PFAS and nitrate leaching from undisturbed soil columns receiving biosolids and mitigation potential of biochar
Data files
Jan 23, 2024 version files 217.31 KB
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Holly_et_al_2023_leaching_data.xlsx
210.62 KB
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README_Holly_et_al_2023_leaching_data.md
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README.md
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Abstract
Land application of biosolids recycles nutrients and reduces the need for commercial fertilizers. However, per- and polyfluoroalkyl substances (PFAS) may leach from biosolids, resulting in groundwater contamination. We measured PFAS leaching from land-applied biosolids through undisturbed soil column trials and evaluated the treatment potential of amending biosolids with biochar. Synthetic rainfall was applied weekly to undisturbed soil columns from four regions in Wisconsin, including two fields with a history of biosolids application, simulating annual precipitation. The treatments consisted of a control (soil only), soil amended with biosolids, and soil receiving a mixture of biosolids and biochar. Concentrations of total PFAS in leachate were significantly affected by soil location and site history, while only long chain PFAS concentrations were significantly affected by biosolids/biochar treatments. One-time application of biosolids may result in groundwater contamination, as PFAS concentrations in leachate exceeded the local groundwater standard (a combined perfluorooctanoic acid and perflourooctanesulfonic acid groundwater concentration of 20 ng L-1) at three locations. Legacy PFAS may pose a risk to human health years after biosolid application, as a control column from a site with an intensive history of biosolid application exceeded PFAS groundwater standards. Incorporation of biochar with biosolids during application mitigated PFAS (specifically from soils with elevated leaching potential) through significant reductions of C7 – C10 perfluoroalkyl carboxylic acids and C4, C6 – C8 perfluorosulfonic acids (40 to 64% reduction in measured Σ28 PFAS). Biochar may facilitate sustainable use of biosolids through mitigation of long-chain PFAS leaching, pending long-term field evaluation.
README
Holly, A.H., Gunn, K.M., Keymer, D., Sanford, J.R. Evaluation of Per- and Polyfluoroalkyl Substances Leaching from Biosolids and Mitigation Potential
of Biochar through Undisturbed Soil Columns.
Summary
Raw data from undisturbed soil column leaching experiment at 4 locations/counties (Columbia, Grant, Marathon, Outagamie) in Wisconsin.
Several treatments were applied to:
1-Estimate the leachability of various PFAS and nitrogen compounds
2-Investigate the ability of biochar to reduce the leachability of the compounds of interest
Data contains weekly leachate volumes from individual soil columns as well as concentrations of compounds of interest in the leachate samples.
Data file
Holly_et_al_2023_leaching_data.xlsx – the only .xlsx file providing raw data for weekly leachate volume and concentrations of compounds of interests. Data are organized by sheets
Sheets description
Metadata: several tables including:
- the counties included in the study (Columbia, Grant, Marathon, Outagamie)
- the treatments applied (Control, Biosolids, Biosolids + Biochar)
- the variables reported in the file.
- PFAS reported
LeachateVolume sheets (one for each counties included: Outagamie, Grand, Columbia, and Marathon). Each sheet includes a table providing:
- Location: county source of soil sample
- Week: number of week (7 days) since the beginning of the experimental procedure
- Column_ID: identification number of the soil column
- Treatment_ID: identification of the treatment applied
- Volume_mL: the weekly amount of leachate collected in mL
- Note: any comment / observation regarding the soil column
“NA” stands for: “no data” or “nothing to report”.
PFAS_Concentration sheets (one for each counties included: Outagamie, Grand, Columbia, and Marathon). Each sheet includes a table providing:
- Location: county source of soil sample
- Week: number of week (7 days) since the beginning of the experimental procedure
- Column_ID: identification number of the soil column
- Treatment_ID: identification of the treatment applied
- PFAS_Chain_Length: length of the backbone carbon chain of the described PFAS molecule
- PFAS: PFAS molecule for which concentration is observed
- Conc_ngperL: observed PFAS concentration in ng/L
- Note: any comment / observation regarding the soil column
“NA” stands for: “no data” or “nothing to report”.
Nitrate_Concentration sheets (one for each counties included: Outagamie, Grand, Columbia, and Marathon). Each sheet includes a table providing:
- Location: county source of soil sample
- Week: number of week (7 days) since the beginning of the experimental procedure
- Column_ID: identification number of the soil column
- Treatment_ID: identification of the treatment applied
- pH: observed leachate pH
- NO2_NO3_mgNperL: measured concentration (mg/L) of Nitrogen as Nitrite and nitrate.
- NH3_NH4_mgNperL: measured concentration (mg/L) of Nitrogen as Ammonia and Ammonium.
- TKN_mgperL: measured concentration (mg/L) of Total Kjeldahl Nitrogen.
- NO2_mgperL: measured concentration (mg/L) of Nitrogen as Nitrite.
- NO3_mgperL: measured concentration (mg/L) of Nitrogen as Nitrate.
- Note: any comment / observation regarding the soil column
“NA” stands for: “no data” or “nothing to report”.
Methods
Raw data was obtained from leaching experiment conducted on undisturbed soil columns collected at 4 locations across Wisconsin to:
1) Evaluate the leachability of added PFAS and Nitrogen compounds under a normal precipitation regime for Wisconsin.
2) Investigate the ability of biochar to reduce the leachability of the compounds of interest.
Composite weekly leachate were collected, measured, and sampled to test for the concentration of several PFAS and Nitrogen compounds. Leachate volume and concentration data were combined to estimate weekly loads of the compounds of interest. Statistical procedures (including two-way ANOVA, Tukey's HSD post-hoc, and ANCOVA) were employed to investigate the difference in leachability between locations, and the effect of biochar on leaching potentials.
Usage notes
The dataset is a .xlsx file and requires Microsoft Excel to open. Alternatively, Google Sheets can be used to open it.