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==Downscaled High Resolution Datasets for Climate Change Projections==
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==Remediation of Stormwater Runoff Contaminated by Munition Constituents==  
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Global climate models (GCMs) have generated projections of temperature, precipitation and other important climate change parameters with spatial resolutions of 100 to 300 km.  However, higher spatial resolution information is required to assess threats to individual installations or regions.  A variety of “downscaling” approaches have been used to produce high spatial resolution output (datasets) from the global climate models at scales that are useful for evaluating potential threats to critical infrastructure at regional and local scales. These datasets enable development of information about projections produced from various climate models, about downscaling to achieve desired locational specificity, and about selecting the appropriate dataset(s) to use for performing specific assessments.  This article describes how these datasets can be accessed and used to evaluate potential climate change impacts.
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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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'''Related Article(s):'''
 
'''Related Article(s):'''
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* [[Climate Change Primer]]
 
  
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'''Contributor(s):''' [[Dr. Rao Kotamarthi]]
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*[[Munitions Constituents]]
  
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'''Key Resource(s):'''
 
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* Use of Climate Information for Decision-Making and Impacts Research: State of our Understanding<ref name="Kotamarthi2016">Kotamarthi, R., Mearns, L., Hayhoe, K., Castro, C.L., and Wuebble, D., 2016. Use of Climate Information for Decision-Making and Impacts Research: State of Our Understanding. Department of Defense, Strategic Environmental Research and Development Program (SERDP), 55pp. Free download from: [https://www.serdp-estcp.org/content/download/38568/364489/file/Use_of_Climate_Information_for_Decision-Making_Technical_Report.pdf SERDP-ESTCP]</ref>
 
  
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* Applying Climate Change Information to Hydrologic and Coastal Design of Transportation Infrastructure, Design Practices<ref name="Kilgore2019">Kilgore, R., Thomas, W.O. Jr., Douglass, S., Webb, B., Hayhoe, K., Stoner, A., Jacobs, J.M., Thompson, D.B., Herrmann, G.R., Douglas, E., and Anderson, C., 2019.  Applying Climate Change Information to Hydrologic and Coastal Design of Transportation Infrastructure, Design Practices. The National Cooperative Highway Research Program, Transportation Research Board, Project 15-61, 154 pages. Free download from: [http://onlinepubs.trb.org/Onlinepubs/nchrp/docs/NCHRP1561_DesignProcedures.pdf The Transportation Research Board]</ref>
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'''Contributor:''' Mark E. Fuller
  
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* Statistical Downscaling and Bias Correction for Climate Research<ref name="Maraun2018">Maraun, D., and Wildmann, M., 2018. Statistical Downscaling and Bias Correction for Climate Research. Cambridge University Press, Cambridge, UK. 347 pages.  [https://doi.org/10.1017/9781107588783 DOI: 10.1017/9781107588783]&nbsp;&nbsp; ISBN: 978-1-107-06605-2</ref>
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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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* Downscaling Techniques for High-Resolution Climate Projections: From Global Change to Local Impacts<ref name="Kotamarthi2021">Kotamarthi, R., Hayhoe, K., Wuebbles, D., Mearns, L.O., Jacobs, J. and Jurado, J., 2021. Downscaling Techniques for High-Resolution Climate Projections: From Global Change to Local Impacts. Cambridge University Press, Cambridge, UK. 202 pages. [https://doi.org/10.1017/9781108601269 DOI: 10.1017/9781108601269]&nbsp;&nbsp; ISBN: 978-1-108-47375-0</ref>
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==Background==
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===Surface Runoff Characteristics and Treatment Approaches===
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[[File: FullerFig1.png | thumb | 400 px | left | Figure 1. Conceptual model of passive trap and treat approach for MC removal from stormwater runoff]]
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During&nbsp;large&nbsp;precipitation&nbsp;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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==Downscaling of Global Climate Models==
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===Surface Runoff on Ranges===
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Some communities and businesses have begun to improve their resilience to climate change by building adaptation plans based on national scale climate datatsets ([https://unfccc.int/topics/adaptation-and-resilience/workstreams/national-adaptation-plans National Adaptation Plans]), regional datasets ([https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State Flood Risk Management Guidance]<ref name="NYDEC2020">New York State Department of Environmental Conservation, 2020. New York State Flood Risk Management Guidance for Implementation of the Community Risk and Resiliency Act. Free download from: [https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State]&nbsp;&nbsp; [[Media: NewYorkState2020.pdf | Report.pdf]]</ref>), and datasets generated at local spatial resolutions. Resilience to the changing climate has also been identified by the US Department of Defense (DoD) as a necessary part of the installation planning and basing process ([https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD Report on Effects of a Changing Climate]<ref name="DoD2019">US Department of Defense, 2019. Report on Effects of a Changing Climate to the Department of Defense. Free download from: [https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD]&nbsp;&nbsp; [[Media: DoD2019.pdf | Report.pdf]]</ref>). More than 79 installations were identified as facing potential threats from climate change. The threats faced due to changing climate include recurrent flooding, droughts, desertification, wildfires and thawing permafrost.  
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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&nbsp;runoff&nbsp;represents&nbsp;a&nbsp;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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Assessing the threats climate change poses at regional and local scales requires data with higher spatial resolution than is currently available from global climate models. Global-scale climate models typically have spatial resolutions of 100 to 300 km, and output from these models needs to be spatially and/or temporally disaggregated in order to be useful in performing assessments at smaller scales. The process of producing higher spatial-temporal resolution climate model output from coarser global climate model outputs is referred to as “downscaling” and results in climate change projections (datasets) at scales that are useful for evaluating potential threats to regional and local communities and businesses.  These datasets provide information on temperature, precipitation and a variety of other climate variables for current and future climate conditions under various greenhouse gas (GHG) emission scenarios. There are a variety of web-based tools available for accessing these datasets to evaluate potential climate change impacts at regional and local scales.
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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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==Methods for Downscaling==
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==Range Runoff Treatment Technology Components==
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{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
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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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|+Table 1.  Two widely used methods for developing downscaled higher resolution climate model projections
 
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!Dynamical Downscaling
 
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!Statistical Downscaling
 
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|Deterministic climate change simulations that output</br>many climate variables with sub-daily information ||Primarily limited to daily temperature and precipitation
 
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|Computationally expensive; hence, limited number of simulations – both</br>GHG emission scenarios and global climate models downscaled||Computationally efficient; hence, downscaled data typically</br>available for many different global climate models and GHG emission scenarios
 
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|May require additional bias correction||Method incorporates bias correction
 
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|Observational data at the downscaled location are not necessary</br>to obtain the downscaled output at the location||Best suited for locations with 30 years or more of observational data
 
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|Does not assume stationarity or in other words the model</br>simulates the future regardless of what has happened in the past||Stationarity assumption - assumes that the statistical relationship between global</br>climate model and observations will remain constant in the future
 
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There are two main approaches to downscaling. One method, commonly referred to as “statistical downscaling”, uses the empirical-statistical relationships between large-scale weather phenomena and historical local weather data. In this method, these statistical relationships are applied to output generated by global climate models. A second method uses physics-based numerical models (regional-scale climate models or RCMs) of weather and climate that operate over a limited region of the earth (e.g., North America) and at spatial resolutions that are typically 3 to 10 times finer than the global-scale climate models. This method is known as “dynamical downscaling”.  These regional-scale climate models are similar to the global models with respect to their reliance on the principles of physics, but because they operate over only part of the earth, they require information about what is coming in from the rest of the earth as well as what is going out of the limited region of the model. This is generally obtained from a global model.  The primary differences between statistical and dynamical downscaling methods are summarized in Table 1.
 
  
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It is important to realize that there is no “best” downscaling method or dataset, and that the best method/dataset for a given problem depends on that problem’s specific needs. Several data products based on downscaling higher level spatial data are available ([https://cida.usgs.gov/gdp/ USGS], [http://maca.northwestknowledge.net/ MACA], [https://www.narccap.ucar.edu/ NARCCAP], [https://na-cordex.org/ CORDEX-NA]). The appropriate method and dataset to use depends on the intended application. The method selected should be able to credibly resolve spatial and temporal scales relevant for the application. For example, to develop a risk analysis of frequent flooding, the data product chosen should include precipitation at greater than a diurnal frequency and over multi-decadal timescales. This kind of product is most likely to be available using the dynamical downscaling method. SERDP reviewed the various advantages and disadvantages of using each type of downscaling method and downscaling dataset, and developed a recommended process that is publicly available<ref name="Kotamarthi2016"/>. In general, the following recommendations should be considered in order to pick the right downscaled dataset for a given analysis:
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===Peat===
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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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* When a problem depends on using a large number of climate models and emission scenarios to perform preliminary assessments and to understand the uncertainty range of projections, then using a statistical downscaled dataset is recommended.   
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===Soybean Oil===
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* When the assessment needs a more extensive parameter list or is analyzing a region with few long-term observational data, dynamically downscaled climate change projections are recommended.  
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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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==Uncertainty in Projections==
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===Biochar===
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A primary cause of uncertainty in climate change projections, especially beyond 30 years into the future, is the uncertainty in the greenhouse gas (GHG) emission scenarios used to make climate model projections. The best method of accounting for this type of uncertainty is to apply a climate change model to multiple GHG emission scenarios (see also: [[Wikipedia: Representative Concentration Pathway]]).  
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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''.
  
−
The uncertainties in climate projections over shorter timescales, less than 30 years out, are dominated by something known as “internal variability” in the models. Different approaches are used to address the uncertainty from internal variability<ref name="Kotamarthi2021"/>. A third type of uncertainty in climate modeling, known as scientific uncertainty, comes from our inability to numerically solve every aspect of the complex earth system. We expect this scientific uncertainty to decrease as we understand more of the earth system and improve its representation in our numerical models. As discussed in [[Climate Change Primer]], numerical experiments based on global climate models are designed to address these uncertainties in various ways. Downscaling methods evaluate this uncertainty by using several independent regional climate models to generate future projections, with the expectation that each of these models will capture some aspects of the physics better than the others, and that by using several different models, we can estimate the range of this uncertainty. Thus, the commonly accepted methods for accounting for uncertainty in climate model projections are either using projections from one model for several emission scenarios, or applying multiple models to project a single scenario.  
+
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>.  
  
−
A comparison of the currently available methods and their characteristics is provided in Table 2 (adapted from Kotamarthi et al., 2016<ref name="Kotamarthi2016"/>).  The table lists the various methodologies and models used for producing downscaled data, and the climate variables that these methods produce.  These datasets are mostly available for download from the data servers and websites listed in the table and in a few cases by contacting the respective source organizations.
+
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.  
  
−
The most popular and widely used format for atmospheric and climate science is known as [[Wikipedia:NetCDF | NetCDF]], which stands for Network Common Data Form. NetCDF is a self-describing data format that saves data in a binary format. The format is self-describing in that a metadata listing is part of every file that describes all the data attributes, such as dimensions, units and data size and in principal should not need additional information to extract the required data for analysis with the right software.  However, specially built software for reading and extracting data from these binary files is necessary for making visualizations and further analysis. Software packages for reading and writing NetCDF datasets and for generating visualizations from these datasets are widely available and obtained free of cost ([https://www.unidata.ucar.edu/software/netcdf/docs/ NetCDF-tools]). Popular geospatial analysis tools such as ARC-GIS, statistical packages such as ‘R’ and programming languages such as Fortran, C++, and Python have built in libraries that can be used to directly read NetCDF files for visualization and analysis.  
+
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.  
  
 +
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.
  
 +
===Other Sorbents===
 +
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.
  
−
[[File: Gschwend1w2fig1.png | thumb | 300px | Figure 1.  A representation of a clam living in a sediment bed that contains a chemical contaminant (depicted as red hexagons).  The contaminant is partly dissolved in the sediment porewater between the solid grains, and partly associated with solid phases, like natural organic matter and "black carbons" such as soots from diesel engines and chars emitted during forest fires.  All of these liquid and solid materials can exchange their contaminant loads with one another, with the distributions dependent on the chemical's relative affinity for each material.  When an animal like the clam moves into this system, the chemical is also accumulated into the animal, until the animal is also equilibrated with the other solids and liquid(s) present.]]
+
==Technology Evaluation==
−
Environmental media such as sediments typically contain many different materials or phases, including liquid solutions (e.g. water, [[Light Non-Aqueous Phase Liquids (LNAPLs)| nonaqueous phase liquids]] like spilled oils) and diverse solids (e.g., quartz, aluminosilicate clays, and combustion-derived soots).  Further, the chemical concentration in the porewater medium includes both molecules that are "truly dissolved" in the water and others that are associated with colloids in the porewater<ref name="Brownawell1986">Brownawell, B.J., and Farrington, J.W., 1986. Biogeochemistry of PCBs in interstitial waters of a coastal marine sediment. Geochimica et Cosmochimica Acta, 50(1), pp. 157-169.  [https://doi.org/10.1016/0016-7037(86)90061-X DOI: 10.1016/0016-7037(86)90061-X]&nbsp;&nbsp; Free download available from: [https://semspub.epa.gov/work/01/268631.pdf US EPA].</ref><ref name="Chin1992">Chin, Y.P., and Gschwend, P.M., 1992. Partitioning of Polycyclic Aromatic Hydrocarbons to Marine Porewater Organic Colloids. Environmental Science and Technology, 26(8), pp. 1621-1626.  [https://doi.org/10.1021/es00032a020 DOI: 10.1021/es00032a020]</ref><ref name="Achman1996">Achman, D.R., Brownawell, B.J., and Zhang, L., 1996. Exchange of Polychlorinated Biphenyls Between Sediment and Water in the Hudson River Estuary. Estuaries, 19(4), pp. 950-965.  [https://doi.org/10.2307/1352310 DOI: 10.2307/1352310]&nbsp;&nbsp; Free download available from: [https://www.academia.edu/download/55010335/135231020171114-2212-b93vic.pdf Academia.edu]</ref>. As a result, contaminant chemicals distribute among these diverse media (Figure 1) according to their affinity for each and the amount of each phase in the system<ref name="Gustafsson1996">Gustafsson, Ö., Haghseta, F., Chan, C., MacFarlane, J., and Gschwend, P.M., 1996. Quantification of the Dilute Sedimentary Soot Phase: Implications for PAH Speciation and Bioavailability. Environmental Science and Technology, 31(1), pp. 203-209.  [https://doi.org/10.1021/es960317s  DOI: 10.1021/es960317s]</ref><ref name="Luthy1997">Luthy, R.G., Aiken, G.R., Brusseau, M.L., Cunningham, S.D., Gschwend, P.M., Pignatello, J.J., Reinhard, M., Traina, S.J., Weber, W.J., and Westall, J.C., 1997. Sequestration of Hydrophobic Organic Contaminants by Geosorbents. Environmental Science and Technology, 31(12), pp. 3341-3347.  [https://doi.org/10.1021/es970512m DOI: 10.1021/es970512m]</ref><ref name="Lohmann2005">Lohmann, R., MacFarlane, J.K., and Gschwend, P.M., 2005. Importance of Black Carbon to Sorption of Native PAHs, PCBs, and PCDDs in Boston and New York Harbor Sediments. Environmental Science and Technology, 39(1), pp.141-148.  [https://doi.org/10.1021/es049424+  DOI: 10.1021/es049424+]</ref><ref name="Cornelissen2005">Cornelissen, G., Gustafsson, Ö., Bucheli, T.D., Jonker, M.T., Koelmans, A.A., and van Noort, P.C., 2005. Extensive Sorption of Organic Compounds to Black Carbon, Coal, and Kerogen in Sediments and Soils: Mechanisms and Consequences for Distribution, Bioaccumulation, and Biodegradation. Environmental Science and Technology, 39(18), pp. 6881-6895.  [https://doi.org/10.1021/es050191b  DOI: 10.1021/es050191b]</ref><ref name="Koelmans2009">Koelmans, A.A., Kaag, K., Sneekes, A., and Peeters, E.T.H.M., 2009. Triple Domain in Situ Sorption Modeling of Organochlorine Pesticides, Polychlorobiphenyls, Polyaromatic Hydrocarbons, Polychlorinated Dibenzo-p-Dioxins, and Polychlorinated Dibenzofurans in Aquatic Sediments. Environmental Science and Technology, 43(23), pp. 8847-8853.  [https://doi.org/10.1021/es9021188 DOI: 10.1021/es9021188]</ref>. As such, the chemical concentration in any one medium (e.g., truly dissolved in porewater) in a multi-material system like sediment is very hard to know from measures of the total sediment concentration, which unfortunately is the information typically found by analyzing for chemicals in sediment samples.
+
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.
  
−
If an animal moves into this system, it will also accumulate the chemical in its tissues from the loads in all the other materials (Figure 1). This can lead to exposures of the chemical to other organisms, including humans, who may eat such animals. Predicting the quantity of contaminant in the animal requires knowledge of the relative affinities of the chemical for the animal versus the sediment materials. For example, if one knew the chemical's truly dissolved concentration in the porewater and could reasonably assume the chemical of interest in the animal has mostly accumulated in its lipids (as is often the case for very hydrophobic compounds), then one could estimate the chemical concentration in the animal (''C<sub><small>animal</small></sub>'', typically in units of &mu;g/kg animal wet weight) using a lipid-water [[Wikipedia: Partition coefficient | partition coefficient]], ''K<sub><small>lipid-water</small></sub>'', typically in units of (&mu;g/kg lipid)'''/'''(&mu;g/L water), and the porewater concentration of the chemical (''C<sub><small>porewater</small></sub>'', in &mu;g/L) with Equation 1.
+
===Sorbents===
−
{|
+
{| class="wikitable" style="margin-right: 30px; margin-left: auto; float:left; text-align:center;"
−
|
+
|+Table 1. [[Wikipedia: Freundlich equation | Freundlich]] and [[Wikipedia: Langmuir adsorption model | Langmuir]] adsorption parameters for insensitive and legacy explosives
 +
|-
 +
! rowspan="2" | Compound
 +
! colspan="5" | Freundlich
 +
! colspan="5" | Langmuir
 +
|-
 +
! <small>Parameter</small> !! Peat !! <small>CAT</small> Pine !! <small>CAT</small> Burlap !! <small>CAT</small> Cotton !! <small>Parameter</small> !! Peat !! <small>CAT</small> Pine !! <small>CAT</small> Burlap !! <small>CAT</small> Cotton
 +
|-
 +
| colspan="12" style="background-color:white;" |
 +
|-
 +
! rowspan="3" | HMX
 +
! ''K<sub>f</sub>''
 +
| 0.08 +/- 0.00 || -- || -- || --
 +
! ''q<sub>m</sub>'' <small>(mg/g)</small>
 +
| 0.29 +/- 0.04 || -- || -- || --
 +
|-
 +
! ''n''
 +
| 1.70 +/- 0.18 || -- || -- || --
 +
! ''b'' <small>(L/mg)</small>
 +
| 0.39 +/- 0.09 || -- || -- || --
 +
|-
 +
! ''r<sup><small>2</small></sup>''
 +
| 0.91 || -- || -- || --
 +
! ''r<sup><small>2</small></sup>''
 +
| 0.93 || -- || -- || --
 +
|-
 +
| colspan="12" style="background-color:white;" |
 +
|-
 +
! rowspan="3" | RDX
 +
! ''K<sub>f</sub>''
 +
| 0.11 +/- 0.02 || -- || -- || --
 +
! ''q<sub>m</sub>'' <small>(mg/g)</small>
 +
| 0.38 +/- 0.05 || -- || -- || --
 +
|-
 +
! ''n''
 +
| 2.75 +/- 0.63 || -- || -- || --
 +
! ''b'' <small>(L/mg)</small>
 +
| 0.23 +/- 0.08 || -- || -- || --
 +
|-
 +
! ''r<sup><small>2</small></sup>''
 +
| 0.69 || -- || -- || --
 +
! ''r<sup><small>2</small></sup>''
 +
| 0.69 || -- || -- || --
 +
|-
 +
| colspan="12" style="background-color:white;" |
 +
|-
 +
! rowspan="3" | TNT
 +
! ''K<sub>f</sub>''
 +
| 1.21 +/- 0.15 || 1.02 +/- 0.04 || 0.36 +/- 0.02 || --
 +
! ''q<sub>m</sub>'' <small>(mg/g)</small>
 +
| 3.63 +/- 0.18 || 1.26 +/- 0.06 || -- || --
 
|-
 
|-
−
| || Equation 1.
+
! ''n''
−
| style="text-align:center;"| <big>'''''C<sub><small>animal</small></sub> '''=''' f<sub><small>lipid</small></sub> '''x''' K<sub><small>lipid-water</small></sub> '''x''' C<sub><small>porewater</small></sub>'''''</big>
+
| 2.78 +/- 0.67 || 4.01 +/- 0.44 || 1.59 +/- 0.09 || --
 +
! ''b'' <small>(L/mg)</small>
 +
| 0.89 +/- 0.13 || 0.76 +/- 0.10 || -- || --
 +
|-
 +
! ''r<sup><small>2</small></sup>''
 +
| 0.81 || 0.93 || 0.98 || --
 +
! ''r<sup><small>2</small></sup>''
 +
| 0.97 || 0.97 || -- || --
 
|-
 
|-
−
| where:
+
| colspan="12" style="background-color:white;" |
 
|-
 
|-
−
| || ''f<sub><small>lipid</small></sub>'' || is the fraction lipids contribute to the total wet weight of the animal (kg lipid/kg animal wet weight), and
+
! rowspan="3" | NTO
 +
! ''K<sub>f</sub>''
 +
| -- || 0.94 +/- 0.05 || 0.41 +/- 0.05 || 0.26 +/- 0.06
 +
! ''q<sub>m</sub>'' <small>(mg/g)</small>
 +
| -- || 4.07 +/- 0.26 || 1.29 +/- 0.12 || 0.83 +/- .015
 
|-
 
|-
−
| || ''C<sub><small>porewater</small></sub>'' || is the freely dissolved contaminant concentration in the porewater surrounding the animal.
+
! ''n''
−
|}
+
| -- || 1.61 +/- 0.11 || 2.43 +/- 0.41 || 2.53 +/- 0.76
−
 
+
! ''b'' <small>(L/mg)</small>
−
While there is a great deal of information on the values of ''K<sub><small>lipid-water</small></sub>'' for many chemicals<ref name="Schwarzenbach2017">Schwarzenbach, R.P., Gschwend, P.M., and Imboden, D.M., 2017.  Environmental Organic Chemistry, 3rd edition. Ch. 16: Equilibrium Partitioning from Water and Air to Biota, pp. 469-521. John Wiley and Sons.  ISBN: 978-1-118-76723-8</ref>, it is often very inaccurate to estimate truly dissolved porewater concentrations from total sediment concentrations using assumptions about the affinity of those chemicals for the solids in the system<ref name="Gustafsson1996"/>. Further, it is difficult to isolate porewater without colloids and/or measure the very low truly dissolved concentrations of hydrophobic contaminants of concern like [[Polycyclic Aromatic Hydrocarbons (PAHs) | polycyclic aromatic hydrocarbons (PAHs)]], [[Wikipedia: Polychlorinated biphenyl | polychlorinated biphenyls (PCBs)]], nonionic pesticides like [[Wikipedia: DDT | dichlorodiphenyltrichloroethane (DDT)]], and [[Wikipedia: Polychlorinated dibenzodioxins | polychlorinated dibenzo-p-dioxins (PCDDs)]]/[[Wikipedia: Polychlorinated dibenzofurans | dibenzofurans (PCDFs)]]<ref name="Hawthorne2005">Hawthorne, S.B., Grabanski, C.B., Miller, D.J., and Kreitinger, J.P., 2005. Solid-Phase Microextraction Measurement of Parent and Alkyl Polycyclic Aromatic Hydrocarbons in Milliliter Sediment Pore Water Samples and Determination of K<sub><small>DOC</small></sub> Values. Environmental Science and Technology, 39(8), pp. 2795-2803. [https://doi.org/10.1021/es0405171 DOI: 10.1021/es0405171]</ref>.
+
| -- || 0.30 +/- 0.04 || 0.36 +/- 0.08 || 0.30 +/- 0.15
−
 
+
|-
−
==Passive Samplers==
+
! ''r<sup><small>2</small></sup>''
−
One approach to address this problem for contaminated sediments is to insert into the sediment billets of organic polymers like low density polyethylene (LDPE), polydimethylsiloxane (PDMS), or polyoxymethylene (POM) that can absorb such hydrophobic chemicals from their surroundings<ref name="Mayer2000">Mayer, P., Vaes, W.H., Wijnker, F., Legierse, K.C., Kraaij, R., Tolls, J., and Hermens, J.L., 2000. Sensing Dissolved Sediment Porewater Concentrations of Persistent and Bioaccumulative Pollutants Using Disposable Solid-Phase Microextraction Fibers. Environmental Science and Technology, 34(24), pp. 5177-5183.  [https://doi.org/10.1021/es001179g DOI: 10.1021/es001179g]</ref><ref name="Booij2003">Booij, K., Hoedemaker, J.R., and Bakker, J.F., 2003. Dissolved PCBs, PAHs, and HCB in Pore Waters and Overlying Waters of Contaminated Harbor Sediments. Environmental Science and Technology, 37(18), pp. 4213-4220.  [https://doi.org/10.1021/es034147c DOI: 10.1021/es034147c]</ref><ref name="Cornelissen2008">Cornelissen, G., Pettersen, A., Broman, D., Mayer, P., and Breedveld, G.D., 2008. Field testing of equilibrium passive samplers to determine freely dissolved native polycyclic aromatic hydrocarbon concentrations. Environmental Toxicology and Chemistry, 27(3), pp. 499-508. [https://doi.org/10.1897/07-253.1 DOI: 10.1897/07-253.1]</ref><ref name="Tomaszewski2008">Tomaszewski, J.E., and Luthy, R.G., 2008. Field Deployment of Polyethylene Devices to Measure PCB Concentrations in Pore Water of Contaminated Sediment. Environmental Science and Technology, 42(16), pp. 6086-6091.  [https://doi.org/10.1021/es800582a DOI: 10.1021/es800582a]</ref><ref name="Fernandez2009">Fernandez, L.A., MacFarlane, J.K., Tcaciuc, A.P., and Gschwend, P.M., 2009. Measurement of Freely Dissolved PAH Concentrations in Sediment Beds Using Passive Sampling with Low-Density Polyethylene Strips. Environmental Science and Technology, 43(5), pp. 1430-1436. [https://doi.org/10.1021/es802288w DOI: 10.1021/es802288w]</ref><ref name="Arp2015">Arp, H.P.H., Hale, S.E., Elmquist Kruså, M., Cornelissen, G., Grabanski, C.B., Miller, D.J., and Hawthorne, S.B., 2015. Review of polyoxymethylene passive sampling methods for quantifying freely dissolved porewater concentrations of hydrophobic organic contaminants. Environmental Toxicology and Chemistry, 34(4), pp. 710-720.  [https://doi.org/10.1002/etc.2864 DOI: 10.1002/etc.2864]&nbsp;&nbsp;  [https://setac.onlinelibrary.wiley.com/doi/epdf/10.1002/etc.2864 Free access article.]&nbsp;&nbsp; [[Media: Arp2015.pdf | Report.pdf]]</ref><ref name="Apell2016"/>. In this approach, the polymer is inserted in the sediment bed where it absorbs some of the contaminant load via the contaminant's diffusion into the polymer from the surroundings. When the polymer achieves sorptive equilibration with the sediments, the chemical concentration in the polymer, ''C<sub><small>polymer</small></sub>'' (&mu;g/kg polymer), can be used to find the corresponding concentration in the porewater,  ''C<sub><small>porewater</small></sub>'' (&mu;g/L), using a polymer-water partition coefficient, ''K<sub><small>polymer-water</small></sub>'' ((&mu;g/kg polymer)'''/'''(&mu;g/L water)), that has previously been found in laboratory testing<ref name="Lohmann2012">Lohmann, R., 2012. Critical Review of Low-Density Polyethylene’s Partitioning and Diffusion Coefficients for Trace Organic Contaminants and Implications for Its Use as a Passive Sampler. Environmental Science and Technology, 46(2), pp. 606-618. [https://doi.org/10.1021/es202702y DOI: 10.1021/es202702y]</ref><ref name="Ghosh2014">Ghosh, U., Kane Driscoll, S., Burgess, R.M., Jonker, M.T., Reible, D., Gobas, F., Choi, Y., Apitz, S.E., Maruya, K.A., Gala, W.R., Mortimer, M., and Beegan, C., 2014. Passive Sampling Methods for Contaminated Sediments: Practical Guidance for Selection, Calibration, and Implementation. Integrated Environmental Assessment and Management, 10(2), pp. 210-223. [https://doi.org/10.1002/ieam.1507 DOI: 10.1002/ieam.1507]&nbsp;&nbsp; [https://setac.onlinelibrary.wiley.com/doi/epdf/10.1002/ieam.1507 Free access article.]&nbsp;&nbsp; [[Media: Ghosh2014.pdf | Report.pdf]]</ref>, as shown in Equation 2.
+
| -- || 0.97 || 0.82 || 0.57
−
{|
+
! ''r<sup><small>2</small></sup>''
−
|
+
| -- || 0.99 || 0.89 || 0.58
 +
|-
 +
| colspan="12" style="background-color:white;" |
 +
|-
 +
! rowspan="3" | DNAN
 +
! ''K<sub>f</sub>''
 +
| 0.38 +/- 0.05 || 0.01 +/- 0.01 || -- || --
 +
! ''q<sub>m</sub>'' <small>(mg/g)</small>
 +
| 2.57 +/- 0.33 || -- || -- || --
 +
|-
 +
! ''n''
 +
| 1.71 +/- 0.20 || 0.70 +/- 0.13 || -- || --
 +
! ''b'' <small>(L/mg)</small>
 +
| 0.13 +/- 0.03 || -- || -- || --
 +
|-
 +
! ''r<sup><small>2</small></sup>''
 +
| 0.89 || 0.76 || -- || --
 +
! ''r<sup><small>2</small></sup>''
 +
| 0.92 || -- || -- || --
 +
|-
 +
| colspan="12" style="background-color:white;" |
 +
|-
 +
! rowspan="3" | ClO<sub>4</sup>
 +
! ''K<sub>f</sub>''
 +
| -- || 1.54 +/- 0.06 || 0.53 +/- 0.03 || --
 +
! ''q<sub>m</sub>'' <small>(mg/g)</small>
 +
| -- || 3.63 +/- 0.18 || 1.26 +/- 0.06 || --
 
|-
 
|-
−
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|| Equation&nbsp;2.
+
! ''n''
−
| style="width:600px; text-align:center;" | <big>'''''C<sub><small>porewater</small></sub> '''=''' C<sub><small>polymer</small></sub> '''/''' K<sub><small>polymer-water</small></sub>'''''</big>
+
| -- || 2.42 +/- 0.16 || 2.42 +/- 0.26 || --
−
|}
+
! ''b'' <small>(L/mg)</small>
−
 
+
| -- || 0.89 +/- 0.13 || 0.76 +/- 0.10 || --
−
Such “passive uptake” by the polymer also reflects the availability of the chemicals for transport to adjacent systems (e.g., overlying surface waters) and for uptake into organisms (e.g., [[Wikipedia: Bioaccumulation | bioaccumulation]]).  Thus, one can use the porewater concentrations to estimate the biotic accumulation of the chemicals, too.  For example, for the concentration in the animal equilibrated with the sediment, ''C<sub><small>animal</small></sub>'' (&mu;g/kg animal), would be found by combining Equations 1 and 2 to get Equation 3.
+
|-
−
{|
+
! ''r<sup><small>2</small></sup>''
−
|
+
| -- || 0.97 || 0.92 || --
 +
! ''r<sup><small>2</small></sup>''
 +
| -- || 0.97 || 0.97 || --
 
|-
 
|-
−
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|| Equation&nbsp;3.
+
| 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>
−
|style="width:700px; text-align:center;" |<big>'''''C<sub><small>animal</small></sub> '''=''' f<sub><small>lipid</small></sub> '''x''' K<sub><small>lipid-water</small></sub> '''x''' C<sub><small>polymer</small></sub> '''/''' K<sub><small>polymer-water</small></sub>'''''</big>
 
 
|}
 
|}
−
[[File: Gschwend1w2fig2a.PNG | thumb | 300px | Figure 2a.  Plot of the initial concentrations of a PRC (green lines) in a polyethylene (PE) sheet inserted in a sediment showing constant concentration across the PE and zero concentration outside the PE.  At the same time, a target contaminant of interest (red lines) initially has a constant concentration in the sediment outside the PE and zero concentration inside the PE.]][[File: Gschwend1w2fig2b.PNG | thumb | 300px | Figure 2b.  After the PE has been deployed for a time, the PRC is depleted from the PE (green lines), especially near the surfaces contacting the sediment, and its concentration is building up outside the PE and diffusing away into the sediment.  Meanwhile, the target chemical leaves the sediment and begins to diffuse into the PE (red lines).  The "jumps" in concentration  at the PE-sediment boundary reflect the equilibrium paritioning coefficient,</br>''K<sub>PE-sed</sub>&nbsp;=&nbsp;C<sub>PE</sub>&nbsp;/&nbsp;C<sub>sediment</sub>''.]]
 
  
−
==Performance Reference Compounds (PRCs)==
+
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.
−
Perhaps unsurprisingly, pollutants with low water solubility like PAHs, PCBs, etc. do not diffuse quickly through sediment beds.  As a result, their accumulation in polymeric materials in sediments can take a long time to achieve equilibration<ref name="Fernandez2009b">Fernandez, L. A., Harvey, C.F., and Gschwend, P.M., 2009. Using Performance Reference Compounds in Polyethylene Passive Samplers to Deduce Sediment Porewater Concentrations for Numerous Target Chemicals. Environmental Science and Technology, 43(23), pp. 8888-8894. [https://doi.org/10.1021/es901877a DOI: 10.1021/es901877a]</ref><ref name="Lampert2015">Lampert, D.J., Thomas, C., and Reible, D.D., 2015. Internal and external transport significance for predicting contaminant uptake rates in passive samplers. Chemosphere, 119, pp. 910-916.  [https://doi.org/10.1016/j.chemosphere.2014.08.063 DOI: 10.1016/j.chemosphere.2014.08.063]&nbsp;&nbsp; Free download available from: [https://www.academia.edu/download/44146586/chemosphere_2014.pdf Academia.edu]</ref><ref name="Apell2016b">Apell, J.N., Tcaciuc, A.P., and Gschwend, P.M., 2016. Understanding the rates of nonpolar organic chemical accumulation into passive samplers deployed in the environment: Guidance for passive sampler deployments. Integrated Environmental Assessment and Management, 12(3), pp. 486-492.  [https://doi.org/10.1002/ieam.1697 DOI: 10.1002/ieam.1697]</ref>. This problem was recognized previously for passive samplers called [[Wikipedia: Semipermeable membrane devices | semipermeable membrane devices]] (SPMDs, e.g. polyethylene bags filled with triolein<ref name="Huckins2002">Huckins, J.N., Petty, J.D., Lebo, J.A., Almeida, F.V., Booij, K., Alvarez, D.A., Cranor, W.L., Clark, R.C., and Mogensen, B.B., 2002. Development of the Permeability/Performance Reference Compound Approach for In Situ Calibration of Semipermeable Membrane Devices. Environmental Science and Technology, 36(1), pp. 85-91.  [https://doi.org/10.1021/es010991w DOI: 10.1021/es010991w]</ref>) that were deployed in surface waters. As a result, representative chemicals called performance reference compound (PRCs) were dosed inside the samplers before their deployment in the environment, and the PRCs' diffusive losses out of the SPMD could be used to quantify the fractional approach toward sampler-environmental surroundings equilibration<ref name="Booij2002">Booij, K., Smedes, F., and van Weerlee, E.M., 2002. Spiking of performance reference compounds in low density polyethylene and silicone passive water samplers. Chemosphere 46(8), pp.1157-1161.  [https://doi.org/10.1016/S0045-6535(01)00200-4 DOI: 10.1016/S0045-6535(01)00200-4]</ref><ref name="Huckins2002"/>. A similar approach can be used for polymers inserted in sediment beds<ref name="Fernandez2009b"/><ref name="Apell2014"/>. Commonly, isotopically labeled forms of the compounds of interest such as deuterated or <sup>13</sup>C-labelled PAHs or PCBs are homogeneously impregnated into the polymers before their deployments.  Upon insertion of the polymer into the sediment bed (or overlying waters or even air), the initially evenly distributed PRCs begin to diffuse out of the sampling polymer and  into the surroundings (Figure 2).  
+
 
 +
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).
  
−
Assuming the contaminants of interest undergo the same mass transfer restrictions limiting their rates of uptake into the polymer (e.g., diffusion through the sedimentary porous medium) that are also limiting transfers of the PRCs out of the polymer<ref name="Fernandez2009b"/><ref name="Apell2014"/>, then fractional losses of the PRCs during a particular deployment can be used to adjust the accumulated contaminant loads to what they would have been at equilibrium with their surroundings with Equation 4.
+
===Slow Release Carbon Sources===
−
{|
+
{| class="wikitable" style="margin-right: 30px; margin-left: auto; float:left; text-align:center;"
−
|
+
|+Table 2. Slow-release Carbon Sources
 
|-
 
|-
−
| || Equation 4.
+
! Material !! Abbreviation !! Commercial Source !! Notes
−
| style="text-align:center;"| <big>'''''C(<sub>&infin;</sub>)<sub><small>polymer</small></sub> '''=''' C(<small>t</small>)<sub><small>polymer</small></sub> '''/''' f<sub><small>PRC lost</small></sub>'''''</big>
 
 
|-
 
|-
−
| where:
+
| polylactic acid || PLA6 || [https://www.goodfellow.com/usa?srsltid=AfmBOoqEiqIbrvWb1Hn1Bc090efBUUfg6V4N3Vrn6ytajHMJR-FG1Ez- Goodfellow] || high molecular weight thermoplastic polyester
 
|-
 
|-
−
| || ''f<sub><small>PRC lost</small></sub>'' || is the fraction of the PRC lost to outward diffusion,
+
| polylactic acid || PLA80 || [https://www.goodfellow.com/usa?srsltid=AfmBOoqEiqIbrvWb1Hn1Bc090efBUUfg6V4N3Vrn6ytajHMJR-FG1Ez- Goodfellow] || low molecular weight thermoplastic polyester
 
|-
 
|-
−
| || ''C(<sub>&infin;</sub>)<sub><small>polymer</small></sub>'' || is the concentration of the contaminant in the polymer at equilibrium, and
+
| polyhydroxybutyrate || PHB || [https://www.goodfellow.com/usa?srsltid=AfmBOoqEiqIbrvWb1Hn1Bc090efBUUfg6V4N3Vrn6ytajHMJR-FG1Ez- Goodfellow] || bacterial polyester
 
|-
 
|-
−
| || ''C(<small>t</small>)<sub><small>polymer</small></sub>'' || is the concentration of the contaminant in the polymer after deployment time, t.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+
| 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
−
|}  
+
|-
 +
| polybutylene succinate || BioPBS || [https://us.mitsubishi-chemical.com/company/performance-polymers/ Mitsubishi Chemical Performance Polymers] || compostable bio-based product
 +
|-
 +
| sucrose ester of fatty acids || SEFA SP10 || [https://www.sisterna.com/ Sisterna] || food and cosmetics additive
 +
|-
 +
| sucrose ester of fatty acids || SEFA SP70 || [https://www.sisterna.com/ Sisterna] || food and cosmetics additive
 +
|}
  
−
Since investigators are commonly interested in many chemicals at the same time, it is impractical to have a PRC for each contaminant of interest.  Instead, a representative set of PRCs is used to characterize the rates of polymer-environment exchange as a function of the PRCs' properties (e.g., diffusivities, partition coefficients), the sediments characteristics (e.g., porosity), and the nature of the polymer used (e.g., film thickness, affinity for the chemicals)<ref name="Fernandez2009b"/><ref name="Lampert2015"/>. The resulting mass transfer model fit can then be used to estimate the fractional approaches to equilibrium for many other contaminants, whose diffusive and partitioning properties are also known.  And these fractions can be used to adjust the target chemical concentrations that have accumulated from the sediment into the same polymeric sampler to find the equilibrated results<ref name="Apell2014"/>.  Finally, these equilibrated concentrations can be used in Eq. 2 to estimate truly dissolved contaminant concentrations in the sediment's porewater.
+
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.
  
−
==Field Applications==
+
[[File: FullerFig3.png | thumb | 400 px | Figure 3. Schematic of interactions between biochar and munitions constituents]]
−
[[File: Gschwend1w2fig3.png | thumb |left| 450px | Figure 3. Passive sampler system made of polyethylene sheet loaded into an aluminum sheet metal frame, before (left), during (middle), and after (right) deployment in sediment.]]
+
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&nbsp;of&nbsp;the&nbsp;mixture&nbsp;of&nbsp;energetics.
−
Polymeric materials can be deployed in sediment in various ways<ref name="Burgess2017"/>. PDMS coatings can be incorporated into slotted silica rods called SPMEs (solid phase micro extraction devices), while thin sheets of polymers like LDPE or POM can be incorporated into sheet metal frames. In both cases, such hardware is used to insert the polymers into sediment beds (Figure 3).
 
  
−
Deployment of the assembled passive samplers can be accomplished via poles from a boat<ref name="Apell2014"/>, by divers<ref name="Apell2016"/>, or by attaching the samplers to a sampling platform lowered off a vessel<ref name="Fernandez2012">Fernandez, L.A., Lao, W., Maruya, K.A., White, C., Burgess, R.M., 2012. Passive Sampling to Measure Baseline Dissolved Persistent Organic Pollutant Concentrations in the Water Column of the Palos Verdes Shelf Superfund Site. Environmental Science and Technology, 46(21), pp. 11937-11947.  [https://doi.org/10.1021/es302139y DOI: 10.1021/es302139y]</ref>. Typically, the method used depends on the water depth.  Small buoys on short lines, sometimes with associated water-sampling polymeric materials in mesh bags (see right panel of Figure 3), are attached to the samplers to facilitate the sampler recoveries.  After recovery, the samplers are wiped to remove any adhering sediment, biofilm, or precipitates and returned to the laboratory for PRC and target contaminant analyses. The resulting measurements of the accumulated target chemical concentrations can be adjusted using the observed PRC losses and publicly available software programs<ref name="Gschwend2014">Gschwend, P.M., Tcaciuc, A.P., and Apell, J.N., 2014. Guidance Document: Passive PE Sampling in Support of In Situ Remediation of Contaminated Sediments – Passive Sampler PRC Calculation Software User’s Guide, US Department of Defense, Environmental Security Technology Certification Program Project ER-200915. Available from: [https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/Contaminated-Sediments/Bioavailability/ER-200915 ESTCP].</ref><ref name="Thompson2015">Thompson, J.M., Hsieh, C.H. and Luthy, R.G., 2015. Modeling Uptake of Hydrophobic Organic Contaminants into Polyethylene Passive Samplers. Environmental Science and Technology, 49(4), pp. 2270-2277. [https://doi.org/10.1021/es504442s DOI: 10.1021/es504442s]</ref>.
+
===Biochar===
 +
[[File: FullerFig4.png | thumb | left | 500 px | Figure 4. Composition of the columns during the sorption-biodegradation experiments]]
 +
[[File: FullerFig5.png | thumb | 500 px | Figure 5. Representative breakthrough curves of energetics during the second replication of the column sorption-biodegradation experiment]]
 +
The&nbsp;ability&nbsp;of&nbsp;biochar&nbsp;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>.
  
−
Subsequently, since the passive sampling reveals the concentrations of contaminants in a sediment bed's porewater and the overlying bottom water<ref name="Booij2003"/>, the data can be used to estimate bed-to-water column diffusive fluxes of contaminants<ref name="Koelmans2010">Koelmans, A.A., Poot, A., De Lange, H.J., Velzeboer, I., Harmsen, J., and van Noort, P.C.M., 2010. Estimation of In Situ Sediment-to-Water Fluxes of Polycyclic Aromatic Hydrocarbons, Polychlorobiphenyls and Polybrominated Diphenylethers. Environmental Science and Technology, 44(8), pp. 3014-3020.  [https://doi.org/10.1021/es903938z DOI: 10.1021/es903938z]</ref><ref name="Fernandez2012"/> and bioirrigation-affected fluxes<ref name="Apell2018">Apell, J.N., Shull, D.H., Hoyt, A.M., and Gschwend, P.M., 2018. Investigating the Effect of Bioirrigation on In Situ Porewater Concentrations and Fluxes of Polychlorinated Biphenyls Using Passive Samplers.  Environmental Science and Technology, 52(8), pp. 4565-4573.  [https://doi.org/10.1021/acs.est.7b05809 DOI: 10.1021/acs.est.7b05809]</ref>. The data are also useful for assessing the tendency of the contaminants to accumulate in benthic organisms<ref name="Vinturella2004">Vinturella, A.E., Burgess, R.M., Coull, B.A., Thompson, K.M., and Shine, J.P., 2004. Use of Passive Samplers to Mimic Uptake of Polycyclic Aromatic Hydrocarbons by Benthic Polychaetes. Environmental Science and Technology, 38(4), pp. 1154-1160.  [https://doi.org/10.1021/es034706f DOI: 10.1021/es034706f]</ref><ref name="Yates2011">Yates, K., Pollard, P., Davies, I.M., Webster, L., and Moffat, C.F., 2011. Application of silicone rubber passive samplers to investigate the bioaccumulation of PAHs by Nereis virens from marine sediments. Environmental Pollution, 159(12), pp. 3351-3356.  [https://doi.org/10.1016/j.envpol.2011.08.038 DOI: 10.1016/j.envpol.2011.08.038]</ref><ref name="Fernandez2015">Fernandez, L.A. and Gschwend, P.M., 2015.  Predicting bioaccumulation of polycyclic aromatic hydrocarbons in soft-shelled clams  (Mya arenaria) using field deployments of polyethylene passive samplers.  Environmental Toxicology and Chemistry, 34(5), pp. 993-1000.  [https://doi.org/10.1002/etc.2892 DOI: 10.1002/etc.2892]</ref>, and by extension into food webs that include such benthic species<ref name="vonStackelberg2017">von Stackelberg, K., Williams, M.A., Clough, J., and Johnson, M.S., 2017. Spatially explicit bioaccumulation modeling in aquatic environments: Results from 2 demonstration sites. Integrated Environmental Assessment and Management, 13(6), pp. 1023-1037.  [https://doi.org/10.1002/ieam.1927 DOI: 10.1002/ieam.1927]</ref>. Furthermore, recent efforts have found that passive sampling observations can be used to infer ''in situ'' transformations of substances like nitro aromatic compounds<ref name="Belles2016">Belles, A., Alary, C., Criquet, J., and Billon, G., 2016. A new application of passive samplers as indicators of in-situ biodegradation processes. Chemosphere, 164, pp. 347-354.  [https://doi.org/10.1016/j.chemosphere.2016.08.111 DOI: 10.1016/j.chemosphere.2016.08.111]</ref> and DDT<ref name="Tcaciuc2018">Tcaciuc, A.P., Borrelli, R., Zaninetta, L.M., and Gschwend, P.M., 2018. Passive sampling of DDT, DDE and DDD in sediments: accounting for degradation processes with reaction–diffusion modeling. Environmental Science: Processes and Impacts, 20(1), pp. 220-231.  [https://doi.org/10.1039/C7EM00501F DOI: 10.1039/C7EM00501F]&nbsp;&nbsp; Open access article available from: [https://pubs.rsc.org/--/content/articlehtml/2018/em/c7em00501f Royal Society of Chemistry].</ref>.
+
===Sorption-Biodegradation Column Experiments===
 +
The&nbsp;selected&nbsp;materials&nbsp;and&nbsp;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&nbsp;removal&nbsp;of&nbsp;other&nbsp;energetics&nbsp;tested.
  
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<br clear="left" />
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===Trap and Treat Technology===
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[[File: FullerFig6.png | thumb | left | 400 px | Figure 6. Energetic mass removal relative to the sorption only removal during the column sorption-biodegradation experiments.  Dashed line given for reference to C1 removal = 1.]]
 +
These&nbsp;results&nbsp;provide&nbsp;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.
  
 
==References==
 
==References==
 
<references />
 
<references />
 +
 
==See Also==
 
==See Also==
−
 
+
*[https://serdp-estcp.mil/projects/details/10760fd6-fb55-4515-a629-f93c555a92f0/er-1689-project-overview Fate and Transport of Colloidal Energetic Residues, SERDP Project ER-1689]
−
[https://www.serdp-estcp.org/Tools-and-Training/Tools/PRC-Correction-Calculator A PRC Correction Calculator for LDPE deployed in sediments]
+
*[https://serdp-estcp.mil/projects/details/20e2f05c-fd50-4fd3-8451-ba73300c7531/er-200434-project-overview In Place Soil Treatments for Prevention of Explosives Contamination, ESTCP Project ER-200434]

Latest revision as of 14:03, 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.

Figure 3. Schematic of interactions between biochar and munitions constituents

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 4. Composition of the columns during the sorption-biodegradation experiments
Figure 5. Representative breakthrough curves of energetics during the second replication of the column sorption-biodegradation experiment

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

Figure 6. Energetic mass removal relative to the sorption only removal during the column sorption-biodegradation experiments. Dashed line given for reference to C1 removal = 1.

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.

References

  1. ^ 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. doi: 10.1016/S0273-1223(99)00023-2
  2. ^ 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. doi: 10.1016/j.jhydrol.2005.05.021
  3. ^ 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. doi: 10.1016/j.watres.2015.10.019
  4. ^ 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. doi: 10.2166/wst.2006.617
  5. ^ 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. doi: 10.1016/j.chemosphere.2023.141023
  6. ^ 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. doi: 10.1016/j.chemosphere.2022.136866  Open Access Article
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