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==Hydrogeophysical methods for characterization and monitoring of surface water-groundwater interactions==  
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==Remediation of Stormwater Runoff Contaminated by Munition Constituents==
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Hydrogeophysical methods can be used to cost-effectively locate and characterize regions of
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Past and ongoing military operations have resulted in contamination of surface soil with [[Munitions Constituents | munition constituents (MC)]], which have human and environmental health impacts. These compounds can be transported off site via stormwater runoff during precipitation events.  Technologies to “trap and treat” surface runoff before it enters downstream receiving bodies (e.g., streams, rivers, ponds) (see Figure 1), and which are compatible with ongoing range activities are needed.  This article describes a passive and sustainable approach for effective management of munition constituents in stormwater runoff.
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enhanced groundwater/surface-water exchange (GWSWE) and to guide effective follow up investigations based on more traditional invasive methods. The most established methods exploit the contrasts in temperature and/or specific conductance that commonly exist between groundwater and surface water.
 
 
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
 
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
  
 
'''Related Article(s):'''
 
'''Related Article(s):'''
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*[[Geophysical Methods]]
 
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*[[Geophysical Methods - Case Studies]]
 
  
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'''Contributor(s):'''
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*[[Munitions Constituents]]
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*[[Dr. Lee Slater]]
 
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*Dr. Ramona Iery
 
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*Dr. Dimitrios Ntarlagiannis
 
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*Henry Moore
 
  
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'''Key Resource(s):'''
 
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*USGS Method Selection Tool: https://code.usgs.gov/water/espd/hgb/gw-sw-mst
 
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*USGS Water Resources: https://www.usgs.gov/mission-areas/water-resources/science/groundwatersurface-water-interaction
 
  
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==Introduction==
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'''Contributor:''' Mark E. Fuller
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Discharges of contaminated groundwater to surface water bodies threaten ecosystems and degrade the quality of surface water resources. Subsurface heterogeneity associated with the geological setting and stratigraphy often results in such discharges occurring as localized zones (or seeps) of contaminated groundwater. Traditional methods for investigating GWSWE include [https://books.gw-project.org/groundwater-surface-water-exchange/chapter/seepage-meters/#:~:text=Seepage%20meters%20measure%20the%20flux,that%20it%20isolates%20water%20exchange. seepage meters]<ref>Rosenberry, D. O., Duque, C., and Lee, D. R., 2020. History and Evolution of Seepage Meters for Quantifying Flow between Groundwater and Surface Water: Part 1 – Freshwater Settings. Earth-Science Reviews, 204(103167). [https://doi.org/10.1016/j.earscirev.2020.103167 doi: 10.1016/j.earscirev.2020.103167].</ref><ref>Duque, C., Russoniello, C. J., and Rosenberry, D. O., 2020. History and Evolution of Seepage Meters for Quantifying Flow between Groundwater and Surface Water: Part 2 – Marine Settings and Submarine Groundwater Discharge. Earth-Science Reviews, 204 ( 103168). [https://doi.org/10.1016/j.earscirev.2020.103168 doi: 10.1016/j.earscirev.2020.103168].</ref>, which directly quantify the volume flux crossing the bed of a surface water body (i.e, a  lake, river or wetland) and point probes that locally measure key water quality parameters (e.g., temperature, pore water velocity, specific conductance, dissolved oxygen, pH). Seepage meters provide direct estimates of seepage fluxes between groundwater and surface- water but are time consuming and can be difficult to deploy in high energy surface water environments and along armored bed sediments. Manual seepage meters rely on quantifying volume changes in a bag of water that is hydraulically connected to the bed. Although automated seepage meters such as the [https://clu-in.org/programs/21m2/navytools/gsw/#ultraseep Ultraseep system] have been developed, they are generally not suitable for long term deployment (weeks to months). The US Navy has developed the [https://clu-in.org/programs/21m2/navytools/gsw/#trident Trident probe] for more rapid (relative to seepage meters) sampling, whereby the probe is inserted into the bed and point-in-time pore water quality and sediment parameters are directly recorded (note that the Trident probe does not measure a seepage flux). Such direct probe-based measurements are still relatively time consuming to acquire, particularly when reconnaissance information is required over large areas to determine the location of discrete seeps for further, more quantitative analysis.  
 
  
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Over the last few decades, a broader toolbox of hydrogeophysical technologies has been developed to rapidly and non-invasively evaluate zones of GWSWE in a variety of surface water settings, spanning from freshwater bodies to saline coastal environments. Many of these technologies are currently being deployed under a Department of Defense Environmental Security Technology Certification Program ([https://serdp-estcp.mil/ ESTCP]) project ([https://serdp-estcp.mil/projects/details/e4a12396-4b56-4318-b9e5-143c3011b8ff ER21-5237]) to demonstrate the value of the toolbox to remedial program managers (RPMs) dealing with the challenge of characterizing surface water contamination via groundwater from facilities proximal to surface water bodies. This article summarizes these technologies and provides references to key resources, mostly provided by the [https://www.usgs.gov/mission-areas/water-resources Water Resources Mission Area] of the United States Geological Survey that describe the technologies in further detail.
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'''Key Resource(s):'''
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*SERDP Project ER19-1106: Development of Innovative Passive and Sustainable Treatment Technologies for Energetic Compounds in Surface Runoff on Active Ranges
  
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==Hydrogeophysical Technologies for Understanding Groundwater-Surface Water Interactions==
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==Background==
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[[Wikipedia: Hydrogeophysics |Hydrogeophysical technologies]] exploit contrasts in the physical properties between groundwater and surface water to detect and monitor zones of pronounced GWSWE. The two most valuable properties to measure are temperature and electrical conductivity. Temperature has been used for decades as an indicator of groundwater-surface water exchange<ref>Constantz, J., 2008. Heat as a Tracer to Determine Streambed Water Exchanges. Water Resources Research, 44 (4).[https://doi.org/https://doi.org/10.1029/2008WR006996 doi: 10.1029/2008WR006996].[https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2008WR006996  Open Access Article]</ref> with early uses including pushing a thermistor into the bed of a surface water body to assess zones of surface water downwelling and groundwater upwelling. Today, a variety of novel technologies that measure temperature over a wide range of spatial and temporal scales are being used to investigate GWSWE. The evaluation of electrical conductivity measurements using point probes and geophysical imaging is also well-established. However, new technologies are now available to exploit electrical conductivity contrasts from GWSWE occurring over a range of spatial and temporal scales.
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===Surface Runoff Characteristics and Treatment Approaches===
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[[File: FullerFig1.png | thumb | 400 px | Figure 1. Conceptual model of passive trap and treat approach for MC removal from stormwater runoff]]
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During large precipitation events the rate of water deposition exceeds the rate of water infiltration, resulting in surface runoff (also called stormwater runoff). Surface characteristics including soil texture, presence of impermeable surfaces (natural and artificial), slope, and density and type of vegetation all influence the amount of surface runoff from a given land area. The use of passive systems such as retention ponds and biofiltration cells for treatment of surface runoff is well established for urban and roadway runoff. Treatment in those cases is typically achieved by directing runoff into and through a small constructed wetland, often at the outlet of a retention basin, or via filtration by directing runoff through a more highly engineered channel or vault containing the treatment materials. Filtration based technologies have proven to be effective for the removal of metals, organics, and suspended solids<ref>Sansalone, J.J., 1999. In-situ performance of a passive treatment system for metal source control. Water Science and Technology, 39(2), pp. 193-200. [https://doi.org/10.1016/S0273-1223(99)00023-2 doi: 10.1016/S0273-1223(99)00023-2]</ref><ref>Deletic, A., Fletcher, T.D., 2006. Performance of grass filters used for stormwater treatment—A field and modelling study. Journal of Hydrology, 317(3-4), pp. 261-275. [http://dx.doi.org/10.1016/j.jhydrol.2005.05.021 doi: 10.1016/j.jhydrol.2005.05.021]</ref><ref>Grebel, J.E., Charbonnet, J.A., Sedlak, D.L., 2016. Oxidation of organic contaminants by manganese oxide geomedia for passive urban stormwater treatment systems. Water Research, 88, pp. 481-491. [http://dx.doi.org/10.1016/j.watres.2015.10.019 doi: 10.1016/j.watres.2015.10.019]</ref><ref>Seelsaen, N., McLaughlan, R., Moore, S., Ball, J.E., Stuetz, R.M., 2006. Pollutant removal efficiency of alternative filtration media in stormwater treatment. Water Science and Technology, 54(6-7), pp. 299-305. [https://doi.org/10.2166/wst.2006.617 doi: 10.2166/wst.2006.617]</ref>.
  
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===Temperature-Based Technologies===
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===Surface Runoff on Ranges===
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Several temperature-based GWSWE methodologies exploit the gradient in temperature between surface water and groundwater that exist during certain times of day or seasons of the year. The thermal insulation provided by the Earth’s land surface means that groundwater is warmer than surface water in winter months, but colder than surface water in summer months away from the equator. Therefore, in temperate climates, localized (or ‘preferential’) groundwater discharge into surface water bodies is often observed as cold temperature anomalies in the summer and warm temperature anomalies in the winter. However, there are times of the year such as fall and spring when contrasts in the temperature between groundwater and surface water will be minimal, or even undetectable. These seasonal-driven points in time correspond to the switch in the polarity of the temperature contrast between groundwater and surface water. Consequently, SW to GW gradient temperature-based methods are most effective when deployed at times of the year when the temperature contrasts between groundwater and surface water are greatest. Other time-series temperature monitoring methods depend more on natural daily signals measured at the bed interface and in bed sediments, and those signals may exist year round except where strongly muted by ice cover or surface water stratification. A variety of sensing technologies now exist within the GWSWE toolbox, from techniques that rapidly characterize temperature contrasts over large areas, down to powerful monitoring methods that can continuously quantify GWSWE fluxes at discrete locations identified as hotspots.
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[[File: FullerFig2.png | thumb | 500 px | Figure 2. Conceptual illustration of munition constituent production and transport on military ranges. Mesoscale residues are qualitatively defined as being easily visible to the naked eye (e.g., from around 50 µm to multiple cm in size) and less likely to be transported by moving water.  Microscale residues are defined as <50 µm down to below 1 µm, and more likely to be entrained in, and transported by, moving water as particulates. Blue arrows represent possible water flow paths and include both dissolved and solid phase energetics. The red vertical arrow represents the predominant energetics dissolution process in close proximity to the residues due to precipitation.]]
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Surface runoff represents a major potential mechanism through which energetics residues and related materials are transported off site from range soils to groundwater and surface water receptors (Figure 2). This process is particularly important for energetics that are water soluble (e.g., [[Wikipedia: Nitrotriazolone | NTO]] and [[Wikipedia: Nitroguanidine | NQ]]) or generate soluble daughter products (e.g., [[Wikipedia: 2,4-Dinitroanisole | DNAN]] and [[Wikipedia: TNT | TNT]]). While traditional MC such as [[Wikipedia: RDX | RDX]] and [[Wikipedia: HMX | HMX]] have limited aqueous solubility, they also exhibit recalcitrance to degrade under most natural conditions. RDX and [[Wikipedia: Perchlorate | perchlorate]] are frequent groundwater contaminants on military training ranges. While actual field measurements of energetics in surface runoff are limited, laboratory experiments have been performed to predict mobile energetics contamination levels based on soil mass loadings<ref>Cubello, F., Polyakov, V., Meding, S.M., Kadoya, W., Beal, S., Dontsova, K., 2024. Movement of TNT and RDX from composition B detonation residues in solution and sediment during runoff. Chemosphere, 350, Article 141023. [https://doi.org/10.1016/j.chemosphere.2023.141023 doi: 10.1016/j.chemosphere.2023.141023]</ref><ref>Karls, B., Meding, S.M., Li, L., Polyakov, V., Kadoya, W., Beal, S., Dontsova, K., 2023. A laboratory rill study of IMX-104 transport in overland flow. Chemosphere, 310, Article 136866. [https://doi.org/10.1016/j.chemosphere.2022.136866 doi: 10.1016/j.chemosphere.2022.136866]&nbsp; [[Media: KarlsEtAl2023.pdf | Open Access Article]]</ref><ref>Polyakov, V., Beal, S., Meding, S.M., Dontsova, K., 2025. Effect of gypsum on transport of IMX-104 constituents in overland flow under simulated rainfall. Journal of Environmental Quality, 54(1), pp. 191-203. [https://doi.org/10.1002/jeq2.20652 doi: 10.1002/jeq2.20652]&nbsp; [[Media: PolyakovEtAl2025.pdf | Open Access Article.pdf]]</ref><ref>Polyakov, V., Kadoya, W., Beal, S., Morehead, H., Hunt, E., Cubello, F., Meding, S.M., Dontsova, K., 2023. Transport of insensitive munitions constituents, NTO, DNAN, RDX, and HMX in runoff and sediment under simulated rainfall. Science of the Total Environment, 866, Article 161434. [https://doi.org/10.1016/j.scitotenv.2023.161434 doi: 10.1016/j.scitotenv.2023.161434]&nbsp; [[Media: PolyakovEtAl2023.pdf | Open Access Article.pdf]]</ref><ref>Price, R.A., Bourne, M., Price, C.L., Lindsay, J., Cole, J., 2011. Transport of RDX and TNT from Composition-B Explosive During Simulated Rainfall. In: Environmental Chemistry of Explosives and Propellant Compounds in Soils and Marine Systems: Distributed Source Characterization and Remedial Technologies. American Chemical Society, pp. 229-240. [https://doi.org/10.1021/bk-2011-1069.ch013 doi: 10.1021/bk-2011-1069.ch013]</ref>. For example, in a previous small study, MC were detected in surface runoff from an active live-fire range<ref>Fuller, M.E., 2015. Fate and Transport of Colloidal Energetic Residues. Department of Defense Strategic Environmental Research and Development Program (SERDP), Project ER-1689. [https://serdp-estcp.mil/projects/details/10760fd6-fb55-4515-a629-f93c555a92f0 Project Website]&nbsp;&nbsp; [[Media: ER-1689-FR.pdf | Final Report.pdf]]</ref>, and more recent sampling has detected MC in marsh surface water adjacent to the same installation (personal communication).  Another recent report from Canada also detected RDX in both surface runoff and surface water at low part per billion levels in a survey of several military demolition sites<ref>Lapointe, M.-C., Martel, R., Diaz, E., 2017. A Conceptual Model of Fate and Transport Processes for RDX Deposited to Surface Soils of North American Active Demolition Sites. Journal of Environmental Quality, 46(6), pp. 1444-1454. [https://doi.org/10.2134/jeq2017.02.0069 doi: 10.2134/jeq2017.02.0069]</ref>. However, overall, data regarding the MC contaminant profile of surface runoff from ranges is very limited, and the possible presence of non-energetic constituents (e.g., metals, binders, plasticizers) in runoff has not been examined.  Additionally, while energetics-contaminated surface runoff is an important concern, mitigation technologies specifically for surface runoff have not yet been developed and widely deployed in the field.  To effectively capture and degrade MC and associated compounds that are present in surface runoff, novel treatment media are needed to sorb a broad range of energetic materials and to transform the retained compounds through abiotic and/or microbial processes.
  
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====Characterization Methods====
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Surface runoff of organic and inorganic contaminants from live-fire ranges is a challenging issue for the Department of Defense (DoD). Potentially even more problematic is the fact that inputs to surface waters from large testing and training ranges typically originate from multiple sources, often encompassing hundreds of acres.  No available technologies are currently considered effective for controlling non-point source energetics-laden surface runoff.  While numerous technologies exist to treat collected explosives residues, contaminated soil and even groundwater, the decentralized nature and sheer volume of military range runoff have precluded the use of treatment technologies at full scale in the field.
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The primary use of the characterization methods is to rapidly determine precise locations of groundwater upwelling over large areas in order to pinpoint locations for subsequent ground-based observations. A common limitation of these methods is that they can only sense groundwater fluxes into surface water. Methods applied at the water surface and in the surface water column generally cannot detect localized regions of surface water transfer to groundwater, for which temperature measurements collected within the bed sediments are needed. This is a more challenging characterization task that may, in the right conditions, be addressed using electrical conductivity-based methods described later in this article.
 
  
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=====Unmanned Aerial Vehicle Infrared (UAV-IR)=====
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==Range Runoff Treatment Technology Components==
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[[File:IeryFig1.png | thumb |600px|Figure 1. UAV IR orthomosaics with estimated scale of (a) a wetland in winter (modified from Briggs et al.<ref>Briggs, M. A., Jackson, K. E., Liu, F., Moore, E. M., Bisson, A., Helton, A. M., 2022. Exploring Local Riverbank Sediment Controls on the Occurrence of Preferential Groundwater Discharge Points. Water, 14(1). [https://doi.org/10.3390/w14010011 doi: 10.3390/w14010011]&nbsp;&nbsp;[https://www.mdpi.com/2073-4441/14/1/11 Open Access Article].</ref>) and (b) a mountain stream in summer (modified from Briggs et al.<ref>Briggs, M. A., Wang, C., Day-Lewis, F. D., Williams, K. H., Dong, W., Lane, J. W., 2019. Return Flows from Beaver Ponds Enhance Floodplain-to-River Metals Exchange in Alluvial Mountain Catchments. Science of the Total Environment, 685, pp. 357–369. [https://doi.org/10.1016/j.scitotenv.2019.05.371 doi: 10.1016/j.scitotenv.2019.05.371].&nbsp;&nbsp;[https://pdf.sciencedirectassets.com/271800/1-s2.0-S0048969719X00273/1-s2.0-S0048969719324246/am.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEE0aCXVzLWVhc3QtMSJGMEQCIBY8ykhAP941wHO1NKj8EmXG3btdpgX6HaUV9zAo0PCMAiACRjzV0D2lbFFwnhUzEqBupGsgX6DkK62ZIEvb%2B0irbiq8BQj2%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F8BEAUaDDA1OTAwMzU0Njg2NSIMPmS2kZBwKKMGD%2F6GKpAFaY6lOuHO%2B1RkV%2FL6NkK74dL6YJculUqyZJn9s09njF1L%2Bb4LgjH%2FbawysWGvGeuH%2FQtSgwqFM90MQ4grDiDQPHUjSEDNVuN2II%2BqPK4oqkjqxwTmC2AObe%2FMY1c45L2nshYodZwtROh6Hl8Jp4B4HoDPE9wx1fEw7DGmB%2Bj70q5PG7%2FUUo3rLl6BCMT%2FWKFGfZSaOmaD5nweVaTRBUbgSVIcmCQKshE28TkHFpmwY58YNO0GjaKHXMsBNciZ2DvIPAHMyA1iymB7UFcoBRDicZJUDZvvnJNGj1bTX9tEQ49yil7IWD22hKPHL5nSogssocX5rRXiIglVT%2BAzHsMMyxfVxfFGBsmmSGAVG9FAeRPgx1T%2FIOqNo%2FOuyV9G%2BVSt5boUg4HBaZSvW5JNkL5bFpaMlrUTpMF%2F6Bbq3Q6EsiZMaFF0JOS3rvX5dkDlfu7OzJDBuRBszYoq%2B4%2FLQGJypfmarz8ZHEzi3Qw85nYbT68UGNa%2BZ9lZQG%2B47mF6Nj11%2F%2Fu%2FDTZD1p4r9nskTevwkRE%2BL7q3OSbqFj4YvN6qsMBLb%2FM7K2xSmaots0YGisZ09fVJBetJ1ILZpN5wCbS%2F77uFeQoxYXGIwz84wyqSueP7qcj3BQ%2FMkZRbmVpokj3vtESlfHvcZV2Ntu95JM9hetE9F5azaZ%2F%2Fm3WTE2mgW48FCbFI09p%2F7%2FSJyEWl54lNG7%2F2y0AayedFUs75otJauCpNJtr2pF4sbAGfgiagA2%2BzeDatKnI7MDhMD0R27wvaVwEup6vkLmTaJh4P8bGFd01Fwj96gZIKESW6HfwGXMBMj%2FoJn3CYpcfVelPmDr6jTeSJapUJoWE8gQVFjWuISuD4PdHYtbiSBL%2Fjn5jPvGMwvrqrrQY6sgEtK%2Fo3hSElpY%2Be20Xj4eNAJ%2BFmkb5nASAJvtygtnSdoc%2FBHMv4U3Je92nbunzwAwXaVCZ8FBK1%2F2cmq3sYLNOyPEJrCNqAo0Lgf137RvhaJb7erYXXfL7UCz1hePrG3I3bgKkBRN5PD%2FSlu%2BSSEimoEn4kCyxoaNYI9QvymaTlHZJM0ueXCYprlRfMneJXxnEVyC3qlMsTMtcL%2B45koHZeeTQJUMXWJB%2BYQxNDmNM3ZHH4&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240119T205045Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTYV2JHRO6K%2F20240119%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=3befd4efcf96517aad4e02a2d76e82cd278f02be8a60a5136a4981889df64f00&hash=c0f70e64bfdb70375c685714475b258099c0d0b19a2a7a556e77182cc6cfac9c&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S0048969719324246&tid=pdf-5d6462f0-c794-4158-b89d-2a1f5b96a226&sid=8b33666922432845420b6d75b151281148eegxrqa&type=client Open Access Manuscript]</ref>) that both capture multiscale groundwater discharge processes. Figure reproduced from Mangel et al.<ref>Mangel, A. R., Dawson, C. B., Rey, D. M., Briggs, M. A., 2022. Drone Applications in Hydrogeophysics: Recent Examples and a Vision for the Future. The Leading Edge, 41 (8), pp. 540–547. [https://doi.org/10.1190/tle41080540.1 doi: 10.1190/tle41080540].</ref>]]
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Based on the conceptual foundation of previous research into surface water runoff treatment for other contaminants, with a goal to “trap and treat” the target compounds, the following components were selected for inclusion in the technology developed to address range runoff contaminated with energetic compounds.
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[[Wikipedia: Unmanned aerial vehicle | Unmanned aerial vehicles (UAVs)]] equipped with thermal infrared (IR) cameras can provide a very powerful tool for rapidly determining zones of pronounced upwelling of groundwater to surface water. Large areas of can be covered with high spatial resolution. The information obtained can be used to rapidly define locations of focused groundwater upwelling and prioritize these for more intensive surface-based observations (Figure 1). As with all thermal methods, flights must be performed when adequate contrasts in temperature between surface water and groundwater are expected to exist. Not just time of year but, because of the effect of the diurnal temperature signal on surface water bodies, time of day might need to be considered in order to maximize the chance of success. Calibration of UAV-IR camera measurements against simultaneously acquired direct measurements of temperature is recommended to optimize the value of these datasets. UAV-IR methods will not work in all situations. One major limitation of the technology is that the temperature expression of groundwater upwelling must be manifested at the surface of the surface water body. Consequently, the technology will not detect relatively small discharges occurring beneath a relatively deep surface water layer, and thermal imaging over the water surface can be complicated by thermal IR reflection. The chances of success with UAV-IR will be strongest in regions of  exposed banks or shallow water where there are no strong currents causing mixing (and thus dilution) of the upwelling groundwater temperature signals. UAV-IR methods will therefore likely be most successful close to shorelines of lakes/ponds, over shallow, low flow streams and rivers and in wetland environments. UAV-IR methods require a licensed pilot, and restrictions on the use of airspace may limit the application of this technology.  
 
  
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=====Handheld Thermal Infrared (TIR) Cameras=====
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===Peat===
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[[File:IeryFig2.png | thumb|left |600px|Figure 2. (a) A TIR camera set up to image groundwater discharges to surface water (b) TIR data inset on a visible light photograph. Cooler (blue) bank seepage groundwater is discharging into warmer (red) stream water (temperature scale in degrees). Both photographs courtesy of Martin Briggs USGS.]]
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Previous research demonstrated that a peat-based system provided a natural and sustainable sorptive medium for organic explosives such as HMX, RDX, and TNT, allowing much longer residence times than predicted from hydraulic loading alone<ref>Fuller, M.E., Hatzinger, P.B., Rungkamol, D., Schuster, R.L., Steffan, R.J., 2004. Enhancing the attenuation of explosives in surface soils at military facilities: Combined sorption and biodegradation. Environmental Toxicology and Chemistry, 23(2), pp. 313-324. [https://doi.org/10.1897/03-187 doi: 10.1897/03-187]</ref><ref>Fuller, M.E., Lowey, J.M., Schaefer, C.E., Steffan, R.J., 2005. A Peat Moss-Based Technology for Mitigating Residues of the Explosives TNT, RDX, and HMX in Soil. Soil and Sediment Contamination: An International Journal, 14(4), pp. 373-385. [https://doi.org/10.1080/15320380590954097 doi: 10.1080/15320380590954097]</ref><ref name="FullerEtAl2009">Fuller, M.E., Schaefer, C.E., Steffan, R.J., 2009. Evaluation of a peat moss plus soybean oil (PMSO) technology for reducing explosive residue transport to groundwater at military training ranges under field conditions. Chemosphere, 77(8), pp. 1076-1083. [https://doi.org/10.1016/j.chemosphere.2009.08.044 doi: 10.1016/j.chemosphere.2009.08.044]</ref><ref>Hatzinger, P.B., Fuller, M.E., Rungkamol, D., Schuster, R.L., Steffan, R.J., 2004. Enhancing the attenuation of explosives in surface soils at military facilities: Sorption-desorption isotherms. Environmental Toxicology and Chemistry, 23(2), pp. 306-312. [https://doi.org/10.1897/03-186 doi: 10.1897/03-186]</ref><ref name="SchaeferEtAl2005">Schaefer, C.E., Fuller, M.E., Lowey, J.M., Steffan, R.J., 2005. Use of Peat Moss Amended with Soybean Oil for Mitigation of Dissolved Explosive Compounds Leaching into the Subsurface: Insight into Mass Transfer Mechanisms. Environmental Engineering Science, 22(3), pp. 337-349. [https://doi.org/10.1089/ees.2005.22.337 doi: 10.1089/ees.2005.22.337]</ref>. Peat moss represents a bioactive environment for treatment of the target contaminants. While the majority of the microbial reactions are aerobic due to the presence of measurable dissolved oxygen in the bulk solution, anaerobic reactions (including methanogenesis) can occur in microsites within the peat. The peat-based substrate acts not only as a long term electron donor as it degrades but also acts as a strong sorbent. This is important in intermittently loaded systems in which a large initial pulse of MC can be temporarily retarded on the peat matrix and then slowly degraded as they desorb<ref name="FullerEtAl2009"/><ref name="SchaeferEtAl2005"/>. This increased residence time enhances the biotransformation of energetics and promotes the immobilization and further degradation of breakdown products. Abiotic degradation reactions are also likely enhanced by association with the organic-rich peat (e.g., via electron shuttling reactions of [[Wikipedia: Humic substance | humics]])<ref>Roden, E.E., Kappler, A., Bauer, I., Jiang, J., Paul, A., Stoesser, R., Konishi, H., Xu, H., 2010. Extracellular electron transfer through microbial reduction of solid-phase humic substances. Nature Geoscience, 3, pp. 417-421. [https://doi.org/10.1038/ngeo870 doi: 10.1038/ngeo870]</ref>.
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Hand-held thermal infrared (TIR) cameras are powerful tools for visual identification of localized seeps of upwelling groundwater. TIR cameras may be used to follow up on UAV-IR surveys to better characterize local seeps identified from the air using UAV-IR. Alternatively, a TIR camera is a valuable tool when performing initial walks of prospective study sites as they may quickly confirm the presence of suspected seeps. TIR cameras provide high resolution images that can define the structure of localized seeps and may provide valuable insights into the role of discrete features (e.g., fractures in rocks or pipes in soil) in determining seep morphology (Figure 2). Like UAV-IR, TIR provides primarily qualitative information (location, extent) of seeps and it only succeeds when there are adequate contrasts between groundwater and surface water that are expressed at the surface of the investigated water body or along bank sediments. The United States Geological Survey (USGS) has made extensive  use of TIR cameras for studying groundwater/surface-water exchange.  
 
  
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=====Continuous Near-bed Temperature Sensing=====
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===Soybean Oil===  
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When performing surveys from a boat a simple yet often powerful technology is continuous
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Modeling has indicated that peat moss amended with crude soybean oil would significantly reduce the flux of dissolved TNT, RDX, and HMX through the vadose zone to groundwater compared to a non-treated soil (see [https://serdp-estcp.mil/projects/details/20e2f05c-fd50-4fd3-8451-ba73300c7531 ESTCP ER-200434]). The technology was validated in field soil plots, showing a greater than 500-fold reduction in the flux of dissolved RDX from macroscale Composition B detonation residues compared to a non-treated control plot<ref name="FullerEtAl2009"/>. Laboratory testing and modeling indicated that the addition of soybean oil increased the biotransformation rates of RDX and HMX at least 10-fold compared to rates observed with peat moss alone<ref name="SchaeferEtAl2005"/>. Subsequent experiments also demonstrated the effectiveness of the amended peat moss material for stimulating perchlorate transformation when added to a highly contaminated soil (Fuller et al., unpublished data).  These previous findings clearly demonstrate the effectiveness of peat-based materials for mitigating transport of both organic and inorganic energetic compounds through soil to groundwater.  
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near-bed temperature sensing, whereby a temperature probe is strategically suspended to float in the water column just above the bed or dragged along it. Compared to UAV-IR, this approach does not rely on upwelling groundwater being expressed as a temperature anomaly at the surface. The utility of the method can be enhanced when a specific conductance probe is co- located with the temperature probe so that anomalies in both temperature and specific conductance can be investigated.
 
  
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====Monitoring Methods====
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===Biochar===
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Monitoring methods allow temperature signals to be recorded with high temporal resolution along the bed interface or within bank or bed sediments. These methods can capture temporal trends in GWSWE driven by variations in the hydraulic gradients around surface water bodies, as well as changes in [[Wikipedia: Hydraulic conductivity | hydraulic conductivity]] due to sedimentation, clogging, scour or microbial mass. If vertical profiles of bed temperature are collected, a range of analytical and numerical models can be applied to infer the vertical water flux rate and direction, similar to a seepage meter. These fluxes may vary as a function of season, rainfall events (enhanced during storm activity), tidal variability in coastal settings and due to engineered controls such as dam discharges. The methods can capture evidence of GWSWE that may not be detected during a single ‘characterization’ survey if the local hydraulic conditions at that point in time result in relatively weak hydraulic gradients.
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Recent reports have highlighted additional materials that, either alone, or in combination with electron donors such as peat moss and soybean oil, may further enhance the sorption and degradation of surface runoff contaminants, including both legacy energetics and [[Wikipedia: Insensitive_munition#Insensitive_high_explosives | insensitive high explosives (IHE)]].  For instance, [[Wikipedia: Biochar | biochar]], a type of black carbon, has been shown to not only sorb a wide range of organic and inorganic contaminants including MCs<ref>Ahmad, M., Rajapaksha, A.U., Lim, J.E., Zhang, M., Bolan, N., Mohan, D., Vithanage, M., Lee, S.S., Ok, Y.S., 2014. Biochar as a sorbent for contaminant management in soil and water: A review. Chemosphere, 99, pp. 19-33. [https://doi.org/10.1016/j.chemosphere.2013.10.071 doi: 10.1016/j.chemosphere.2013.10.071]</ref><ref>Mohan, D., Sarswat, A., Ok, Y.S., Pittman, C.U., 2014. Organic and inorganic contaminants removal from water with biochar, a renewable, low cost and sustainable adsorbent – A critical review. Bioresource Technology, 160, pp. 191-202. [https://doi.org/10.1016/j.biortech.2014.01.120 doi: 10.1016/j.biortech.2014.01.120]</ref><ref>Oh, S.-Y., Seo, Y.-D., Jeong, T.-Y., Kim, S.-D., 2018. Sorption of Nitro Explosives to Polymer/Biomass-Derived Biochar. Journal of Environmental Quality, 47(2), pp. 353-360. [https://doi.org/10.2134/jeq2017.09.0357 doi: 10.2134/jeq2017.09.0357]</ref><ref>Xie, T., Reddy, K.R., Wang, C., Yargicoglu, E., Spokas, K., 2015. Characteristics and Applications of Biochar for Environmental Remediation: A Review. Critical Reviews in Environmental Science and Technology, 45(9), pp. 939-969. [https://doi.org/10.1080/10643389.2014.924180 doi: 10.1080/10643389.2014.924180]</ref>, but also to facilitate their degradation<ref>Oh, S.-Y., Cha, D.K., Kim, B.-J., Chiu, P.C., 2002. Effect of adsorption to elemental iron on the transformation of 2,4,6-trinitrotoluene and hexahydro-1,3,5-trinitro-1,3,5-triazine in solution. Environmental Toxicology and Chemistry, 21(7), pp. 1384-1389. [https://doi.org/10.1002/etc.5620210708 doi: 10.1002/etc.5620210708]</ref><ref>Ye, J., Chiu, P.C., 2006. Transport of Atomic Hydrogen through Graphite and its Reaction with Azoaromatic Compounds. Environmental Science and Technology, 40(12), pp. 3959-3964. [https://doi.org/10.1021/es060038x doi: 10.1021/es060038x]</ref><ref name="OhChiu2009">Oh, S.-Y., Chiu, P.C., 2009. Graphite- and Soot-Mediated Reduction of 2,4-Dinitrotoluene and Hexahydro-1,3,5-trinitro-1,3,5-triazine. Environmental Science and Technology, 43(18), pp. 6983-6988. [https://doi.org/10.1021/es901433m doi: 10.1021/es901433m]</ref><ref name="OhEtAl2013">Oh, S.-Y., Son, J.-G., Chiu, P.C., 2013. Biochar-mediated reductive transformation of nitro herbicides and explosives. Environmental Toxicology and Chemistry, 32(3), pp. 501-508. [https://doi.org/10.1002/etc.2087 doi: 10.1002/etc.2087]&nbsp;&nbsp; [[Media: OhEtAl2013.pdf | Open Access Article.pdf]]</ref><ref name="XuEtAl2010">Xu, W., Dana, K.E., Mitch, W.A., 2010. Black Carbon-Mediated Destruction of Nitroglycerin and RDX by Hydrogen Sulfide. Environmental Science and Technology, 44(16), pp. 6409-6415. [https://doi.org/10.1021/es101307n doi: 10.1021/es101307n]</ref><ref>Xu, W., Pignatello, J.J., Mitch, W.A., 2013. Role of Black Carbon Electrical Conductivity in Mediating Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) Transformation on Carbon Surfaces by Sulfides. Environmental Science and Technology, 47(13), pp. 7129-7136. [https://doi.org/10.1021/es4012367 doi: 10.1021/es4012367]</ref>. Depending on the source biomass and [[Wikipedia: Pyrolysis| pyrolysis]] conditions, biochar can possess a high [[Wikipedia: Specific surface area | specific surface area]] (on the order of several hundred m<small><sup>2</sup></small>/g)<ref>Zhang, J., You, C., 2013. Water Holding Capacity and Absorption Properties of Wood Chars. Energy and Fuels, 27(5), pp. 2643-2648. [https://doi.org/10.1021/ef4000769 doi: 10.1021/ef4000769]</ref><ref>Gray, M., Johnson, M.G., Dragila, M.I., Kleber, M., 2014. Water uptake in biochars: The roles of porosity and hydrophobicity. Biomass and Bioenergy, 61, pp. 196-205. [https://doi.org/10.1016/j.biombioe.2013.12.010 doi: 10.1016/j.biombioe.2013.12.010]</ref> and hence a high sorption capacity.  Biochar and other black carbon also exhibit especially high affinity for [[Wikipedia: Nitro compound | nitroaromatic compounds (NACs)]] including TNT and 2,4-dinitrotoluene (DNT)<ref>Sander, M., Pignatello, J.J., 2005. Characterization of Charcoal Adsorption Sites for Aromatic Compounds:  Insights Drawn from Single-Solute and Bi-Solute Competitive Experiments. Environmental Science and Technology, 39(6), pp. 1606-1615. [https://doi.org/10.1021/es049135l doi: 10.1021/es049135l]</ref><ref name="ZhuEtAl2005">Zhu, D., Kwon, S., Pignatello, J.J., 2005. Adsorption of Single-Ring Organic Compounds to Wood Charcoals Prepared Under Different Thermochemical Conditions. Environmental Science and Technology 39(11), pp. 3990-3998. [https://doi.org/10.1021/es050129e doi: 10.1021/es050129e]</ref><ref name="ZhuPignatello2005">Zhu, D., Pignatello, J.J., 2005. Characterization of Aromatic Compound Sorptive Interactions with Black Carbon (Charcoal) Assisted by Graphite as a Model. Environmental Science and Technology, 39(7), pp. 2033-2041. [https://doi.org/10.1021/es0491376 doi: 10.1021/es0491376]</ref>. This is due to the strong [[Wikipedia: Pi-interaction | ''&pi;-&pi;'' electron donor-acceptor interactions]] between electron-rich graphitic domains in black carbon and the electron-deficient aromatic ring of the NAC<ref name="ZhuEtAl2005"/><ref name="ZhuPignatello2005"/>. These characteristics make biochar a potentially effective, low cost, and sustainable sorbent for removing MC and other contaminants from surface runoff and retaining them for subsequent degradation ''in situ''.
  
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=====Fiber-optic Distributed Temperature Sensing (FO-DTS)=====
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Furthermore, black carbon such as biochar can promote abiotic and microbial transformation reactions by facilitating electron transfer. That is, biochar is not merely a passive sorbent for contaminants, but also a redox mediator for their degradation. Biochar can promote contaminant degradation through two different mechanisms: electron conduction and electron storage<ref>Sun, T., Levin, B.D.A., Guzman, J.J.L., Enders, A., Muller, D.A., Angenent, L.T., Lehmann, J., 2017. Rapid electron transfer by the carbon matrix in natural pyrogenic carbon. Nature Communications, 8, Article 14873. [https://doi.org/10.1038/ncomms14873 doi: 10.1038/ncomms14873]&nbsp;&nbsp; [[Media: SunEtAl2017.pdf | Open Access Article.pdf]]</ref>.  
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Fiber-optic distributed temperature sensing (FO-DTS) is a powerful monitoring technology used in fire detection, industrial process monitoring, and petroleum reservoir monitoring. The method is also used to obtain spatially rich datasets for monitoring GWSWE<ref name=”Selker2006”>Selker, J. S., Thévenaz, L., Huwald, H., Mallet, A., Luxemburg, W., van de Giesen, N., Stejskal, M., Zeman, J., Westhoff, M., Parlange, M. B., 2006. Distributed Fiber-Optic Temperature Sensing for Hydrologic Systems. Water Resources Research, 42 (12). [https://doi.org/10.1029/2006WR005326 doi: 10.1029/2006WR005326].&nbsp;&nbsp;[https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2006WR005326 Open Access Article]</ref><ref name=”Tyler2009”>Tyler, S. W., Selker, J. S., Hausner, M. B., Hatch, C. E., Torgersen, T., Thodal, C. E., Schladow, S. G., 2009. Environmental Temperature Sensing Using Raman Spectra DTS Fiber-Optic Methods. Water Resources Research, 45(4). [https://doi.org/https://doi.org/10.1029/2008WR007052 doi: 10.1029/2008WR007052].&nbsp;&nbsp;[https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2008WR007052 Open Access Article]</ref>. The sensor consists of standard telecommunications fiber-optic fiber typically housed in armored cable and the physics is based on temperature-dependent backscatter mechanisms including Brillouin and Raman backscatter<ref name=”Selker2006”/>.
 
  
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First, the microscopic graphitic regions in biochar can adsorb contaminants like NACs strongly, as noted above, and also conduct reducing equivalents such as electrons and atomic hydrogen to the sorbed contaminants, thus promoting their reductive degradation.  This catalytic process has been demonstrated for TNT, DNT, RDX, HMX, and [[Wikipedia: Nitroglycerin | nitroglycerin]]<ref>Oh, S.-Y., Cha, D.K., Chiu, P.C., 2002. Graphite-Mediated Reduction of 2,4-Dinitrotoluene with Elemental Iron. Environmental Science and Technology, 36(10), pp. 2178-2184. [https://doi.org/10.1021/es011474g doi: 10.1021/es011474g]</ref><ref>Oh, S.-Y., Cha, D.K., Kim, B.J., Chiu, P.C., 2004. Reduction of Nitroglycerin with Elemental Iron:  Pathway, Kinetics, and Mechanisms. Environmental Science and Technology, 38(13), pp. 3723-3730. [https://doi.org/10.1021/es0354667 doi: 10.1021/es0354667]</ref><ref>Oh, S.-Y., Cha, D.K., Kim, B.J., Chiu, P.C., 2005. Reductive transformation of hexahydro-1,3,5-trinitro-1,3,5-triazine, octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine, and methylenedinitramine with elemental iron. Environmental Toxicology and Chemistry, 24(11), pp. 2812-2819. [https://doi.org/10.1897/04-662R.1 doi: 10.1897/04-662R.1]</ref><ref name="OhChiu2009"/><ref name="XuEtAl2010"/> and is expected to occur also for IHE including DNAN and NTO.
  
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The two most predominant forms of organic carbon in natural systems are natural organic matter (NOM) and black carbon (BC)<ref name="Schumacher2002">Schumacher, B.A., 2002. Methods for the Determination of Total Organic Carbon (TOC) in Soils and Sediments. U.S. EPA, Ecological Risk Assessment Support Center. [http://bcodata.whoi.edu/LaurentianGreatLakes_Chemistry/bs116.pdf Free download.]</ref>. Black carbon includes charcoal, soot, graphite, and coal. Until the early 2000s black carbon was considered to be a class of (bio)chemically inert geosorbents<ref name="Schmidt2000">Schmidt, M.W.I., and Noack, A.G., 2000. Black carbon in soils and sediments: Analysis, distribution, implications, and current challenges. Global Biogeochemical Cycles, 14(3), pp. 777–793.  [https://doi.org/10.1029/1999GB001208 DOI: 10.1029/1999GB001208]&nbsp;&nbsp; [https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/1999GB001208 Open access article.]</ref>. However, it has been shown that BC can contain abundant quinone functional groups and thus can store and exchange electrons<ref name="Klüpfel2014">Klüpfel, L., Keiluweit, M., Kleber, M., and Sander, M., 2014. Redox Properties of Plant Biomass-Derived Black Carbon (Biochar). Environmental Science and Technology, 48(10), pp. 5601–5611. [https://doi.org/10.1021/es500906d DOI: 10.1021/es500906d]</ref> with chemical<ref name="Xin2019">Xin, D., Xian, M., and Chiu, P.C., 2019. New methods for assessing electron storage capacity and redox reversibility of biochar. Chemosphere, 215, 827–834. [https://doi.org/10.1016/j.chemosphere.2018.10.080 DOI: 10.1016/j.chemosphere.2018.10.080]</ref> and biological<ref name="Saquing2016">Saquing, J.M., Yu, Y.-H., and Chiu, P.C., 2016. Wood-Derived Black Carbon (Biochar) as a Microbial Electron Donor and Acceptor. Environmental Science and Technology Letters, 3(2), pp. 62–66. [https://doi.org/10.1021/acs.estlett.5b00354 DOI: 10.1021/acs.estlett.5b00354]</ref> agents in the surroundings. Specifically, BC such as biochar has been shown to reductively transform MCs including NTO, DNAN, and RDX<ref name="Xin2022"/>.
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Second, biochar contains in its structure abundant redox-facile functional groups such as [[Wikipedia: Quinone | quinones]] and [[Wikipedia: Hydroquinone | hydroquinones]], which are known to accept and donate electrons reversibly.  Depending on the biomass and pyrolysis temperature, certain biochar can possess a rechargeable electron storage capacity (i.e., reversible electron accepting and donating capacity) on the order of several millimoles e<small><sup>–</sup></small>/g<ref>Klüpfel, L., Keiluweit, M., Kleber, M., Sander, M., 2014. Redox Properties of Plant Biomass-Derived Black Carbon (Biochar). Environmental Science and Technology, 48(10), pp. 5601-5611. [https://doi.org/10.1021/es500906d doi: 10.1021/es500906d]</ref><ref>Prévoteau, A., Ronsse, F., Cid, I., Boeckx, P., Rabaey, K., 2016. The electron donating capacity of biochar is dramatically underestimated. Scientific Reports, 6, Article 32870. [https://doi.org/10.1038/srep32870 doi: 10.1038/srep32870]&nbsp;&nbsp; [[Media: PrevoteauEtAl2016.pdf | Open Access Article.pdf]]</ref><ref>Xin, D., Xian, M., Chiu, P.C., 2018. Chemical methods for determining the electron storage capacity of black carbon. MethodsX, 5, pp. 1515-1520. [https://doi.org/10.1016/j.mex.2018.11.007 doi: 10.1016/j.mex.2018.11.007]&nbsp;&nbsp; [[Media: XinEtAl2018.pdf | Open Access Article.pdf]]</ref>. This means that when "charged", biochar can provide electrons for either abiotic or biotic degradation of reducible compounds such as MC. The abiotic reduction of DNT and RDX mediated by biochar has been demonstrated<ref name="OhEtAl2013"/> and similar reactions are expected to occur for DNAN and NTO as well. Recent studies have shown that the electron storage capacity of biochar is also accessible to microbes.  For example, soil bacteria such as [[Wikipedia: Geobacter | ''Geobacter'']] and [[Wikipedia: Shewanella | ''Shewanella'']] species can utilize oxidized (or "discharged") biochar as an electron acceptor for the oxidation of organic substrates such as lactate and acetate<ref>Kappler, A., Wuestner, M.L., Ruecker, A., Harter, J., Halama, M., Behrens, S., 2014. Biochar as an Electron Shuttle between Bacteria and Fe(III) Minerals. Environmental Science and Technology Letters, 1(8), pp. 339-344. [https://doi.org/10.1021/ez5002209 doi: 10.1021/ez5002209]</ref><ref name="SaquingEtAl2016">Saquing, J.M., Yu, Y.-H., Chiu, P.C., 2016. Wood-Derived Black Carbon (Biochar) as a Microbial Electron Donor and Acceptor. Environmental Science and Technology Letters, 3(2), pp. 62-66. [https://doi.org/10.1021/acs.estlett.5b00354 doi: 10.1021/acs.estlett.5b00354]</ref> and reduced (or "charged") biochar as an electron donor for the reduction of nitrate<ref name="SaquingEtAl2016"/>. This is significant because, through microbial access of stored electrons in biochar, contaminants that do not sorb strongly to biochar can still be degraded.  
  
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NOM encompasses all the organic compounds present in terrestrial and aquatic environments and can be classified into two groups, non-humic and humic substances. Humic substances (HS) contain a wide array of functional groups including carboxyl, enol, ether, ketone, ester, amide, (hydro)quinone, and phenol<ref name="Sparks2003">Sparks, D.L., 2003. Environmental Soil Chemistry, 2nd Edition. Elsevier Science and Technology Books.  [https://doi.org/10.1016/B978-0-12-656446-4.X5000-2 DOI: 10.1016/B978-0-12-656446-4.X5000-2]</ref>. Quinone and hydroquinone groups are believed to be the predominant redox moieties responsible for the capacity of HS and BC to store and reversibly accept and donate electrons (i.e., through reduction and oxidation of HS/BC, respectively)<ref name="Schwarzenbach1990"/><ref name="Dunnivant1992"/><ref name="Klüpfel2014"/><ref name="Scott1998">Scott, D.T., McKnight, D.M., Blunt-Harris, E.L., Kolesar, S.E., and Lovley, D.R., 1998. Quinone Moieties Act as Electron Acceptors in the Reduction of Humic Substances by Humics-Reducing Microorganisms. Environmental Science and Technology, 32(19), pp. 2984–2989.  [https://doi.org/10.1021/es980272q DOI: 10.1021/es980272q]</ref><ref name="Cory2005">Cory, R.M., and McKnight, D.M., 2005. Fluorescence Spectroscopy Reveals Ubiquitous Presence of Oxidized and Reduced Quinones in Dissolved Organic Matter. Environmental Science & Technology, 39(21), pp 8142–8149.  [https://doi.org/10.1021/es0506962 DOI: 10.1021/es0506962]</ref><ref name="Fimmen2007">Fimmen, R.L., Cory, R.M., Chin, Y.P., Trouts, T.D., and McKnight, D.M., 2007. Probing the oxidation–reduction properties of terrestrially and microbially derived dissolved organic matter. Geochimica et Cosmochimica Acta, 71(12), pp. 3003–3015.  [https://doi.org/10.1016/j.gca.2007.04.009 DOI: 10.1016/j.gca.2007.04.009]</ref><ref name="Struyk2001">Struyk, Z., and Sposito, G., 2001. Redox properties of standard humic acids. Geoderma, 102(3-4), pp. 329–346.  [https://doi.org/10.1016/S0016-7061(01)00040-4 DOI: 10.1016/S0016-7061(01)00040-4]</ref><ref name="Ratasuk2007">Ratasuk, N., and Nanny, M.A., 2007. Characterization and Quantification of Reversible Redox Sites in Humic Substances. Environmental Science and Technology, 41(22), pp. 7844–7850.  [https://doi.org/10.1021/es071389u DOI: 10.1021/es071389u]</ref><ref name="Aeschbacher2010">Aeschbacher, M., Sander, M., and Schwarzenbach, R.P., 2010. Novel Electrochemical Approach to Assess the Redox Properties of Humic Substances. Environmental Science and Technology, 44(1), pp. 87–93.  [https://doi.org/10.1021/es902627p DOI: 10.1021/es902627p]</ref><ref name="Aeschbacher2011">Aeschbacher, M., Vergari, D., Schwarzenbach, R.P., and Sander, M., 2011. Electrochemical Analysis of Proton and Electron Transfer Equilibria of the Reducible Moieties in Humic Acids. Environmental Science and Technology, 45(19), pp. 8385–8394.  [https://doi.org/10.1021/es201981g DOI: 10.1021/es201981g]</ref><ref name="Bauer2009">Bauer, I., and Kappler, A., 2009. Rates and Extent of Reduction of Fe(III) Compounds and O<sub>2</sub> by Humic Substances. Environmental Science and Technology, 43(13), pp. 4902–4908.  [https://doi.org/10.1021/es900179s DOI: 10.1021/es900179s]</ref><ref name="Maurer2010">Maurer, F., Christl, I. and Kretzschmar, R., 2010. Reduction and Reoxidation of Humic Acid: Influence on Spectroscopic Properties and Proton Binding. Environmental Science and Technology, 44(15), pp. 5787–5792.  [https://doi.org/10.1021/es100594t DOI: 10.1021/es100594t]</ref><ref name="Walpen2016">Walpen, N., Schroth, M.H., and Sander, M., 2016. Quantification of Phenolic Antioxidant Moieties in Dissolved Organic Matter by Flow-Injection Analysis with Electrochemical Detection. Environmental Science and Technology, 50(12), pp. 6423–6432.  [https://doi.org/10.1021/acs.est.6b01120 DOI: 10.1021/acs.est.6b01120]&nbsp;&nbsp; [https://pubs.acs.org/doi/pdf/10.1021/acs.est.6b01120 Open access article.]</ref><ref name="Aeschbacher2012">Aeschbacher, M., Graf, C., Schwarzenbach, R.P., and Sander, M., 2012.  Antioxidant Properties of Humic Substances. Environmental Science and Technology, 46(9), pp. 4916–4925.  [https://doi.org/10.1021/es300039h DOI: 10.1021/es300039h]</ref><ref name="Nurmi2002">Nurmi, J.T., and Tratnyek, P.G., 2002. Electrochemical Properties of Natural Organic Matter (NOM), Fractions of NOM, and Model Biogeochemical Electron Shuttles. Environmental Science and Technology, 36(4), pp. 617–624.  [https://doi.org/10.1021/es0110731 DOI: 10.1021/es0110731]</ref>.  
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Similar to nitrate, perchlorate and other relatively water-soluble energetic compounds (e.g., NTO and NQ) may also be similarly transformed using reduced biochar as an electron donor.  Unlike other electron donors, biochar can be recharged through biodegradation of organic substrates<ref name="SaquingEtAl2016"/> and thus can serve as a long-lasting sorbent and electron repository in soil.  Similar to peat moss, the high porosity and surface area of biochar not only facilitate contaminant sorption but also create anaerobic reducing microenvironments in its inner pores, where reductive degradation of energetic compounds can take place.
  
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Hydroquinones have been widely used as surrogates to understand the reductive transformation of NACs and MCs by NOM. Figure 4 shows the chemical structures of the singly deprotonated forms of four hydroquinone species previously used to study NAC/MC reduction. The second-order rate constants (''k<sub>R</sub>'') for the reduction of NACs/MCs by these hydroquinone species are listed in Table 1, along with the aqueous-phase one electron reduction potentials of the NACs/MCs (''E<sub>H</sub><sup>1’</sup>'') where available. ''E<sub>H</sub><sup>1’</sup>'' is an experimentally measurable thermodynamic property that reflects the propensity of a given NAC/MC to accept an electron in water (''E<sub>H</sub><sup>1</sup>''(R-NO<sub>2</sub>)):
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===Other Sorbents===
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Chitin and unmodified cellulose were predicted by [[Wikipedia: Density functional theory | Density Functional Theory]] methods to be favorable for absorption of NTO and NQ, as well as the legacy explosives<ref>Todde, G., Jha, S.K., Subramanian, G., Shukla, M.K., 2018. Adsorption of TNT, DNAN, NTO, FOX7, and NQ onto Cellulose, Chitin, and Cellulose Triacetate. Insights from Density Functional Theory Calculations. Surface Science, 668, pp. 54-60. [https://doi.org/10.1016/j.susc.2017.10.004 doi: 10.1016/j.susc.2017.10.004]&nbsp;&nbsp; [[Media: ToddeEtAl2018.pdf | Open Access Manuscript.pdf]]</ref>. Cationized cellulosic materials (e.g., cotton, wood shavings) have been shown to effectively remove negatively charged energetics like perchlorate and NTO from solution<ref name="FullerEtAl2022">Fuller, M.E., Farquharson, E.M., Hedman, P.C., Chiu, P., 2022. Removal of munition constituents in stormwater runoff: Screening of native and cationized cellulosic sorbents for removal of insensitive munition constituents NTO, DNAN, and NQ, and legacy munition constituents HMX, RDX, TNT, and perchlorate. Journal of Hazardous Materials, 424(C), Article 127335. [https://doi.org/10.1016/j.jhazmat.2021.127335 doi: 10.1016/j.jhazmat.2021.127335]&nbsp;&nbsp; [[Media: FullerEtAl2022.pdf | Open Access Manuscript.pdf]]</ref>. A substantial body of work has shown that modified cellulosic biopolymers can also be effective sorbents for removing metals from solution<ref>Burba, P., Willmer, P.G., 1983. Cellulose: a biopolymeric sorbent for heavy-metal traces in waters. Talanta, 30(5), pp. 381-383. [https://doi.org/10.1016/0039-9140(83)80087-3 doi: 10.1016/0039-9140(83)80087-3]</ref><ref>Brown, P.A., Gill, S.A., Allen, S.J., 2000. Metal removal from wastewater using peat. Water Research, 34(16), pp. 3907-3916. [https://doi.org/10.1016/S0043-1354(00)00152-4 doi: 10.1016/S0043-1354(00)00152-4]</ref><ref>O’Connell, D.W., Birkinshaw, C., O’Dwyer, T.F., 2008. Heavy metal adsorbents prepared from the modification of cellulose: A review. Bioresource Technology, 99(15), pp. 6709-6724. [https://doi.org/10.1016/j.biortech.2008.01.036 doi: 10.1016/j.biortech.2008.01.036]</ref><ref>Wan Ngah, W.S., Hanafiah, M.A.K.M., 2008. Removal of heavy metal ions from wastewater by chemically modified plant wastes as adsorbents: A review. Bioresource Technology, 99(10), pp. 3935-3948. [https://doi.org/10.1016/j.biortech.2007.06.011 doi: 10.1016/j.biortech.2007.06.011]</ref> and therefore will also likely be applicable for some of the metals that may be found in surface runoff at firing ranges.
  
−
:::::<big>'''Equation 1:'''&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;''R-NO<sub>2</sub> + e<sup>-</sup> ⇔ R-NO<sub>2</sub><sup>•-</sup>''</big>
+
==Technology Evaluation==
 +
Based on the properties of the target munition constituents, a combination of materials was expected to yield the best results to facilitate the sorption and subsequent biotic and abiotic degradation of the contaminants.
  
−
Knowing the identity of and reaction order in the reductant is required to derive the second-order rate constants listed in Table 1. This same reason limits the utility of reduction rate constants measured with complex carbonaceous reductants such as NOM<ref name="Dunnivant1992"/>, BC<ref name="Oh2013"/><ref name="Oh2009"/><ref name="Xu2015"/><ref name="Xin2021">Xin, D., 2021. Understanding the Electron Storage Capacity of Pyrogenic Black Carbon: Origin, Redox Reversibility, Spatial Distribution, and Environmental Applications. Doctoral Thesis, University of Delaware.  [https://udspace.udel.edu/bitstream/handle/19716/30105/Xin_udel_0060D_14728.pdf?sequence=1 Free download.]</ref>, and HS<ref name="Luan2010"/><ref name="Murillo-Gelvez2021"/>, whose chemical structures and redox moieties responsible for the reduction, as well as their abundance, are not clearly defined or known. In other words, the observed rate constants in those studies are specific to the experimental conditions (e.g., pH and NOM source and concentration), and may not be easily comparable to other studies.
+
===Sorbents===
−
 
+
{| class="wikitable" style="margin-right: 30px; margin-left: auto; float:left; text-align:center;"
−
{| class="wikitable mw-collapsible" style="float:left; margin-right:40px; text-align:center;"
+
|+Table 1. [[Wikipedia: Freundlich equation | Freundlich]] and [[Wikipedia: Langmuir adsorption model | Langmuir]] adsorption parameters for insensitive and legacy explosives
−
|+ Table&nbsp;1.&nbsp;Aqueous&nbsp;phase one electron reduction potentials and logarithm of second-order rate constants for the reduction of NACs and MCs by the singly deprotonated form of the hydroquinones lawsone, juglone, AHQDS and AHQS, with the second-order rate constants for the deprotonated NAC/MC species (i.e., nitrophenolates and NTO<sup>–</sup>) in parentheses.
+
|-
 +
! rowspan="2" | Compound
 +
! colspan="5" | Freundlich
 +
! colspan="5" | Langmuir
 
|-
 
|-
−
! Compound 
+
! Parameter !! Peat !! CAT Pine !! CAT Burlap !! CAT Cotton !! Parameter !! Peat !! CAT Pine !! CAT Burlap !! CAT Cotton
−
! rowspan="2" |''E<sub>H</sub><sup>1'</sup>'' (V)
 
−
! colspan="4"| Hydroquinone [log ''k<sub>R</sub>''&nbsp;(M<sup>-1</sup>s<sup>-1</sup>)]
 
 
|-
 
|-
−
! (NAC/MC)
+
| colspan="12" style="background-color:white;" |
−
! LAW<sup>-</sup>
 
−
! JUG<sup>-</sup>
 
−
! AHQDS<sup>-</sup>
 
−
! AHQS<sup>-</sup>
 
 
|-
 
|-
−
| Nitrobenzene (NB) || -0.485<ref name="Schwarzenbach1990"/> || 0.380<ref name="Schwarzenbach1990"/> || -1.102<ref name="Schwarzenbach1990"/> || 2.050<ref name="Murillo-Gelvez2019"/> || 3.060<ref name="Murillo-Gelvez2019"/>
+
! rowspan="3" | HMX
 +
! ''K<sub>f</sub>''
 +
| 0.08 +/- 0.00 || -- || -- || --
 +
! ''q<sub>m</sub>'' (mg/g)
 +
| 0.29 +/- 0.04 || -- || -- || --
 
|-
 
|-
−
| 2-nitrotoluene (2-NT) || -0.590<ref name="Schwarzenbach1990"/> || -1.432<ref name="Schwarzenbach1990"/> || -2.523<ref name="Schwarzenbach1990"/> || 0.775<ref name="Hartenbach2008"/> ||  
+
! ''n''
 +
| 1.70 +/- 0.18 || -- || -- || --
 +
! ''b'' (L/mg)
 +
| 0.39 +/- 0.09 || -- || -- || --
 
|-  
 
|-  
−
| 3-nitrotoluene (3-NT) || -0.475<ref name="Schwarzenbach1990"/> || 0.462<ref name="Schwarzenbach1990"/> || -0.921<ref name="Schwarzenbach1990"/> || ||
+
! ''r<sup>2</sup>''
 +
| 0.91 || -- || -- || --
 +
! ''r<sup>2</sup>''
 +
| 0.93 || -- || -- || --
 
|-
 
|-
−
| 4-nitrotoluene (4-NT) || -0.500<ref name="Schwarzenbach1990"/> || 0.041<ref name="Schwarzenbach1990"/> || -1.292<ref name="Schwarzenbach1990"/> || 1.822<ref name="Hartenbach2008"/> || 2.610<ref name="Murillo-Gelvez2019"/>
+
| colspan="12" style="background-color:white;" |
 
|-
 
|-
−
| 2-chloronitrobenzene (2-ClNB) || -0.485<ref name="Schwarzenbach1990"/> || 0.342<ref name="Schwarzenbach1990"/> || -0.824<ref name="Schwarzenbach1990"/> ||2.412<ref name="Hartenbach2008"/> ||
+
! rowspan="3" | RDX
 +
! ''K<sub>f</sub>''
 +
| 0.11 +/- 0.02 || -- || -- || --
 +
! ''q<sub>m</sub>'' (mg/g)
 +
| 0.38 +/- 0.05 || -- || -- || --
 
|-
 
|-
−
| 3-chloronitrobenzene (3-ClNB) || -0.405<ref name="Schwarzenbach1990"/> || 1.491<ref name="Schwarzenbach1990"/> || 0.114<ref name="Schwarzenbach1990"/> || ||
+
! ''n''
 +
| 2.75 +/- 0.63 || -- || -- || --
 +
! ''b'' (L/mg)
 +
| 0.23 +/- 0.08 || -- || -- || --
 +
|-
 +
! ''r<sup>2</sup>''
 +
| 0.69 || -- || -- || --
 +
! ''r<sup>2</sup>''
 +
| 0.69 || -- || -- || --
 
|-
 
|-
−
| 4-chloronitrobenzene (4-ClNB) || -0.450<ref name="Schwarzenbach1990"/> || 1.041<ref name="Schwarzenbach1990"/> || -0.301<ref name="Schwarzenbach1990"/> || 2.988<ref name="Hartenbach2008"/> ||
+
| colspan="12" style="background-color:white;" |
 
|-
 
|-
−
| 2-acetylnitrobenzene (2-AcNB) || -0.470<ref name="Schwarzenbach1990"/> || 0.519<ref name="Schwarzenbach1990"/> || -0.456<ref name="Schwarzenbach1990"/> || ||  
+
! rowspan="3" | TNT
 +
! ''K<sub>f</sub>''
 +
| 1.21 +/- 0.15 || 1.02 +/- 0.04 || 0.36 +/- 0.02 || --
 +
! ''q<sub>m</sub>'' (mg/g)
 +
| 3.63 +/- 0.18 || 1.26 +/- 0.06 || -- || --
 
|-
 
|-
−
| 3-acetylnitrobenzene (3-AcNB) || -0.405<ref name="Schwarzenbach1990"/> || 1.663<ref name="Schwarzenbach1990"/> || 0.398<ref name="Schwarzenbach1990"/> || ||
+
! ''n''
 +
| 2.78 +/- 0.67 || 4.01 +/- 0.44 || 1.59 +/- 0.09 || --
 +
! ''b'' (L/mg)
 +
| 0.89 +/- 0.13 || 0.76 +/- 0.10 || -- || --
 +
|-
 +
! ''r<sup>2</sup>''
 +
| 0.81 || 0.93 || 0.98 || --
 +
! ''r<sup>2</sup>''
 +
| 0.97 || 0.97 || -- || --
 
|-
 
|-
−
| 4-acetylnitrobenzene (4-AcNB) || -0.360<ref name="Schwarzenbach1990"/> || 2.519<ref name="Schwarzenbach1990"/> || 1.477<ref name="Schwarzenbach1990"/> || ||
+
| colspan="12" style="background-color:white;" |
 
|-
 
|-
−
| 2-nitrophenol (2-NP) || || 0.568 (0.079)<ref name="Schwarzenbach1990"/> || || ||
+
! rowspan="3" | NTO
 +
! ''K<sub>f</sub>''
 +
| -- || 0.94 +/- 0.05 || 0.41 +/- 0.05 || 0.26 +/- 0.06
 +
! ''q<sub>m</sub>'' (mg/g)
 +
| -- || 4.07 +/- 0.26 || 1.29 +/- 0.12 || 0.83 +/- .015
 
|-
 
|-
−
| 4-nitrophenol (4-NP) || || -0.699 (-1.301)<ref name="Schwarzenbach1990"/> || || ||
+
! ''n''
 +
| -- || 1.61 +/- 0.11 || 2.43 +/- 0.41 || 2.53 +/- 0.76
 +
! ''b'' (L/mg)
 +
| -- || 0.30 +/- 0.04 || 0.36 +/- 0.08 || 0.30 +/- 0.15
 +
|-
 +
! ''r<sup>2</sup>''
 +
| -- || 0.97 || 0.82 || 0.57
 +
! ''r<sup>2</sup>''
 +
| -- || 0.99 || 0.89 || 0.58
 
|-
 
|-
−
| 4-methyl-2-nitrophenol (4-Me-2-NP) || || 0.748 (0.176)<ref name="Schwarzenbach1990"/> || || ||  
+
| colspan="12" style="background-color:white;" |
 
|-
 
|-
−
| 4-chloro-2-nitrophenol (4-Cl-2-NP) || || 1.602 (1.114)<ref name="Schwarzenbach1990"/> || || ||
+
! rowspan="3" | DNAN
 +
! ''K<sub>f</sub>''
 +
| 0.38 +/- 0.05 || 0.01 +/- 0.01 || -- || --
 +
! ''q<sub>m</sub>'' (mg/g)
 +
| 2.57 +/- 0.33 || -- || -- || --
 
|-
 
|-
−
| 5-fluoro-2-nitrophenol (5-Cl-2-NP) || || 0.447 (-0.155)<ref name="Schwarzenbach1990"/> || || ||
+
! ''n''
 +
| 1.71 +/- 0.20 || 0.70 +/- 0.13 || -- || --
 +
! ''b'' (L/mg)
 +
| 0.13 +/- 0.03 || -- || -- || --
 +
|-
 +
! ''r<sup>2</sup>''
 +
| 0.89 || 0.76 || -- || --
 +
! ''r<sup>2</sup>''
 +
| 0.92 || -- || -- || --
 
|-
 
|-
−
| 2,4,6-trinitrotoluene (TNT) || -0.280<ref name="Schwarzenbach2016"/> || || 2.869<ref name="Hofstetter1999"/> || 5.204<ref name="Hartenbach2008"/> ||  
+
| colspan="12" style="background-color:white;" |
 
|-
 
|-
−
| 2-amino-4,6-dinitrotoluene (2-A-4,6-DNT) || -0.400<ref name="Schwarzenbach2016"/> || || 0.987<ref name="Hofstetter1999"/> || ||  
+
! rowspan="3" | ClO<sub>4</sup>
 +
! ''K<sub>f</sub>''
 +
| -- || 1.54 +/- 0.06 || 0.53 +/- 0.03 || --
 +
! ''q<sub>m</sub>'' (mg/g)
 +
| -- || 3.63 +/- 0.18 || 1.26 +/- 0.06 || --
 
|-
 
|-
−
| 4-amino-2,6-dinitrotoluene (4-A-2,6-DNT) || -0.440<ref name="Schwarzenbach2016"/>  || || 0.079<ref name="Hofstetter1999"/> || ||
+
! ''n''
−
|-
+
| -- || 2.42 +/- 0.16 || 2.42 +/- 0.26 || --
−
| 2,4-diamino-6-nitrotoluene (2,4-DA-6-NT) || -0.505<ref name="Schwarzenbach2016"/> || || -1.678<ref name="Hofstetter1999"/> || ||
+
! ''b'' (L/mg)
−
|-
+
| -- || 0.89 +/- 0.13 || 0.76 +/- 0.10 || --
−
| 2,6-diamino-4-nitrotoluene (2,6-DA-4-NT) || -0.495<ref name="Schwarzenbach2016"/> || || -1.252<ref name="Hofstetter1999"/> || ||  
+
|-  
−
|-
+
! ''r<sup>2</sup>''
−
| 1,3-dinitrobenzene (1,3-DNB) || -0.345<ref name="Hofstetter1999"/> || || 1.785<ref name="Hofstetter1999"/> || ||
+
| -- || 0.97 || 0.92 || --
−
|-
+
! ''r<sup>2</sup>''
−
| 1,4-dinitrobenzene (1,4-DNB) || -0.257<ref name="Hofstetter1999"/> || || 3.839<ref name="Hofstetter1999"/> || ||
+
| -- || 0.97 || 0.97 || --
−
|-
 
−
| 2-nitroaniline (2-NANE) || < -0.560<ref name="Hofstetter1999"/> || || -2.638<ref name="Hofstetter1999"/> || ||
 
−
|-
 
−
| 3-nitroaniline (3-NANE) || -0.500<ref name="Hofstetter1999"/> || || -1.367<ref name="Hofstetter1999"/> || ||
 
 
|-
 
|-
−
| 1,2-dinitrobenzene (1,2-DNB) || -0.290<ref name="Hofstetter1999"/> || || || 5.407<ref name="Hartenbach2008"/> ||
+
| colspan="12" style="text-align:left; background-color:white;" |<small>Notes:</small><br /><big>'''--'''</big> <small>Indicates the algorithm failed to converge on the model fitting parameters, therefore there was no successful model fit.<br />'''CAT''' Indicates cationized material.</small>
−
|-
 
−
| 4-nitroanisole (4-NAN) || || -0.661<ref name="Murillo-Gelvez2019"/> || || 1.220<ref name="Murillo-Gelvez2019"/> ||
 
−
|-
 
−
| 2-amino-4-nitroanisole (2-A-4-NAN) || || -0.924<ref name="Murillo-Gelvez2019"/> || || 1.150<ref name="Murillo-Gelvez2019"/> || 2.190<ref name="Murillo-Gelvez2019"/>  
 
−
|-
 
−
| 4-amino-2-nitroanisole (4-A-2-NAN) || || || ||1.610<ref name="Murillo-Gelvez2019"/> || 2.360<ref name="Murillo-Gelvez2019"/>  
 
−
|-
 
−
| 2-chloro-4-nitroaniline (2-Cl-5-NANE) || || -0.863<ref name="Murillo-Gelvez2019"/> || || 1.250<ref name="Murillo-Gelvez2019"/> || 2.210<ref name="Murillo-Gelvez2019"/>
 
−
|-
 
−
| N-methyl-4-nitroaniline (MNA) || || -1.740<ref name="Murillo-Gelvez2019"/> || || -0.260<ref name="Murillo-Gelvez2019"/> || 0.692<ref name="Murillo-Gelvez2019"/>
 
−
|-
 
−
| 3-nitro-1,2,4-triazol-5-one (NTO) || || || || 5.701 (1.914)<ref name="Murillo-Gelvez2021"/> ||
 
−
|-
 
−
| Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) || || || || -0.349<ref name="Kwon2008"/> ||
 
 
|}
 
|}
  
−
[[File:AbioMCredFig5.png | thumb |500px|Figure 5. Relative reduction rate constants of the NACs/MCs listed in Table 1 for AHQDS<sup>–</sup>. Rate constants are compared with respect to RDX. Abbreviations of NACs/MCs as listed in Table 1.]]
+
The&nbsp;materials&nbsp;screened&nbsp;included [[Wikipedia: Sphagnum | ''Sphagnum'' peat moss]], primarily for sorption of HMX, RDX, TNT, and DNAN, as well as [[Wikipedia: Cationization of cotton | cationized cellulosics]] for removal of perchlorate and NTO.  The cationized cellulosics that were examined included: pine sawdust, pine shavings, aspen shavings, cotton linters (fine, silky fibers which adhere to cotton seeds after ginning), [[Wikipedia: Chitin | chitin]], [[Wikipedia: Chitosan |  chitosan]], burlap (landscaping grade), [[Wikipedia: Coir | coconut coir]], raw cotton, raw organic cotton, cleaned raw cotton, cotton fabric, and commercially cationized fabrics.
−
Most of the current knowledge about MC degradation is derived from studies using NACs. The reduction kinetics of only four MCs, namely TNT, N-methyl-4-nitroaniline (MNA), NTO, and RDX, have been investigated with hydroquinones. Of these four MCs, only the reduction rates of MNA and TNT have been modeled<ref name="Hofstetter1999"/><ref name="Murillo-Gelvez2019"/><ref name="Riefler2000">Riefler, R.G., and Smets, B.F., 2000. Enzymatic Reduction of 2,4,6-Trinitrotoluene and Related Nitroarenes: Kinetics Linked to One-Electron Redox Potentials. Environmental Science and Technology, 34(18), pp. 3900–3906.  [https://doi.org/10.1021/es991422f DOI: 10.1021/es991422f]</ref><ref name="Salter-Blanc2015">Salter-Blanc, A.J., Bylaska, E.J., Johnston, H.J., and Tratnyek, P.G., 2015. Predicting Reduction Rates of Energetic Nitroaromatic Compounds Using Calculated One-Electron Reduction Potentials. Environmental Science and Technology, 49(6), pp. 3778–3786.  [https://doi.org/10.1021/es505092s DOI: 10.1021/es505092s]&nbsp;&nbsp; [https://pubs.acs.org/doi/pdf/10.1021/es505092s Open access article.]</ref>.  
 
  
−
Using the rate constants obtained with AHQDS<sup>–</sup>, a relative reactivity trend can be obtained (Figure 5). RDX is the slowest reacting MC in Table 1, hence it was selected to calculate the relative rates of reaction (i.e., log ''k<sub>NAC/MC</sub>'' – log ''k<sub>RDX</sub>''). If only the MCs in Figure 5 are considered, the reactivity spans 6 orders of magnitude following the trend: RDX ≈ MNA < NTO<sup>–</sup> < DNAN < TNT < NTO. The rate constant for DNAN reduction by AHQDS<sup>–</sup> is not yet published and hence not included in Table 1. Note that speciation of NACs/MCs can significantly affect their reduction rates. Upon deprotonation, the NAC/MC becomes negatively charged and less reactive as an oxidant (i.e., less prone to accept an electron). As a result, the second-order rate constant can decrease by 0.5-0.6 log unit in the case of nitrophenols and approximately 4 log units in the case of NTO (numbers in parentheses in Table 1)<ref name="Schwarzenbach1990"/><ref name="Murillo-Gelvez2021"/>.
+
As shown in Table 1<ref name="FullerEtAl2022"/>, batch sorption testing indicated that a combination of Sphagnum peat moss and cationized pine shavings provided good removal of both the neutral organic energetics (HMX, RDX, TNT, DNAN) as well as the negatively charged energetics (perchlorate, NTO).
  
−
==Ferruginous Reductants==
+
===Slow Release Carbon Sources===
−
{| class="wikitable mw-collapsible" style="float:right; margin-left:40px; text-align:center;"
+
{| class="wikitable" style="margin-right: 30px; margin-left: auto; float:left; text-align:center;"
−
|+ Table&nbsp;2.&nbsp;Logarithm&nbsp;of&nbsp;second-order rate constants for reduction of NACs and MCs by dissolved Fe(II) complexes with the stoichiometry of ligand and iron in square brackets
+
|+Table 2. Slow-release Carbon Sources
−
|-
 
−
! rowspan="2" | Compound
 
−
! rowspan="2" | E<sub>H</sub><sup>1'</sup>  (V)
 
−
! Cysteine<ref name="Naka2008"/></br>[FeL<sub>2</sub>]<sup>2-</sup>
 
−
! Thioglycolic acid<ref name="Naka2008"/></br>[FeL<sub>2</sub>]<sup>2-</sup>
 
−
! DFOB<ref name="Kim2009"/></br>[FeHL]<sup>0</sup>
 
−
! AcHA<ref name="Kim2009"/></br>[FeL<sub>3</sub>]<sup>-</sup>
 
−
! Tiron <sup>a</sup></br>[FeL<sub>2</sub>]<sup>6-</sup>
 
−
! Fe-Porphyrin <sup>b</sup>
 
−
|-
 
−
! colspan="6" | Fe(II)-Ligand [log ''k<sub>R</sub>'' (M<sup>-1</sup>s<sup>-1</sup>)]
 
−
|-
 
−
| Nitrobenzene || -0.485<ref name="Schwarzenbach1990"/> || -0.347 || 0.874 || 2.235 || -0.136 || 1.424<ref name="Gao2021">Gao, Y., Zhong, S., Torralba-Sanchez, T.L., Tratnyek, P.G., Weber, E.J., Chen, Y., and Zhang, H., 2021. Quantitative structure activity relationships (QSARs) and machine learning models for abiotic reduction of organic compounds by an aqueous Fe(II) complex. Water Research, 192, p. 116843.  [https://doi.org/10.1016/j.watres.2021.116843 DOI: 10.1016/j.watres.2021.116843]</ref></br>4.000<ref name="Salter-Blanc2015"/> || -0.018<ref name="Schwarzenbach1990"/></br>0.026<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| 2-nitrotoluene || -0.590<ref name="Schwarzenbach1990"/> || || || || || || -0.602<ref name="Schwarzenbach1990"/>
 
−
|-
 
−
| 3-nitrotoluene || -0.475<ref name="Schwarzenbach1990"/> || -0.434 || 0.767 || 2.106 || -0.229 || 1.999<ref name="Gao2021"/></br>3.800<ref name="Salter-Blanc2015"/> || 0.041<ref name="Schwarzenbach1990"/>
 
 
|-
 
|-
−
| 4-nitrotoluene || -0.500<ref name="Schwarzenbach1990"/> || -0.652 || 0.528 || 2.013 || -0.402 || 1.446<ref name="Gao2021"/></br>3.500<ref name="Salter-Blanc2015"/> || -0.174<ref name="Schwarzenbach1990"/>
+
! Material !! Abbreviation !! Commercial Source !! Notes
 
|-
 
|-
−
| 2-chloronitrobenzene || -0.485<ref name="Schwarzenbach1990"/> || || || || || || 0.944<ref name="Schwarzenbach1990"/>
+
| polylactic acid || PLA6 || [https://www.goodfellow.com/usa?srsltid=AfmBOoqEiqIbrvWb1Hn1Bc090efBUUfg6V4N3Vrn6ytajHMJR-FG1Ez- Goodfellow] || high molecular weight thermoplastic polyester
 
|-
 
|-
−
| 3-chloronitrobenzene || -0.405<ref name="Schwarzenbach1990"/> || 0.360 || 1.810 || 2.888 || 0.691 || 2.882<ref name="Gao2021"/></br>4.900<ref name="Salter-Blanc2015"/> || 0.724<ref name="Schwarzenbach1990"/>
+
| polylactic acid || PLA80 || [https://www.goodfellow.com/usa?srsltid=AfmBOoqEiqIbrvWb1Hn1Bc090efBUUfg6V4N3Vrn6ytajHMJR-FG1Ez- Goodfellow] || low molecular weight thermoplastic polyester
 
|-
 
|-
−
| 4-chloronitrobenzene || -0.450<ref name="Schwarzenbach1990"/> || 0.230 || 1.415 || 2.512 || 0.375 || 3.937<ref name="Gao2021"/></br>4.581<ref name="Naka2006"/> || 0.431<ref name="Schwarzenbach1990"/></br>0.289<ref name="Salter-Blanc2015"/>
+
| polyhydroxybutyrate || PHB || [https://www.goodfellow.com/usa?srsltid=AfmBOoqEiqIbrvWb1Hn1Bc090efBUUfg6V4N3Vrn6ytajHMJR-FG1Ez- Goodfellow] || bacterial polyester
−
|-
 
−
| 2-acetylnitrobenzene || -0.470<ref name="Schwarzenbach1990"/> || || || || || || 1.377<ref name="Schwarzenbach1990"/>
 
 
|-
 
|-
−
| 3-acetylnitrobenzene || -0.405<ref name="Schwarzenbach1990"/> || || || || || || 0.799<ref name="Schwarzenbach1990"/>
+
| polycaprolactone || PCL || [https://www.sarchemlabs.com/?hsa_acc=4540346154&hsa_cam=20281343997&hsa_grp&hsa_ad&hsa_src=x&hsa_tgt&hsa_kw&hsa_mt&hsa_net=adwords&hsa_ver=3&gad_source=1&gad_campaignid=21209931835 Sarchem Labs] || biodegradable polyester
 
|-
 
|-
−
| 4-acetylnitrobenzene || -0.360<ref name="Schwarzenbach1990"/> || 0.965 || 2.771 || || 1.872 || 5.028<ref name="Gao2021"/></br>6.300<ref name="Salter-Blanc2015"/> || 1.693<ref name="Schwarzenbach1990"/>
+
| polybutylene succinate || BioPBS || [https://us.mitsubishi-chemical.com/company/performance-polymers/ Mitsubishi Chemical Performance Polymers] || compostable bio-based product
 
|-
 
|-
−
| RDX || -0.550<ref name="Uchimiya2010">Uchimiya, M., Gorb, L., Isayev, O., Qasim, M.M., and Leszczynski, J., 2010.  One-electron standard reduction potentials of nitroaromatic and cyclic nitramine explosives. Environmental Pollution, 158(10), pp. 3048–3053.  [https://doi.org/10.1016/j.envpol.2010.06.033 DOI: 10.1016/j.envpol.2010.06.033]</ref> || || || || || 2.212<ref name="Gao2021"/></br>2.864<ref name="Kim2007"/> ||  
+
| sucrose ester of fatty acids || SEFA SP10 || [https://www.sisterna.com/ Sisterna] || food and cosmetics additive
 
|-
 
|-
−
| HMX || -0.660<ref name="Uchimiya2010"/> || || || || || -2.762<ref name="Gao2021"/> ||
+
| sucrose ester of fatty acids || SEFA SP70 || [https://www.sisterna.com/ Sisterna] || food and cosmetics additive
−
|-
 
−
| TNT || -0.280<ref name="Schwarzenbach2016"/> || || || || || 7.427<ref name="Gao2021"/> || 2.050<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| 1,3-dinitrobenzene || -0.345<ref name="Hofstetter1999"/> || || || || || || 1.220<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| 2,4-dinitrotoluene || -0.380<ref name="Schwarzenbach2016"/> || || || || || 5.319<ref name="Gao2021"/> || 1.156<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| Nitroguanidine (NQ) || -0.700<ref name="Uchimiya2010"/> || || || || || -0.185<ref name="Gao2021"/> ||
 
−
|-
 
−
| 2,4-dinitroanisole (DNAN) || -0.400<ref name="Uchimiya2010"/> || || || || || || 1.243<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| colspan="8" style="text-align:left; background-color:white;" | Notes:</br>''<sup>a</sup>'' 4,5-dihydroxybenzene-1,3-disulfonate (Tiron). ''<sup>b</sup>'' meso-tetra(N-methyl-pyridyl)iron porphin in cysteine.
 
−
|}
 
−
{| class="wikitable mw-collapsible" style="float:left; margin-right:40px; text-align:center;"
 
−
|+ Table&nbsp;3.&nbsp;Rate constants for the reduction of MCs by iron minerals
 
−
|-
 
−
! MC
 
−
! Iron Mineral
 
−
! Iron mineral loading</br>(g/L)
 
−
! Surface area</br>(m<sup>2</sup>/g)
 
−
! Fe(II)<sub>aq</sub> initial</br>(mM) ''<sup>b</sup>''
 
−
! Fe(II)<sub>aq</sub> after 24 h</br>(mM) ''<sup>c</sup>''
 
−
! Fe(II)<sub>aq</sub> sorbed</br>(mM) ''<sup>d</sup>''
 
−
! pH
 
−
! Buffer
 
−
! Buffer</br>(mM)
 
−
! MC initial</br>(&mu;M) ''<sup>e</sup>''
 
−
! log ''k<sub>obs</sub>''</br>(h<sup>-1</sup>) ''<sup>f</sup>''
 
−
! log ''k<sub>SA</sub>''</br>(Lh<sup>-1</sup>m<sup>-2</sup>) ''<sup>g</sup>''
 
−
|-
 
−
| TNT<ref name="Hofstetter1999"/> || Goethite || 0.64 || 17.5 || 1.5 || || || 7.0 || MOPS || 25 || 50 || 1.200 || 0.170
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 0.1 || 0 || 0.10 || 7.0 || HEPES || 50 || 50 || -3.500 || -5.200
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 0.2 || 0.02 || 0.18 || 7.0 || HEPES || 50 || 50 || -2.900 || -4.500
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 0.5 || 0.23 || 0.27 || 7.0 || HEPES || 50 || 50 || -1.900 || -3.600
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 1.5 || 0.94 || 0.56 || 7.0 || HEPES || 50 || 50 || -1.400 || -3.100
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 3.0 || 1.74 || 1.26 || 7.0 || HEPES || 50 || 50 || -1.200 || -2.900
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 5.0 || 3.38 || 1.62 || 7.0 || HEPES || 50 || 50 || -1.100 || -2.800
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 10.0 || 7.77 || 2.23 || 7.0 || HEPES || 50 || 50 || -1.000 || -2.600
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 1.6 || 1.42 || 0.16 || 6.0 || MES || 50 || 50 || -2.700 || -4.300
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 1.6 || 1.34 || 0.24 || 6.5 || MOPS || 50 || 50 || -1.800 || -3.400
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 1.6 || 1.21 || 0.37 || 7.0 || MOPS || 50 || 50 || -1.200 || -2.900
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 1.6 || 1.01 || 0.57 || 7.0 || HEPES || 50 || 50 || -1.200 || -2.800
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 1.6 || 0.76 || 0.82 || 7.5 || HEPES || 50 || 50 || -0.490 || -2.100
 
−
|-
 
−
| RDX<ref name="Gregory2004"/> || Magnetite || 1.00 || 44 || 1.6 || 0.56 || 1.01 || 8.0 || HEPES || 50 || 50 || -0.590 || -2.200
 
−
|-
 
−
| NG<ref name="Oh2004"/> || Magnetite || 4.00 || 0.56|| 4.0 || || || 7.4 || HEPES || 90 || 226 || ||
 
−
|-
 
−
| NG<ref name="Oh2008"/> || Pyrite || 20.00 || 0.53 || || || || 7.4 || HEPES || 100 || 307 || -2.213 || -3.238
 
−
|-
 
−
| TNT<ref name="Oh2008"/> || Pyrite || 20.00 || 0.53 ||  || || || 7.4 || HEPES || 100 || 242 || -2.812 || -3.837
 
−
|-
 
−
| RDX<ref name="Oh2008"/> || Pyrite || 20.00 || 0.53 || || ||  || 7.4 || HEPES || 100 || 201 || -3.058 || -4.083
 
−
|-
 
−
| RDX<ref name="Larese-Casanova2008"/> || Carbonate Green Rust || 5.00 || 36 || || || || 7.0 || || || 100 || ||
 
−
|-
 
−
| RDX<ref name="Larese-Casanova2008"/> || Sulfate Green Rust || 5.00 || 20 || || || || 7.0 || || || 100 || ||
 
−
|-
 
−
| DNAN<ref name="Khatiwada2018"/> || Sulfate Green Rust || 10.00 || || || || || 8.4 || || || 500 || ||
 
−
|-
 
−
| NTO<ref name="Khatiwada2018"/> || Sulfate Green Rust || 10.00 || || || || || 8.4 || || || 500 || ||
 
−
|-
 
−
| DNAN<ref name="Berens2019"/> || Magnetite || 2.00 || 17.8 || 1.0 || || || 7.0 || NaHCO<sub>3</sub> || 10 || 200 || -0.100 || -1.700
 
−
|-
 
−
| DNAN<ref name="Berens2019"/> || Mackinawite || 1.50 || || || || || 7.0 || NaHCO<sub>3</sub> || 10 || 200 || 0.061 ||
 
−
|-
 
−
| DNAN<ref name="Berens2019"/> || Goethite || 1.00 || 103.8 || 1.0 || || || 7.0 || NaHCO<sub>3</sub> || 10 || 200 || 0.410 || -1.600
 
−
|-
 
−
| RDX<ref name="Strehlau2018"/> || Magnetite || 0.62 ||  || 1.0 ||  ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 17.5 || -1.100 ||
 
−
|-
 
−
| RDX<ref name="Strehlau2018"/> || Magnetite || 0.62 ||  ||  ||  ||  || 7.0 || MOPS || 50 || 17.5 || -0.270 ||
 
−
|-
 
−
| RDX<ref name="Strehlau2018"/> || Magnetite || 0.62 ||  || 1.0 ||  ||  || 7.0 || MOPS || 10 || 17.6 || -0.480 ||
 
−
|-
 
−
| NTO<ref name="Cardenas-Hernandez2020"/> || Hematite || 1.00 || 5.7 || 1.0 || 0.92 || 0.08 || 5.5 || MES || 50 || 30 || -0.550 || -1.308
 
−
|-
 
−
| NTO<ref name="Cardenas-Hernandez2020"/> || Hematite || 1.00 || 5.7 || 1.0 || 0.85 || 0.15 || 6.0 || MES || 50 || 30 || 0.619 || -0.140
 
−
|-
 
−
| NTO<ref name="Cardenas-Hernandez2020"/> || Hematite || 1.00 || 5.7 || 1.0 || 0.9 || 0.10 || 6.5 || MES || 50 || 30 || 1.348 || 0.590
 
−
|-
 
−
| NTO<ref name="Cardenas-Hernandez2020"/> || Hematite || 1.00 || 5.7 || 1.0 || 0.77 || 0.23 || 7.0 || MOPS || 50 || 30 || 2.167 || 1.408
 
−
|-
 
−
| NTO<ref name="Cardenas-Hernandez2020"/> || Hematite ''<sup>a</sup>'' || 1.00 || 5.7 ||  || 1.01 ||  || 5.5 || MES || 50 || 30 || -1.444 || -2.200
 
−
|-
 
−
| NTO<ref name="Cardenas-Hernandez2020"/> || Hematite ''<sup>a</sup>'' || 1.00 || 5.7 ||  || 0.97 ||  || 6.0 || MES || 50 || 30 || -0.658 || -1.413
 
−
|-
 
−
| NTO<ref name="Cardenas-Hernandez2020"/> || Hematite ''<sup>a</sup>'' || 1.00 || 5.7 ||  || 0.87 ||  || 6.5 || MES || 50 || 30 || 0.068 || -0.688
 
−
|-
 
−
| NTO<ref name="Cardenas-Hernandez2020"/> || Hematite ''<sup>a</sup>'' || 1.00 || 5.7 ||  || 0.79 ||  || 7.0 || MOPS || 50 || 30 || 1.210 || 0.456
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Mackinawite || 0.45 ||  ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.092 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Mackinawite || 0.45 ||  ||  ||  ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || 0.009 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Mackinawite || 0.45 ||  ||  ||  ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || 0.158 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Green Rust || 5 ||  ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -1.301 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Green Rust || 5 ||  ||  ||  ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || -1.097 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Green Rust || 5 ||  ||  ||  ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.745 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Goethite || 0.5 ||  || 1 || 1 ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.921 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Goethite || 0.5 ||  || 1 || 1 ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || -0.347 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Goethite || 0.5 ||  || 1 || 1 ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || 0.009 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Hematite || 0.5 ||  || 1 || 1 ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.824 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Hematite || 0.5 ||  || 1 || 1 ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || -0.456 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Hematite || 0.5 ||  || 1 || 1 ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.237 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Magnetite || 2 ||  || 1 || 1 ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -1.523 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Magnetite || 2 ||  || 1 || 1 ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || -0.824 ||
 
−
|-
 
−
| RDX<ref name="Tong2021"/>  || Magnetite || 2 || || 1 || 1 ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.229 ||
 
−
|-
 
−
| DNAN<ref name="Menezes2021"/> || Mackinawite || 4.28 || 0.25 ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 8.5 + 20% CO<sub>2</sub>(g) || 400 || 0.836 || 0.806
 
−
|-
 
−
| DNAN<ref name="Menezes2021"/> || Mackinawite || 4.28 || 0.25 ||  ||  ||  || 7.6 || NaHCO<sub>3</sub> || 95.2 + 20% CO<sub>2</sub>(g) || 400 || 0.762 || 0.732
 
−
|-
 
−
| DNAN<ref name="Menezes2021"/> || Commercial FeS || 5.00 || 0.214 ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 8.5 + 20% CO<sub>2</sub>(g) || 400 || 0.477 || 0.447
 
−
|-
 
−
| DNAN<ref name="Menezes2021"/> || Commercial FeS || 5.00 || 0.214 ||  ||  ||  || 7.6 || NaHCO<sub>3</sub> || 95.2 + 20% CO<sub>2</sub>(g) || 400 || 0.745 || 0.716
 
−
|-
 
−
| NTO<ref name="Menezes2021"/> || Mackinawite || 4.28 || 0.25 ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 8.5 + 20% CO<sub>2</sub>(g) || 1000 || 0.663 || 0.633
 
−
|-
 
−
| NTO<ref name="Menezes2021"/> || Mackinawite || 4.28 || 0.25 ||  ||  ||  || 7.6 || NaHCO<sub>3</sub> || 95.2 + 20% CO<sub>2</sub>(g) || 1000 || 0.521 || 0.491
 
−
|-
 
−
| NTO<ref name="Menezes2021"/> || Commercial FeS || 5.00 || 0.214 ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 8.5 + 20% CO<sub>2</sub>(g) || 1000 || 0.492 || 0.462
 
−
|-
 
−
| NTO<ref name="Menezes2021"/> || Commercial FeS || 5.00 || 0.214 ||  ||  ||  || 7.6 || NaHCO<sub>3</sub> || 95.2 + 20% CO<sub>2</sub>(g) || 1000 || 0.427 || 0.398
 
−
|-
 
−
| colspan="13" style="text-align:left; background-color:white;" | Notes:</br>''<sup>a</sup>'' Dithionite-reduced hematite; experiments conducted in the presence of 1 mM sulfite. ''<sup>b</sup>'' Initial aqueous Fe(II); not added for Fe(II) bearing minerals. ''<sup>c</sup>'' Aqueous Fe(II) after 24h of equilibration. ''<sup>d</sup>'' Difference between b and c. ''<sup>e</sup>'' Initial nominal MC concentration. ''<sup>f</sup>'' Pseudo-first order rate constant. ''<sup>g</sup>'' Surface area normalized rate constant calculated as ''k<sub>Obs</sub>'' '''/''' (surface area concentration) or ''k<sub>Obs</sub>'' '''/''' (surface area × mineral loading).
 
−
|}
 
−
{| class="wikitable mw-collapsible" style="float:right; margin-left:40px; text-align:center;"
 
−
|+ Table&nbsp;4.&nbsp;Rate constants for the reduction of NACs by iron oxides in the presence of aqueous Fe(II)
 
−
|-
 
−
! NAC ''<sup>a</sup>''
 
−
! Iron Oxide
 
−
! Iron oxide loading</br>(g/L)
 
−
! Surface area</br>(m<sup>2</sup>/g)
 
−
! Fe(II)<sub>aq</sub> initial</br>(mM) ''<sup>b</sup>''
 
−
! Fe(II)<sub>aq</sub> after 24 h</br>(mM) ''<sup>c</sup>''
 
−
! Fe(II)<sub>aq</sub> sorbed</br>(mM) ''<sup>d</sup>''
 
−
! pH
 
−
! Buffer
 
−
! Buffer</br>(mM)
 
−
! NAC initial</br>(μM) ''<sup>e</sup>''
 
−
! log ''k<sub>obs</sub>''</br>(h<sup>-1</sup>) ''<sup>f</sup>''
 
−
! log ''k<sub>SA</sub>''</br>(Lh<sup>-1</sup>m<sup>-2</sup>) ''<sup>g</sup>''
 
−
|-
 
−
| NB<ref name="Klausen1995"/> || Magnetite || 0.200 || 56.00 || 1.5000 ||  ||  || 7.00 || Phosphate || 10 || 50 || 1.05E+00 || 7.75E-04
 
−
|-
 
−
| 4-ClNB<ref name="Klausen1995"/> || Magnetite || 0.200 || 56.00 || 1.5000 ||  ||  || 7.00 || Phosphate || 10 || 50 || 1.14E+00 || 8.69E-02
 
−
|-
 
−
| 4-ClNB<ref name="Hofstetter1999"/> || Goethite || 0.640 || 17.50 || 1.5000 ||  ||  || 7.00 || MOPS || 25 || 50 || -1.01E-01 || -1.15E+00
 
−
|-
 
−
| 4-ClNB<ref name="Elsner2004"/>  || Goethite || 1.500 || 16.20 || 1.2400 || 0.9600 || 0.2800 || 7.20 || MOPS || 1.2 || 0.5 - 3 || 1.68E+00 || 2.80E-01
 
−
|-
 
−
| 4-ClNB<ref name="Elsner2004"/>  || Hematite || 1.800 || 13.70 || 1.0400 || 1.0100 || 0.0300 || 7.20 || MOPS || 1.2 || 0.5 - 3 || -2.32E+00 || -3.72E+00
 
−
|-
 
−
| 4-ClNB<ref name="Elsner2004"/>  || Lepidocrocite || 1.400 || 17.60 || 1.1400 || 1.0000 || 0.1400 || 7.20 || MOPS || 1.2 || 0.5 - 3 || 1.51E+00 || 1.20E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3500 || 0.0300 || 7.97 || HEPES || 25 || 15 || -7.47E-01 || -8.61E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3700 || 0.0079 || 7.67 || HEPES || 25 || 15 || -1.51E+00 || -1.62E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3600 || 0.0200 || 7.50 || MOPS || 25 || 15 || -2.15E+00 || -2.26E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3600 || 0.0120 || 7.28 || MOPS || 25 || 15 || -3.08E+00 || -3.19E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3700 || 0.0004 || 7.00 || MOPS || 25 || 15 || -3.22E+00 || -3.34E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3700 || 0.0024 || 6.80 || MOPSO || 25 || 15 || -3.72E+00 || -3.83E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3700 || 0.0031 || 6.60 || MES || 25 || 15 || -3.83E+00 || -3.94E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.020 || 292.00 || 0.3750 || 0.3700 || 0.0031 || 6.60 || MES || 25 || 15 || -3.83E+00 || -4.60E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.110 || 292.00 || 0.3750 || 0.3700 || 0.0032 || 6.60 || MES || 25 || 15 || -1.57E+00 || -3.08E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.220 || 292.00 || 0.3750 || 0.3700 || 0.0040 || 6.60 || MES || 25 || 15 || -1.12E+00 || -2.93E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 0.551 || 292.00 || 0.3750 || 0.3700 || 0.0092 || 6.60 || MES || 25 || 15 || -6.18E-01 || -2.82E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 1.099 || 292.00 || 0.3750 || 0.3500 || 0.0240 || 6.60 || MES || 25 || 15 || -3.66E-01 || -2.87E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 1.651 || 292.00 || 0.3750 || 0.3400 || 0.0340 || 6.60 || MES || 25 || 15 || -8.35E-02 || -2.77E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Ferrihydrite || 2.199 || 292.00 || 0.3750 || 0.3300 || 0.0430 || 6.60 || MES || 25 || 15 || -3.11E-02 || -2.84E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.038 || 34.00 || 0.3750 || 0.3320 || 0.0430 || 7.97 || HEPES || 25 || 15 || 1.63E+00 || 1.52E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.038 || 34.00 || 0.3750 || 0.3480 || 0.0270 || 7.67 || HEPES || 25 || 15 || 1.26E+00 || 1.15E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.038 || 34.00 || 0.3750 || 0.3470 || 0.0280 || 7.50 || MOPS || 25 || 15 || 7.23E-01 || 6.10E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.038 || 34.00 || 0.3750 || 0.3680 || 0.0066 || 7.28 || MOPS || 25 || 15 || 4.53E-02 || -6.86E-02
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.038 || 34.00 || 0.3750 || 0.3710 || 0.0043 || 7.00 || MOPS || 25 || 15 || -3.12E-01 || -4.26E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.038 || 34.00 || 0.3750 || 0.3710 || 0.0042 || 6.80 || MOPSO || 25 || 15 || -7.75E-01 || -8.89E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.038 || 34.00 || 0.3750 || 0.3680 || 0.0069 || 6.60 || MES || 25 || 15 || -1.39E+00 || -1.50E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.038 || 34.00 || 0.3750 || 0.3750 || 0.0003 || 6.10 || MES || 25 || 15 || -2.77E+00 || -2.88E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.016 || 34.00 || 0.3750 || 0.3730 || 0.0024 || 6.60 || MES || 25 || 15 || -3.20E+00 || -2.95E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.024 || 34.00 || 0.3750 || 0.3690 || 0.0064 || 6.60 || MES || 25 || 15 || -2.74E+00 || -2.66E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.033 || 34.00 || 0.3750 || 0.3680 || 0.0069 || 6.60 || MES || 25 || 15 || -1.39E+00 || -1.43E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.177 || 34.00 || 0.3750 || 0.3640 || 0.0110 || 6.60 || MES || 25 || 15 || 3.58E-01 || -4.22E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.353 || 34.00 || 0.3750 || 0.3630 || 0.0120 || 6.60 || MES || 25 || 15 || 9.97E-01|| -8.27E-02
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 0.885 || 34.00 || 0.3750 || 0.3480 || 0.0270 || 6.60 || MES || 25 || 15 || 1.34E+00 || -1.34E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Hematite || 1.771 || 34.00 || 0.3750 || 0.3380 || 0.0370 || 6.60 || MES || 25 || 15 || 1.78E+00 || 3.59E-03
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3460 || 0.0290 || 7.97 || HEPES || 25 || 15 || 1.31E+00 || 1.20E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3610 || 0.0140 || 7.67 || HEPES || 25 || 15 || 5.82E-01 || 4.68E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3480 || 0.0270 || 7.50 || MOPS || 25 || 15 || 4.92E-02 || -6.47E-02
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3640 || 0.0110 || 7.28 || MOPS || 25 || 15 || 1.62E+00 || -4.90E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3640 || 0.0110 || 7.00 || MOPS || 25 || 15 || -1.25E+00 || -1.36E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3620 || 0.0130 || 6.80 || MOPSO || 25 || 15 || -1.74E+00 || -1.86E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3740 || 0.0015 || 6.60 || MES || 25 || 15 || -2.58E+00 || -2.69E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3700 || 0.0046 || 6.10 || MES || 25 || 15 || -3.80E+00 || -3.92E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.020 || 49.00 || 0.3750 || 0.3740 || 0.0014 || 6.60 || MES || 25 || 15 || -2.58E+00 || -2.57E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 11.980 || 49.00 || 0.3750 || 0.3620 || 0.0130 || 6.60 || MES || 25 || 15 || -5.78E-01 || -3.35E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.239 || 49.00 || 0.3750 || 0.3530 || 0.0220 || 6.60 || MES || 25 || 15 || -2.78E-02 || -1.10E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 0.600 || 49.00 || 0.3750 || 0.3190 || 0.0560 || 6.60 || MES || 25 || 15 || 3.75E-01 || -1.09E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 1.198 || 49.00 || 0.3750 || 0.2700 || 0.1050 || 6.60 || MES || 25 || 15 || 5.05E-01 || -1.26E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 1.798 || 49.00 || 0.3750 || 0.2230 || 0.1520 || 6.60 || MES || 25 || 15 || 5.56E-01 || -1.39E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Lepidocrocite || 2.388 || 49.00 || 0.3750 || 0.1820 || 0.1930 || 6.60 || MES || 25 || 15 || 5.28E-01 || -1.54E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.025 || 51.00 || 0.3750 || 0.3440 || 0.0310 || 7.97 || HEPES || 25 || 15 || 9.21E-01 || 8.07E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.025 || 51.00 || 0.3750 || 0.3660 || 0.0094 || 7.67 || HEPES || 25 || 15 || 3.05E-01 || 1.91E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.025 || 51.00 || 0.3750 || 0.3570 || 0.0180 || 7.50 || MOPS || 25 || 15 || -9.96E-02 || -2.14E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.025 || 51.00 || 0.3750 || 0.3640 || 0.0110 || 7.28 || MOPS || 25 || 15 || -8.18E-01 || -9.32E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.025 || 51.00 || 0.3750 || 0.3670 || 0.0084 || 7.00 || MOPS || 25 || 15 || -1.61E+00 || -1.73E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.025 || 51.00 || 0.3750 || 0.3750 || 0.0004 || 6.80 || MOPSO || 25 || 15 || -1.82E+00 || -1.93E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.025 || 51.00 || 0.3750 || 0.3730 || 0.0018 || 6.60 || MES || 25 || 15 || -2.26E+00 || -2.37E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.025 || 51.00 || 0.3750 || 0.3670 || 0.0076 || 6.10 || MES || 25 || 15 || -3.56E+00 || -3.67E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.020 || 51.00 || 0.3750 || 0.3680 || 0.0069 || 6.60 || MES || 25 || 15 || -2.26E+00 || -2.27E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.110 || 51.00 || 0.3750 || 0.3660 || 0.0090 || 6.60 || MES || 25 || 15 || -3.19E-01 || -1.07E+00
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.220 || 51.00 || 0.3750 || 0.3540 || 0.0210 || 6.60 || MES || 25 || 15 || 5.00E-01 || -5.50E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.551 || 51.00 || 0.3750 || 0.3220 || 0.0530 || 6.60 || MES || 25 || 15 || 1.03E+00 || -4.15E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 1.100 || 51.00 || 0.3750 || 0.2740 || 0.1010 || 6.60 || MES || 25 || 15 || 1.46E+00 || -2.88E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 1.651 || 51.00 || 0.3750 || 0.2330 || 0.1420 || 6.60 || MES || 25 || 15 || 1.66E+00 || -2.70E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 2.196 || 51.00 || 0.3750 || 0.1910 || 0.1840 || 6.60 || MES || 25 || 15 || 1.83E+00 || -2.19E-01
 
−
|-
 
−
| 4-CNNB<ref name="Colón2006"/> || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || 1.99E-01 || -6.61E-01
 
−
|-
 
−
| 4-AcNB<ref name="Colón2006"/> || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -6.85E-02 || -9.28E-01
 
−
|-
 
−
| 4-ClNB<ref name="Colón2006"/> || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -5.47E-01 || -1.41E+00
 
−
|-
 
−
| 4-BrNB<ref name="Colón2006"/> || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -5.73E-01 || -1.43E+00
 
−
|-
 
−
| NB<ref name="Colón2006"/> || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -7.93E-01 || -1.65E+00
 
−
|-
 
−
| 4-MeNB<ref name="Colón2006"/> || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -9.79E-01 || -1.84E+00
 
−
|-
 
−
| 4-ClNB<ref name="Jones2016"/>  || Goethite || 0.040 || 186.75 || 1.0000 || 0.8050 || 0.1950 || 7.00 ||  ||  ||  || 1.05E+00 || -3.20E-01
 
−
|-
 
−
| 4-ClNB<ref name="Jones2016"/>  || Goethite || 7.516 || 16.10 || 1.0000 || 0.9260 || 0.0740 || 7.00 ||  ||  ||  || 1.14E+00 || 0.00E+00
 
−
|-
 
−
| 4-ClNB<ref name="Jones2016"/>  || Ferrihydrite || 0.111 || 252.60 || 1.0000 || 0.6650 || 0.3350 || 7.00 ||  ||  ||  || 1.05E+00 || -1.56E+00
 
−
|-
 
−
| 4-ClNB<ref name="Jones2016"/>  || Lepidocrocite || 2.384 || 60.40 || 1.0000 || 0.9250 || 0.0750 || 7.00 ||  ||  ||  || 1.14E+00 || -8.60E-01
 
−
|-
 
−
| 4-ClNB<ref name="Fan2016"/> || Goethite || 10.000 || 14.90 || 1.0000 ||  ||  || 7.20 || HEPES || 10 || 10 - 50 || 2.26E+00 || 8.00E-02
 
−
|-
 
−
| 4-ClNB<ref name="Fan2016"/> || Goethite || 3.000 || 14.90 || 1.0000 ||  ||  || 7.20 || HEPES || 10 || 10 - 50 || 2.38E+00 || 7.30E-01
 
−
|-
 
−
| 4-ClNB<ref name="Fan2016"/> || Lepidocrocite || 2.700 || 16.20 || 1.0000 ||  ||  || 7.20 || HEPES || 10 || 10 - 50 || 9.20E-01 || -7.20E-01
 
−
|-
 
−
| 4-ClNB<ref name="Fan2016"/> || Lepidocrocite || 10.000 || 16.20 || 1.0000 ||  ||  || 7.20 || HEPES || 10 || 10 - 50 || 1.03E+00 || -1.18E+00
 
−
|-
 
−
| 4-ClNB<ref name="Strehlau2016"/> || Goethite || 0.325 || 140.00 || 1.0000 ||  ||  || 7.00 || Bicarbonate || 10 || 100 || 1.14E+00 || -1.79E+00
 
−
|-
 
−
| 4-ClNB<ref name="Strehlau2016"/> || Goethite || 0.325 || 140.00 || 1.0000 ||  ||  || 6.50 || Bicarbonate || 10 || 100 || 1.11E+00 || -2.10E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 0.500 || 30.70 || 0.1000 || 0.1120 || 0.0090 || 6.00 || MES || 25 || 12 || -1.42E+00 || -2.61E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 0.500 || 30.70 || 0.5000 || 0.5150 || 0.0240 || 6.00 || MES || 25 || 15 || -7.45E-01 || -1.93E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 0.500 || 30.70 || 1.0000 || 1.0280 || 0.0140 || 6.00 || MES || 25 || 19 || -7.45E-01 || -1.93E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 1.000 || 30.70 || 0.1000 || 0.0960 || 0.0260 || 6.00 || MES || 25 || 13 || -1.12E+00 || -2.61E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 1.000 || 30.70 || 0.5000 || 0.4890 || 0.0230 || 6.00 || MES || 25 || 14 || -5.53E-01 || -2.04E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 1.000 || 30.70 || 1.0000 || 0.9870 || 0.0380 || 6.00 || MES || 25 || 19 || -2.52E-01 || -1.74E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 2.000 || 30.70 || 0.1000 || 0.0800 || 0.0490 || 6.00 || MES || 25 || 11 || -8.86E-01 || -2.67E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 2.000 || 30.70 || 0.6000 || 0.4890 || 0.0640 || 6.00 || MES || 25 || 14 || -1.08E-01 || -1.90E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 2.000 || 30.70 || 1.1000 || 0.9870 || 0.0670 || 6.00 || MES || 25 || 14 || 2.30E-01 || -1.56E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 4.000 || 30.70 || 0.1000 || 0.0600 || 0.0650 || 6.00 || MES || 25 || 11 || -8.89E-01 || -2.98E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 4.000 || 30.70 || 0.6000 || 0.3960 || 0.1550 || 6.00 || MES || 25 || 17 || 1.43E-01 || -1.95E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 4.000 || 30.70 || 1.0000 || 0.8360 || 0.1450 || 6.00 || MES || 25 || 16 || 4.80E-01 || -1.61E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 4.000 || 30.70 || 5.6000 || 5.2110 || 0.3790 || 6.00 || MES || 25 || 15 || 1.17E+00 || -9.19E-01
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 1.000 || 30.70 || 0.1000 || 0.0870 || 0.0300 || 6.50 || MES || 25 || 5.5 || -1.74E-01 || -1.66E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 1.000 || 30.70 || 0.5000 || 0.4920 || 0.0300 || 6.50 || MES || 25 || 15 || 3.64E-01 || -1.12E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 1.000 || 30.70 || 1.0000 || 0.9390 || 0.0650 || 6.50 || MES || 25 || 18 || 6.70E-01 || -8.17E-01
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 2.000 || 30.70 || 0.1000 || 0.0490 || 0.0730 || 6.50 || MES || 25 || 5.2 || 3.01E-01 || -1.49E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 2.000 || 30.70 || 0.5000 || 0.4640 || 0.0710 || 6.50 || MES || 25 || 14 || 8.85E-01 || -9.03E-01
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 2.000 || 30.70 || 1.0000 || 0.9130 || 0.1280 || 6.50 || MES || 25 || 16 || 1.12E+00 || -6.64E-01
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 1.000 || 30.70 || 0.1000 || 0.0630 || 0.0480 || 7.00 || MOPS || 25 || 5.3 || 6.12E-01 || -8.75E-01
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 1.000 || 30.70 || 0.5000 || 0.4690 || 0.0520 || 7.00 || MOPS || 25 || 9 || 1.51E+00 || 2.07E-02
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 1.000 || 30.70 || 1.0000 || 0.9360 || 0.1090 || 7.00 || MOPS || 25 || 18 || 1.33E+00 || -1.53E-01
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 2.000 || 30.70 || 0.1000 || 0.0290 || 0.0880 || 7.00 || MOPS || 25 || 12 || 6.85E-01 || -1.10E+00
 
−
|-
 
−
| NB<ref name="Stewart2018"/> || Goethite || 2.000 || 30.70 || 0.5000 || 0.3950 || 0.1450 || 7.00 || MOPS || 25 || 15 || 1.59E+00 || -1.95E-01
 
−
|-
 
−
| colspan="13" style="text-align:left; background-color:white;" | Notes:</br>''<sup>a</sup>'' The NACs are Nitrobenzene (NB), 4-chloronitrobenzene(4-ClNB), 4-cyanonitrobenzene (4-CNNB), 4-acetylnitrobenzene (4-AcNB), 4-bromonitrobenzene (4-BrNB), 4-nitrotoluene (4-MeNB). ''<sup>b</sup>'' Initial aqueous Fe(II). ''<sup>c</sup>'' Aqueous Fe(II) after 24h of equilibration. ''<sup>d</sup>'' Difference between b and c. ''<sup>e</sup>'' Initial nominal NAC concentration. ''<sup>f</sup>'' Pseudo-first order rate constant. ''<sup>g</sup>'' Surface area normalized rate constant calculated as ''k<sub>Obs</sub>'' '''/''' (surface area × mineral loading).
 
 
|}
 
|}
  
−
Iron(II)&nbsp;can&nbsp;be&nbsp;complexed by a myriad of organic ligands and may thereby become more reactive towards MCs and other pollutants. The reactivity of an Fe(II)-organic complex depends on the relative preference of the organic ligand for Fe(III) versus Fe(II)<ref name="Kim2009"/>. Since the majority of naturally occurring ligands complex Fe(III) more strongly than Fe(II), the reduction potential of the resulting Fe(III) complex is lower than that of aqueous Fe(III); therefore, complexation by organic ligands often renders Fe(II) a stronger reductant thermodynamically<ref name="Strathmann2011">Strathmann, T.J., 2011. Redox Reactivity of Organically Complexed Iron(II) Species with Aquatic Contaminants. Aquatic Redox Chemistry, American Chemical Society,1071(14), pp. 283-313. [https://doi.org/10.1021/bk-2011-1071.ch014 DOI: 10.1021/bk-2011-1071.ch014]</ref>. The reactivity of dissolved Fe(II)-organic complexes towards NACs/MCs has been investigated. The intrinsic, second-order rate constants and one electron reduction potentials are listed in Table 2.
+
A&nbsp;range&nbsp;of&nbsp;biopolymers&nbsp;widely used in the production of biodegradable plastics were screened for their ability to support aerobic and anoxic biodegradation of the target munition constituents. These compounds and their sources are listed in Table 2.
 +
 
 +
Multiple pure bacterial strains and mixed cultures were screened for their ability to utilize the solid biopolymers as a carbon source to support energetic compound transformation and degradation. Pure strains included the aerobic RDX degrader [[Wikipedia: Rhodococcus | ''Rhodococcus'']] species DN22 (DN22 henceforth)<ref name="ColemanEtAl1998">Coleman, N.V., Nelson, D.R., Duxbury, T., 1998. Aerobic biodegradation of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) as a nitrogen source by a Rhodococcus sp., strain DN22. Soil Biology and Biochemistry, 30(8-9), pp. 1159-1167. [https://doi.org/10.1016/S0038-0717(97)00172-7 doi: 10.1016/S0038-0717(97)00172-7]</ref> and [[Wikipedia: Gordonia (bacterium)|''Gordonia'']] species KTR9 (KTR9 henceforth)<ref name="ColemanEtAl1998"/>, the anoxic RDX degrader [[Wikipedia: Pseudomonas fluorencens | ''Pseudomonas fluorencens'']] species I-C (I-C henceforth)<ref>Pak, J.W., Knoke, K.L., Noguera, D.R., Fox, B.G., Chambliss, G.H., 2000. Transformation of 2,4,6-Trinitrotoluene by Purified Xenobiotic Reductase B from Pseudomonas fluorescens I-C. Applied and Environmental Microbiology, 66(11), pp. 4742-4750. [https://doi.org/10.1128/AEM.66.11.4742-4750.2000 doi: 10.1128/AEM.66.11.4742-4750.2000]&nbsp;&nbsp; [[Media: PakEtAl2000.pdf | Open AccessArticle.pdf]]</ref><ref>Fuller, M.E., McClay, K., Hawari, J., Paquet, L., Malone, T.E., Fox, B.G., Steffan, R.J., 2009. Transformation of RDX and other energetic compounds by xenobiotic reductases XenA and XenB. Applied Microbiology and Biotechnology, 84, pp. 535-544. [https://doi.org/10.1007/s00253-009-2024-6 doi: 10.1007/s00253-009-2024-6]&nbsp;&nbsp; [[Media: FullerEtAl2009.pdf | Open Access Manuscript]]</ref>, and the aerobic NQ degrader [[Wikipedia: Pseudomonas | ''Pseudomonas extremaustralis'']] species NQ5 (NQ5 henceforth)<ref>Kim, J., Fuller, M.E., Hatzinger, P.B., Chu, K.-H., 2024. Isolation and characterization of nitroguanidine-degrading microorganisms. Science of the Total Environment, 912, Article 169184. [https://doi.org/10.1016/j.scitotenv.2023.169184 doi: 10.1016/j.scitotenv.2023.169184]</ref>. Anaerobic mixed cultures were obtained from a membrane bioreactor (MBR) degrading a mixture of six explosives (HMX, RDX, TNT, NTO, NQ, DNAN), as well as perchlorate and nitrate<ref name="FullerEtAl2023">Fuller, M.E., Hedman, P.C., Chu, K.-H., Webster, T.S., Hatzinger, P.B., 2023. Evaluation of a sequential anaerobic-aerobic membrane bioreactor system for treatment of traditional and insensitive munitions constituents. Chemosphere, 340, Article 139887. [https://doi.org/10.1016/j.chemosphere.2023.139887 doi: 10.1016/j.chemosphere.2023.139887]</ref>. The results indicated that the slow release carbon sources [[Wikipedia: Polyhydroxybutyrate | polyhydroxybutyrate (PHB)]], [[Wikipedia: Polycaprolactone | polycaprolactone (PCL)]], and [[Wikipedia: Polybutylene succinate | polybutylene succinate (BioPBS)]] were effective for supporting the biodegradation of the mixture of energetics.
  
−
In addition to forming organic complexes, iron is ubiquitous in minerals. Iron-bearing minerals play an important role in controlling the environmental fate of contaminants through adsorption<ref name="Linker2015">Linker, B.R., Khatiwada, R., Perdrial, N., Abrell, L., Sierra-Alvarez, R., Field, J.A., and Chorover, J., 2015. Adsorption of novel insensitive munitions compounds at clay mineral and metal oxide surfaces. Environmental Chemistry, 12(1), pp. 74–84.  [https://doi.org/10.1071/EN14065 DOI: 10.1071/EN14065]</ref><ref name="Jenness2020">Jenness, G.R., Giles, S.A., and Shukla, M.K., 2020. Thermodynamic Adsorption States of TNT and DNAN on Corundum and Hematite. The Journal of Physical Chemistry C, 124(25), pp. 13837–13844.  [https://doi.org/10.1021/acs.jpcc.0c04512 DOI: 10.1021/acs.jpcc.0c04512]</ref> and reduction<ref name="Gorski2011">Gorski, C.A., and Scherer, M.M., 2011. Fe<sup>2+</sup> Sorption at the Fe Oxide-Water Interface: A Revised Conceptual Framework. Aquatic Redox Chemistry, American Chemical Society, 1071(15), pp. 315–343.  [https://doi.org/10.1021/bk-2011-1071.ch015 DOI: 10.1021/bk-2011-1071.ch015]</ref> processes. Studies have shown that aqueous Fe(II) itself cannot reduce NACs/MCs at circumneutral pH<ref name="Klausen1995"/><ref name="Gregory2004">Gregory, K.B., Larese-Casanova, P., Parkin, G.F., and Scherer, M.M., 2004. Abiotic Transformation of Hexahydro-1,3,5-trinitro-1,3,5-triazine by Fe<sup>II</sup> Bound to Magnetite. Environmental Science and Technology, 38(5), pp. 1408–1414.  [https://doi.org/10.1021/es034588w DOI: 10.1021/es034588w]</ref> but in the presence of an iron oxide (e.g., goethite, hematite, lepidocrocite, ferrihydrite, or magnetite), NACs<ref name="Colón2006"/><ref name="Klausen1995"/><ref name="Strehlau2016"/><ref name="Elsner2004"/><ref name="Hofstetter2006"/> and MCs such as TNT<ref name="Hofstetter1999"/>, RDX<ref name="Gregory2004"/>, DNAN<ref name="Berens2019">Berens, M.J., Ulrich, B.A., Strehlau, J.H., Hofstetter, T.B., and Arnold, W.A., 2019. Mineral identity, natural organic matter, and repeated contaminant exposures do not affect the carbon and nitrogen isotope fractionation of 2,4-dinitroanisole during abiotic reduction. Environmental Science: Processes and Impacts, 21(1), pp. 51-62.  [https://doi.org/10.1039/C8EM00381E DOI: 10.1039/C8EM00381E]</ref>, and NG<ref name="Oh2004">Oh, S.-Y., Cha, D.K., Kim, B.J., and Chiu, P.C., 2004. Reduction of Nitroglycerin with Elemental Iron:  Pathway, Kinetics, and Mechanisms. Environmental Science and Technology, 38(13), pp. 3723–3730.  [https://doi.org/10.1021/es0354667 DOI: 10.1021/es0354667]</ref> can be rapidly reduced. Unlike ferric oxides, Fe(II)-bearing minerals including clays<ref name="Hofstetter2006"/><ref name="Schultz2000"/><ref name="Luan2015a"/><ref name="Luan2015b"/><ref name="Hofstetter2003"/><ref name="Neumann2008"/><ref name="Hofstetter2008"/>, green rust<ref name="Larese-Casanova2008"/><ref name="Khatiwada2018">Khatiwada, R., Root, R.A., Abrell, L., Sierra-Alvarez, R., Field, J.A., and Chorover, J., 2018. Abiotic reduction of insensitive munition compounds by sulfate green rust. Environmental Chemistry, 15(5), pp. 259–266.  [https://doi.org/10.1071/EN17221 DOI: 10.1071/EN17221]</ref>, mackinawite<ref name="Elsner2004"/><ref name="Berens2019"/><ref name="Menezes2021">Menezes, O., Yu, Y., Root, R.A., Gavazza, S., Chorover, J., Sierra-Alvarez, R., and Field, J.A., 2021. Iron(II) monosulfide (FeS) minerals reductively transform the insensitive munitions compounds 2,4-dinitroanisole (DNAN) and 3-nitro-1,2,4-triazol-5-one (NTO). Chemosphere, 285, p. 131409.  [https://doi.org/10.1016/j.chemosphere.2021.131409 DOI: 10.1016/j.chemosphere.2021.131409]</ref> and pyrite<ref name="Elsner2004"/><ref name="Oh2008">Oh, S.-Y., Chiu, P.C., and Cha, D.K., 2008. Reductive transformation of 2,4,6-trinitrotoluene,  hexahydro-1,3,5-trinitro-1,3,5-triazine, and nitroglycerin by pyrite and magnetite. Journal of hazardous materials, 158(2-3), pp. 652–655. [https://doi.org/10.1016/j.jhazmat.2008.01.078 DOI: 10.1016/j.jhazmat.2008.01.078]</ref> do not need aqueous Fe(II) to be reactive toward NACs/MCs. However, upon oxidation, sulfate green rust was converted into lepidocrocite<ref name="Khatiwada2018"/>, and mackinawite into goethite<ref name="Menezes2021"/>, suggesting that aqueous Fe(II) coupled to Fe(III) oxides might be at least partially responsible for continued degradation of NACs/MCs in the subsurface once the parent reductant (e.g., green rust or iron sulfide) oxidizes.
+
===Biochar===
 +
[[File: FullerFig3.png | thumb | 400 px | Figure 3. Schematic of interactions between biochar and munitions constituents]]
 +
The ability of biochar to sorb and abiotically reduce legacy and insensitive munition constituents, as well as biochar’s use as an electron donor for microbial biodegradation of energetic compounds was examined.  Batch experiments indicated that biochar was a reasonable sorbent for some of the energetics (RDX, DNAN), but could also serve as both an electron acceptor and an electron donor to facilitate abiotic (RDX, DNAN, NTO) and biotic (perchlorate) degradation (Figure 3)<ref>Xin, D., Giron, J., Fuller, M.E., Chiu, P.C., 2022. Abiotic reduction of 3-nitro-1,2,4-triazol-5-one (NTO), DNAN, and RDX by wood-derived biochars through their rechargeable electron storage capacity. Environmental Science: Processes and Impacts, 24(2), pp. 316-329. [https://doi.org/10.1039/D1EM00447F doi: 10.1039/D1EM00447F]&nbsp;&nbsp; [[Media: XinEtAl2022.pdf | Open Access Manuscript.pdf]]</ref>.
  
−
The reaction conditions and rate constants for a list of studies on MC reduction by iron oxide-aqueous Fe(II)  redox couples and by other Fe(II)-containing minerals are shown in Table 3<ref name="Hofstetter1999"/><ref name="Larese-Casanova2008"/><ref name="Gregory2004"/><ref name="Berens2019"/><ref name="Oh2008"/><ref name="Strehlau2018">Strehlau, J.H., Berens, M.J., and Arnold, W.A., 2018. Mineralogy and buffer identity effects on RDX kinetics and intermediates during reaction with natural and synthetic magnetite. Chemosphere, 213, pp. 602–609.  [https://doi.org/10.1016/j.chemosphere.2018.09.139 DOI: 10.1016/j.chemosphere.2018.09.139]</ref><ref name="Cardenas-Hernandez2020">Cárdenas-Hernandez, P.A., Anderson, K.A., Murillo-Gelvez, J., di Toro, D.M., Allen, H.E., Carbonaro, R.F., and Chiu, P.C., 2020. Reduction of 3-Nitro-1,2,4-Triazol-5-One (NTO) by the Hematite–Aqueous Fe(II) Redox Couple. Environmental Science and Technology, 54(19), pp. 12191–12201.  [https://doi.org/10.1021/acs.est.0c03872 DOI: 10.1021/acs.est.0c03872]</ref>. Unlike hydroquinones and Fe(II) complexes, where second-order rate constants can be readily calculated, the reduction rate constants of NACs/MCs in mineral suspensions are often specific to the experimental conditions used and are usually reported as BET surface area-normalized reduction rate constants (''k<sub>SA</sub>''). In the case of iron oxide-Fe(II) redox couples, reduction rate constants have been shown to increase with pH (specifically, with [OH<sup>– </sup>]<sup>2</sup>) and aqueous Fe(II) concentration, both of which correspond to a decrease in the system's reduction potential<ref name="Colón2006"/><ref name="Gorski2016"/><ref name="Cardenas-Hernandez2020"/>.
+
===Sorption-Biodegradation Column Experiments===
 +
The selected materials and cultures discussed above, along with a small amount of range soil and crushed oyster shell as a slow-release pH buffering agent, were packed into columns, and a steady flow of dissolved energetics was passed through the columns. The composition of the four columns is presented in Figure 4. The influent and effluent concentrations of the energetics was monitored over time. The column experiment was performed twice. As seen in Figure 5, there was sustained almost complete removal of RDX and ClO<sub>4</sub><sup>-</sup>, and more removal of the other energetics in the bioactive columns compared to the sorption only columns, over the course of the experiments. For reference, 100 PV is approximately equivalent to three months of operation.  The higher effectiveness of sorption with biodegradation compared to sorption only is further illustrated in Figure 6, where the energetics mass removal in the bioactive columns was shown to be 2-fold (TNT) to 20-fold (RDX) higher relative to that observed in the sorption only column.  The mass removal of HMX and NQ were both over 40% higher with biochar added to the sorption with biodegradation treatment, although biochar showed little added benefit for removal of other energetics tested.  
  
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For minerals that contain structural iron(II) and can reduce pollutants in the absence of aqueous Fe(II), the observed rates of reduction increased with increasing structural Fe(II) content, as seen with iron-bearing clays<ref name="Luan2015a"/><ref name="Luan2015b"/> and green rust<ref name="Larese-Casanova2008"/>. This dependency on Fe(II) content allows for the derivation of second-order rate constants, as shown on Table 3 for the reduction of RDX by green rust<ref name="Larese-Casanova2008"/>, and the development of reduction potential (E<sub>H</sub>)-based models<ref name="Luan2015a"/><ref name="Gorski2012a">Gorski, C.A., Aeschbacher, M., Soltermann, D., Voegelin, A., Baeyens, B., Marques Fernandes, M., Hofstetter, T.B., and Sander, M., 2012. Redox Properties of Structural Fe in Clay Minerals. 1. Electrochemical Quantification of Electron-Donating and -Accepting Capacities of Smectites. Environmental Science and Technology, 46(17), pp. 9360–9368.  [https://doi.org/10.1021/es3020138 DOI: 10.1021/es3020138]</ref><ref name="Gorski2012b">Gorski, C.A., Klüpfel, L., Voegelin, A., Sander, M., and Hofstetter, T.B., 2012. Redox Properties of Structural Fe in Clay Minerals. 2. Electrochemical and Spectroscopic Characterization of Electron Transfer Irreversibility in Ferruginous Smectite, SWa-1. Environmental Science and Technology, 46(17), pp. 9369–9377.  [https://doi.org/10.1021/es302014u DOI: 10.1021/es302014u]</ref><ref name="Gorski2013">Gorski, C.A., Klüpfel, L.E., Voegelin, A., Sander, M. and Hofstetter, T.B., 2013. Redox Properties of Structural Fe in Clay Minerals: 3. Relationships between Smectite Redox and Structural Properties. Environmental Science and Technology, 47(23), pp. 13477–13485.  [https://doi.org/10.1021/es403824x DOI: 10.1021/es403824x]</ref>, where E<sub>H</sub> represents the reduction potential of the iron-bearing clays. Iron-bearing expandable clay minerals represent a special case, which in addition to reduction can remove NACs/MCs through adsorption. This is particularly important for planar NACs/MCs that contain multiple electron-withdrawing nitro groups and can form strong electron donor-acceptor (EDA) complexes with the clay surface<ref name="Hofstetter2006"/><ref name="Hofstetter2003"/><ref name="Neumann2008"/>.
+
===Trap and Treat Technology===
 +
These results provide a proof-of-concept for the further development of a passive and sustainable “trap-and-treat” technology for remediation of energetic compounds in stormwater runoff at military testing and training ranges.  At a given site, the stormwater runoff would need to be fully characterized with respect to key parameters (e.g., pH, major anions), and site specific treatability testing would be recommended to assure there was nothing present in the runoff that would reduce performance. Effluent monitoring on a regular basis would also be needed (and would be likely be expected by state and local regulators) to assess performance decline over time.
  
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Although the second-order rate constants derived for Fe(II)-bearing minerals may allow comparison among different studies, they may not reflect changes in reactivity due to variations in surface area, pH, and the presence of ions. Anions such as bicarbonate<ref name="Larese-Casanova2008"/><ref name="Strehlau2018"/><ref name="Chen2020">Chen, G., Hofstetter, T.B., and Gorski, C.A., 2020. Role of Carbonate in Thermodynamic Relationships Describing Pollutant Reduction Kinetics by Iron Oxide-Bound Fe<sup>2+</sup>. Environmental Science and Technology, 54(16), pp. 10109–10117.  [https://doi.org/10.1021/acs.est.0c02959 DOI: 10.1021/acs.est.0c02959]</ref> and phosphate<ref name="Larese-Casanova2008"/><ref name="Bocher2004">Bocher, F., Géhin, A., Ruby, C., Ghanbaja, J., Abdelmoula, M., and Génin, J.M.R., 2004. Coprecipitation of Fe(II–III) hydroxycarbonate green rust stabilised by phosphate adsorption. Solid State Sciences, 6(1), pp. 117–124.  [https://doi.org/10.1016/j.solidstatesciences.2003.10.004 DOI: 10.1016/j.solidstatesciences.2003.10.004]</ref> are known to decrease the reactivity of iron oxides-Fe(II) redox couples and green rust. Sulfite has also been shown to decrease the reactivity of hematite-Fe(II) towards the deprotonated form of NTO (Table 3)<ref name="Cardenas-Hernandez2020"/>. Exchanging cations in iron-bearing clays can change the reactivity of these minerals by up to 7-fold<ref name="Hofstetter2006"/>. Thus, more comprehensive models are needed to account for the complexities in the subsurface environment.
+
The components of the technology would be predominantly peat moss and cationized pine shavings, supplemented with biochar, ground oyster shell, the biopolymer carbon sources, and the bioaugmentation cultures.  The entire mix would likely be emplaced in a concrete vault at the outflow end of the stormwater runoff retention basin at the contaminated site. The deployed treatment system would have further design elements, such as a system to trap and retain suspended solids in the runoff in order to minimize clogging the matrix. the inside of the vault would be baffled to maximize the hydraulic retention time of the contaminated runoff. The biopolymer carbon sources and oyster shell may need be refreshed periodically (perhaps yearly) to maintain performance.  However, a complete removal and replacement of the base media (peat moss, CAT pine) would not be advised, as that would lead to a loss of the acclimated biomass.
  
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The reduction of NACs has been widely studied in the presence of different iron minerals, pH, and Fe(II)<sub>(aq)</sub> concentrations (Table 4)<ref name="Colón2006"/><ref name="Klausen1995"/><ref name="Strehlau2016"/><ref name="Elsner2004"/><ref name="Hofstetter2006"/>. Only selected NACs are included in Table 4. For more information on other NACs and ferruginous reductants, please refer to the cited references.
+
==Summary==
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<br clear="right" />
+
Novel sorbents and slow release carbon sources can be an effective way to promote the sorption and biodegradation of a range of legacy and insensitive munition constituents from surface runoff, and the added benefits of biochar for both sorption and biotic and abiotic degradation of these compounds was demonstrated.  These results establish a foundation for a passive, sustainable surface runoff treatment technology for both active and inactive military ranges.
  
 
==References==
 
==References==
Line 579: Line 219:
  
 
==See Also==
 
==See Also==
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*[https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/Contaminated-Groundwater/Persistent-Contamination/ER-2617 Measuring and Predicting the Natural and Enhanced Rate and Capacity of Abiotic Reduction of Munition Constituents]
+
[https://www.atsdr.cdc.gov/pfas/health-studies/index.html Agency for Toxic Substances and Disease Registry (ATSDR) PFAS Health Studies]
−
 
 
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*[https://www.epa.gov/fedfac/military-munitionsunexploded-ordnance Military Munitions/Unexploded Ordnance - EPA]
 

Latest revision as of 11:41, 30 October 2025

Remediation of Stormwater Runoff Contaminated by Munition Constituents

Past and ongoing military operations have resulted in contamination of surface soil with munition constituents (MC), which have human and environmental health impacts. These compounds can be transported off site via stormwater runoff during precipitation events. Technologies to “trap and treat” surface runoff before it enters downstream receiving bodies (e.g., streams, rivers, ponds) (see Figure 1), and which are compatible with ongoing range activities are needed. This article describes a passive and sustainable approach for effective management of munition constituents in stormwater runoff.

Related Article(s):


Contributor: Mark E. Fuller

Key Resource(s):

  • SERDP Project ER19-1106: Development of Innovative Passive and Sustainable Treatment Technologies for Energetic Compounds in Surface Runoff on Active Ranges

Background

Surface Runoff Characteristics and Treatment Approaches

Figure 1. Conceptual model of passive trap and treat approach for MC removal from stormwater runoff

During large precipitation events the rate of water deposition exceeds the rate of water infiltration, resulting in surface runoff (also called stormwater runoff). Surface characteristics including soil texture, presence of impermeable surfaces (natural and artificial), slope, and density and type of vegetation all influence the amount of surface runoff from a given land area. The use of passive systems such as retention ponds and biofiltration cells for treatment of surface runoff is well established for urban and roadway runoff. Treatment in those cases is typically achieved by directing runoff into and through a small constructed wetland, often at the outlet of a retention basin, or via filtration by directing runoff through a more highly engineered channel or vault containing the treatment materials. Filtration based technologies have proven to be effective for the removal of metals, organics, and suspended solids[1][2][3][4].

Surface Runoff on Ranges

Figure 2. Conceptual illustration of munition constituent production and transport on military ranges. Mesoscale residues are qualitatively defined as being easily visible to the naked eye (e.g., from around 50 µm to multiple cm in size) and less likely to be transported by moving water. Microscale residues are defined as <50 µm down to below 1 µm, and more likely to be entrained in, and transported by, moving water as particulates. Blue arrows represent possible water flow paths and include both dissolved and solid phase energetics. The red vertical arrow represents the predominant energetics dissolution process in close proximity to the residues due to precipitation.

Surface runoff represents a major potential mechanism through which energetics residues and related materials are transported off site from range soils to groundwater and surface water receptors (Figure 2). This process is particularly important for energetics that are water soluble (e.g., NTO and NQ) or generate soluble daughter products (e.g., DNAN and TNT). While traditional MC such as RDX and HMX have limited aqueous solubility, they also exhibit recalcitrance to degrade under most natural conditions. RDX and perchlorate are frequent groundwater contaminants on military training ranges. While actual field measurements of energetics in surface runoff are limited, laboratory experiments have been performed to predict mobile energetics contamination levels based on soil mass loadings[5][6][7][8][9]. For example, in a previous small study, MC were detected in surface runoff from an active live-fire range[10], and more recent sampling has detected MC in marsh surface water adjacent to the same installation (personal communication). Another recent report from Canada also detected RDX in both surface runoff and surface water at low part per billion levels in a survey of several military demolition sites[11]. However, overall, data regarding the MC contaminant profile of surface runoff from ranges is very limited, and the possible presence of non-energetic constituents (e.g., metals, binders, plasticizers) in runoff has not been examined. Additionally, while energetics-contaminated surface runoff is an important concern, mitigation technologies specifically for surface runoff have not yet been developed and widely deployed in the field. To effectively capture and degrade MC and associated compounds that are present in surface runoff, novel treatment media are needed to sorb a broad range of energetic materials and to transform the retained compounds through abiotic and/or microbial processes.

Surface runoff of organic and inorganic contaminants from live-fire ranges is a challenging issue for the Department of Defense (DoD). Potentially even more problematic is the fact that inputs to surface waters from large testing and training ranges typically originate from multiple sources, often encompassing hundreds of acres. No available technologies are currently considered effective for controlling non-point source energetics-laden surface runoff. While numerous technologies exist to treat collected explosives residues, contaminated soil and even groundwater, the decentralized nature and sheer volume of military range runoff have precluded the use of treatment technologies at full scale in the field.

Range Runoff Treatment Technology Components

Based on the conceptual foundation of previous research into surface water runoff treatment for other contaminants, with a goal to “trap and treat” the target compounds, the following components were selected for inclusion in the technology developed to address range runoff contaminated with energetic compounds.

Peat

Previous research demonstrated that a peat-based system provided a natural and sustainable sorptive medium for organic explosives such as HMX, RDX, and TNT, allowing much longer residence times than predicted from hydraulic loading alone[12][13][14][15][16]. Peat moss represents a bioactive environment for treatment of the target contaminants. While the majority of the microbial reactions are aerobic due to the presence of measurable dissolved oxygen in the bulk solution, anaerobic reactions (including methanogenesis) can occur in microsites within the peat. The peat-based substrate acts not only as a long term electron donor as it degrades but also acts as a strong sorbent. This is important in intermittently loaded systems in which a large initial pulse of MC can be temporarily retarded on the peat matrix and then slowly degraded as they desorb[14][16]. This increased residence time enhances the biotransformation of energetics and promotes the immobilization and further degradation of breakdown products. Abiotic degradation reactions are also likely enhanced by association with the organic-rich peat (e.g., via electron shuttling reactions of humics)[17].

Soybean Oil

Modeling has indicated that peat moss amended with crude soybean oil would significantly reduce the flux of dissolved TNT, RDX, and HMX through the vadose zone to groundwater compared to a non-treated soil (see ESTCP ER-200434). The technology was validated in field soil plots, showing a greater than 500-fold reduction in the flux of dissolved RDX from macroscale Composition B detonation residues compared to a non-treated control plot[14]. Laboratory testing and modeling indicated that the addition of soybean oil increased the biotransformation rates of RDX and HMX at least 10-fold compared to rates observed with peat moss alone[16]. Subsequent experiments also demonstrated the effectiveness of the amended peat moss material for stimulating perchlorate transformation when added to a highly contaminated soil (Fuller et al., unpublished data). These previous findings clearly demonstrate the effectiveness of peat-based materials for mitigating transport of both organic and inorganic energetic compounds through soil to groundwater.

Biochar

Recent reports have highlighted additional materials that, either alone, or in combination with electron donors such as peat moss and soybean oil, may further enhance the sorption and degradation of surface runoff contaminants, including both legacy energetics and insensitive high explosives (IHE). For instance, biochar, a type of black carbon, has been shown to not only sorb a wide range of organic and inorganic contaminants including MCs[18][19][20][21], but also to facilitate their degradation[22][23][24][25][26][27]. Depending on the source biomass and pyrolysis conditions, biochar can possess a high specific surface area (on the order of several hundred m2/g)[28][29] and hence a high sorption capacity. Biochar and other black carbon also exhibit especially high affinity for nitroaromatic compounds (NACs) including TNT and 2,4-dinitrotoluene (DNT)[30][31][32]. This is due to the strong π-π electron donor-acceptor interactions between electron-rich graphitic domains in black carbon and the electron-deficient aromatic ring of the NAC[31][32]. These characteristics make biochar a potentially effective, low cost, and sustainable sorbent for removing MC and other contaminants from surface runoff and retaining them for subsequent degradation in situ.

Furthermore, black carbon such as biochar can promote abiotic and microbial transformation reactions by facilitating electron transfer. That is, biochar is not merely a passive sorbent for contaminants, but also a redox mediator for their degradation. Biochar can promote contaminant degradation through two different mechanisms: electron conduction and electron storage[33].

First, the microscopic graphitic regions in biochar can adsorb contaminants like NACs strongly, as noted above, and also conduct reducing equivalents such as electrons and atomic hydrogen to the sorbed contaminants, thus promoting their reductive degradation. This catalytic process has been demonstrated for TNT, DNT, RDX, HMX, and nitroglycerin[34][35][36][24][26] and is expected to occur also for IHE including DNAN and NTO.

Second, biochar contains in its structure abundant redox-facile functional groups such as quinones and hydroquinones, which are known to accept and donate electrons reversibly. Depending on the biomass and pyrolysis temperature, certain biochar can possess a rechargeable electron storage capacity (i.e., reversible electron accepting and donating capacity) on the order of several millimoles e–/g[37][38][39]. This means that when "charged", biochar can provide electrons for either abiotic or biotic degradation of reducible compounds such as MC. The abiotic reduction of DNT and RDX mediated by biochar has been demonstrated[25] and similar reactions are expected to occur for DNAN and NTO as well. Recent studies have shown that the electron storage capacity of biochar is also accessible to microbes. For example, soil bacteria such as Geobacter and Shewanella species can utilize oxidized (or "discharged") biochar as an electron acceptor for the oxidation of organic substrates such as lactate and acetate[40][41] and reduced (or "charged") biochar as an electron donor for the reduction of nitrate[41]. This is significant because, through microbial access of stored electrons in biochar, contaminants that do not sorb strongly to biochar can still be degraded.

Similar to nitrate, perchlorate and other relatively water-soluble energetic compounds (e.g., NTO and NQ) may also be similarly transformed using reduced biochar as an electron donor. Unlike other electron donors, biochar can be recharged through biodegradation of organic substrates[41] and thus can serve as a long-lasting sorbent and electron repository in soil. Similar to peat moss, the high porosity and surface area of biochar not only facilitate contaminant sorption but also create anaerobic reducing microenvironments in its inner pores, where reductive degradation of energetic compounds can take place.

Other Sorbents

Chitin and unmodified cellulose were predicted by Density Functional Theory methods to be favorable for absorption of NTO and NQ, as well as the legacy explosives[42]. Cationized cellulosic materials (e.g., cotton, wood shavings) have been shown to effectively remove negatively charged energetics like perchlorate and NTO from solution[43]. A substantial body of work has shown that modified cellulosic biopolymers can also be effective sorbents for removing metals from solution[44][45][46][47] and therefore will also likely be applicable for some of the metals that may be found in surface runoff at firing ranges.

Technology Evaluation

Based on the properties of the target munition constituents, a combination of materials was expected to yield the best results to facilitate the sorption and subsequent biotic and abiotic degradation of the contaminants.

Sorbents

Table 1. Freundlich and Langmuir adsorption parameters for insensitive and legacy explosives
Compound Freundlich Langmuir
Parameter Peat CAT Pine CAT Burlap CAT Cotton Parameter Peat CAT Pine CAT Burlap CAT Cotton
HMX Kf 0.08 +/- 0.00 -- -- -- qm (mg/g) 0.29 +/- 0.04 -- -- --
n 1.70 +/- 0.18 -- -- -- b (L/mg) 0.39 +/- 0.09 -- -- --
r2 0.91 -- -- -- r2 0.93 -- -- --
RDX Kf 0.11 +/- 0.02 -- -- -- qm (mg/g) 0.38 +/- 0.05 -- -- --
n 2.75 +/- 0.63 -- -- -- b (L/mg) 0.23 +/- 0.08 -- -- --
r2 0.69 -- -- -- r2 0.69 -- -- --
TNT Kf 1.21 +/- 0.15 1.02 +/- 0.04 0.36 +/- 0.02 -- qm (mg/g) 3.63 +/- 0.18 1.26 +/- 0.06 -- --
n 2.78 +/- 0.67 4.01 +/- 0.44 1.59 +/- 0.09 -- b (L/mg) 0.89 +/- 0.13 0.76 +/- 0.10 -- --
r2 0.81 0.93 0.98 -- r2 0.97 0.97 -- --
NTO Kf -- 0.94 +/- 0.05 0.41 +/- 0.05 0.26 +/- 0.06 qm (mg/g) -- 4.07 +/- 0.26 1.29 +/- 0.12 0.83 +/- .015
n -- 1.61 +/- 0.11 2.43 +/- 0.41 2.53 +/- 0.76 b (L/mg) -- 0.30 +/- 0.04 0.36 +/- 0.08 0.30 +/- 0.15
r2 -- 0.97 0.82 0.57 r2 -- 0.99 0.89 0.58
DNAN Kf 0.38 +/- 0.05 0.01 +/- 0.01 -- -- qm (mg/g) 2.57 +/- 0.33 -- -- --
n 1.71 +/- 0.20 0.70 +/- 0.13 -- -- b (L/mg) 0.13 +/- 0.03 -- -- --
r2 0.89 0.76 -- -- r2 0.92 -- -- --
ClO4 Kf -- 1.54 +/- 0.06 0.53 +/- 0.03 -- qm (mg/g) -- 3.63 +/- 0.18 1.26 +/- 0.06 --
n -- 2.42 +/- 0.16 2.42 +/- 0.26 -- b (L/mg) -- 0.89 +/- 0.13 0.76 +/- 0.10 --
r2 -- 0.97 0.92 -- r2 -- 0.97 0.97 --
Notes:
-- Indicates the algorithm failed to converge on the model fitting parameters, therefore there was no successful model fit.
CAT Indicates cationized material.

The materials screened included Sphagnum peat moss, primarily for sorption of HMX, RDX, TNT, and DNAN, as well as cationized cellulosics for removal of perchlorate and NTO. The cationized cellulosics that were examined included: pine sawdust, pine shavings, aspen shavings, cotton linters (fine, silky fibers which adhere to cotton seeds after ginning), chitin, chitosan, burlap (landscaping grade), coconut coir, raw cotton, raw organic cotton, cleaned raw cotton, cotton fabric, and commercially cationized fabrics.

As shown in Table 1[43], batch sorption testing indicated that a combination of Sphagnum peat moss and cationized pine shavings provided good removal of both the neutral organic energetics (HMX, RDX, TNT, DNAN) as well as the negatively charged energetics (perchlorate, NTO).

Slow Release Carbon Sources

Table 2. Slow-release Carbon Sources
Material Abbreviation Commercial Source Notes
polylactic acid PLA6 Goodfellow high molecular weight thermoplastic polyester
polylactic acid PLA80 Goodfellow low molecular weight thermoplastic polyester
polyhydroxybutyrate PHB Goodfellow bacterial polyester
polycaprolactone PCL Sarchem Labs biodegradable polyester
polybutylene succinate BioPBS Mitsubishi Chemical Performance Polymers compostable bio-based product
sucrose ester of fatty acids SEFA SP10 Sisterna food and cosmetics additive
sucrose ester of fatty acids SEFA SP70 Sisterna food and cosmetics additive

A range of biopolymers widely used in the production of biodegradable plastics were screened for their ability to support aerobic and anoxic biodegradation of the target munition constituents. These compounds and their sources are listed in Table 2.

Multiple pure bacterial strains and mixed cultures were screened for their ability to utilize the solid biopolymers as a carbon source to support energetic compound transformation and degradation. Pure strains included the aerobic RDX degrader Rhodococcus species DN22 (DN22 henceforth)[48] and Gordonia species KTR9 (KTR9 henceforth)[48], the anoxic RDX degrader Pseudomonas fluorencens species I-C (I-C henceforth)[49][50], and the aerobic NQ degrader Pseudomonas extremaustralis species NQ5 (NQ5 henceforth)[51]. Anaerobic mixed cultures were obtained from a membrane bioreactor (MBR) degrading a mixture of six explosives (HMX, RDX, TNT, NTO, NQ, DNAN), as well as perchlorate and nitrate[52]. The results indicated that the slow release carbon sources polyhydroxybutyrate (PHB), polycaprolactone (PCL), and polybutylene succinate (BioPBS) were effective for supporting the biodegradation of the mixture of energetics.

Biochar

Figure 3. Schematic of interactions between biochar and munitions constituents

The ability of biochar to sorb and abiotically reduce legacy and insensitive munition constituents, as well as biochar’s use as an electron donor for microbial biodegradation of energetic compounds was examined. Batch experiments indicated that biochar was a reasonable sorbent for some of the energetics (RDX, DNAN), but could also serve as both an electron acceptor and an electron donor to facilitate abiotic (RDX, DNAN, NTO) and biotic (perchlorate) degradation (Figure 3)[53].

Sorption-Biodegradation Column Experiments

The selected materials and cultures discussed above, along with a small amount of range soil and crushed oyster shell as a slow-release pH buffering agent, were packed into columns, and a steady flow of dissolved energetics was passed through the columns. The composition of the four columns is presented in Figure 4. The influent and effluent concentrations of the energetics was monitored over time. The column experiment was performed twice. As seen in Figure 5, there was sustained almost complete removal of RDX and ClO4-, and more removal of the other energetics in the bioactive columns compared to the sorption only columns, over the course of the experiments. For reference, 100 PV is approximately equivalent to three months of operation. The higher effectiveness of sorption with biodegradation compared to sorption only is further illustrated in Figure 6, where the energetics mass removal in the bioactive columns was shown to be 2-fold (TNT) to 20-fold (RDX) higher relative to that observed in the sorption only column. The mass removal of HMX and NQ were both over 40% higher with biochar added to the sorption with biodegradation treatment, although biochar showed little added benefit for removal of other energetics tested.

Trap and Treat Technology

These results provide a proof-of-concept for the further development of a passive and sustainable “trap-and-treat” technology for remediation of energetic compounds in stormwater runoff at military testing and training ranges. At a given site, the stormwater runoff would need to be fully characterized with respect to key parameters (e.g., pH, major anions), and site specific treatability testing would be recommended to assure there was nothing present in the runoff that would reduce performance. Effluent monitoring on a regular basis would also be needed (and would be likely be expected by state and local regulators) to assess performance decline over time.

The components of the technology would be predominantly peat moss and cationized pine shavings, supplemented with biochar, ground oyster shell, the biopolymer carbon sources, and the bioaugmentation cultures. The entire mix would likely be emplaced in a concrete vault at the outflow end of the stormwater runoff retention basin at the contaminated site. The deployed treatment system would have further design elements, such as a system to trap and retain suspended solids in the runoff in order to minimize clogging the matrix. the inside of the vault would be baffled to maximize the hydraulic retention time of the contaminated runoff. The biopolymer carbon sources and oyster shell may need be refreshed periodically (perhaps yearly) to maintain performance. However, a complete removal and replacement of the base media (peat moss, CAT pine) would not be advised, as that would lead to a loss of the acclimated biomass.

Summary

Novel sorbents and slow release carbon sources can be an effective way to promote the sorption and biodegradation of a range of legacy and insensitive munition constituents from surface runoff, and the added benefits of biochar for both sorption and biotic and abiotic degradation of these compounds was demonstrated. These results establish a foundation for a passive, sustainable surface runoff treatment technology for both active and inactive military ranges.

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See Also

Agency for Toxic Substances and Disease Registry (ATSDR) PFAS Health Studies

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