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Geophysical methods can be used for cost-effective site characterization and monitoring by observing variations in the electrical, magnetic, and seismic properties of subsurface materials. Common data collection approaches include borehole, surface, and cross borehole geophysics. Analysis of surface and cross borehole geophysical data produces images or spatially distributed models of subsurface properties. There are also common approaches for identifying the most appropriate geophysical methods and their limitations depending on project goals.  
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The heterogeneous distribution of munitions constituents, released as particles from munitions firing and detonations on military training ranges, presents challenges for representative soil sample collection and for defensible decision making. Military range characterization studies and the development of the incremental sampling methodology (ISM) have enabled the development of recommended methods for soil sampling that produce representative and reproducible concentration data for munitions constituents. This article provides a broad overview of recommended soil sampling and processing practices for analysis of munitions constituents on military ranges.  
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<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
  
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
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'''Related Article(s)''':  
  
'''Related Article(s)''':
 
*[[Geophysical Methods – Case Studies]]
 
  
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'''CONTRIBUTOR(S):'''  [[Dr. Samuel Beal]]
  
'''CONTRIBUTOR(S):''' [[Dr. Lee Slater]]
 
  
 
'''Key Resource(s)''':  
 
'''Key Resource(s)''':  
*[https://doi.org/10.1007/1-4020-3102-5 Hydrogeophysics]<ref>Rubin, Y. and Hubbard, S.S. eds., 2006. Hydrogeophysics (Vol. 50). Springer Science & Business Media. [https://doi.org/10.1007/1-4020-3102-5 doi: 10.1007/1-4020-3102-5]</ref>
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*[[media:Taylor-2011 ERDC-CRREL TR-11-15.pdf| Guidance for Soil Sampling of Energetics and Metals]]<ref name= "Taylor2011">Taylor, S., Jenkins, T.F., Bigl, S., Hewitt, A.D., Walsh, M.E. and Walsh, M.R., 2011. Guidance for Soil Sampling for Energetics and Metals (No. ERDC/CRREL-TR-11-15). [[media:Taylor-2011 ERDC-CRREL TR-11-15.pdf| Report.pdf]]</ref>
*[https://doi.org/10.1007/978-1-4020-4912-5 Applied Hydrogeophysics]<ref>Vereecken, H., Binley, A., Cassiani, G., Revil, A. and K. Titov, eds. Applied Hydrogeophysics. Springer Netherlands. [https://doi.org/10.1007/978-1-4020-4912-5 doi: 10.1007/978-1-4020-4912-5]</ref>
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*[[Media:Hewitt-2009 ERDC-CRREL TR-09-6.pdf| Report.pdf | Validation of Sampling Protocol and the Promulgation of Method Modifications for the Characterization of Energetic Residues on Military Testing and Training Ranges]]<ref name= "Hewitt2009">Hewitt, A.D., Jenkins, T.F., Walsh, M.E., Bigl, S.R. and Brochu, S., 2009. Validation of sampling protocol and the promulgation of method modifications for the characterization of energetic residues on military testing and training ranges (No. ERDC/CRREL-TR-09-6). Engineer Research and Development Center / Cold Regions Research and Engineering Lab (ERDC/CRREL) TR-09-6, Hanover, NH, USA. [[Media:Hewitt-2009 ERDC-CRREL TR-09-6.pdf | Report.pdf]]</ref>
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*[[media:Epa-2006-method-8330b.pdf| U.S. EPA SW-846 Method 8330B: Nitroaromatics, Nitramines, and Nitrate Esters by High Performance Liquid Chromatography (HPLC)]]<ref name= "USEPA2006M">U.S. Environmental Protection Agency (USEPA), 2006. Method 8330B (SW-846): Nitroaromatics, Nitramines, and Nitrate Esters by High Performance Liquid Chromatography (HPLC), Rev. 2. Washington, D.C. [[media:Epa-2006-method-8330b.pdf | Report.pdf]]</ref>
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*[[media:Epa-2007-method-8095.pdf | U.S. EPA SW-846 Method 8095: Explosives by Gas Chromatography.]]<ref name= "USEPA2007M">U.S. Environmental Protection Agency (US EPA), 2007. Method 8095 (SW-846): Explosives by Gas Chromatography. Washington, D.C. [[media:Epa-2007-method-8095.pdf| Report.pdf]]</ref>
  
 
==Introduction==
 
==Introduction==
Here we overview geophysical techniques commonly used by site remediation professionals including near surface geophysical properties, and how these properties relate to contamination and remediation, geophysical survey methods and data analysis, hydrogeophysical characterization of contaminated sites, and geophysical methods for monitoring remediation.
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[[File:Beal1w2 Fig1.png|thumb|200 px|left|Figure 1: Downrange distance of visible propellant plume on snow from the firing of different munitions. Note deposition behind firing line for the 84-mm rocket. Data from: Walsh et al.<ref>Walsh, M.R., Walsh, M.E., Ampleman, G., Thiboutot, S., Brochu, S. and Jenkins, T.F., 2012. Munitions propellants residue deposition rates on military training ranges. Propellants, Explosives, Pyrotechnics, 37(4), pp.393-406. [http://dx.doi.org/10.1002/prep.201100105 doi: 10.1002/prep.201100105]</ref><ref>Walsh, M.R., Walsh, M.E., Hewitt, A.D., Collins, C.M., Bigl, S.R., Gagnon, K., Ampleman, G., Thiboutot, S., Poulin, I. and Brochu, S., 2010. Characterization and Fate of Gun and Rocket Propellant Residues on Testing and Training Ranges: Interim Report 2. (ERDC/CRREL TR-10-13.  Also: ESTCP Project ER-1481)  [[media:Walsh-2010 ERDC-CRREL TR-11-15 ESTCP ER-1481.pdf| Report]]</ref>]]
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[[File:Beal1w2 Fig2.png|thumb|left|200 px|Figure 2: A low-order detonation mortar round (top) with surrounding discrete soil samples produced concentrations spanning six orders of magnitude within a 10m by 10m area (bottom). (Photo and data: A.D. Hewitt)]]
  
Many geophysical properties of near surface geologic materials are controlled by the intrinsic properties of the solid, liquid, and gaseous phases and their geometric arrangement. Contamination and remediation of these materials alter the chemical composition of the pore-filling fluids and can change their electrical, electromagnetic, and seismic properties. The low-frequency electrical properties are primarily determined by electrolytic conduction occurring through pores and ionic conduction in the electrical double-layer (EDL) that forms at the grain-fluid interface. The minerals themselves (excluding metallic minerals) are poor conductors and therefore considered insulators. High frequency electrical properties are also strongly controlled by the presence of water and the geometric arrangement of the solid, liquid and gas phases. Similarly, the strong difference in seismic velocities between the pore-filling fluids and the mineral matrix control the seismic properties. Consequently, geophysical properties are often related to porosity, pore connectivity, permeability, water content, and the physicochemical properties of the fluids themselves. Measuring variations in geophysical properties can provide valuable information required to understand the fate of contaminants in the subsurface and its architecture.
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Munitions constituents are released on military testing and training ranges through several common mechanisms. Some are locally dispersed as solid particles from incomplete combustion during firing and detonation. Also, small residual particles containing propellant compounds (e.g., [[Wikipedia: Nitroglycerin | nitroglycerin [NG]]] and [[Wikipedia: 2,4-Dinitrotoluene | 2,4-dinitrotoluene [2,4-DNT]]]) are distributed in front of and surrounding target practice firing lines (Figure 1). At impact areas and demolition areas, high order detonations typically yield very small amounts (<1 to 10 mg/round) of residual high explosive compounds (e.g., [[Wikipedia: TNT | TNT ]], [[Wikipedia: RDX | RDX ]] and [[Wikipedia: HMX | HMX ]]) that are distributed up to and sometimes greater than) 24 m from the site of detonation<ref name= "Walsh2017">Walsh, M.R., Temple, T., Bigl, M.F., Tshabalala, S.F., Mai, N. and Ladyman, M., 2017. Investigation of Energetic Particle Distribution from High‐Order Detonations of Munitions. Propellants, Explosives, Pyrotechnics, 42(8), pp.932-941. [https://doi.org/10.1002/prep.201700089 doi: 10.1002/prep.201700089] [[media: Walsh-2017-High-Order-Detonation-Residues-Particle-Distribution-PEP.pdf| Report.pdf]]</ref>.
 
 
The magnetic properties of the near surface Earth are also relevant to contamination assessment. Magnetic properties of the near surface are affected by erosion and deposition, along with multiple biogeochemical processes controlling iron cycling. Contaminant transformations associated with active or natural attenuation can modify magnetic properties through the formation or dissolution of iron minerals<ref>Atekwana, E.A. and Slater, L.D., 2009. Biogeophysics: A new frontier in earth science research. Reviews of Geophysics, 47(4). [https://doi.org/10.1029/2009rg000285 doi: 10.1029/2009RG000285]</ref><ref>Atekwana, E.A., Mewafy, F.M., Abdel Aal, G., Werkema, D.D., Revil, A. and Slater, L.D., 2014. High‐resolution magnetic susceptibility measurements for investigating magnetic mineral formation during microbial mediated iron reduction. Journal of Geophysical Research: Biogeosciences, 119(1), pp.80-94. [https://doi.org/10.1002/2013jg002414 doi: 10.1002/2013JG002414]</ref>.
 
  
Common methods of acquiring geophysical data include borehole logging, surface-based, and cross-borehole methods. Borehole logging often provides the highest resolution information on materials immediately adjoining the borehole. Surface-based approaches can provide information for much larger aquifer volumes, but this information tends to be lower resolution than from borehole logging. Cross-borehole methods provide intermediate resolution and coverage compared to borehole and surface-based methods.  
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Low-order detonations and duds are thought to be the primary source of munitions constituents on ranges<ref>Hewitt, A.D., Jenkins, T.F., Walsh, M.E., Walsh, M.R. and Taylor, S., 2005. RDX and TNT residues from live-fire and blow-in-place detonations. Chemosphere, 61(6), pp.888-894. [https://doi.org/10.1016/j.chemosphere.2005.04.058 doi: 10.1016/j.chemosphere.2005.04.058]</ref><ref>Walsh, M.R., Walsh, M.E., Poulin, I., Taylor, S. and Douglas, T.A., 2011. Energetic residues from the detonation of common US ordnance. International Journal of Energetic Materials and Chemical Propulsion, 10(2). [https://doi.org/10.1615/intjenergeticmaterialschemprop.2012004956 doi: 10.1615/IntJEnergeticMaterialsChemProp.2012004956] [[media:Walsh-2011-Energetic-Residues-Common-US-Ordnance.pdf| Report.pdf]]</ref>. Duds are initially intact but may become perforated or fragmented into micrometer to centimeter;o0i0k-sized particles by nearby detonations<ref>Walsh, M.R., Thiboutot, S., Walsh, M.E., Ampleman, G., Martel, R., Poulin, I. and Taylor, S., 2011. Characterization and fate of gun and rocket propellant residues on testing and training ranges (No. ERDC/CRREL-TR-11-13). Engineer Research and Development Center / Cold Regions Research and Engineering Lab (ERDC/CRREL) TR-11-13, Hanover, NH, USA. [[media:Epa-2006-method-8330b.pdf| Report.pdf]]</ref>. Low-order detonations can scatter micrometer to centimeter-sized particles up to 20 m from the site of detonation<ref name= "Taylor2004">Taylor, S., Hewitt, A., Lever, J., Hayes, C., Perovich, L., Thorne, P. and Daghlian, C., 2004. TNT particle size distributions from detonated 155-mm howitzer rounds. Chemosphere, 55(3), pp.357-367.[[media:Taylor-2004 TNT PSDs.pdf| Report.pdf]]</ref>
  
==Borehole Logging==
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The particulate nature of munitions constituents in the environment presents a distinct challenge to representative soil sampling. Figure 2 shows an array of discrete soil samples collected around the site of a low-order detonation – resultant soil concentrations vary by orders of magnitude within centimeters of each other. The inadequacy of discrete sampling is apparent in characterization studies from actual ranges which show wide-ranging concentrations and poor precision (Table 1).
Borehole logging tools have been available for decades and are routinely used at remediation sites. Collection and interpretation of borehole geophysical data is usually straightforward. A logging tool is lowered into a borehole and sensors record vertical variations in geophysical properties for a localized, rock mass volume just beyond the borehole wall. Most geophysical logs provide a direct measure of a geophysical property without the need for complex data interpretation. We list common borehole-logging tools used at contaminated sites in Table 1.
 
  
Processing most geophysical logs is limited to generating vertical profiles of geophysical properties, and then qualitative interpretation of the vertical variations of the physical properties in terms of hydrogeological units or variations in groundwater composition. Borehole logging equipment is physically manageable (Fig. 1a,b). Geophysical logs often show variations in parameters as a function of depth. For example, Figure 1c shows vertical variations in the formation electrical conductivity, the specific conductance of the fluids filling the interconnected pore spaces, the vugosity of the borehole determined from a caliper log, and acoustic televiewer imaging of the borehole wall<ref name="Johnson2002">Johnson, C.D., Haeni, F.P., Lane, J.W. and White, E.A., 2002. Borehole-geophysical investigation of the University of Connecticut landfill, Storrs, Connecticut: US Geological Survey. Water Resources Investigations Report, pp.01-4033. [http://www.environmentalrestoration.wiki/images/2/2a/Johnson-2002-Borehole-Geophysical_Investigation.pdf Report pdf]</ref>. By jointly interpreting such data, one can infer fracture locations, geologic contacts, and transmissive intervals of the borehole. The interpretation of such well-established logs is relatively straightforward. However, the interpretation of temperature<ref>Koch, F.W., Voytek, E.B., Day‐Lewis, F.D., Healy, R., Briggs, M.A., Lane, J.W. and Werkema, D., 2015. 1DTempPro V2: New Features for Inferring Groundwater/Surface‐Water Exchange. Groundwater. [https://doi.org/10.1111/gwat.12369 doi: 10.1111/gwat.12369]</ref>, flow meter ''' (e.g., Day-Lewis et al., 2011)''' and cross-hole flow meter<ref>Roubinet, D., Irving, J. and Day-Lewis, F.D., 2015. Development of a new semi-analytical model for cross-borehole flow experiments in fractured media. Advances in Water Resources, 76, pp.97-108. [https://doi.org/10.1016/j.advwatres.2014.12.002 doi: 10.1016/j.advwatres.2014.12.002]</ref> logging can be substantially more complicated.
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In comparison to discrete sampling, incremental sampling tends to yield reproducible concentrations (low relative standard deviation [RSD]) that statistically better represent an area of interest<ref name= "Hewitt2009"/>.
[[File:Slater Intro Table1.jpg|400px|thumbnail|left|Table 1. Details of borehole geophysical logging methods commonly used at remediation sites. The lateral depth of penetration into the formation and resolution of the measurement are approximate ranges for site investigation. The measured parameters can be derived directly from the acquired data. The recovered properties are obtained through processing and/or inversion of the acquired data.]]
 
[[File:Slater Intro Fig1.jpg|350px|thumbnail|center|Figure 1. Example borehole logging equipment and log panel from the U. Connecticut Landfill in which major fractures appear in multiple logs for well MW105R at ~110 ft, 90 ft, and 75 ft depths (after Johnson et al., 2002)<ref name="Johnson2002"/>. (a) Borehole tool outside of the hole, (b) tool deployment, and (c) panel of logs including natural gamma, electromagnetic induction (formation [or FM] conductivity), fluid specific conductance and temperature, mechanical and acoustic caliper, and acoustic and optical televiewer (ATV and OTV).]]
 
  
==Surface-Based Methods==
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{| class="wikitable" style="float: right; text-align: center; margin-left: auto; margin-right: auto;"
Surface-based geophysical imaging is fundamentally different from borehole logging because spatial variations in subsurface physical properties are reconstructed from measurements acquired using sensors placed on the surface of the Earth (Fig. 2). In borehole logging, the source and sensor are physically moved deeper into the Earth to directly sense vertical variations in physical properties. In surface imaging, sensors (e.g. electrodes in resistivity surveys, geophones in seismic surveys) are distributed across the surface either in a line (a 2D survey) or on a grid (a 3D survey). Table 2 summarizes the surface-based geophysical methods commonly used at contaminated sites.
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|+ Table 1. Soil Sample Concentrations and Precision from Military Ranges Using Discrete and Incremental Sampling. (Data from Taylor et al. <ref name= "Taylor2011"/> and references therein.)
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|-
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! Military Range Type !! Analyte !! Range<br/>(mg/kg) !! Median<br/>(mg/kg) !! RSD<br/>(%)
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|-
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| colspan="5" style="text-align: left;" | '''Discrete Samples'''
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|-
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| Artillery FP || 2,4-DNT || <0.04 – 6.4 || 0.65 || 110
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|-
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| Antitank Rocket || HMX || 5.8 – 1,200 || 200 || 99
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|-
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| Bombing || TNT || 0.15 – 780 || 6.4 || 274
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|-
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| Mortar || RDX || <0.04 – 2,400 || 1.7 || 441
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|-
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| Artillery || RDX || <0.04 – 170 || <0.04 || 454
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|-
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| colspan="5" style="text-align: left;" | '''Incremental Samples*'''
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|-
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| Artillery FP || 2,4-DNT || 0.60 – 1.4 || 0.92 || 26
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|-
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| Bombing || TNT || 13 – 17 || 14 || 17
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|-
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| Artillery/Bombing || RDX || 3.9 – 9.4 || 4.8 || 38
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|-
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| Thermal Treatment || HMX || 3.96 – 4.26 || 4.16 || 4
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|-
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| colspan="5" style="text-align: left; background-color: white;" | * For incremental samples, 30-100 increments and 3-10 replicate samples were collected.
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|}
  
Parameter estimation or ‘inverse’ methods (described below) are needed to reconstruct lateral and vertical variations in geophysical properties from the sensor observations. The spatial resolution and depth of investigation is controlled by (1) the position and number of sensors, (2) the number and configuration of measurements acquired, (3) the size of the sources and resulting energy produced/data quality, and (4) the unknown distribution of the geophysical properties. The resolution of all surface-based geophysical imaging decreases with distance from the sensors (i.e. depth).  
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==Incremental Sampling Approach==
[[File:Slater Intro Fig2.jpg|600px|thumbnail|center|Figure 2. Example of a surface-based geophysical method. (a) Schematic diagram of an electromagnetic induction tool in operation, which comprises a transmitter (Tx) and receiver (Rx) to respectively produce a primary electromagnetic field and measure a secondary electromagnetic field affected by the Earth’s electrical structure. (b) Photograph showing a multi-frequency electromagnetic induction tool in operation at a remediation site in Brandywine, MD.]]
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ISM is a requisite for representative and reproducible sampling of training ranges, but it is an involved process that is detailed thoroughly elsewhere<ref name= "Hewitt2009"/><ref name= "Taylor2011"/><ref name= "USEPA2006M"/>. In short, ISM involves the collection of many (30 to >100) increments in a systematic pattern within a decision unit (DU). The DU may cover an area where releases are thought to have occurred or may represent an area relevant to ecological receptors (e.g., sensitive species). Figure 3 shows the ISM sampling pattern in a simplified (5x5 square) DU. Increments are collected at a random starting point with systematic distances between increments. Replicate samples can be collected by starting at a different random starting point, often at a different corner of the DU. Practically, this grid pattern can often be followed with flagging or lathe marking DU boundaries and/or sampling lanes and with individual pacing keeping systematic distances between increments. As an example, an artillery firing point might include a 100x100 m DU with 81 increments.
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[[File:Beal1w2 Fig3.png|thumb|200 px|left|Figure 3. Example ISM sampling pattern on a square decision unit. Replicates are collected in a systematic pattern from a random starting point at a corner of the DU. Typically more than the 25 increments shown are collected]]
  
A site remediation professional should tread cautiously when engaging a geophysical contractor for surface geophysical imaging services. Collection and analysis of surface geophysical data is a complicated task involving numerous decisions about survey design. We tabulate recommendations for assessing the appropriateness of different geophysical approaches for different potential targets (Table 2).
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DUs can vary in shape (Figure 4), size, number of increments, and number of replicates according to a project’s data quality objectives.
[[File:Slater Intro Table2.jpg|400px|thumbnail|center|Table 2. Surface-based geophysical methods commonly used at remediation sites. The extent and depth of the survey region and the resolution are all approximate ranges. The measured parameters can be derived directly from the acquired data. The recovered properties are obtained through processing and/or inversion of the acquired data.]]
 
  
==Cross-borehole Methods==
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[[File:Beal1w2 Fig4.png|thumb|right|250 px|Figure 4: Incremental sampling of a circular DU on snow shows sampling lanes with a two-person team in process of collecting the second replicate in a perpendicular path to the first replicate. (Photo: Matthew Bigl)]]
Cross-borehole imaging methods are potentially very powerful, but remain a specialty application in site remediation. Cross-borehole imaging is an extension of surface imaging where sensors are placed in a limited number of boreholes in order to perform high resolution (relative to surface imaging) imaging of the Earth between the boreholes (Fig. 3). By placing sensors in boreholes, resolution does not decrease with depth from the Earth surface compared to surface-based approaches. Instead, resolution decreases towards the inter-borehole region away from the sensors. Consequently, cross-borehole imaging becomes ineffective (due to resolution limitations) when the boreholes containing the sensors are too far apart. A general rule of thumb in cross-borehole imaging is that the ratio of the vertical borehole distance containing sensors to the borehole separation should be no less than 1.5. Once again, the information content (spatial resolution, depth of investigation) in the measurements at the sensors is controlled by (1) the position and number of sensors, (2) the number and configuration of measurements acquired, (3) the size of the sources and resulting energy produced/data quality, and (4) the unknown distribution of the geophysical properties themselves. There are several common cross-borehole methods that are used at contaminated sites (Table 3).
 
[[File:Slater Intro Fig3.jpg|thumbnail|left|350px|Figure 3. Example cross-borehole method. (a) Schematic crosshole radar tomography, in which a transmitting antenna is moved vertically in one well, and a receiver antenna is moved vertically in another well. High-frequency electromagnetic waves are transmitted through the interwell region, and received travel times and amplitudes are inverse modeled to produce cross sections of electromagnetic properties. (b) Photograph of data collection at a remediation site in Brandywine, MD. (c) Two radar tomograms from a remediation site in Fridley, MN, where radar was used to monitor emplacement of a vegetable oil emulsion (VOE) amendment which produces a negative change in slowness (1/velocity) relative to background conditions (after Lane et al., 2006)<ref>Lane, J.W., Day‐Lewis, F.D. and Casey, C.C., 2006. Geophysical monitoring of a field‐scale biostimulation pilot project. Ground water, 44(3), pp.430-443. [https://doi.org/10.1111/j.1745-6584.2005.00134.x doi: 10.1111/j.1745-6584.2005.00134.x]</ref>.]]
 
[[File:Slater Intro Table3.jpg|400px|thumbnail|center|Table 3. Details of four single-hole and crosshole geophysical imaging methods with potential application to contaminated sites. The lateral extent and depth of the surveyed region, and resolution of the measurement, are all typical values for environmental site investigation. The measured parameters can be derived directly from the acquired data. The recovered properties are obtained through processing and/or inversion of the acquired data.]]
 
Relative to surface imaging, cross-borehole imaging requires additional expertize to perform worthwhile surveys. Parameter estimation or ‘inverse’ methods (described below), is used to reconstruct the variations in physical properties between boreholes that best satisfy the measurements are more specialized and less available. All imaging methods rely on the position of the sensors being precisely known. This is a straightforward requirement for surface imaging surveys where the sensors are visible. In contrast, cross-borehole imaging requires accurate borehole deviation logs to determine the assumed sensor positions. Errors in the location of the sensors will generate errors in the resulting images. The presence of the borehole itself complicates the estimation of the physical properties, as the fluid-filled borehole has physical properties that are different from the rock matrix. This can complicate image reconstruction and result in significant artifacts if the boreholes are not explicitly incorporated in the modeling. In summary, only highly skilled geophysical service contractors with experience performing cross-borehole geophysical imaging should be contracted by a site remediation professional.
 
  
==Analysis and Modeling of Surface and Cross Borehole Data==
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==Sampling Tools==
Surface and cross borehole geophysical imaging methods rely on geophysical data analysis to generate the images that provide estimates of subsurface structure away from the sensors. Two main computational methods are used in this processing are forward and inversion modeling (Fig. 4).  
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In many cases, energetic compounds are expected to reside within the soil surface. Figure 5 shows soil depth profiles on some studied impact areas and firing points. Overall, the energetic compound concentrations below 5-cm soil depth are negligible relative to overlying soil concentrations. For conventional munitions, this is to be expected as the energetic particles are relatively insoluble, and any dissolved compounds readily adsorb to most soils<ref>Pennington, J.C., Jenkins, T.F., Ampleman, G., Thiboutot, S., Brannon, J.M., Hewitt, A.D., Lewis, J., Brochu, S., 2006. Distribution and fate of energetics on DoD test and training ranges: Final Report. ERDC TR-06-13, Vicksburg, MS, USA. Also: SERDP/ESTCP Project ER-1155. [[media:Pennington-2006_ERDC-TR-06-13_ESTCP-ER-1155-FR.pdf| Report.pdf]]</ref>. Physical disturbance, as on hand grenade ranges, may require deeper sampling either with a soil profile or a corer/auger.
[[File:Slater Intro Fig4.PNG|400px|thumbnail|left|Figure 4. Schematic explanation of the concepts of (a) forward modeling and (b) inverse modeling.]]
 
  
===Forward Modeling===
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[[File:Beal1w2 Fig5.png|thumb|left|200 px|Figure 5. Depth profiles of high explosive compounds at impact areas (bottom) and of propellant compounds at firing points (top). Data from: Hewitt et al. <ref>Hewitt, A.D., Jenkins, T.F., Ramsey, C.A., Bjella, K.L., Ranney, T.A. and Perron, N.M., 2005. Estimating energetic residue loading on military artillery ranges: Large decision units (No. ERDC/CRREL-TR-05-7). [[media:Hewitt-2005 ERDC-CRREL TR-05-7.pdf| Report.pdf]]</ref> and Jenkins et al. <ref>Jenkins, T.F., Ampleman, G., Thiboutot, S., Bigl, S.R., Taylor, S., Walsh, M.R., Faucher, D., Mantel, R., Poulin, I., Dontsova, K.M. and Walsh, M.E., 2008. Characterization and fate of gun and rocket propellant residues on testing and training ranges (No. ERDC-TR-08-1). [[media:Jenkins-2008 ERDC TR-08-1.pdf| Report.pdf]]</ref>]]
Forward (or synthetic) modeling (Fig. 4a) can be used to evaluate whether specific geophysical measurements are worthwhile at a given site. In this approach, the approximate size and physical property contrast between the target and background are estimated and used to generate synthetic datasets that represent the data that might be acquired in the field. These synthetic datasets can be corrupted with noise to better represent true field data, and then inverted to examine whether the target is likely to be detected with the proposed geophysical method. While forward modeling can never prove a geophysical method will be effective at a site, it can identify situations where that method will not be effective. Forward modeling should always be done prior to expending the time and expense of surface or cross borehole survey.<br />
 
  
===Parameter Estimation or ‘Inverse’ Modeling===
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Soil sampling with the Cold Regions Research and Engineering Laboratory (CRREL) Multi-Increment Sampling Tool (CMIST) or similar device is an easy way to collect ISM samples rapidly and reproducibly. This tool has an adjustable diameter size corer and adjustable depth to collect surface soil plugs (Figure 6). The CMIST can be used at almost a walking pace (Figure 7) using a two-person sampling team, with one person operating the CMIST and the other carrying the sample container and recording the number of increments collected. The CMIST with a small diameter tip works best in soils with low cohesion, otherwise conventional scoops may be used. Maintaining consistent soil increment dimensions is critical.
Parameter estimation or ‘inverse’ modeling (Fig. 4b) is used to estimate the spatial distribution of geophysical properties based on measurements at individual points. The most common inverse methods use an iterative approach where a mathematical model attempts to minimize the difference between the field measurements and the theoretical predictions based on a forward model for a synthetic model. Iterative parameter updates continue until these differences are less than the convergence criteria. At this point, the estimated model is a plausible representation of the physical structure of the subsurface. Unfortunately, geophysical inverse problems are usually under-determined, meaning there are many more model parameters than sensor observations. In this case, several different images or representations of the subsurface can match the field observations equally well. Additional model constraints are often included to favor certain models or images over others to narrow down the plausible possibilities further.  
 
  
One of the most common constraints is called smooth inversion or smoothness constrained inversion because it produces models with smooth variations in physical properties. The result of a smoothness-constrained inversion is somewhat akin to looking at the earth with a very bad pair of glasses. The true structure appears ‘fuzzy’ and provides a low resolution glimpse into the structure of the earth (Fig. 4b)<ref>Day‐Lewis, F.D., Singha, K. and Binley, A.M., 2005. Applying petrophysical models to radar travel time and electrical resistivity tomograms: Resolution‐dependent limitations. Journal of Geophysical Research: Solid Earth, 110(B8). [https://doi.org/10.1029/2004jb003569 doi:10.1029/2004JB003569]</ref>, which is a low-resolution approximation of the true subsurface structure (e.g., Fig. 4a). Site remediation professionals should be wary of high-resolution images with lots of structural detail. This structural detail may arise from an error in the inverse modeling. Reliable inverse modeling requires a trained user knowing how to correctly set up an inverse model and appropriately handle the data errors.
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The sampling tool should be cleaned between replicates and between DUs to minimize potential for cross-contamination<ref>Walsh, M.R., 2009. User’s manual for the CRREL Multi-Increment Sampling Tool. Engineer Research and Development Center / Cold Regions Research and Engineering Lab (ERDC/CRREL) SR-09-1, Hanover, NH, USA. [[media:Walsh-2009 ERDC-CRREL SR-09-1.pdf | Report.pdf]]</ref>.
  
===Interpreting Modeling Results Caveats===
+
==Sample Processing==
While some subsurface processes do result in a smooth transition (i.e. the diffuse edge of a contaminant plume), the interface between an aquifer and an aquitard may not be well represented by a smoothness constraint. Alternative model constraints can be included to honor such sharp contrasts. However, commercially available inverse codes often implement smooth regularization by default. Site remediation professionals should interpret smooth images with caution and question whether the smoothness constraint is likely to provide a meaningful image based on the site conceptual model. For example, fractured sedimentary rock aquifers are often characterized by very sharp physical property contrasts between fractured zones and native rock mass. The use of smoothness constraints for inversion of geophysical data from fractured rock aquifers may not be appropriate.
+
While only 10 g of soil is typically used for chemical analysis, incremental sampling generates a sample weighing on the order of 1 kg. Splitting of a sample, either in the field or laboratory, seems like an easy way to reduce sample mass; however this approach has been found to produce high uncertainty for explosives and propellants, with a median RSD of 43.1%<ref name= "Hewitt2009"/>. Even greater error is associated with removing a discrete sub-sample from an unground sample. Appendix A in [https://www.epa.gov/sites/production/files/2015-07/documents/epa-8330b.pdf U.S. EPA Method 8330B]<ref name= "USEPA2006M"/> provides details on recommended ISM sample processing procedures.
  
There are numerous caveats to the interpretation of subsurface structures based on geophysical images generated by inverse methods. Use of a 2D survey to characterize a 3D object can introduce errors and artifacts into the images generated by the inverse model. 3D surveys are now increasingly being implemented in environmental investigations, but demand a high level of expertise to execute and evaluate the results effectively.
+
Incremental soil samples are typically air dried over the course of a few days. Oven drying thermally degrades some energetic compounds and should be avoided<ref>Cragin, J.H., Leggett, D.C., Foley, B.T., and Schumacher, P.W., 1985. TNT, RDX and HMX explosives in soils and sediments: Analysis techniques and drying losses. (CRREL Report 85-15) Hanover, NH, USA. [[media:Cragin-1985 CRREL 85-15.pdf| Report.pdf]]</ref>. Once dry, the samples are sieved with a 2-mm screen, with only the less than 2-mm fraction processed further. This size fraction represents the USDA definition of soil. Aggregate soil particles should be broken up and vegetation shredded to pass through the sieve. Samples from impact or demolition areas may contain explosive particles from low order detonations that are greater than 2 mm and should be identified, given appropriate caution, and potentially weighed.
  
==How to Select the Right Geophysical Method?==
+
The <2-mm soil fraction is typically still ≥1 kg and impractical to extract in full for analysis. However, subsampling at this stage is not possible due to compositional heterogeneity, with the energetic compounds generally present as <0.5 mm particles<ref name= "Walsh2017"/><ref name= "Taylor2004"/>. Particle size reduction is required to achieve a representative and precise measure of the sample concentration. Grinding in a puck mill to a soil particle size <75 µm has been found to be required for representative/reproducible sub-sampling (Figure 8). For samples thought to contain propellant particles, a prolonged milling time is required to break down these polymerized particles and achieve acceptable precision (Figure 9). Due to the multi-use nature of some ranges, a 5-minute puck milling period can be used for all soils. Cooling periods between 1-minute milling intervals are recommended to avoid thermal degradation. Similar to field sampling, sub-sampling is done incrementally by spreading the sample out to a thin layer and collecting systematic random increments of consistent volume to a total mass for extraction of 10 g (Figure 10).
To site remediation professionals, geophysics may feel like voodoo. Drilling provides direct information on the subsurface, and ground water sampling allows direct measurement of fluid chemistry. The information acquired is relatively straightforward to interpret and very tangible. In contrast, geophysics offers the opportunity to look into the Earth and capture distributions in physical properties. However, the geophysical properties that are measured are not always directly related to the hydrologic and chemical parameters that are of actual interest for site management. In addition, the science behind geophysics is complex and site managers must rely on geophysical contractors to perform the measurements and data processing. Unfortunately, geophysics has been applied at some sites without a full understanding of the limitations of this approach.
 
  
Technology transfer tools are being developed to help site manages make informed decisions about geophysics. The Fractured Rock Geophysics Toolbox-Methods Selection Tool (FRGT-MST)<ref>Day-Lewis, F.D., Johnson, C.D., Slater, L.D., Robinson, J.L., Williams, J.H., Boyden, C.L., Werkema, D.D. and Lane, J.W., 2016. A fractured rock geophysical toolbox method selection tool. Groundwater, 54(3), pp.315-316. [https://doi.org/10.1111/gwat.12397 doi: 10.1111/gwat.12397]</ref> is a user-friendly Excel-based tool available from the U.S. Geological Survey ([http://water.usgs.gov/ogw/bgas/frgt/ FRGT-MST]) to help identify appropriate and effective geophysical methods for specific project goals and site conditions. This toolbox comprises 30 different geophysical methods divided into 4 categories: surface, cross-hole, borehole, and hydrologic. The user enters information in two tables (1) project and site parameters, including budget level; and (2) project goals. A third table is populated with indicators for whether each method could potentially support any of the specified goals, and whether each method is likely to work at the site described. The suite of potentially suitable methods is the intersection of the sets of appropriate and feasible methods.
+
<li style="display: inline-block;">[[File:Beal1w2 Fig6.png|thumb|200 px|Figure 6: CMIST soil sampling tool (top) and with ejected increment core using a large diameter tip (bottom).]]</li>
 +
<li style="display: inline-block;">[[File:Beal1w2 Fig7.png|thumb|200 px|Figure 7: Two person sampling team using CMIST, bag-lined bucket, and increment counter. (Photos: Matthew Bigl)]]</li>
 +
<li style="display: inline-block;">[[File:Beal1w2 Fig8.png|thumb|200 px|Figure 8: Effect of machine grinding on RDX and TNT concentration and precision in soil from a hand grenade range. Data from Walsh et al.<ref>Walsh, M.E., Ramsey, C.A. and Jenkins, T.F., 2002. The effect of particle size reduction by grinding on subsampling variance for explosives residues in soil. Chemosphere, 49(10), pp.1267-1273. [https://doi.org/10.1016/S0045-6535(02)00528-3 doi: 10.1016/S0045-6535(02)00528-3]</ref> ]]</li>
 +
<li style="display: inline-block;">[[File:Beal1w2 Fig9.png|thumb|200 px|Figure 9: Effect of puck milling time on 2,4-DNT concentration and precision in soil from a firing point. Data from Walsh et al.<ref>Walsh, M.E., Ramsey, C.A., Collins, C.M., Hewitt, A.D., Walsh, M.R., Bjella, K.L., Lambert, D.J. and Perron, N.M., 2005. Collection methods and laboratory processing of samples from Donnelly Training Area Firing Points, Alaska, 2003 (No. ERDC/CRREL-TR-05-6). [[media:Walsh-2005 ERDC-CRREL TR-05-6.pdf| Report.pdf]]</ref>.]]</li>
 +
<li style="display: inline-block;">[[File:Beal1w2 Fig10.png|thumb|200 px|center|Figure 10: Incremental sub-sampling of a milled soil sample spread out on aluminum foil.]]</li>
 +
 
 +
==Analysis==
 +
Soil sub-samples are extracted and analyzed following [[Media: epa-2006-method-8330b.pdf | EPA Method 8330B]]<ref name= "USEPA2006M"/> and [[Media:epa-2007-method-8095.pdf | Method 8095]]<ref name= "USEPA2007M"/> using [[Wikipedia: High-performance liquid chromatography | High Performance Liquid Chromatography (HPLC)]] and [[Wikipedia: Gas chromatography | Gas Chromatography (GC)]], respectively. Common estimated reporting limits for these analysis methods are listed in Table 2.
 +
 
 +
{| class="wikitable" style="float: center; text-align: center; margin-left: auto; margin-right: auto;"
 +
|+ Table 2. Typical Method Reporting Limits for Energetic Compounds in Soil. (Data from Hewitt et al.<ref>Hewitt, A., Bigl, S., Walsh, M., Brochu, S., Bjella, K. and Lambert, D., 2007. Processing of training range soils for the analysis of energetic compounds (No. ERDC/CRREL-TR-07-15). Hanover, NH, USA. [[media:Hewitt-2007 ERDC-CRREL TR-07-15.pdf| Report.pdf]]</ref>)
 +
|-
 +
! rowspan="2" | Compound
 +
! colspan="2" | Soil Reporting Limit (mg/kg)
 +
|-
 +
! HPLC (8330)
 +
! GC (8095)
 +
|-
 +
| HMX || 0.04 || 0.01
 +
|-
 +
| RDX || 0.04 || 0.006
 +
|-
 +
| [[Wikipedia: 1,3,5-Trinitrobenzene | TNB]] || 0.04 || 0.003
 +
|-
 +
| TNT || 0.04 || 0.002
 +
|-
 +
| [[Wikipedia: 2,6-Dinitrotoluene | 2,6-DNT]] || 0.08 || 0.002
 +
|-
 +
| 2,4-DNT || 0.04 || 0.002
 +
|-
 +
| 2-ADNT || 0.08 || 0.002
 +
|-
 +
| 4-ADNT || 0.08 || 0.002
 +
|-
 +
| NG || 0.1 || 0.01
 +
|-
 +
| [[Wikipedia: Dinitrobenzene | DNB ]] || 0.04 || 0.002
 +
|-
 +
| [[Wikipedia: Tetryl | Tetryl ]]  || 0.04 || 0.01
 +
|-
 +
| [[Wikipedia: Pentaerythritol tetranitrate | PETN ]] || 0.2 || 0.016
 +
|}
  
 
==References==
 
==References==
 
 
<references/>
 
<references/>
  
 
==See Also==
 
==See Also==
*[https://water.usgs.gov/ogw/bgas/  USGS Branch of Geophysics]
+
*[https://itrcweb.org/ Interstate Technology and Regulatory Council]
*[https://water.usgs.gov/ogw/bgas/frgt/ Fractured Rock Geophysical Toolbox Method Selection Tool]
+
*[http://www.hawaiidoh.org/tgm.aspx Hawaii Department of Health]
*[https://www.ncas.rutgers.edu/technology-transferTechnology Transfer]
+
*[http://envirostat.org/ Envirostat]
*[https://www.ncas.rutgers.edu/t2-geophysics-er-201567-t2 T2-Geophysics (ER-201567-T2)]
 
*[https://www.ncas.rutgers.edu/fractured-rock Fractured Rock Geophysics Toolbox for Characterization and Monitoring of DNAPL Biodegradation in Fractured Rock Aquifers]
 
*[https://clu-in.org/characterization/technologies/geophysics/pages/decisionSupport.htm EPA Environmental Geophysics Decision Support System]
 
*[https://clu-in.org/characterization/technologies/geophysics/ EPA Geophysic Notice]
 
*[https://youtu.be/HTukq9jDOzM USGS Fractured Rock Geophysical Toolbox Video]
 

Latest revision as of 18:58, 29 April 2020

The heterogeneous distribution of munitions constituents, released as particles from munitions firing and detonations on military training ranges, presents challenges for representative soil sample collection and for defensible decision making. Military range characterization studies and the development of the incremental sampling methodology (ISM) have enabled the development of recommended methods for soil sampling that produce representative and reproducible concentration data for munitions constituents. This article provides a broad overview of recommended soil sampling and processing practices for analysis of munitions constituents on military ranges.

Related Article(s):


CONTRIBUTOR(S): Dr. Samuel Beal


Key Resource(s):

Introduction

Figure 1: Downrange distance of visible propellant plume on snow from the firing of different munitions. Note deposition behind firing line for the 84-mm rocket. Data from: Walsh et al.[5][6]
Figure 2: A low-order detonation mortar round (top) with surrounding discrete soil samples produced concentrations spanning six orders of magnitude within a 10m by 10m area (bottom). (Photo and data: A.D. Hewitt)

Munitions constituents are released on military testing and training ranges through several common mechanisms. Some are locally dispersed as solid particles from incomplete combustion during firing and detonation. Also, small residual particles containing propellant compounds (e.g., nitroglycerin [NG] and 2,4-dinitrotoluene [2,4-DNT]) are distributed in front of and surrounding target practice firing lines (Figure 1). At impact areas and demolition areas, high order detonations typically yield very small amounts (<1 to 10 mg/round) of residual high explosive compounds (e.g., TNT , RDX and HMX ) that are distributed up to and sometimes greater than) 24 m from the site of detonation[7].

Low-order detonations and duds are thought to be the primary source of munitions constituents on ranges[8][9]. Duds are initially intact but may become perforated or fragmented into micrometer to centimeter;o0i0k-sized particles by nearby detonations[10]. Low-order detonations can scatter micrometer to centimeter-sized particles up to 20 m from the site of detonation[11]

The particulate nature of munitions constituents in the environment presents a distinct challenge to representative soil sampling. Figure 2 shows an array of discrete soil samples collected around the site of a low-order detonation – resultant soil concentrations vary by orders of magnitude within centimeters of each other. The inadequacy of discrete sampling is apparent in characterization studies from actual ranges which show wide-ranging concentrations and poor precision (Table 1).

In comparison to discrete sampling, incremental sampling tends to yield reproducible concentrations (low relative standard deviation [RSD]) that statistically better represent an area of interest[2].

Table 1. Soil Sample Concentrations and Precision from Military Ranges Using Discrete and Incremental Sampling. (Data from Taylor et al. [1] and references therein.)
Military Range Type Analyte Range
(mg/kg)
Median
(mg/kg)
RSD
(%)
Discrete Samples
Artillery FP 2,4-DNT <0.04 – 6.4 0.65 110
Antitank Rocket HMX 5.8 – 1,200 200 99
Bombing TNT 0.15 – 780 6.4 274
Mortar RDX <0.04 – 2,400 1.7 441
Artillery RDX <0.04 – 170 <0.04 454
Incremental Samples*
Artillery FP 2,4-DNT 0.60 – 1.4 0.92 26
Bombing TNT 13 – 17 14 17
Artillery/Bombing RDX 3.9 – 9.4 4.8 38
Thermal Treatment HMX 3.96 – 4.26 4.16 4
* For incremental samples, 30-100 increments and 3-10 replicate samples were collected.

Incremental Sampling Approach

ISM is a requisite for representative and reproducible sampling of training ranges, but it is an involved process that is detailed thoroughly elsewhere[2][1][3]. In short, ISM involves the collection of many (30 to >100) increments in a systematic pattern within a decision unit (DU). The DU may cover an area where releases are thought to have occurred or may represent an area relevant to ecological receptors (e.g., sensitive species). Figure 3 shows the ISM sampling pattern in a simplified (5x5 square) DU. Increments are collected at a random starting point with systematic distances between increments. Replicate samples can be collected by starting at a different random starting point, often at a different corner of the DU. Practically, this grid pattern can often be followed with flagging or lathe marking DU boundaries and/or sampling lanes and with individual pacing keeping systematic distances between increments. As an example, an artillery firing point might include a 100x100 m DU with 81 increments.

Figure 3. Example ISM sampling pattern on a square decision unit. Replicates are collected in a systematic pattern from a random starting point at a corner of the DU. Typically more than the 25 increments shown are collected

DUs can vary in shape (Figure 4), size, number of increments, and number of replicates according to a project’s data quality objectives.

Figure 4: Incremental sampling of a circular DU on snow shows sampling lanes with a two-person team in process of collecting the second replicate in a perpendicular path to the first replicate. (Photo: Matthew Bigl)

Sampling Tools

In many cases, energetic compounds are expected to reside within the soil surface. Figure 5 shows soil depth profiles on some studied impact areas and firing points. Overall, the energetic compound concentrations below 5-cm soil depth are negligible relative to overlying soil concentrations. For conventional munitions, this is to be expected as the energetic particles are relatively insoluble, and any dissolved compounds readily adsorb to most soils[12]. Physical disturbance, as on hand grenade ranges, may require deeper sampling either with a soil profile or a corer/auger.

Figure 5. Depth profiles of high explosive compounds at impact areas (bottom) and of propellant compounds at firing points (top). Data from: Hewitt et al. [13] and Jenkins et al. [14]

Soil sampling with the Cold Regions Research and Engineering Laboratory (CRREL) Multi-Increment Sampling Tool (CMIST) or similar device is an easy way to collect ISM samples rapidly and reproducibly. This tool has an adjustable diameter size corer and adjustable depth to collect surface soil plugs (Figure 6). The CMIST can be used at almost a walking pace (Figure 7) using a two-person sampling team, with one person operating the CMIST and the other carrying the sample container and recording the number of increments collected. The CMIST with a small diameter tip works best in soils with low cohesion, otherwise conventional scoops may be used. Maintaining consistent soil increment dimensions is critical.

The sampling tool should be cleaned between replicates and between DUs to minimize potential for cross-contamination[15].

Sample Processing

While only 10 g of soil is typically used for chemical analysis, incremental sampling generates a sample weighing on the order of 1 kg. Splitting of a sample, either in the field or laboratory, seems like an easy way to reduce sample mass; however this approach has been found to produce high uncertainty for explosives and propellants, with a median RSD of 43.1%[2]. Even greater error is associated with removing a discrete sub-sample from an unground sample. Appendix A in U.S. EPA Method 8330B[3] provides details on recommended ISM sample processing procedures.

Incremental soil samples are typically air dried over the course of a few days. Oven drying thermally degrades some energetic compounds and should be avoided[16]. Once dry, the samples are sieved with a 2-mm screen, with only the less than 2-mm fraction processed further. This size fraction represents the USDA definition of soil. Aggregate soil particles should be broken up and vegetation shredded to pass through the sieve. Samples from impact or demolition areas may contain explosive particles from low order detonations that are greater than 2 mm and should be identified, given appropriate caution, and potentially weighed.

The <2-mm soil fraction is typically still ≥1 kg and impractical to extract in full for analysis. However, subsampling at this stage is not possible due to compositional heterogeneity, with the energetic compounds generally present as <0.5 mm particles[7][11]. Particle size reduction is required to achieve a representative and precise measure of the sample concentration. Grinding in a puck mill to a soil particle size <75 µm has been found to be required for representative/reproducible sub-sampling (Figure 8). For samples thought to contain propellant particles, a prolonged milling time is required to break down these polymerized particles and achieve acceptable precision (Figure 9). Due to the multi-use nature of some ranges, a 5-minute puck milling period can be used for all soils. Cooling periods between 1-minute milling intervals are recommended to avoid thermal degradation. Similar to field sampling, sub-sampling is done incrementally by spreading the sample out to a thin layer and collecting systematic random increments of consistent volume to a total mass for extraction of 10 g (Figure 10).

  • Figure 6: CMIST soil sampling tool (top) and with ejected increment core using a large diameter tip (bottom).
  • Figure 7: Two person sampling team using CMIST, bag-lined bucket, and increment counter. (Photos: Matthew Bigl)
  • Figure 8: Effect of machine grinding on RDX and TNT concentration and precision in soil from a hand grenade range. Data from Walsh et al.[17]
  • Figure 9: Effect of puck milling time on 2,4-DNT concentration and precision in soil from a firing point. Data from Walsh et al.[18].
  • Figure 10: Incremental sub-sampling of a milled soil sample spread out on aluminum foil.
  • Analysis

    Soil sub-samples are extracted and analyzed following EPA Method 8330B[3] and Method 8095[4] using High Performance Liquid Chromatography (HPLC) and Gas Chromatography (GC), respectively. Common estimated reporting limits for these analysis methods are listed in Table 2.

    Table 2. Typical Method Reporting Limits for Energetic Compounds in Soil. (Data from Hewitt et al.[19])
    Compound Soil Reporting Limit (mg/kg)
    HPLC (8330) GC (8095)
    HMX 0.04 0.01
    RDX 0.04 0.006
    TNB 0.04 0.003
    TNT 0.04 0.002
    2,6-DNT 0.08 0.002
    2,4-DNT 0.04 0.002
    2-ADNT 0.08 0.002
    4-ADNT 0.08 0.002
    NG 0.1 0.01
    DNB 0.04 0.002
    Tetryl 0.04 0.01
    PETN 0.2 0.016

    References

    1. ^ 1.0 1.1 1.2 Taylor, S., Jenkins, T.F., Bigl, S., Hewitt, A.D., Walsh, M.E. and Walsh, M.R., 2011. Guidance for Soil Sampling for Energetics and Metals (No. ERDC/CRREL-TR-11-15). Report.pdf
    2. ^ 2.0 2.1 2.2 2.3 Hewitt, A.D., Jenkins, T.F., Walsh, M.E., Bigl, S.R. and Brochu, S., 2009. Validation of sampling protocol and the promulgation of method modifications for the characterization of energetic residues on military testing and training ranges (No. ERDC/CRREL-TR-09-6). Engineer Research and Development Center / Cold Regions Research and Engineering Lab (ERDC/CRREL) TR-09-6, Hanover, NH, USA. Report.pdf
    3. ^ 3.0 3.1 3.2 3.3 U.S. Environmental Protection Agency (USEPA), 2006. Method 8330B (SW-846): Nitroaromatics, Nitramines, and Nitrate Esters by High Performance Liquid Chromatography (HPLC), Rev. 2. Washington, D.C. Report.pdf
    4. ^ 4.0 4.1 U.S. Environmental Protection Agency (US EPA), 2007. Method 8095 (SW-846): Explosives by Gas Chromatography. Washington, D.C. Report.pdf
    5. ^ Walsh, M.R., Walsh, M.E., Ampleman, G., Thiboutot, S., Brochu, S. and Jenkins, T.F., 2012. Munitions propellants residue deposition rates on military training ranges. Propellants, Explosives, Pyrotechnics, 37(4), pp.393-406. doi: 10.1002/prep.201100105
    6. ^ Walsh, M.R., Walsh, M.E., Hewitt, A.D., Collins, C.M., Bigl, S.R., Gagnon, K., Ampleman, G., Thiboutot, S., Poulin, I. and Brochu, S., 2010. Characterization and Fate of Gun and Rocket Propellant Residues on Testing and Training Ranges: Interim Report 2. (ERDC/CRREL TR-10-13. Also: ESTCP Project ER-1481) Report
    7. ^ 7.0 7.1 Walsh, M.R., Temple, T., Bigl, M.F., Tshabalala, S.F., Mai, N. and Ladyman, M., 2017. Investigation of Energetic Particle Distribution from High‐Order Detonations of Munitions. Propellants, Explosives, Pyrotechnics, 42(8), pp.932-941. doi: 10.1002/prep.201700089 Report.pdf
    8. ^ Hewitt, A.D., Jenkins, T.F., Walsh, M.E., Walsh, M.R. and Taylor, S., 2005. RDX and TNT residues from live-fire and blow-in-place detonations. Chemosphere, 61(6), pp.888-894. doi: 10.1016/j.chemosphere.2005.04.058
    9. ^ Walsh, M.R., Walsh, M.E., Poulin, I., Taylor, S. and Douglas, T.A., 2011. Energetic residues from the detonation of common US ordnance. International Journal of Energetic Materials and Chemical Propulsion, 10(2). doi: 10.1615/IntJEnergeticMaterialsChemProp.2012004956 Report.pdf
    10. ^ Walsh, M.R., Thiboutot, S., Walsh, M.E., Ampleman, G., Martel, R., Poulin, I. and Taylor, S., 2011. Characterization and fate of gun and rocket propellant residues on testing and training ranges (No. ERDC/CRREL-TR-11-13). Engineer Research and Development Center / Cold Regions Research and Engineering Lab (ERDC/CRREL) TR-11-13, Hanover, NH, USA. Report.pdf
    11. ^ 11.0 11.1 Taylor, S., Hewitt, A., Lever, J., Hayes, C., Perovich, L., Thorne, P. and Daghlian, C., 2004. TNT particle size distributions from detonated 155-mm howitzer rounds. Chemosphere, 55(3), pp.357-367. Report.pdf
    12. ^ Pennington, J.C., Jenkins, T.F., Ampleman, G., Thiboutot, S., Brannon, J.M., Hewitt, A.D., Lewis, J., Brochu, S., 2006. Distribution and fate of energetics on DoD test and training ranges: Final Report. ERDC TR-06-13, Vicksburg, MS, USA. Also: SERDP/ESTCP Project ER-1155. Report.pdf
    13. ^ Hewitt, A.D., Jenkins, T.F., Ramsey, C.A., Bjella, K.L., Ranney, T.A. and Perron, N.M., 2005. Estimating energetic residue loading on military artillery ranges: Large decision units (No. ERDC/CRREL-TR-05-7). Report.pdf
    14. ^ Jenkins, T.F., Ampleman, G., Thiboutot, S., Bigl, S.R., Taylor, S., Walsh, M.R., Faucher, D., Mantel, R., Poulin, I., Dontsova, K.M. and Walsh, M.E., 2008. Characterization and fate of gun and rocket propellant residues on testing and training ranges (No. ERDC-TR-08-1). Report.pdf
    15. ^ Walsh, M.R., 2009. User’s manual for the CRREL Multi-Increment Sampling Tool. Engineer Research and Development Center / Cold Regions Research and Engineering Lab (ERDC/CRREL) SR-09-1, Hanover, NH, USA. Report.pdf
    16. ^ Cragin, J.H., Leggett, D.C., Foley, B.T., and Schumacher, P.W., 1985. TNT, RDX and HMX explosives in soils and sediments: Analysis techniques and drying losses. (CRREL Report 85-15) Hanover, NH, USA. Report.pdf
    17. ^ Walsh, M.E., Ramsey, C.A. and Jenkins, T.F., 2002. The effect of particle size reduction by grinding on subsampling variance for explosives residues in soil. Chemosphere, 49(10), pp.1267-1273. doi: 10.1016/S0045-6535(02)00528-3
    18. ^ Walsh, M.E., Ramsey, C.A., Collins, C.M., Hewitt, A.D., Walsh, M.R., Bjella, K.L., Lambert, D.J. and Perron, N.M., 2005. Collection methods and laboratory processing of samples from Donnelly Training Area Firing Points, Alaska, 2003 (No. ERDC/CRREL-TR-05-6). Report.pdf
    19. ^ Hewitt, A., Bigl, S., Walsh, M., Brochu, S., Bjella, K. and Lambert, D., 2007. Processing of training range soils for the analysis of energetic compounds (No. ERDC/CRREL-TR-07-15). Hanover, NH, USA. Report.pdf

    See Also