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− | ==Downscaled High Resolution Datasets for Climate Change Projections== | + | ==Munitions Constituents – Sample Extraction and Analytical Techniques== |
− | Global climate models (GCMs) have generated projections of temperature, precipitation and other important climate change parameters with spatial resolutions of 100 to 300 km. However, higher spatial resolution information is required to assess threats to individual installations or regions. A variety of “downscaling” approaches have been used to produce high spatial resolution output (datasets) from the global climate models at scales that are useful for evaluating potential threats to critical infrastructure at regional and local scales. These datasets enable development of information about projections produced from various climate models, about downscaling to achieve desired locational specificity, and about selecting the appropriate dataset(s) to use for performing specific assessments. This article describes how these datasets can be accessed and used to evaluate potential climate change impacts.
| + | Munitions Constituents, including [[Wikipedia: Insensitive munition | insensitive munitions]] (IM), are a broad category of compounds which, in areas where manufactured or used, can be found in a variety of environmental matrices (waters, soil, and tissues). This presents an analytical challenge when a variety of these munitions are to be quantified. This article discusses sample extraction methods for each typical sample matrix (high level water, low level water, soil and tissue) as well as the accompanying [[Wikipedia: High-performance liquid chromatography | HPLC]]-UV analytical method for 27 compounds of interest (legacy munitions, insensitive munitions, and surrogates). |
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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):''' |
− | * [[Climate Change Primer]]
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− | '''Contributor(s):''' [[Dr. Rao Kotamarthi]] | + | *[[Munitions Constituents]] |
| + | |
| + | '''Contributor(s):''' |
| + | |
| + | *Dr. Austin Scircle |
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| '''Key Resource(s):''' | | '''Key Resource(s):''' |
− | * Use of Climate Information for Decision-Making and Impacts Research: State of our Understanding<ref name="Kotamarthi2016">Kotamarthi, R., Mearns, L., Hayhoe, K., Castro, C.L., and Wuebble, D., 2016. Use of Climate Information for Decision-Making and Impacts Research: State of Our Understanding. Department of Defense, Strategic Environmental Research and Development Program (SERDP), 55pp. Free download from: [https://www.serdp-estcp.org/content/download/38568/364489/file/Use_of_Climate_Information_for_Decision-Making_Technical_Report.pdf SERDP-ESTCP]</ref>
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− | * Applying Climate Change Information to Hydrologic and Coastal Design of Transportation Infrastructure, Design Practices<ref name="Kilgore2019">Kilgore, R., Thomas, W.O. Jr., Douglass, S., Webb, B., Hayhoe, K., Stoner, A., Jacobs, J.M., Thompson, D.B., Herrmann, G.R., Douglas, E., and Anderson, C., 2019. Applying Climate Change Information to Hydrologic and Coastal Design of Transportation Infrastructure, Design Practices. The National Cooperative Highway Research Program, Transportation Research Board, Project 15-61, 154 pages. Free download from: [http://onlinepubs.trb.org/Onlinepubs/nchrp/docs/NCHRP1561_DesignProcedures.pdf The Transportation Research Board]</ref> | + | *[https://www.epa.gov/sites/default/files/2015-07/documents/epa-8330b.pdf USEPA Method 8330B]<ref name= "8330B">United States Environmental Protection Agency (USEPA), 2006. EPA Method 8330B (SW-846) Nitroaromatics, Nitramines, and Nitrate Esters by High Performance Liquid Chromatography (HPLC), Revision 2. [https://www.epa.gov/esam/epa-method-8330b-sw-846-nitroaromatics-nitramines-and-nitrate-esters-high-performance-liquid USEPA Website] [[Media: Epa-2006-method-8330b.pdf | EPA Method 8330b]]</ref> |
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− | * Statistical Downscaling and Bias Correction for Climate Research<ref name="Maraun2018">Maraun, D., and Wildmann, M., 2018. Statistical Downscaling and Bias Correction for Climate Research. Cambridge University Press, Cambridge, UK. 347 pages. [https://doi.org/10.1017/9781107588783 DOI: 10.1017/9781107588783] ISBN: 978-1-107-06605-2</ref> | + | *Methods for simultaneous quantification of legacy and insensitive munition (IM) constituents in aqueous, soil/sediment, and tissue matrices<ref name="CrouchEtAl2020">Crouch, R.A., Smith, J.C., Stromer, B.S., Hubley, C.T., Beal, S., Lotufo, G.R., Butler, A.D., Wynter, M.T., Russell, A.L., Coleman, J.G., Wayne, K.M., Clausen, J.L., Bednar, A.J., 2020. Methods for simultaneous determination of legacy and insensitive munition (IM) constituents in aqueous, soil/sediment, and tissue matrices. Talanta, 217, Article 121008. [https://doi.org/10.1016/j.talanta.2020.121008 doi: 10.1016/j.talanta.2020.121008] [[Media: CrouchEtAl2020.pdf | Open Access Manuscript.pdf]]</ref> |
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− | * Downscaling Techniques for High-Resolution Climate Projections: From Global Change to Local Impacts<ref name="Kotamarthi2021">Kotamarthi, R., Hayhoe, K., Wuebbles, D., Mearns, L.O., Jacobs, J. and Jurado, J., 2021. Downscaling Techniques for High-Resolution Climate Projections: From Global Change to Local Impacts. Cambridge University Press, Cambridge, UK. 202 pages. [https://doi.org/10.1017/9781108601269 DOI: 10.1017/9781108601269] ISBN: 978-1-108-47375-0</ref>
| + | ==Introduction== |
| + | {| class="wikitable mw-collapsible" style="float:left; margin-right:20px; text-align:center;" |
| + | |+Table 1. Analyte list with acronyms and CAS numbers. |
| + | |- |
| + | !Compound |
| + | ! Acronym |
| + | !CAS Number |
| + | |- |
| + | | 1,2-Dinitrobenzene (surrogate) ||'''1,2-DNB (surr.)''' || 528-29-0 |
| + | |- |
| + | | 1,3-Dinitrobenzene || 1,3-DNB || 99-65-0 |
| + | |- |
| + | | 1,3,5-Trinitrobenzene || 1,3,5-TNB || 99-35-4 |
| + | |- |
| + | | 1,4-Dinitrobenzene || '''1,4-DNB (surr.)''' || 100-25-4 |
| + | |- |
| + | | 2-Amino-4,6-dinitrotoluene || 2-Am-4,6-DNT || 35572-78-2 |
| + | |- |
| + | | 2-Nitrophenol || '''2-NP''' || 88-75-5 |
| + | |- |
| + | | 2-Nitrotoluene || 2-NT || 88-72-2 |
| + | |- |
| + | | 2,4-Dinitrophenol || '''2,4-DNP''' || 51-28-5 |
| + | |- |
| + | | 2,4-Dinitrotoluene || 2,4-DNT || 121-14-2 |
| + | |- |
| + | | 2,4,6-Trinitrophenol || '''Picric Acid (PA)''' || 88-89-1 |
| + | |- |
| + | | 2,4,6-Trinitrotoluene || 2,4,6-TNT || 118-96-7 |
| + | |- |
| + | | 2,6-Dinitrotoluene || 2,6-DNT || 606-20-2 |
| + | |- |
| + | | 3-Nitrotoluene || 3-NT || 99-08-1 |
| + | |- |
| + | | 3,5-Dinitroaniline || 3,5-DNA || 618-87-1 |
| + | |- |
| + | | 4-Amino-2,6-dinitrotoluene || 4-Am-2,6-DNT || 19406-51-0 |
| + | |- |
| + | | 4-Nitrophenol || '''4-NP''' || 100-02-7 |
| + | |- |
| + | | 4-Nitrotoluene || 4-NT || 99-99-0 |
| + | |- |
| + | | 2,4-Dinitroanisole || '''DNAN''' || 119-27-7 |
| + | |- |
| + | | Octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine || HMX || 2691-41-0 |
| + | |- |
| + | | Nitrobenzene || NB || 98-95-3 |
| + | |- |
| + | | Nitroglycerine || NG || 55-63-0 |
| + | |- |
| + | | Nitroguanidine || '''NQ''' || 556-88-7 |
| + | |- |
| + | | 3-Nitro-1,2,4-triazol-5-one || '''NTO''' || 932-64-9 |
| + | |- |
| + | | ''ortho''-Nitrobenzoic acid || '''''o''-NBA (surr.)''' || 552-16-9 |
| + | |- |
| + | | Pentaerythritol tetranitrate || PETN || 78-11-5 |
| + | |- |
| + | | Hexahydro-1,3,5-trinitro-1,3,5-triazine || RDX || 121-82-4 |
| + | |- |
| + | | N-Methyl-N-(2,4,6-trinitrophenyl)nitramide || Tetryl || 479-45-8 |
| + | |- |
| + | | colspan="3" style="background-color:white;" | Note: Analytes in '''bold''' are not identified by EPA Method 8330B. |
| + | |} |
| + | [[File: ScircleFig1.png | thumb | 400px | Figure 1. Primary Method labeled chromatograms]] |
| + | [[File: ScircleFig2.png | thumb | 400px | Figure 2. Secondary Method labeled chromatograms]] |
| + | The primary intention of the analytical methods presented here is to support the monitoring of legacy and insensitive munitions contamination on test and training ranges, however legacy and insensitive munitions often accompany each other at demilitarization facilities, manufacturing facilities, and other environmental sites. Energetic materials typically appear on ranges as small, solid particulates and due to their varying functional groups and polarities, can partition in various environmental compartments<ref>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]</ref>. To ensure that contaminants are monitored and controlled at these sites and to sustainably manage them a variety of sample matrices (surface or groundwater, process waters, soil, and tissues) must be considered. (Process water refers to water used during industrial manufacturing or processing of legacy and insensitive munitions.) Furthermore, additional analytes must be added to existing methodologies as the usage of IM compounds changes and as new degradation compounds are identified. Of note, relatively new IM formulations containing [[Wikipedia: Nitrotriazolone | NTO]], [[Wikipedia: 2,4-Dinitroanisole | DNAN]], and [[Wikipedia: Nitroguanidine | NQ]] are seeing use in [[Wikipedia: IMX-101 | IMX-101]], IMX-104, Pax-21 and Pax-41 (Table 1)<ref>Mainiero, C. 2015. Picatinny Employees Recognized for Insensitive Munitions. U.S. Army, Picatinny Arsenal Public Affairs. [https://www.army.mil/article/148873/picatinny_employees_recognized_for_insensitive_munitions Open Access Press Release]</ref><ref>Frem, D., 2022. A Review on IMX-101 and IMX-104 Melt-Cast Explosives: Insensitive Formulations for the Next-Generation Munition Systems. Propellants, Explosives, Pyrotechnics, 48(1), e202100312. [https://doi.org/10.1002/prep.202100312 doi: 10.1002/prep.202100312]</ref>. |
| + | |
| + | Sampling procedures for legacy and insensitive munitions are identical and utilize multi-increment sampling procedures found in USEPA Method 8330B Appendix A<ref name= "8330B"/>. Sample hold times, subsampling and quality control requirements are also unchanged. The key differences lie in the extraction methods and instrumental methods. Briefly, legacy munitions analysis of low concentration waters uses a single cartridge reverse phase [[Wikipedia: Solid-phase extraction | SPE]] procedure, and [[Wikipedia: Acetonitrile | acetonitrile]] (ACN) is used for both extraction and [[Wikipedia: Elution | elution]] for aqueous and solid samples<ref name= "8330B"/><ref>United States Environmental Protection Agency (USEPA), 2007. EPA Method 3535A (SW-846) Solid-Phase Extraction (SPE), Revision 1. [https://www.epa.gov/esam/epa-method-3535a-sw-846-solid-phase-extraction-spe USEPA Website] [[Media: epa-3535a.pdf | Method 3535A.pdf]]</ref>. An [[Wikipedia: High-performance_liquid_chromatography#Isocratic_and_gradient_elution | isocratic]] separation via reversed-phase C-18 column with 50:50 methanol:water mobile phase or a C-8 column with 15:85 isopropanol:water mobile phase is used to separate legacy munitions<ref name= "8330B"/>. While these procedures are sufficient for analysis of legacy munitions, alternative solvents, additional SPE cartridges, and a gradient elution are all required for the combined analysis of legacy and insensitive munitions. |
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− | ==Downscaling of Global Climate Models==
| + | Previously, analysis of legacy and insensitive munitions required multiple analytical techniques, however the methods presented here combine the two munitions categories resulting in an HPLC-UV method and accompanying extraction methods for a variety of common sample matrices. A secondary HPLC-UV method and a HPLC-MS method were also developed as confirmatory methods. The methods discussed in this article were validated extensively by single-blind round robin testing and subsequent statistical treatment as part of ESTCP [https://serdp-estcp.mil/projects/details/d05c1982-bbfa-42f8-811d-51b540d7ebda ER19-5078]. Wherever possible, the quality control criteria in the Department of Defense Quality Systems Manual for Environmental Laboratories were adhered to<ref>US Department of Defense and US Department of Energy, 2021. Consolidated Quality Systems Manual (QSM) for Environmental Laboratories, Version 5.4. 387 pages. [https://www.denix.osd.mil/edqw/denix-files/sites/43/2021/10/QSM-Version-5.4-FINAL.pdf Free Download] [[Media: QSM-Version-5.4.pdf | QSM Version 5.4.pdf]]</ref>. Analytes included in the methods presented here are found in Table 1. |
− | Some communities and businesses have begun to improve their resilience to climate change by building adaptation plans based on national scale climate datatsets ([https://unfccc.int/topics/adaptation-and-resilience/workstreams/national-adaptation-plans National Adaptation Plans]), regional datasets ([https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State Flood Risk Management Guidance]<ref name="NYDEC2020">New York State Department of Environmental Conservation, 2020. New York State Flood Risk Management Guidance for Implementation of the Community Risk and Resiliency Act. Free download from: [https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State] [[Media: NewYorkState2020.pdf | Report.pdf]]</ref>), and datasets generated at local spatial resolutions. Resilience to the changing climate has also been identified by the US Department of Defense (DoD) as a necessary part of the installation planning and basing process (https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD Report on Effects of a Changing Climate]<ref name="DoD2019">US Department of Defense, 2019. Report on Effects of a Changing Climate to the Department of Defense. Free download from: [https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD] [[Media: DoD2019.pdf | Report.pdf]]</ref>). More than 79 installations were identified as facing potential threats from climate change. The threats faced due to changing climate include recurrent flooding, droughts, desertification, wildfires and thawing permafrost.
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− | Assessing the threats climate change poses at regional and local scales requires data with higher spatial resolution than is currently available from global climate models. Global-scale climate models typically have spatial resolutions of 100 to 300 km, and output from these models needs to be spatially and/or temporally disaggregated in order to be useful in performing assessments at smaller scales. The process of producing higher spatial-temporal resolution climate model output from coarser global climate model outputs is referred to as “downscaling” and results in climate change projections (datasets) at scales that are useful for evaluating potential threats to regional and local communities and businesses. These datasets provide information on temperature, precipitation and a variety of other climate variables for current and future climate conditions under various greenhouse gas (GHG) emission scenarios. There are a variety of web-based tools available for accessing these datasets to evaluate potential climate change impacts at regional and local scales.
| + | The chromatograms produced by the primary and secondary HPLC-UV methods are shown in Figure 1 and Figure 2, respectively. Chromatograms for each detector wavelength used are shown (315, 254, and 210 nm). |
| | | |
− | ==Methods for Downscaling== | + | ==Extraction Methods== |
− | {| class="wikitable" style="float:right; margin-left:10px;text-align:center;" | + | [[File: ScircleFig3.PNG |thumb|400px|Figure 3. Triple cartridge SPE setup]] |
− | |+Table 1. Two widely used methods for developing downscaled higher resolution climate model projections | + | [[File: ScircleFig4.PNG |thumb|400px|Figure 4. A flow chart of the soil extraction procedure]] |
| + | ===High Concentration Waters (> 1 ppm)=== |
| + | Aqueous samples suspected to contain the compounds of interest at concentrations detectable without any extraction or pre-concentration are suitable for analysis by direct injection. The method deviates from USEPA Method 8330B by adding a pH adjustment and use of MeOH rather than ACN for dilution<ref name= "8330B"/>. The pH adjustment is needed to ensure method accuracy for ionic compounds (like NTO or PA) in basic samples. A solution of 1% HCl/MeOH is added to both acidify and dilute the samples to a final acid concentration of 0.5% (vol/vol) and a final solvent ratio of 1:1 MeOH/H<sub><small>2</small></sub>O. The direct injection samples are then ready for analysis. |
| + | |
| + | ===Low Concentration Waters (< 1 ppm)=== |
| + | Aqueous samples suspected to contain the compounds of interest at low concentrations require extraction and pre-concentration using solid phase extraction (SPE). The SPE setup described here uses a triple cartridge setup shown in Figure 3. Briefly, the extraction procedure loads analytes of interest onto the cartridges in this order: Strata<sup><small>TM</small></sup> X, Strata<sup><small>TM</small></sup> X-A, and Envi-Carb<sup><small>TM</small></sup>. Then the cartridge order is reversed, and analytes are eluted via a two-step elution, resulting in 2 extracts (which are combined prior to analysis). Five milliliters of MeOH is used for the first elution, while 5 mL of acidified MeOH (2% HCl) is used for the second elution. The particular SPE cartridges used are noncritical so long as cartridge chemistries are comparable to those above. |
| + | |
| + | {| class="wikitable mw-collapsible" style="float:left; margin-right:20px; text-align:center;" |
| + | |+Table 2. Primary HPLC-UV mobile phase gradient method concentrations |
| + | |- |
| + | | colspan="5" style="background-color:white;"| Method run time = 48 minutes; Column temperature = 25°C<br>Injection volume = 50 μL; Flow rate = 1.0 mL/min<br>Detector wavelengths = 210, 254, and 310 nm |
| |- | | |- |
− | !Dynamical Downscaling | + | ! Time<br>(min) |
− | !Statistical Downscaling | + | ! Reagent Water<br>(%) |
| + | ! MeOH<br>(%) |
| + | ! 0.1% TFA/Water<br>(%) |
| + | ! ACN<br>(%) |
| |- | | |- |
− | |Deterministic climate change simulations that output</br>many climate variables with sub-daily information ||Primarily limited to daily temperature and precipitation | + | | 0.00 || 89 || 3 || 3 || 5 |
| |- | | |- |
− | |Computationally expensive; hence, limited number of simulations – both</br>GHG emission scenarios and global climate models downscaled||Computationally efficient; hence, downscaled data typically</br>available for many different global climate models and GHG emission scenarios | + | | 2.00 || 89 || 3 || 3 || 5 |
| |- | | |- |
− | |May require additional bias correction||Method incorporates bias correction | + | | 2.20 || 52 || 40 || 3 || 5 |
| |- | | |- |
− | |Observational data at the downscaled location are not necessary</br>to obtain the downscaled output at the location||Best suited for locations with 30 years or more of observational data | + | | 12.5 || 52 || 40 || 3 || 5 |
| |- | | |- |
− | |Does not assume stationarity or in other words the model</br>simulates the future regardless of what has happened in the past||Stationarity assumption - assumes that the statistical relationship between global</br>climate model and observations will remain constant in the future | + | | 19.0 || 57 ||35 || 3 || 5 |
| + | |- |
| + | | 28.0 || 48 || 44 || 3 || 5 |
| + | |- |
| + | | 32.0 || 48 || 44 || 3 || 5 |
| + | |- |
| + | | 44.0 || 32 || 60 || 3 || 5 |
| + | |- |
| + | | 44.1 || 89 || 3 || 3 || 5 |
| + | |- |
| + | | 48.0 || 89 || 3 || 3 || 5 |
| |} | | |} |
− | There are two main approaches to downscaling. One method, commonly referred to as “statistical downscaling”, uses the empirical-statistical relationships between large-scale weather phenomena and historical local weather data. In this method, these statistical relationships are applied to output generated by global climate models. A second method uses physics-based numerical models (regional-scale climate models or RCMs) of weather and climate that operate over a limited region of the earth (e.g., North America) and at spatial resolutions that are typically 3 to 10 times finer than the global-scale climate models. This method is known as “dynamical downscaling”. These regional-scale climate models are similar to the global models with respect to their reliance on the principles of physics, but because they operate over only part of the earth, they require information about what is coming in from the rest of the earth as well as what is going out of the limited region of the model. This is generally obtained from a global model. The primary differences between statistical and dynamical downscaling methods are summarized in Table 1.
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| + | ===Soils=== |
| + | Soil collection, storage, drying and grinding procedures are identical to the USEPA Method 8330B procedures<ref name= "8330B"/>; however, the solvent extraction procedure differs in the number of sonication steps, sample mass and solvent used. A flow chart of the soil extraction procedure is shown in Figure 4. Soil masses of approximately 2 g and a sample to solvent ratio of 1:5 (g/mL) are used for soil extraction. The extraction is carried out in a sonication bath chilled below 20 ⁰C and is a two-part extraction, first extracting in MeOH (6 hours) followed by a second sonication in 1:1 MeOH:H<sub><small>2</small></sub>O solution (14 hours). The extracts are centrifuged, and the supernatant is filtered through a 0.45 μm PTFE disk filter. |
| + | |
| + | The solvent volume should generally be 10 mL but if different soil masses are required, solvent volume should be 5 mL/g. The extraction results in 2 separate extracts (MeOH and MeOH:H<sub><small>2</small></sub>O) that are combined prior to analysis. |
| + | |
| + | ===Tissues=== |
| | | |
| + | Tissue matrices are extracted by 18-hour sonication using a ratio of 1 gram of wet tissue per 5 mL of MeOH. This extraction is performed in a sonication bath chilled below 20 ⁰C and the supernatant (MeOH) is filtered through a 0.45 μm PTFE disk filter. |
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− | [[File: Gschwend1w2fig1.png | thumb | 300px | Figure 1. A representation of a clam living in a sediment bed that contains a chemical contaminant (depicted as red hexagons). The contaminant is partly dissolved in the sediment porewater between the solid grains, and partly associated with solid phases, like natural organic matter and "black carbons" such as soots from diesel engines and chars emitted during forest fires. All of these liquid and solid materials can exchange their contaminant loads with one another, with the distributions dependent on the chemical's relative affinity for each material. When an animal like the clam moves into this system, the chemical is also accumulated into the animal, until the animal is also equilibrated with the other solids and liquid(s) present.]]
| + | Due to the complexity of tissue matrices, an additional tissue cleanup step, adapted from prior research, can be used to reduce interferences<ref name="RussellEtAl2014">Russell, A.L., Seiter, J.M., Coleman, J.G., Winstead, B., Bednar, A.J., 2014. Analysis of munitions constituents in IMX formulations by HPLC and HPLC-MS. Talanta, 128, pp. 524–530. [https://doi.org/10.1016/j.talanta.2014.02.013 doi: 10.1016/j.talanta.2014.02.013]</ref><ref name="CrouchEtAl2020"/>. The cleanup procedure uses small scale chromatography columns prepared by loading 5 ¾” borosilicate pipettes with 0.2 g activated silica gel (100–200 mesh). The columns are wetted with 1 mL MeOH, which is allowed to fully elute and then discarded prior to loading with 1 mL of extract and collecting in a new amber vial. After the extract is loaded, a 1 mL aliquot of MeOH followed by a 1 mL aliquot of 2% HCL/MeOH is added. This results in a 3 mL silica treated tissue extract. This extract is vortexed and diluted to a final solvent ratio of 1:1 MeOH/H<sub><small>2</small></sub>O before analysis. |
− | Environmental media such as sediments typically contain many different materials or phases, including liquid solutions (e.g. water, [[Light Non-Aqueous Phase Liquids (LNAPLs)| nonaqueous phase liquids]] like spilled oils) and diverse solids (e.g., quartz, aluminosilicate clays, and combustion-derived soots). Further, the chemical concentration in the porewater medium includes both molecules that are "truly dissolved" in the water and others that are associated with colloids in the porewater<ref name="Brownawell1986">Brownawell, B.J., and Farrington, J.W., 1986. Biogeochemistry of PCBs in interstitial waters of a coastal marine sediment. Geochimica et Cosmochimica Acta, 50(1), pp. 157-169. [https://doi.org/10.1016/0016-7037(86)90061-X DOI: 10.1016/0016-7037(86)90061-X] Free download available from: [https://semspub.epa.gov/work/01/268631.pdf US EPA].</ref><ref name="Chin1992">Chin, Y.P., and Gschwend, P.M., 1992. Partitioning of Polycyclic Aromatic Hydrocarbons to Marine Porewater Organic Colloids. Environmental Science and Technology, 26(8), pp. 1621-1626. [https://doi.org/10.1021/es00032a020 DOI: 10.1021/es00032a020]</ref><ref name="Achman1996">Achman, D.R., Brownawell, B.J., and Zhang, L., 1996. Exchange of Polychlorinated Biphenyls Between Sediment and Water in the Hudson River Estuary. Estuaries, 19(4), pp. 950-965. [https://doi.org/10.2307/1352310 DOI: 10.2307/1352310] Free download available from: [https://www.academia.edu/download/55010335/135231020171114-2212-b93vic.pdf Academia.edu]</ref>. As a result, contaminant chemicals distribute among these diverse media (Figure 1) according to their affinity for each and the amount of each phase in the system<ref name="Gustafsson1996">Gustafsson, Ö., Haghseta, F., Chan, C., MacFarlane, J., and Gschwend, P.M., 1996. Quantification of the Dilute Sedimentary Soot Phase: Implications for PAH Speciation and Bioavailability. Environmental Science and Technology, 31(1), pp. 203-209. [https://doi.org/10.1021/es960317s DOI: 10.1021/es960317s]</ref><ref name="Luthy1997">Luthy, R.G., Aiken, G.R., Brusseau, M.L., Cunningham, S.D., Gschwend, P.M., Pignatello, J.J., Reinhard, M., Traina, S.J., Weber, W.J., and Westall, J.C., 1997. Sequestration of Hydrophobic Organic Contaminants by Geosorbents. Environmental Science and Technology, 31(12), pp. 3341-3347. [https://doi.org/10.1021/es970512m DOI: 10.1021/es970512m]</ref><ref name="Lohmann2005">Lohmann, R., MacFarlane, J.K., and Gschwend, P.M., 2005. Importance of Black Carbon to Sorption of Native PAHs, PCBs, and PCDDs in Boston and New York Harbor Sediments. Environmental Science and Technology, 39(1), pp.141-148. [https://doi.org/10.1021/es049424+ DOI: 10.1021/es049424+]</ref><ref name="Cornelissen2005">Cornelissen, G., Gustafsson, Ö., Bucheli, T.D., Jonker, M.T., Koelmans, A.A., and van Noort, P.C., 2005. Extensive Sorption of Organic Compounds to Black Carbon, Coal, and Kerogen in Sediments and Soils: Mechanisms and Consequences for Distribution, Bioaccumulation, and Biodegradation. Environmental Science and Technology, 39(18), pp. 6881-6895. [https://doi.org/10.1021/es050191b DOI: 10.1021/es050191b]</ref><ref name="Koelmans2009">Koelmans, A.A., Kaag, K., Sneekes, A., and Peeters, E.T.H.M., 2009. Triple Domain in Situ Sorption Modeling of Organochlorine Pesticides, Polychlorobiphenyls, Polyaromatic Hydrocarbons, Polychlorinated Dibenzo-p-Dioxins, and Polychlorinated Dibenzofurans in Aquatic Sediments. Environmental Science and Technology, 43(23), pp. 8847-8853. [https://doi.org/10.1021/es9021188 DOI: 10.1021/es9021188]</ref>. As such, the chemical concentration in any one medium (e.g., truly dissolved in porewater) in a multi-material system like sediment is very hard to know from measures of the total sediment concentration, which unfortunately is the information typically found by analyzing for chemicals in sediment samples.
| |
| | | |
− | If an animal moves into this system, it will also accumulate the chemical in its tissues from the loads in all the other materials (Figure 1). This can lead to exposures of the chemical to other organisms, including humans, who may eat such animals. Predicting the quantity of contaminant in the animal requires knowledge of the relative affinities of the chemical for the animal versus the sediment materials. For example, if one knew the chemical's truly dissolved concentration in the porewater and could reasonably assume the chemical of interest in the animal has mostly accumulated in its lipids (as is often the case for very hydrophobic compounds), then one could estimate the chemical concentration in the animal (''C<sub><small>animal</small></sub>'', typically in units of μg/kg animal wet weight) using a lipid-water [[Wikipedia: Partition coefficient | partition coefficient]], ''K<sub><small>lipid-water</small></sub>'', typically in units of (μg/kg lipid)'''/'''(μg/L water), and the porewater concentration of the chemical (''C<sub><small>porewater</small></sub>'', in μg/L) with Equation 1.
| + | ==HPLC-UV and HPLC-MS Methods== |
− | {|
| + | {| class="wikitable mw-collapsible" style="float:left; margin-right:20px; text-align:center;" |
− | |
| + | |+Table 3. Secondary HPLC-UV mobile phase gradient method concentrations |
| + | |- |
| + | | colspan="5" style="background-color:white;" | Method run time = 43 minutes; Column temperature = 25°C<br>Injection volume = 50 μL; Flow rate = 0.8 mL/min<br>Detector wavelengths = 210, 254, and 310 nm |
| |- | | |- |
− | | || Equation 1.
| + | ! Time<br>(min) |
− | | style="text-align:center;"| <big>'''''C<sub><small>animal</small></sub> '''=''' f<sub><small>lipid</small></sub> '''x''' K<sub><small>lipid-water</small></sub> '''x''' C<sub><small>porewater</small></sub>'''''</big>
| + | ! Reagent Water<br>(%) |
| + | ! MeOH<br>(%) |
| + | ! 0.1% TFA/Water<br>(%) |
| + | ! ACN<br>(%) |
| |- | | |- |
− | | where: | + | | 0.00 || 75 || 10 || 10 || 5 |
| |- | | |- |
− | | || ''f<sub><small>lipid</small></sub>'' || is the fraction lipids contribute to the total wet weight of the animal (kg lipid/kg animal wet weight), and | + | | 2.50 || 75 || 10 || 10 || 5 |
| |- | | |- |
− | | || ''C<sub><small>porewater</small></sub>'' || is the freely dissolved contaminant concentration in the porewater surrounding the animal. | + | | 2.60 || 39 || 46 ||10 || 5 |
− | |} | + | |- |
− | | + | | 9.00 || 39 || 46 ||10 || 5 |
− | While there is a great deal of information on the values of ''K<sub><small>lipid-water</small></sub>'' for many chemicals<ref name="Schwarzenbach2017">Schwarzenbach, R.P., Gschwend, P.M., and Imboden, D.M., 2017. Environmental Organic Chemistry, 3rd edition. Ch. 16: Equilibrium Partitioning from Water and Air to Biota, pp. 469-521. John Wiley and Sons. ISBN: 978-1-118-76723-8</ref>, it is often very inaccurate to estimate truly dissolved porewater concentrations from total sediment concentrations using assumptions about the affinity of those chemicals for the solids in the system<ref name="Gustafsson1996"/>. Further, it is difficult to isolate porewater without colloids and/or measure the very low truly dissolved concentrations of hydrophobic contaminants of concern like [[Polycyclic Aromatic Hydrocarbons (PAHs) | polycyclic aromatic hydrocarbons (PAHs)]], [[Wikipedia: Polychlorinated biphenyl | polychlorinated biphenyls (PCBs)]], nonionic pesticides like [[Wikipedia: DDT | dichlorodiphenyltrichloroethane (DDT)]], and [[Wikipedia: Polychlorinated dibenzodioxins | polychlorinated dibenzo-p-dioxins (PCDDs)]]/[[Wikipedia: Polychlorinated dibenzofurans | dibenzofurans (PCDFs)]]<ref name="Hawthorne2005">Hawthorne, S.B., Grabanski, C.B., Miller, D.J., and Kreitinger, J.P., 2005. Solid-Phase Microextraction Measurement of Parent and Alkyl Polycyclic Aromatic Hydrocarbons in Milliliter Sediment Pore Water Samples and Determination of K<sub><small>DOC</small></sub> Values. Environmental Science and Technology, 39(8), pp. 2795-2803. [https://doi.org/10.1021/es0405171 DOI: 10.1021/es0405171]</ref>.
| + | |- |
− | | + | | 9.10 || 33.5 || 51.5 || 10 || 5 |
− | ==Passive Samplers==
| + | |- |
− | One approach to address this problem for contaminated sediments is to insert into the sediment billets of organic polymers like low density polyethylene (LDPE), polydimethylsiloxane (PDMS), or polyoxymethylene (POM) that can absorb such hydrophobic chemicals from their surroundings<ref name="Mayer2000">Mayer, P., Vaes, W.H., Wijnker, F., Legierse, K.C., Kraaij, R., Tolls, J., and Hermens, J.L., 2000. Sensing Dissolved Sediment Porewater Concentrations of Persistent and Bioaccumulative Pollutants Using Disposable Solid-Phase Microextraction Fibers. Environmental Science and Technology, 34(24), pp. 5177-5183. [https://doi.org/10.1021/es001179g DOI: 10.1021/es001179g]</ref><ref name="Booij2003">Booij, K., Hoedemaker, J.R., and Bakker, J.F., 2003. Dissolved PCBs, PAHs, and HCB in Pore Waters and Overlying Waters of Contaminated Harbor Sediments. Environmental Science and Technology, 37(18), pp. 4213-4220. [https://doi.org/10.1021/es034147c DOI: 10.1021/es034147c]</ref><ref name="Cornelissen2008">Cornelissen, G., Pettersen, A., Broman, D., Mayer, P., and Breedveld, G.D., 2008. Field testing of equilibrium passive samplers to determine freely dissolved native polycyclic aromatic hydrocarbon concentrations. Environmental Toxicology and Chemistry, 27(3), pp. 499-508. [https://doi.org/10.1897/07-253.1 DOI: 10.1897/07-253.1]</ref><ref name="Tomaszewski2008">Tomaszewski, J.E., and Luthy, R.G., 2008. Field Deployment of Polyethylene Devices to Measure PCB Concentrations in Pore Water of Contaminated Sediment. Environmental Science and Technology, 42(16), pp. 6086-6091. [https://doi.org/10.1021/es800582a DOI: 10.1021/es800582a]</ref><ref name="Fernandez2009">Fernandez, L.A., MacFarlane, J.K., Tcaciuc, A.P., and Gschwend, P.M., 2009. Measurement of Freely Dissolved PAH Concentrations in Sediment Beds Using Passive Sampling with Low-Density Polyethylene Strips. Environmental Science and Technology, 43(5), pp. 1430-1436. [https://doi.org/10.1021/es802288w DOI: 10.1021/es802288w]</ref><ref name="Arp2015">Arp, H.P.H., Hale, S.E., Elmquist Kruså, M., Cornelissen, G., Grabanski, C.B., Miller, D.J., and Hawthorne, S.B., 2015. Review of polyoxymethylene passive sampling methods for quantifying freely dissolved porewater concentrations of hydrophobic organic contaminants. Environmental Toxicology and Chemistry, 34(4), pp. 710-720. [https://doi.org/10.1002/etc.2864 DOI: 10.1002/etc.2864] [https://setac.onlinelibrary.wiley.com/doi/epdf/10.1002/etc.2864 Free access article.] [[Media: Arp2015.pdf | Report.pdf]]</ref><ref name="Apell2016"/>. In this approach, the polymer is inserted in the sediment bed where it absorbs some of the contaminant load via the contaminant's diffusion into the polymer from the surroundings. When the polymer achieves sorptive equilibration with the sediments, the chemical concentration in the polymer, ''C<sub><small>polymer</small></sub>'' (μg/kg polymer), can be used to find the corresponding concentration in the porewater, ''C<sub><small>porewater</small></sub>'' (μg/L), using a polymer-water partition coefficient, ''K<sub><small>polymer-water</small></sub>'' ((μg/kg polymer)'''/'''(μg/L water)), that has previously been found in laboratory testing<ref name="Lohmann2012">Lohmann, R., 2012. Critical Review of Low-Density Polyethylene’s Partitioning and Diffusion Coefficients for Trace Organic Contaminants and Implications for Its Use as a Passive Sampler. Environmental Science and Technology, 46(2), pp. 606-618. [https://doi.org/10.1021/es202702y DOI: 10.1021/es202702y]</ref><ref name="Ghosh2014">Ghosh, U., Kane Driscoll, S., Burgess, R.M., Jonker, M.T., Reible, D., Gobas, F., Choi, Y., Apitz, S.E., Maruya, K.A., Gala, W.R., Mortimer, M., and Beegan, C., 2014. Passive Sampling Methods for Contaminated Sediments: Practical Guidance for Selection, Calibration, and Implementation. Integrated Environmental Assessment and Management, 10(2), pp. 210-223. [https://doi.org/10.1002/ieam.1507 DOI: 10.1002/ieam.1507] [https://setac.onlinelibrary.wiley.com/doi/epdf/10.1002/ieam.1507 Free access article.] [[Media: Ghosh2014.pdf | Report.pdf]]</ref>, as shown in Equation 2.
| + | | 15.00 || 35 || 50 || 10 || 5 |
− | {|
| + | |- |
− | | | + | | 15.10 || 43 || 42 || 10 || 5 |
| + | |- |
| + | | 33.00 || 30 || 55 || 10 || 5 |
| |- | | |- |
− | | || Equation 2. | + | | 33.10 || 75 || 10 || 10 || 5 |
− | | style="width:600px; text-align:center;" | <big>'''''C<sub><small>porewater</small></sub> '''=''' C<sub><small>polymer</small></sub> '''/''' K<sub><small>polymer-water</small></sub>'''''</big> | |
− | |} | |
− | | |
− | Such “passive uptake” by the polymer also reflects the availability of the chemicals for transport to adjacent systems (e.g., overlying surface waters) and for uptake into organisms (e.g., [[Wikipedia: Bioaccumulation | bioaccumulation]]). Thus, one can use the porewater concentrations to estimate the biotic accumulation of the chemicals, too. For example, for the concentration in the animal equilibrated with the sediment, ''C<sub><small>animal</small></sub>'' (μg/kg animal), would be found by combining Equations 1 and 2 to get Equation 3.
| |
− | {|
| |
− | | | |
| |- | | |- |
− | | || Equation 3. | + | | 43.00 || 75 || 10 || 10 || 5 |
− | |style="width:700px; text-align:center;" |<big>'''''C<sub><small>animal</small></sub> '''=''' f<sub><small>lipid</small></sub> '''x''' K<sub><small>lipid-water</small></sub> '''x''' C<sub><small>polymer</small></sub> '''/''' K<sub><small>polymer-water</small></sub>'''''</big> | |
| |} | | |} |
− | [[File: Gschwend1w2fig2a.PNG | thumb | 300px | Figure 2a. Plot of the initial concentrations of a PRC (green lines) in a polyethylene (PE) sheet inserted in a sediment showing constant concentration across the PE and zero concentration outside the PE. At the same time, a target contaminant of interest (red lines) initially has a constant concentration in the sediment outside the PE and zero concentration inside the PE.]][[File: Gschwend1w2fig2b.PNG | thumb | 300px | Figure 2b. After the PE has been deployed for a time, the PRC is depleted from the PE (green lines), especially near the surfaces contacting the sediment, and its concentration is building up outside the PE and diffusing away into the sediment. Meanwhile, the target chemical leaves the sediment and begins to diffuse into the PE (red lines). The "jumps" in concentration at the PE-sediment boundary reflect the equilibrium paritioning coefficient,</br>''K<sub>PE-sed</sub> = C<sub>PE</sub> / C<sub>sediment</sub>''.]]
| + | {| class="wikitable mw-collapsible" style="float:right; margin-left:20px; text-align:center;" |
− | | + | |+Table 4. Ionization source and detector parameters |
− | ==Performance Reference Compounds (PRCs)==
| + | |- |
− | Perhaps unsurprisingly, pollutants with low water solubility like PAHs, PCBs, etc. do not diffuse quickly through sediment beds. As a result, their accumulation in polymeric materials in sediments can take a long time to achieve equilibration<ref name="Fernandez2009b">Fernandez, L. A., Harvey, C.F., and Gschwend, P.M., 2009. Using Performance Reference Compounds in Polyethylene Passive Samplers to Deduce Sediment Porewater Concentrations for Numerous Target Chemicals. Environmental Science and Technology, 43(23), pp. 8888-8894. [https://doi.org/10.1021/es901877a DOI: 10.1021/es901877a]</ref><ref name="Lampert2015">Lampert, D.J., Thomas, C., and Reible, D.D., 2015. Internal and external transport significance for predicting contaminant uptake rates in passive samplers. Chemosphere, 119, pp. 910-916. [https://doi.org/10.1016/j.chemosphere.2014.08.063 DOI: 10.1016/j.chemosphere.2014.08.063] Free download available from: [https://www.academia.edu/download/44146586/chemosphere_2014.pdf Academia.edu]</ref><ref name="Apell2016b">Apell, J.N., Tcaciuc, A.P., and Gschwend, P.M., 2016. Understanding the rates of nonpolar organic chemical accumulation into passive samplers deployed in the environment: Guidance for passive sampler deployments. Integrated Environmental Assessment and Management, 12(3), pp. 486-492. [https://doi.org/10.1002/ieam.1697 DOI: 10.1002/ieam.1697]</ref>. This problem was recognized previously for passive samplers called [[Wikipedia: Semipermeable membrane devices | semipermeable membrane devices]] (SPMDs, e.g. polyethylene bags filled with triolein<ref name="Huckins2002">Huckins, J.N., Petty, J.D., Lebo, J.A., Almeida, F.V., Booij, K., Alvarez, D.A., Cranor, W.L., Clark, R.C., and Mogensen, B.B., 2002. Development of the Permeability/Performance Reference Compound Approach for In Situ Calibration of Semipermeable Membrane Devices. Environmental Science and Technology, 36(1), pp. 85-91. [https://doi.org/10.1021/es010991w DOI: 10.1021/es010991w]</ref>) that were deployed in surface waters. As a result, representative chemicals called performance reference compound (PRCs) were dosed inside the samplers before their deployment in the environment, and the PRCs' diffusive losses out of the SPMD could be used to quantify the fractional approach toward sampler-environmental surroundings equilibration<ref name="Booij2002">Booij, K., Smedes, F., and van Weerlee, E.M., 2002. Spiking of performance reference compounds in low density polyethylene and silicone passive water samplers. Chemosphere 46(8), pp.1157-1161. [https://doi.org/10.1016/S0045-6535(01)00200-4 DOI: 10.1016/S0045-6535(01)00200-4]</ref><ref name="Huckins2002"/>. A similar approach can be used for polymers inserted in sediment beds<ref name="Fernandez2009b"/><ref name="Apell2014"/>. Commonly, isotopically labeled forms of the compounds of interest such as deuterated or <sup>13</sup>C-labelled PAHs or PCBs are homogeneously impregnated into the polymers before their deployments. Upon insertion of the polymer into the sediment bed (or overlying waters or even air), the initially evenly distributed PRCs begin to diffuse out of the sampling polymer and into the surroundings (Figure 2).
| + | ! Parameter |
− | | + | ! Value |
− | Assuming the contaminants of interest undergo the same mass transfer restrictions limiting their rates of uptake into the polymer (e.g., diffusion through the sedimentary porous medium) that are also limiting transfers of the PRCs out of the polymer<ref name="Fernandez2009b"/><ref name="Apell2014"/>, then fractional losses of the PRCs during a particular deployment can be used to adjust the accumulated contaminant loads to what they would have been at equilibrium with their surroundings with Equation 4.
| + | |- |
− | {|
| + | | Ionization Source || APCI |
− | | | + | |- |
| + | | Ionization Mode || Negative |
| + | |- |
| + | | Drying Gas Temperature (°C) || 350 |
| + | |- |
| + | | Vaporizer Temperature (°C) || 325 |
| + | |- |
| + | | Drying Gas Flow (L/min) || 4.0 |
| + | |- |
| + | | Nebulizer Pressure (psig) || 40 |
| + | |- |
| + | | Corona Current (μA) || 10 |
| + | |- |
| + | | Capillary Potential (V) || 1500 |
| + | |- |
| + | | Mass Range || 40 – 400 |
| + | |- |
| + | | Fragmentor || 100 |
| |- | | |- |
− | | || Equation 4. | + | | Gain || 1 |
− | | style="text-align:center;"| <big>'''''C(<sub>∞</sub>)<sub><small>polymer</small></sub> '''=''' C(<small>t</small>)<sub><small>polymer</small></sub> '''/''' f<sub><small>PRC lost</small></sub>'''''</big>
| |
| |- | | |- |
− | | where: | + | | Threshold || 0 |
| |- | | |- |
− | | || ''f<sub><small>PRC lost</small></sub>'' || is the fraction of the PRC lost to outward diffusion, | + | | Step Size || 0.20 |
| + | |- |
| + | | Speed (μ/sec) || 743 |
| |- | | |- |
− | | || ''C(<sub>∞</sub>)<sub><small>polymer</small></sub>'' || is the concentration of the contaminant in the polymer at equilibrium, and | + | | Peak Width (min) || 0.06 |
| |- | | |- |
− | | || ''C(<small>t</small>)<sub><small>polymer</small></sub>'' || is the concentration of the contaminant in the polymer after deployment time, t. | + | | Cycle Time (sec/cycle) || 0.57 |
− | |} | + | |} |
− | | |
− | Since investigators are commonly interested in many chemicals at the same time, it is impractical to have a PRC for each contaminant of interest. Instead, a representative set of PRCs is used to characterize the rates of polymer-environment exchange as a function of the PRCs' properties (e.g., diffusivities, partition coefficients), the sediments characteristics (e.g., porosity), and the nature of the polymer used (e.g., film thickness, affinity for the chemicals)<ref name="Fernandez2009b"/><ref name="Lampert2015"/>. The resulting mass transfer model fit can then be used to estimate the fractional approaches to equilibrium for many other contaminants, whose diffusive and partitioning properties are also known. And these fractions can be used to adjust the target chemical concentrations that have accumulated from the sediment into the same polymeric sampler to find the equilibrated results<ref name="Apell2014"/>. Finally, these equilibrated concentrations can be used in Eq. 2 to estimate truly dissolved contaminant concentrations in the sediment's porewater.
| |
− | | |
− | ==Field Applications==
| |
− | [[File: Gschwend1w2fig3.png | thumb |left| 450px | Figure 3. Passive sampler system made of polyethylene sheet loaded into an aluminum sheet metal frame, before (left), during (middle), and after (right) deployment in sediment.]]
| |
− | Polymeric materials can be deployed in sediment in various ways<ref name="Burgess2017"/>. PDMS coatings can be incorporated into slotted silica rods called SPMEs (solid phase micro extraction devices), while thin sheets of polymers like LDPE or POM can be incorporated into sheet metal frames. In both cases, such hardware is used to insert the polymers into sediment beds (Figure 3).
| |
| | | |
− | Deployment of the assembled passive samplers can be accomplished via poles from a boat<ref name="Apell2014"/>, by divers<ref name="Apell2016"/>, or by attaching the samplers to a sampling platform lowered off a vessel<ref name="Fernandez2012">Fernandez, L.A., Lao, W., Maruya, K.A., White, C., Burgess, R.M., 2012. Passive Sampling to Measure Baseline Dissolved Persistent Organic Pollutant Concentrations in the Water Column of the Palos Verdes Shelf Superfund Site. Environmental Science and Technology, 46(21), pp. 11937-11947. [https://doi.org/10.1021/es302139y DOI: 10.1021/es302139y]</ref>. Typically, the method used depends on the water depth. Small buoys on short lines, sometimes with associated water-sampling polymeric materials in mesh bags (see right panel of Figure 3), are attached to the samplers to facilitate the sampler recoveries. After recovery, the samplers are wiped to remove any adhering sediment, biofilm, or precipitates and returned to the laboratory for PRC and target contaminant analyses. The resulting measurements of the accumulated target chemical concentrations can be adjusted using the observed PRC losses and publicly available software programs<ref name="Gschwend2014">Gschwend, P.M., Tcaciuc, A.P., and Apell, J.N., 2014. Guidance Document: Passive PE Sampling in Support of In Situ Remediation of Contaminated Sediments – Passive Sampler PRC Calculation Software User’s Guide, US Department of Defense, Environmental Security Technology Certification Program Project ER-200915. Available from: [https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/Contaminated-Sediments/Bioavailability/ER-200915 ESTCP].</ref><ref name="Thompson2015">Thompson, J.M., Hsieh, C.H. and Luthy, R.G., 2015. Modeling Uptake of Hydrophobic Organic Contaminants into Polyethylene Passive Samplers. Environmental Science and Technology, 49(4), pp. 2270-2277. [https://doi.org/10.1021/es504442s DOI: 10.1021/es504442s]</ref>.
| + | The Primary HPLC-UV method uses a Phenomenex Synergi 4 µm Hydro-RP column (80Å, 250 x 4.6 mm), or comparable, and is based on both the HPLC method found in USEPA 8330B and previous work<ref name= "8330B"/><ref name="RussellEtAl2014"/><ref name="CrouchEtAl2020"/>. This separation relies on a reverse phase column and uses a gradient elution, shown in Table 2. Depending on the analyst’s needs and equipment availability, the method has been proven to work with either 0.1% TFA or 0.25% FA (vol/vol) mobile phase. Addition of a guard column like a Phenomenex SecurityGuard AQ C18 pre-column guard cartridge can be optionally used. These optional changes to the method have no impact on the method’s performance. |
| | | |
− | Subsequently, since the passive sampling reveals the concentrations of contaminants in a sediment bed's porewater and the overlying bottom water<ref name="Booij2003"/>, the data can be used to estimate bed-to-water column diffusive fluxes of contaminants<ref name="Koelmans2010">Koelmans, A.A., Poot, A., De Lange, H.J., Velzeboer, I., Harmsen, J., and van Noort, P.C.M., 2010. Estimation of In Situ Sediment-to-Water Fluxes of Polycyclic Aromatic Hydrocarbons, Polychlorobiphenyls and Polybrominated Diphenylethers. Environmental Science and Technology, 44(8), pp. 3014-3020. [https://doi.org/10.1021/es903938z DOI: 10.1021/es903938z]</ref><ref name="Fernandez2012"/> and bioirrigation-affected fluxes<ref name="Apell2018">Apell, J.N., Shull, D.H., Hoyt, A.M., and Gschwend, P.M., 2018. Investigating the Effect of Bioirrigation on In Situ Porewater Concentrations and Fluxes of Polychlorinated Biphenyls Using Passive Samplers. Environmental Science and Technology, 52(8), pp. 4565-4573. [https://doi.org/10.1021/acs.est.7b05809 DOI: 10.1021/acs.est.7b05809]</ref>. The data are also useful for assessing the tendency of the contaminants to accumulate in benthic organisms<ref name="Vinturella2004">Vinturella, A.E., Burgess, R.M., Coull, B.A., Thompson, K.M., and Shine, J.P., 2004. Use of Passive Samplers to Mimic Uptake of Polycyclic Aromatic Hydrocarbons by Benthic Polychaetes. Environmental Science and Technology, 38(4), pp. 1154-1160. [https://doi.org/10.1021/es034706f DOI: 10.1021/es034706f]</ref><ref name="Yates2011">Yates, K., Pollard, P., Davies, I.M., Webster, L., and Moffat, C.F., 2011. Application of silicone rubber passive samplers to investigate the bioaccumulation of PAHs by Nereis virens from marine sediments. Environmental Pollution, 159(12), pp. 3351-3356. [https://doi.org/10.1016/j.envpol.2011.08.038 DOI: 10.1016/j.envpol.2011.08.038]</ref><ref name="Fernandez2015">Fernandez, L.A. and Gschwend, P.M., 2015. Predicting bioaccumulation of polycyclic aromatic hydrocarbons in soft-shelled clams (Mya arenaria) using field deployments of polyethylene passive samplers. Environmental Toxicology and Chemistry, 34(5), pp. 993-1000. [https://doi.org/10.1002/etc.2892 DOI: 10.1002/etc.2892]</ref>, and by extension into food webs that include such benthic species<ref name="vonStackelberg2017">von Stackelberg, K., Williams, M.A., Clough, J., and Johnson, M.S., 2017. Spatially explicit bioaccumulation modeling in aquatic environments: Results from 2 demonstration sites. Integrated Environmental Assessment and Management, 13(6), pp. 1023-1037. [https://doi.org/10.1002/ieam.1927 DOI: 10.1002/ieam.1927]</ref>. Furthermore, recent efforts have found that passive sampling observations can be used to infer ''in situ'' transformations of substances like nitro aromatic compounds<ref name="Belles2016">Belles, A., Alary, C., Criquet, J., and Billon, G., 2016. A new application of passive samplers as indicators of in-situ biodegradation processes. Chemosphere, 164, pp. 347-354. [https://doi.org/10.1016/j.chemosphere.2016.08.111 DOI: 10.1016/j.chemosphere.2016.08.111]</ref> and DDT<ref name="Tcaciuc2018">Tcaciuc, A.P., Borrelli, R., Zaninetta, L.M., and Gschwend, P.M., 2018. Passive sampling of DDT, DDE and DDD in sediments: accounting for degradation processes with reaction–diffusion modeling. Environmental Science: Processes and Impacts, 20(1), pp. 220-231. [https://doi.org/10.1039/C7EM00501F DOI: 10.1039/C7EM00501F] Open access article available from: [https://pubs.rsc.org/--/content/articlehtml/2018/em/c7em00501f Royal Society of Chemistry].</ref>.
| + | The Secondary HPLC-UV method uses a Restek Pinnacle II Biphenyl 5 µm (150 x 4.6 mm) or comparable column and is intended as a confirmatory method. Like the Primary method, this method can use an optional guard column and utilizes a gradient elution, shown in Table 3. |
| + | |
| + | For instruments equipped with a mass spectrometer (MS), a secondary MS method is available and was developed alongside the Primary UV method. The method was designed for use with a single quadrupole MS equipped with an atmospheric pressure chemical ionization (APCI) source, such as an Agilent 6120B. A majority of the analytes shown in Table 1 are amenable to this MS method, however nitroglycerine (which is covered extensively in USEPA method 8332) and 2-,3-, and 4-nitrotoluene compounds aren’t compatible with the MS method. MS method parameters are shown in Table 4. |
| | | |
− | <br clear="left" />
| + | ==Summary== |
| + | The extraction methods and instrumental methods in this article build upon prior munitions analytical methods by adding new compounds, combining legacy and insensitive munitions analysis, and expanding usable sample matrices. These methods have been verified through extensive round robin testing and validation, and while the methods are somewhat challenging, they are crucial when simultaneous analysis of both insensitive and legacy munitions is needed. |
| | | |
| ==References== | | ==References== |
| <references /> | | <references /> |
| + | |
| ==See Also== | | ==See Also== |
− | | + | *[[Media: ERDC_TR-21-12.pdf | Preparative, Extraction, and Analytical Methods for Simultaneous Determination of Legacy and Insensitive Munition (IM) Constituents in Aqueous, Soil or Sediment, and Tissue Matrices]] |
− | [https://www.serdp-estcp.org/Tools-and-Training/Tools/PRC-Correction-Calculator A PRC Correction Calculator for LDPE deployed in sediments] | + | *[https://serdp-estcp.mil/focusareas/9f7a342a-1b13-4ce5-bda0-d7693cf2b82d/uxo#subtopics SERDP/ESTCP Focus Areas – UXO – Munitions Constituents] |
| + | *[https://denix.osd.mil/edqw/home/ Environmental Data Quality Workgroup] |
Munitions Constituents – Sample Extraction and Analytical Techniques
Munitions Constituents, including insensitive munitions (IM), are a broad category of compounds which, in areas where manufactured or used, can be found in a variety of environmental matrices (waters, soil, and tissues). This presents an analytical challenge when a variety of these munitions are to be quantified. This article discusses sample extraction methods for each typical sample matrix (high level water, low level water, soil and tissue) as well as the accompanying HPLC-UV analytical method for 27 compounds of interest (legacy munitions, insensitive munitions, and surrogates).
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- Methods for simultaneous quantification of legacy and insensitive munition (IM) constituents in aqueous, soil/sediment, and tissue matrices[2]
Introduction
Table 1. Analyte list with acronyms and CAS numbers.
Compound
|
Acronym
|
CAS Number
|
1,2-Dinitrobenzene (surrogate) |
1,2-DNB (surr.) |
528-29-0
|
1,3-Dinitrobenzene |
1,3-DNB |
99-65-0
|
1,3,5-Trinitrobenzene |
1,3,5-TNB |
99-35-4
|
1,4-Dinitrobenzene |
1,4-DNB (surr.) |
100-25-4
|
2-Amino-4,6-dinitrotoluene |
2-Am-4,6-DNT |
35572-78-2
|
2-Nitrophenol |
2-NP |
88-75-5
|
2-Nitrotoluene |
2-NT |
88-72-2
|
2,4-Dinitrophenol |
2,4-DNP |
51-28-5
|
2,4-Dinitrotoluene |
2,4-DNT |
121-14-2
|
2,4,6-Trinitrophenol |
Picric Acid (PA) |
88-89-1
|
2,4,6-Trinitrotoluene |
2,4,6-TNT |
118-96-7
|
2,6-Dinitrotoluene |
2,6-DNT |
606-20-2
|
3-Nitrotoluene |
3-NT |
99-08-1
|
3,5-Dinitroaniline |
3,5-DNA |
618-87-1
|
4-Amino-2,6-dinitrotoluene |
4-Am-2,6-DNT |
19406-51-0
|
4-Nitrophenol |
4-NP |
100-02-7
|
4-Nitrotoluene |
4-NT |
99-99-0
|
2,4-Dinitroanisole |
DNAN |
119-27-7
|
Octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine |
HMX |
2691-41-0
|
Nitrobenzene |
NB |
98-95-3
|
Nitroglycerine |
NG |
55-63-0
|
Nitroguanidine |
NQ |
556-88-7
|
3-Nitro-1,2,4-triazol-5-one |
NTO |
932-64-9
|
ortho-Nitrobenzoic acid |
o-NBA (surr.) |
552-16-9
|
Pentaerythritol tetranitrate |
PETN |
78-11-5
|
Hexahydro-1,3,5-trinitro-1,3,5-triazine |
RDX |
121-82-4
|
N-Methyl-N-(2,4,6-trinitrophenyl)nitramide |
Tetryl |
479-45-8
|
Note: Analytes in bold are not identified by EPA Method 8330B.
|
Figure 1. Primary Method labeled chromatograms
Figure 2. Secondary Method labeled chromatograms
The primary intention of the analytical methods presented here is to support the monitoring of legacy and insensitive munitions contamination on test and training ranges, however legacy and insensitive munitions often accompany each other at demilitarization facilities, manufacturing facilities, and other environmental sites. Energetic materials typically appear on ranges as small, solid particulates and due to their varying functional groups and polarities, can partition in various environmental compartments[3]. To ensure that contaminants are monitored and controlled at these sites and to sustainably manage them a variety of sample matrices (surface or groundwater, process waters, soil, and tissues) must be considered. (Process water refers to water used during industrial manufacturing or processing of legacy and insensitive munitions.) Furthermore, additional analytes must be added to existing methodologies as the usage of IM compounds changes and as new degradation compounds are identified. Of note, relatively new IM formulations containing NTO, DNAN, and NQ are seeing use in IMX-101, IMX-104, Pax-21 and Pax-41 (Table 1)[4][5].
Sampling procedures for legacy and insensitive munitions are identical and utilize multi-increment sampling procedures found in USEPA Method 8330B Appendix A[1]. Sample hold times, subsampling and quality control requirements are also unchanged. The key differences lie in the extraction methods and instrumental methods. Briefly, legacy munitions analysis of low concentration waters uses a single cartridge reverse phase SPE procedure, and acetonitrile (ACN) is used for both extraction and elution for aqueous and solid samples[1][6]. An isocratic separation via reversed-phase C-18 column with 50:50 methanol:water mobile phase or a C-8 column with 15:85 isopropanol:water mobile phase is used to separate legacy munitions[1]. While these procedures are sufficient for analysis of legacy munitions, alternative solvents, additional SPE cartridges, and a gradient elution are all required for the combined analysis of legacy and insensitive munitions.
Previously, analysis of legacy and insensitive munitions required multiple analytical techniques, however the methods presented here combine the two munitions categories resulting in an HPLC-UV method and accompanying extraction methods for a variety of common sample matrices. A secondary HPLC-UV method and a HPLC-MS method were also developed as confirmatory methods. The methods discussed in this article were validated extensively by single-blind round robin testing and subsequent statistical treatment as part of ESTCP ER19-5078. Wherever possible, the quality control criteria in the Department of Defense Quality Systems Manual for Environmental Laboratories were adhered to[7]. Analytes included in the methods presented here are found in Table 1.
The chromatograms produced by the primary and secondary HPLC-UV methods are shown in Figure 1 and Figure 2, respectively. Chromatograms for each detector wavelength used are shown (315, 254, and 210 nm).
Figure 3. Triple cartridge SPE setup
Figure 4. A flow chart of the soil extraction procedure
High Concentration Waters (> 1 ppm)
Aqueous samples suspected to contain the compounds of interest at concentrations detectable without any extraction or pre-concentration are suitable for analysis by direct injection. The method deviates from USEPA Method 8330B by adding a pH adjustment and use of MeOH rather than ACN for dilution[1]. The pH adjustment is needed to ensure method accuracy for ionic compounds (like NTO or PA) in basic samples. A solution of 1% HCl/MeOH is added to both acidify and dilute the samples to a final acid concentration of 0.5% (vol/vol) and a final solvent ratio of 1:1 MeOH/H2O. The direct injection samples are then ready for analysis.
Low Concentration Waters (< 1 ppm)
Aqueous samples suspected to contain the compounds of interest at low concentrations require extraction and pre-concentration using solid phase extraction (SPE). The SPE setup described here uses a triple cartridge setup shown in Figure 3. Briefly, the extraction procedure loads analytes of interest onto the cartridges in this order: StrataTM X, StrataTM X-A, and Envi-CarbTM. Then the cartridge order is reversed, and analytes are eluted via a two-step elution, resulting in 2 extracts (which are combined prior to analysis). Five milliliters of MeOH is used for the first elution, while 5 mL of acidified MeOH (2% HCl) is used for the second elution. The particular SPE cartridges used are noncritical so long as cartridge chemistries are comparable to those above.
Table 2. Primary HPLC-UV mobile phase gradient method concentrations
Method run time = 48 minutes; Column temperature = 25°C Injection volume = 50 μL; Flow rate = 1.0 mL/min Detector wavelengths = 210, 254, and 310 nm
|
Time (min)
|
Reagent Water (%)
|
MeOH (%)
|
0.1% TFA/Water (%)
|
ACN (%)
|
0.00 |
89 |
3 |
3 |
5
|
2.00 |
89 |
3 |
3 |
5
|
2.20 |
52 |
40 |
3 |
5
|
12.5 |
52 |
40 |
3 |
5
|
19.0 |
57 |
35 |
3 |
5
|
28.0 |
48 |
44 |
3 |
5
|
32.0 |
48 |
44 |
3 |
5
|
44.0 |
32 |
60 |
3 |
5
|
44.1 |
89 |
3 |
3 |
5
|
48.0 |
89 |
3 |
3 |
5
|
Soils
Soil collection, storage, drying and grinding procedures are identical to the USEPA Method 8330B procedures[1]; however, the solvent extraction procedure differs in the number of sonication steps, sample mass and solvent used. A flow chart of the soil extraction procedure is shown in Figure 4. Soil masses of approximately 2 g and a sample to solvent ratio of 1:5 (g/mL) are used for soil extraction. The extraction is carried out in a sonication bath chilled below 20 ⁰C and is a two-part extraction, first extracting in MeOH (6 hours) followed by a second sonication in 1:1 MeOH:H2O solution (14 hours). The extracts are centrifuged, and the supernatant is filtered through a 0.45 μm PTFE disk filter.
The solvent volume should generally be 10 mL but if different soil masses are required, solvent volume should be 5 mL/g. The extraction results in 2 separate extracts (MeOH and MeOH:H2O) that are combined prior to analysis.
Tissues
Tissue matrices are extracted by 18-hour sonication using a ratio of 1 gram of wet tissue per 5 mL of MeOH. This extraction is performed in a sonication bath chilled below 20 ⁰C and the supernatant (MeOH) is filtered through a 0.45 μm PTFE disk filter.
Due to the complexity of tissue matrices, an additional tissue cleanup step, adapted from prior research, can be used to reduce interferences[8][2]. The cleanup procedure uses small scale chromatography columns prepared by loading 5 ¾” borosilicate pipettes with 0.2 g activated silica gel (100–200 mesh). The columns are wetted with 1 mL MeOH, which is allowed to fully elute and then discarded prior to loading with 1 mL of extract and collecting in a new amber vial. After the extract is loaded, a 1 mL aliquot of MeOH followed by a 1 mL aliquot of 2% HCL/MeOH is added. This results in a 3 mL silica treated tissue extract. This extract is vortexed and diluted to a final solvent ratio of 1:1 MeOH/H2O before analysis.
HPLC-UV and HPLC-MS Methods
Table 3. Secondary HPLC-UV mobile phase gradient method concentrations
Method run time = 43 minutes; Column temperature = 25°C Injection volume = 50 μL; Flow rate = 0.8 mL/min Detector wavelengths = 210, 254, and 310 nm
|
Time (min)
|
Reagent Water (%)
|
MeOH (%)
|
0.1% TFA/Water (%)
|
ACN (%)
|
0.00 |
75 |
10 |
10 |
5
|
2.50 |
75 |
10 |
10 |
5
|
2.60 |
39 |
46 |
10 |
5
|
9.00 |
39 |
46 |
10 |
5
|
9.10 |
33.5 |
51.5 |
10 |
5
|
15.00 |
35 |
50 |
10 |
5
|
15.10 |
43 |
42 |
10 |
5
|
33.00 |
30 |
55 |
10 |
5
|
33.10 |
75 |
10 |
10 |
5
|
43.00 |
75 |
10 |
10 |
5
|
Table 4. Ionization source and detector parameters
Parameter
|
Value
|
Ionization Source |
APCI
|
Ionization Mode |
Negative
|
Drying Gas Temperature (°C) |
350
|
Vaporizer Temperature (°C) |
325
|
Drying Gas Flow (L/min) |
4.0
|
Nebulizer Pressure (psig) |
40
|
Corona Current (μA) |
10
|
Capillary Potential (V) |
1500
|
Mass Range |
40 – 400
|
Fragmentor |
100
|
Gain |
1
|
Threshold |
0
|
Step Size |
0.20
|
Speed (μ/sec) |
743
|
Peak Width (min) |
0.06
|
Cycle Time (sec/cycle) |
0.57
|
The Primary HPLC-UV method uses a Phenomenex Synergi 4 µm Hydro-RP column (80Å, 250 x 4.6 mm), or comparable, and is based on both the HPLC method found in USEPA 8330B and previous work[1][8][2]. This separation relies on a reverse phase column and uses a gradient elution, shown in Table 2. Depending on the analyst’s needs and equipment availability, the method has been proven to work with either 0.1% TFA or 0.25% FA (vol/vol) mobile phase. Addition of a guard column like a Phenomenex SecurityGuard AQ C18 pre-column guard cartridge can be optionally used. These optional changes to the method have no impact on the method’s performance.
The Secondary HPLC-UV method uses a Restek Pinnacle II Biphenyl 5 µm (150 x 4.6 mm) or comparable column and is intended as a confirmatory method. Like the Primary method, this method can use an optional guard column and utilizes a gradient elution, shown in Table 3.
For instruments equipped with a mass spectrometer (MS), a secondary MS method is available and was developed alongside the Primary UV method. The method was designed for use with a single quadrupole MS equipped with an atmospheric pressure chemical ionization (APCI) source, such as an Agilent 6120B. A majority of the analytes shown in Table 1 are amenable to this MS method, however nitroglycerine (which is covered extensively in USEPA method 8332) and 2-,3-, and 4-nitrotoluene compounds aren’t compatible with the MS method. MS method parameters are shown in Table 4.
Summary
The extraction methods and instrumental methods in this article build upon prior munitions analytical methods by adding new compounds, combining legacy and insensitive munitions analysis, and expanding usable sample matrices. These methods have been verified through extensive round robin testing and validation, and while the methods are somewhat challenging, they are crucial when simultaneous analysis of both insensitive and legacy munitions is needed.
References
- ^ 1.0 1.1 1.2 1.3 1.4 1.5 1.6 United States Environmental Protection Agency (USEPA), 2006. EPA Method 8330B (SW-846) Nitroaromatics, Nitramines, and Nitrate Esters by High Performance Liquid Chromatography (HPLC), Revision 2. USEPA Website EPA Method 8330b
- ^ 2.0 2.1 2.2 Crouch, R.A., Smith, J.C., Stromer, B.S., Hubley, C.T., Beal, S., Lotufo, G.R., Butler, A.D., Wynter, M.T., Russell, A.L., Coleman, J.G., Wayne, K.M., Clausen, J.L., Bednar, A.J., 2020. Methods for simultaneous determination of legacy and insensitive munition (IM) constituents in aqueous, soil/sediment, and tissue matrices. Talanta, 217, Article 121008. doi: 10.1016/j.talanta.2020.121008 Open Access Manuscript.pdf
- ^ 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
- ^ Mainiero, C. 2015. Picatinny Employees Recognized for Insensitive Munitions. U.S. Army, Picatinny Arsenal Public Affairs. Open Access Press Release
- ^ Frem, D., 2022. A Review on IMX-101 and IMX-104 Melt-Cast Explosives: Insensitive Formulations for the Next-Generation Munition Systems. Propellants, Explosives, Pyrotechnics, 48(1), e202100312. doi: 10.1002/prep.202100312
- ^ United States Environmental Protection Agency (USEPA), 2007. EPA Method 3535A (SW-846) Solid-Phase Extraction (SPE), Revision 1. USEPA Website Method 3535A.pdf
- ^ US Department of Defense and US Department of Energy, 2021. Consolidated Quality Systems Manual (QSM) for Environmental Laboratories, Version 5.4. 387 pages. Free Download QSM Version 5.4.pdf
- ^ 8.0 8.1 Russell, A.L., Seiter, J.M., Coleman, J.G., Winstead, B., Bednar, A.J., 2014. Analysis of munitions constituents in IMX formulations by HPLC and HPLC-MS. Talanta, 128, pp. 524–530. doi: 10.1016/j.talanta.2014.02.013
See Also