increase in extraction time above 10 min did not have a significant impact on the responses of analytes. Optimal desorption time is 1 min. For quantification of all analytes, except undecane, vials with samples should not stand on the autosampler tray for more than 8 h. Quantification of 22 of the most stable analytes can be conducted during 24 h after sampling. Spike recoveries of 21 of the 25 chosen analytes were 90-105%. Recoveries of other analytes were 51-89% at RSDs of 7.4-43%.  
The developed method was successfully applied for quantification of chosen analytes in atmospheric air of Almaty in Spring, 2019. On average, the completely automated analysis of one sample took 50-60 min, which was enough to analyze 24 (18 air + 6 calibration) air samples per day. All analytes were detected, except methyl ethyl ketone and 1,2-dichloroethane. RSDs of the responses of 23 VOCs varied from 0.1% to 15.6%. The use of three replicate samples allowed identifying outliers. For 18 detected analytes, the fraction of outliers was \(<\)18%. Results for the other five detected analytes contained 10-20% outliers. Mean concentrations of 23 VOCs during all sampling times ranged from 0.1 to 83 \(\upmu\)m\({}^{-3}\). Toluene-to-benzene concentrations ratios were below 1.0 in colder days of sampling, indicating that most BTEX in these days originated from non-transport-related sources. The obtained results prove that the method is very simple, automated, low-cost and provides sufficiently low detection limits, which allow recommending it for monitoring of a wide range of VOCs in atmospheric air of Almaty and other similar cities. The measured concentrations cannot be used to generalize the air pollution problem in Almaty because additional research is needed for this purpose. These data along with the developed method can be useful for improving the air pollution monitoring program in Almaty.  
The following are available online at [[http://www.mdpi.com/2297-8739/6/4/51/s1](http://www.mdpi.com/2297-8739/6/4/51/s1)]([http://www.mdpi.com/2297-8739/6/4/51/s1](http://www.mdpi.com/2297-8739/6/4/51/s1)), Figure S1: Chromatogram obtained using the developed method based on SPME-GC-MS of air sample with \(C_{add}=100\)\(\upmu\)g m\({}^{-3}\). Figure S2: Effect of desorption time on responses of analytes, Table S1: The list of chosen VOCs and its physical properties, Table S2: Coordinates of sampling locations, Table S3: Weather conditions on sampling days, Table S4: Probabilities of difference between initial responses of analytes and their responses after different storage times, Table S5: Sampling locations where lowest and highest concentrations of analytes were determined at different sampling times.  
Conceptualization, B.K. and N.B.; methodology, O.P.I. and N.B.; validation, O.P.I., N.B. and B.K.; formal analysis, O.P.I., N.B. and B.K.; investigation, O.P.I. and N.B.; writing--original draft preparation, O.P.I. and N.B.; writing--review and editing, B.K.; visualization, O.P.I., N.B. and B.K.; supervision, B.K.; project administration, N.B.; funding acquisition, B.K.  
This research was funded by the Ministry of Education and Science of the Republic of Kazakhstan, grant number AP05133158.  
The authors would like to thank Al-Farabi Kazakh National University for the postdoctoral scholarship of [PERSON], and a Ph.D. student of Al-Farabi Kazakh National University, [PERSON], for technical support during this study.  
The authors declare no conflict of interest.