A Rapid Field Method to Estimate the Concentration of Sorbing Particulate Amendments in Soil Samples
Bibliographic record
Abstract
The immobilization of plumes of contaminants in groundwater via in-situ adsorption is an emerging remediation technology. This technology involves injecting adsorbent particles into the subsurface to form a stationary barrier that intercepts a contaminant plume. As the plume travels through the barrier, the target contaminants can adsorb onto the injected particles and become immobilized. In-situ immobilization has been utilized for the treatment of groundwater contaminated with petroleum hydrocarbons and chlorinated solvents. It has also been applied or proposed for the treatment of a variety of other compounds, including per- and polyfluoroalkyl substances (PFAS), which are emerging groundwater contaminants that have garnered worldwide attention. \n \nThere are a wide variety of adsorbents that could be used to form an in-situ barrier, including activated carbon (AC). The ability of an AC barrier to immobilize contaminants partially depends on the concentration and distribution of AC particles. Ideally, the concentration of AC in a barrier would be sufficient to adsorb all target compounds entering the barrier. Additionally, AC particles should be uniformly distributed so that the plume is fully intercepted. A common method used in the field to determine if these two criteria have been met is to visually inspect soil cores taken shortly after an injection event. Although visual inspection can indicate if the distribution of AC particles in the barrier is uniform, this approach is prone to human bias. Moreover, this method cannot quantitatively assess if the AC concentration is sufficient (i.e., falls within the range specified for the barrier design) or if additional injections are required. Alternatively, the concentration of AC in a soil core could be quantitatively determined via total organic carbon (TOC) analysis. However, TOC analysis is time-consuming and generally cannot be performed in the field. Therefore, there is a need for a rapid and simple method to quantify AC in soil samples to provide real-time or near-real-time feedback to the injection team. The objective of this research was to develop such a method. The method was designed to be rapid (less than 30 min), simple, easily performed in the field, and was envisioned to rely upon a tracer that adsorbs to AC particles. By quantifying the percent of the tracer adsorbed, the concentration of AC in the soil sample could be determined. \n \nThe development of the tracer method commenced with screening for a tracer that adsorbs preferentially to AC than to soil (Phase 1). Of the tracers tested, Orange G, which is a hydrophilic dye that can be readily measured using a portable spectrophotometer, did not appreciably adsorb (<10 %) to nine types of sandy soils. To further assess if Orange G could be employed as a tracer, the relationship between the concentration of AC in artificial samples (i.e., soils spiked with known amounts of AC) and the amount of Orange G adsorbed was investigated (Phase 2). Reproducible, linear adsorption trends between these variables were observed for PlumeStop¨ colloidal activated carbon and Calgon WPC powdered activated carbon, which are two AC materials that are widely used in in-situ applications. Finally, the method was validated using samples collected from two AC-soil column studies and soil cores collected from two field sites where AC was injected (Phase 3). The AC concentration in these soil samples was measured based on Orange G adsorption as well as by TOC analysis. For eight of the nine tested samples in which the AC concentrations derived via Orange G adsorption fell within the tracer method limits (i.e., between 0.065 Р0.75 wt. % for PlumeStop¨ or between 0.2 Р1 wt. % for Calgon WPC), the percent difference between the AC concentrations derived via the two methods was below 35 %. This confirms that the tracer analysis has the potential to be a quick and robust method for the quantification of AC in soil samples. While this research focused specifically on AC, the developed approach (i.e., tracer adsorption) and methodologies could potentially be used to quantify other types of adsorbents utilized in in-situ immobilization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".