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Blooms of phytoplankton or algae can cause major environmental problems. Harmful algal blooms (HABs) occur when phytoplankton (algae and cyanobacteria) rapidly increase or accumulate, producing harmful conditions that negatively impact people, freshwater and marine ecosystems, and economies. Certain environmental conditions including high nutrient concentrations from stormwater runoff or wastewater and insufficient mixing of the water column can trigger HABs.  
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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.  
 
 
 
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
 
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
  
 
'''Related Article(s)''':  
 
'''Related Article(s)''':  
  
'''CONTRIBUTOR(S):''' [[Dr. Nathan Hall]] and [[Dr. Katie Werkhoven]]
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'''CONTRIBUTOR(S):''' [[Dr. Samuel Beal]]
  
  
 
'''Key Resource(s)''':  
 
'''Key Resource(s)''':  
*[https://oceanservice.noaa.gov/facts/eutrophication.htm NOAA Eutrophication])
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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://www.epa.gov/nutrientpollution/harmful-algal-blooms US EPA - Harmful Algal Blooms])
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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>
  
==Phytoplankton==
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==Introduction==
[https://en.wikipedia.org/wiki/Phytoplankton Phytoplankton] are microscopic, unicellular, filamentous, or colonial, photosynthetic microalgae or cyanobacteria that live in water (Figure 1). A [https://en.wikipedia.org/wiki/Algal_bloom phytoplankton bloom] is the development of a level of phytoplankton biomass that is uncharacteristically high for a given water body<ref>Carstensen, J., Henriksen, P. and Heiskanen, A.S., 2007. Summer algal blooms in shallow estuaries: definition, mechanisms, and link to eutrophication. Limnology and Oceanography, 52(1), pp.370-384. Does the benthos control phytoplankton blooms in South San Francisco Bay? Marine Ecology Progress Series 9: 191–202. [https://doi.org/10.1016/j.hal.2010.08.006 doi: 10.1016/j.hal.2010.08.006]</ref>. Often, but not always, blooms are formed by a single species.
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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>]]
[[File:Hall1w2Fig1.png|thumb|Fig 1. Phytoplankton come in many shapes and sizes.]]
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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)]]
  
For a phytoplankton bloom to occur, the net growth rate of a population must be positive for enough time to build a high biomass level. The net growth rate can be described as
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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>.
::'''Equation 1:'''&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<big>''Net Growth = Division – Mortality – Sedimentation – Dilution''</big>.
 
  
The division rate, also called the intrinsic growth rate, is the rate of new cell production. The total rate of cell loss is driven by three mechanisms: mortality, dilution, and sedimentation.
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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>
  
'''Phytoplankton Growth Rate.''' Like terrestrial plants, phytoplankton require sunlight and inorganic nutrients to produce new biomass. Limited supplies of light or nutrients can slow or stop cell division, preventing bloom formation.
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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).
  
Nitrogen and phosphorus are the nutrients most likely to be in short supply relative to demand, and by [https://en.wikipedia.org/wiki/Liebig%27s_law_of_the_minimum Liebig’s law of the minimum], are the primary growth-limiting nutrients. Nitrogen supplies tend to be limited in marine waters, and phosphorus supplies tend to be limited in freshwaters. However, many exceptions to these trends exist<ref name= "Howarth1988">Howarth, R.W., 1988. Nutrient limitation of net primary production in marine ecosystems. Annual review of ecology and systematics, 19(1), pp.89-110. [https://doi.org/10.1146/annurev.ecolsys.19.1.89 doi: 10.1146/annurev.ecolsys.19.1.89]</ref><ref>Sterner, R.W., 2008. On the phosphorus limitation paradigm for lakes. International Review of Hydrobiology, 93(4‐5), pp.433-445. [https://doi.org/10.1002/iroh.200811068 doi: 10.1002/iroh.200811068]</ref>. Humans contribute to nitrogen and phosphorus loads primarily through wastewater inputs and runoff from agricultural, urban, and residential land. While anthropogenic loads increase the probability that a bloom will occur, there must also be sufficient light and low enough loss rates (mortality, sedimentation and dilution) for a bloom to develop.  
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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"/>.
  
The amount of light available for phytoplankton growth varies according to time of year, extent of cloud cover, and water depth and clarity. During summer, higher light levels and higher water temperatures promote phytoplankton growth. Additionally, heating of surface waters can create a surface layer that is less dense than cooler bottom waters, separated by a region of strong density gradient called the thermocline. Strong density gradients resist mixing by wind or currents and can confine phytoplankton to a shallow upper mixed layer where there is enough light for phytoplankton growth. In estuaries, salinity differences between upper and lower layers can enhance vertical stratification, creating similar favorable conditions for phytoplankton growth in the upper layer.
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{| class="wikitable" style="float: right; text-align: center; margin-left: auto; margin-right: auto;"
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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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! 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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|}
  
'''Phytoplankton Mortality. ''' Consumption by organisms at higher trophic levels generally constitutes the largest source of mortality for phytoplankton. Grazing by protistan zooplankton is often the dominant source of mortality for phytoplankton in marine waters<ref>Schmoker, C., Hernández-León, S. and Calbet, A., 2013. Microzooplankton grazing in the oceans: impacts, data variability, knowledge gaps and future directions. Journal of Plankton Research, 35(4), pp.691-706. [https://doi.org/10.1093/plankt/fbt023 doi: 10.1093/plankt/fbt023]</ref> while grazing by crustacean zooplankton is often more important in freshwaters<ref>Tessier, A.J., Bizina, E.V. and Geedey, K.C., 2001. Grazer - resource interactions in the plankton: Are all daphniids alike. Limnology and Oceanography, 46(7), pp.1585-1595. [https://doi.org/10.4319/lo.2001.46.7.1585 doi: 10.4319/lo.2001.46.7.1585]</ref>. In shallow systems with a relatively low ratio of volume to benthic surface area, grazing by benthic bivalves can be substantial and dominate grazing losses<ref>Cloern, J.E., 1982. Does the Benthos Control Phytoplankton Biomass in South San Francisco Bay. Marine Ecology Progress Series. Oldendorf, 9(2), pp.191-202. [https://doi.org/10.3354/meps009191 doi:  10.3354/meps009191 ]</ref>. Infections by viruses, fungi, bacteria, and protists can also contribute substantially to phytoplankton mortality. High cell densities of a single-species bloom favor the spread of infections during blooms, and can result in rapid bloom termination<ref>Lehahn, Y., Koren, I., Schatz, D., Frada, M., Sheyn, U., Boss, E., Efrati, S., Rudich, Y., Trainic, M., Sharoni, S. and Laber, C., 2014. Decoupling physical from biological processes to assess the impact of viruses on a mesoscale algal bloom. Current Biology, 24(17), pp.2041-2046. [https://doi.org/10.1016/j.cub.2014.07.046 doi: 10.1016/j.cub.2014.07.046]</ref><ref>Donk, E.V. and Ringelberg, J., 1983. The effect of fungal parasitism on the succession of diatoms in Lake Maarsseveen I (The Netherlands). Freshwater Biology, 13(3), pp.241-251. [https://doi.org/10.1111/j.1365-2427.1983.tb00674.x doi: 10.1111/j.1365-2427.1983.tb00674.x]</ref>.
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==Incremental Sampling Approach==
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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]]
  
'''Sedimentation.''' Phytoplankton are typically 3 to 5 percent denser than their surrounding environment. Consequently, most phytoplankton are constantly sinking and require turbulent mixing to stay in the upper mixed layer where light levels are appropriate for growth. According to Stoke’s law, larger and more dense phytoplankton tend to sink faster (0.1-1 m/d) while settling velocities are negligible for the smallest phytoplankton (0.001 m/d)<ref>Fogg, G.E., 1991. The phytoplanktonic ways of life. New Phytologist, 118(2), pp.191-232. [https://doi.org/10.1111/j.1469-8137.1991.tb00974.x doi: 10.1111/j.1469-8137.1991.tb00974.x]</ref>. Many phytoplankton, particularly bloom-forming taxa, avoid settling losses by having either flagella that allow them to swim or ballast mechanisms that provide buoyancy<ref>Paerl, H.W., 1988. Nuisance phytoplankton blooms in coastal, estuarine, and inland waters 1. Limnology and Oceanography, 33(4part2), pp.823-843. [https://doi.org/10.4319/lo.1988.33.4part2.0823 doi: 10.4319/lo.1988.33.4part2.0823]</ref>. Cyanobacteria are notorious for accumulating by flotation into dense surface scums (Figure 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:Hall1w2Fig2.png|thumb| Fig 2.  Surface Scum of the Cyanobacteria, Microcystsis sp. in the Chowan River, NC. Photo credit, Chowan/Edenton Environmental Group]]
 
  
'''Dilution.''' In a water body with constant volume, any water inputs must be accompanied by an equivalent water loss. For example, riverine water inputs to a lake are matched by outflows from the lake. If we assume that the river contains negligible phytoplankton, then river water dilutes phytoplankton densities in the lake at a rate equivalent to the river flow rate divided by lake volume. If the dilution rate is higher than net growth rate, then the physical effect of flushing will prevent bloom development.
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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)]]
  
The reciprocal of dilution rate is the water residence time which is the average amount of time that a parcel of water spends within a body of water. Generally, water bodies with residence times of a few days or less will not develop phytoplankton blooms. In water bodies with long residence times (e.g. more than a couple of weeks), phytoplankton blooms are more likely to develop. In addition to natural flow conditions, residence time and bloom development can be affected by water control infrastructure<ref>Gasith, A. and Gafny, S., 1998. Importance of physical structures in lakes: the case of Lake Kinneret and general implications. In The structuring role of submerged macrophytes in lakes (pp. 331-338). Springer, New York, NY. [https://doi.org/10.1007/978-1-4612-0695-8_24 doi:10.1007/978-1-4612-0695-8_24]</ref><ref>Hall, N.S., Paerl, H.W., Peierls, B.L., Whipple, A.C. and Rossignol, K.L., 2013. Effects of climatic variability on phytoplankton community structure and bloom development in the eutrophic, microtidal, New River Estuary, North Carolina, USA. Estuarine, Coastal and Shelf Science, 117, pp.70-82. [https://doi.org/10.1016/j.ecss.2012.10.004 doi: 10.1016/j.ecss.2012.10.004]</ref><ref>Scavia, D. and Liu, Y., 2009. Exploring estuarine nutrient susceptibility. Environmental Science & Technology, 43(10), pp.3474-3479. [https://doi.org/10.1021/es803401y doi: 10.1021/es803401y]</ref>. Dams and other flow manipulating structures (e.g. causeways, pumping stations, locks etc.) can significantly increase the residence time and can therefore greatly increase the potential for phytoplankton bloom development.
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==Sampling Tools==
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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.
  
==Consequences of Phytoplankton Blooms==
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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>]]
Phytoplankton blooms threaten the health of aquatic organisms and the health of humans, pets, or livestock that use affected waters for drinking or recreation. High concentrations of phytoplankton during bloom conditions colors and clouds the water limiting the transmission of light in the water column. In shallow systems, light levels along the bottom may become insufficient to support beneficial submerged aquatic vegetation (SAV) that provide habitat, remove nutrients from the water column, and stabilize bottom sediments. Once the SAV is gone, suspension of destabilized sediments causes an increase in turbidity, which in turn often prevents the SAV from returning. The nutrients that were previously consumed by SAV, are consumed by phytoplankton instead, further perpetuating blooms. These feedback mechanisms can trap a water body in this undesirable alternative stable state<ref>Scheffer, M., Jeppesen, E. 1998. Alternative Stable States. In: The Structuring Role of Submerged Macrophytes in Lakes (ed. E. Jeppesen, M. Sondergaard, M. Sondergaard & K. Christoffersen). Ecological Studies (Analysis and Synthesis), vol. 131, pp. 397-406. Springer, New York, NY [https://doi.org/10.1007/978-1-4612-0695-8_31 doi: 10.1007/978-1-4612-0695-8_31 ]</ref>.
 
  
Of all the negative impacts of phytoplankton blooms, production of toxins by some bloom-forming species represents the most direct threat to human health. Cyanobacteria and dinoflagellates are the most common toxin producing group of phytoplankton in fresh and marine waters, respectively. Cyanobacteria produce a wide variety of cyanotoxins including hepatotoxic (liver-damaging) microcystins, nodularins, and cylindrospermopsins, neurotoxic (nerve-damaging) saxitoxins and anatoxins, and dermatoxic (skin-damaging) lyngbya toxins <ref>Humpage, A. 2008. Toxin types, toxicokinetics and toxicodynamics. In: Hudnell, K. (Ed). Cyanobacterial harmful algal blooms: State of the science and research needs. Advances in Experimental Medicine and Biology Volume 619, Springer. Pp 383- 416 [https://doi.org/10.1007/978-0-387-75865-7  doi: 10.1007/978-0-387-75865-7]</ref>.
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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.
  
Ingestion of toxins in drinking water and contact during recreation activities are the two most common exposure pathways to humans, pets and livestock. Cyanotoxins and taste and odor compounds produced by cyanobacteria can be removed from drinking water by treatment with activated carbon and/or ozone, increasing treatment costs<ref>He, X., Liu, Y.L., Conklin, A., Westrick, J., Weavers, L.K., Dionysiou, D.D., Lenhart, J.J., Mouser, P.J., Szlag, D. and Walker, H.W., 2016. Toxic cyanobacteria and drinking water: impacts, detection, and treatment. Harmful Algae, 54, pp.174-193. [https://doi.org/10.1016/j.hal.2016.01.001 doi: 10.1016/j.hal.2016.01.001]</ref>. Some dinoflagellate blooms also produce the neurotoxin saxitoxin which can bioaccumulate in shellfish and cause paralytic shellfish poisoning in humans or other shellfish eating animals. Red tide dinoflagellate blooms of the genus ''Karenia'' produce brevetoxins that kill fish and other marine life and, when aerosolized by wave action, can cause respiratory irritation in humans<ref>Fleming, L.E., Kirkpatrick, B., Backer, L.C., Walsh, C.J., Nierenberg, K., Clark, J., Reich, A., Hollenbeck, J., Benson, J., Cheng, Y.S. and Naar, J., 2011. Review of Florida red tide and human health effects. Harmful algae, 10(2), pp.224-233. [https://doi.org/10.1016/j.hal.2010.08.006 doi: 10.1016/j.hal.2010.08.006]</ref>.
+
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>.
  
Habitat loss is another potential consequence of phytoplankton blooms. Although phytoplankton photosynthesis produces oxygen, the decomposition of the dead phytoplankton organic matter can deplete dissolved oxygen in the water to levels too low for fish and other animals. The result is restricted habitat availability due to these dead zones and occasionally mass mortality events (i.e., fish kills)<ref>Eby, L.A. and Crowder, L.B., 2002. Hypoxia-based habitat compression in the Neuse River Estuary: context-dependent shifts in behavioral avoidance thresholds. Canadian Journal of Fisheries and Aquatic Sciences, 59(6), pp.952-965. [https://doi.org/10.1139/f02-067 doi: 10.1139/f02-067]</ref>. Hypoxia (low oxygen) or anoxia (no oxygen) is particularly common in bottom waters that are disconnected from the atmosphere by a temperature gradient (thermocline) in lakes or salinity gradient (halocline) in estuaries. Further exacerbating the problem, hypoxia increases nutrient release from sediments. Under hypoxic conditions phosphorus (P) is released from the sediments due to reduction of iron hydroxides that bind phosphate. Additionally, fluxes of ammonium-nitrogen (N) into the water column are enhanced under hypoxic or anoxic conditions when denitrification becomes limited by a lack of nitrate<ref>Kemp, W.M., Sampou, P., Caffrey, J., Mayer, M., Henriksen, K. and Boynton, W.R., 1990. Ammonium recycling versus denitrification in Chesapeake Bay sediments. Limnology and Oceanography, 35(7), pp.1545-1563. [https://doi.org/10.4319/lo.1990.35.7.1545 doi: 10.4319/lo.1990.35.7.1545]</ref>. Under oxic (normal oxygen) conditions, nitrate would be produced by nitrification of ammonium. The increased release of N and P from the sediments under hypoxic conditions can fuel phytoplankton blooms presenting a major challenge to restoring water quality and aquatic habitats. Water bodies that are enriched with nutrients and characterized by degraded habitats are referred to as [https://en.wikipedia.org/wiki/Eutrophication eutrophic] (Figure 3)<ref>Bricker, S.B., Clement, C.G., Pirhalla, D.E., Orlando, S.P., Farrow, D.R.G. 1999. National estuarine eutrophication assessment: effects of nutrient enrichment in the nation's estuaries. Silver Spring: NOAA, National Ocean Service, Special Projects Office and the National Centers for Coastal Ocean Science. [[media:1999-Bricker-National_Estuarine_Eutrophication_Assessment.pdf]]</ref>.
+
==Sample Processing==
[[File:Hall1w2Fig3.png|thumb|450 px|left|Fig 3. Diagram Showing the Eutrophication Process]]
+
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.
  
==Bloom Mitigation Strategies==
+
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.
Bloom mitigation strategies can broadly be grouped by those strategies that address the root causes versus those that alleviate the symptoms of an algal bloom. Elevated nutrient loading and/or manipulation of circulation are common root causes of bloom problems that can be corrected through well designed mitigation strategies.
 
  
'''Reduce External Nutrient Loading. ''' The first step in designing nutrient controls is determining what nutrient(s) limit phytoplankton growth. Nitrogen (N) and phosphorus (P) have been commonly assumed to be the limiting nutrients for fresh and marine waters<ref name= "Howarth1988"/>, respectively.  However, recent studies<ref>Lewis Jr, W.M. and Wurtsbaugh, W.A., 2008. Control of lacustrine phytoplankton by nutrients: erosion of the phosphorus paradigm. International Review of Hydrobiology, 93(4‐5), pp.446-465. [https://doi.org/10.1002/iroh.200811065 doi: 10.1002/iroh.200811065]</ref><ref>Paerl, H.W., Scott, J.T., McCarthy, M.J., Newell, S.E., Gardner, W.S., Havens, K.E., Hoffman, D.K., Wilhelm, S.W. and Wurtsbaugh, W.A., 2016. It takes two to tango: When and where dual nutrient (N & P) reductions are needed to protect lakes and downstream ecosystems. Environmental Science & Technology, 50(20), pp.10805-10813. [https://doi.org/10.1021/acs.est.6b02575  doi: 10.1021/acs.est.6b02575]</ref> have shown that the limiting nutrient can change seasonally. Once the limiting nutrients have been identified, nutrient reduction targets are generally formulated using models that relate nutrient loads to phytoplankton biomass. These models may be experimental models with natural water containing the natural phytoplankton communities, simple nutrient budget-based models, or mechanistic, coupled circulation/water quality models. Mechanistic circulation/water quality models are the primary means of designing mitigation options for large water bodies. Enacting watershed-based controls on nutrient sources is the best strategy for large water bodies<ref name= "Paerl2011">Paerl, H.W., Hall, N.S. and Calandrino, E.S., 2011. Controlling harmful cyanobacterial blooms in a world experiencing anthropogenic and climatic-induced change. Science of the Total Environment, 409(10), pp.1739-1745. [https://doi.org/10.1016/j.scitotenv.2011.02.001 doi: 10.1016/j.scitotenv.2011.02.001]</ref>.
+
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).
  
'''Water Column Mixing. ''' Artificial vertical mixing can reduce the intensity of cyanobacteria blooms through two mechanisms. First, mixing oxygenated surface waters downward reduces sediment loading of N and P that results when sediments become anoxic. Second, vigorous vertical mixing negates the floating ability of cyanobacteria which leads to lower light availability and minimizes the competitive advantage buoyant taxa have over more desirable, negatively buoyant taxa (e.g. green algae and diatoms)<ref>Huisman, J., Sharples, J., Stroom, J.M., Visser, P.M., Kardinaal, W.E.A., Verspagen, J.M. and Sommeijer, B., 2004. Changes in turbulent mixing shift competition for light between phytoplankton species. Ecology, 85(11), pp.2960-2970. [https://doi.org/10.1890/03-0763 doi: 10.1890/03-0763]</ref>. Energy requirements to produce sufficiently vigorous mixing are high, and attempts to mix large water bodies with low powered mixers have been unsuccessful<ref>Olson, I., 2016. Evaluating the effectiveness of water remediation techniques for nutrient reduction and the control of cyanobacteria blooms in municipal drinking water reservoirs in the SE United States. [[media:2016-Olson-Evaluating_the_effectiveness_of_water_remediation_techniques.pdf| Report.pdf]]</ref><ref>Upadhyay, S., Bierlein, K.A., Little, J.C., Burch, M.D., Elam, K.P. and Brookes, J.D., 2013. Mixing potential of a surface-mounted solar-powered water mixer (SWM) for controlling cyanobacterial blooms. Ecological Engineering, 61, pp.245-250. [https://doi.org/10.1016/j.ecoleng.2013.09.032 doi: 10.1016/j.ecoleng.2013.09.032]</ref>. For large water bodies, nutrient control and, where possible, prevention of long residence time conditions are the most feasible, long term solutions to bloom problems<ref name= "Paerl2011"/>.
+
<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>
  
'''Legacy Nutrient Removal. ''' Organic-rich sediments that result from decades of nutrient over-enrichment can continue to provide high internal nutrient loads that fuel blooms even after external sources of N and P have been reduced<ref name= "Paerl2011"/>.  Application of alum or modified clay has been used successfully in small to medium sized freshwater bodies to flocculate P and phytoplankton cells out of the water column. Once the clay has settled, it can form a cap on the sediments to prevent P from diffusing back to the water column during anoxic periods. Physical removal of organic rich surficial sediments by dredging has also been used effectively but the high cost of both clay application and dredging largely restricts this practice to small water bodies<ref name= "Paerl2011"/>. Nutrients in a water body can also be intercepted and removed from a water body by intentionally growing and harvesting macroalgae in a relatively new process called algal turf scrubbing <ref>Craggs, R.J., Adey, W.H., Jenson, K.R., John, M.S.S., Green, F.B. and Oswald, W.J., 1996. Phosphorus removal from wastewater using an algal turf scrubber. Water Science and Technology, 33(7), pp.191-198. [https://doi.org/10.1016/j.hal.2010.08.006 doi: 10.1016/j.hal.2010.08.006]</ref>.  
+
==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.
  
'''Biological and Chemical Controls. ''' For some water bodies, blooms can be managed by manipulating the food web (e.g. removing certain fishes) to increase the numbers of zooplankton grazers<ref>Carpenter, S.R., Kitchell, J.F. and Hodgson, J.R., 1985. Cascading trophic interactions and lake productivity. BioScience, 35(10), pp.634-639. [https://doi.org/10.2307/1309989 doi: 10.2307/1309989]</ref><ref>Triest, L., Stiers, I. and Van Onsem, S., 2016. Biomanipulation as a nature-based solution to reduce cyanobacterial blooms. Aquatic Ecology, 50(3), pp.461-483. [https://doi.org/10.1007/s10452-015-9548-x doi: 10.1007/s10452-015-9548-x]</ref>. As a very short-term fix, algaecides can be used to control phytoplankton blooms. Copper-based algaecides can effectively kill most phytoplankton groups, and algaecides containing hydrogen peroxide can be equally effective on cyanobacteria<ref>Matthijs, H.C., Visser, P.M., Reeze, B., Meeuse, J., Slot, P.C., Wijn, G., Talens, R. and Huisman, J., 2012. Selective suppression of harmful cyanobacteria in an entire lake with hydrogen peroxide. Water Research, 46(5), pp.1460-1472. [https://doi.org/10.1016/j.watres.2011.11.016 doi: 10.1016/j.watres.2011.11.016]</ref>, without potential unintended toxic effects on higher trophic levels<ref>Willis, B.E. and Bishop, W.M., 2016. Understanding fate and effects of copper pesticides in aquatic systems. Journal of Geoscience and Environment Protection, 4(05), pp. 37 - 42. [https://doi.org/10.4236/gep.2016.45004 doi: 10.4236/gep.2016.45004]</ref>. High costs of algaecide also largely restrict its use to small water bodies.  
+
{| 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://itrcweb.org/ Interstate Technology and Regulatory Council]
 +
*[http://www.hawaiidoh.org/tgm.aspx Hawaii Department of Health]
 +
*[http://envirostat.org/ Envirostat]

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