Datasets of a stormwater treatment train facility consisting of a gross pollutant trap and biofilters/sand filter in Sundsvall, Sweden

The data were collected from a stormwater treatment train facility in Sundsvall, Sweden. The facility consists of a gross pollutant trap (GPT) followed by three parallel biofilter cells: a vegetated, chalk-amended biofilter (BFC or F1), a non-vegetated sand filter (SF or F2), and a vegetated biofilter (BF or F3).
One of the objectives of our research project was to assess and monitor stormwater quality received from a major road catchment (incl. E4 highway bridge in Sundsvall) and also evaluate the performance of the various sections of the treatment train in removing organic micropollutants from the stormwater in terms of both inter- and intra-event variability.

The file named "StormwaterRunoffQualityData_SND.csv" contains event mean concentration (EMC) data on stormwater samples collected from 8 rain events (coded by A to H) in one year between September 2020 and September 2021. The samples have been analyzed for organic micropollutants and global water quality parameters (42 parameters in total). EMCs have been mathematically generated by a Monte-Carlo simulation from measured concentrations in sub-samples collected during each event. The data elaborate on the generated distribution for each EMC with Q2.5, Q50, and Q97.5 percentiles and standard deviation from the mean. Besides, the number of detected and non-detected (censored) data of sub-samples are mentioned. The list of all pollutants and their abbreviations are included in the documentation file named "StormwaterRunoffQualityData_SND.docx". Stormwater flow data are also presented in the file "VolumeData_Stormwater_SND.csv".

The file named "TreatmentTrainQualityData_SND.csv" presents event mean concentration (EMC) data not only for the stormwater runoff quality but also for the treated stormwater in the GPT-biofilter/sand filter treatment train downstream of the catchment. In addition to the untreated stormwater runoff as the system's inflow (SW), EMCs have been presented for 4 more sampling points: GPT outflow (GPT), vegetated, chalk-amended biofilter outflow (BFC), non-vegetated sand filter (SF), and vegetated biofilter outflow (BF). For this part of the research, a total of 11 rain events (coded by A to K) were covered from Sep. 2020 until Sep. 2021. The samples have been analyzed for organic micropollutants and other conventional water quality parameters (42 parameters in total). EMCs have been mathematically generated by a Monte-Carlo simulation from measured concentrations in sub-samples collected during each event. The data present a distribution for each EMC with Q2.5, Q50, and Q97.5 percentiles and standard deviation from the mean. The number of detected and non-detected (censored) data of sub-samples is also mentioned. The list of all pollutants and their abbreviations are included in the documentation file named "TreatmentTrainQualityData_SND.docx". Flow data are also presented in the file "VolumeData_Treatment train_SND.csv".

The file entitled "Intra-event Data_SND.csv" includes intra-event concentration data for stormwater runoff and effluents of the GPT-biofilter/sand filter treatment train. These data represent the concentrations measured for the subsamples taken at an chronological order (subsample #no. and time in the file) during each event. The corresponding flow volume passed (in m3 and % of total volume) at a certain sampling point are also included in the file. A total of 11 rain events (coded by A to K) were covered between Sep. 2020 and Sep. 2021 on the sampling dates mentioned in the file. Show less..