Published January 8, 2022 | Version v1
Dataset Open

LC-HRMS files from wastewater samples collected in Portugal

Creators

  • 1. Universidade de Santiago de Compostela
  • 2. Universidade do Porto
  • 3. EFACEC
  • 4. University of Arizona

Description

LC-HRMS files corresponding to wastewater samples associated to the paper:

M.F.T. Sá et al. Tracking pollutants in a municipal sewage network impairing the operation of a wastewater treatment plant. Science of the Total Environment, 2022, 817, 152518. DOI: 10.1016/j.scitotenv.2021.152518

These files contain the LC-QTOF-HRMS data associated with the manuscript:

Please note:

Data was acquired with an Agilent 6550 QTOF in both:
- AutoMSMS (data-dependent acquisition, DDA) 
- All Ions (data-independent acquisition, DIA)

Data is provided in Agilent MassHunter B.10.00 format.

In the case of AutoMSMS the iterative mode with two injections per sample was employed.
Further details on how samples were processed is presented in the manuscript.

Data is therefore structure in two folders, one for DDA and one for DIA.
Each folder is then further divided between positive and negative mode.

Files are named accordingly to the sample, using the same codes than in the manuscript.
The number after the code refers to the sample campaign.
Besides, there are "A" and "B" files in the DDA files, corresponding to the first and second iterative injection, respectively.

As an example, the file:
"PVZ-2 2_B.d" in the AutoMSMS_DDA (either pos or neg) folder:
corresponds to the sample PVZ-2 from the second sampling campaign and second injection

If you reuse this data, please cite this dataset (DOI: 10.5281/zenodo.5830725) and the orginal article cited above (DOI: 10.1016/j.scitotenv.2021.152518)

Notes

This work was financially supported by: i) Base-UIDB/50020/2020 and Programmatic-UIDP/50020/2020 Funding of LSRE-LCM, funded by national funds through FCT/MCTES (PIDDAC); ii) European Regional Development Fund through the Interreg V-A Spain-Portugal Programme (POCTEP) 2014–2020 (ref. 0725_NOR_WATER_1_P); iii) Xunta de Galicia (Verónica Castro predoctoral contract: ED481A-2017/156, and ED431C2017/36), the Spanish Agencia Estatal de Investigación – MCIN/AEI/ 10.13039/501100011033 (ref. PID2020-117686RB-C32); iv) NORTE-01-0145-FEDER-000069 (Healthy Waters) co-funded by European Regional Development Fund (ERDF), through North Portugal Regional Operational Programme (NORTE2020), under the PORTUGAL 2020 Partnership Agreement. The authors also acknowledge Águas do Norte, S.A. for supporting the development of this work. Daniela F.S. Morais acknowledges her Ph.D. scholarship supported by FCT (SFRH/BD/146476/2019). Bianca M. Souza Chaves gratefully acknowledges her postdoctoral scholarship supported by CNPq through the Science Without Borders Program (Process No. 201989/2014-0). Vítor J.P. Vilar acknowledges the FCT Individual Call to Scientific Employment Stimulus 2017 (CEECIND/01317/2017). It must be stated that this work only reflects the author's view; thus Program authorities are not liable for any use that may be made of the information contained therein.

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Portugal_wastewater_LCHRMS_dataset.zip

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