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==Downscaled High Resolution Datasets for Climate Change Projections==
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==''In Situ'' Toxicity Identification Evaluation (iTIE)==  
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Global climate models (GCMs) have generated projections of temperature, precipitation and other important climate change parameters with spatial resolutions of 100 to 300 km. However, higher spatial resolution information is required to assess threats to individual installations or regions.  A variety of “downscaling” approaches have been used to produce high spatial resolution output (datasets) from the global climate models at scales that are useful for evaluating potential threats to critical infrastructure at regional and local scales. These datasets enable development of information about projections produced from various climate models, about downscaling to achieve desired locational specificity, and about selecting the appropriate dataset(s) to use for performing specific assessments.  This article describes how these datasets can be accessed and used to evaluate potential climate change impacts.
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The ''in situ'' Toxicity Identification Evaluation system is a tool to incorporate in weight-of-evidence studies at sites with numerous chemical toxicant classes present. The technology works by continuously sampling site water, immediately fractionating the water using diagnostic sorptive resins, and then exposing test organisms to the water to observe toxicity responses with minimal sample manipulation. It is compatible with various resins, test organisms, and common acute and chronic toxicity tests, and can be deployed at sites with a wide variety of physical and logistical considerations.
 
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
 
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
  
 
'''Related Article(s):'''
 
'''Related Article(s):'''
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* [[Climate Change Primer]]
 
  
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'''Contributor(s):''' [[Dr. Rao Kotamarthi]]
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*[[Contaminated Sediments - Introduction]]
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*[[Contaminated Sediment Risk Assessment]]
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*[[Passive Sampling of Sediments]]
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*[[Sediment Porewater Dialysis Passive Samplers for Inorganics (Peepers)]]
  
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'''Key Resource(s):'''
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'''Contributors:''' Dr. G. Allen Burton Jr., Austin Crane
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* Use of Climate Information for Decision-Making and Impacts Research: State of our Understanding<ref name="Kotamarthi2016">Kotamarthi, R., Mearns, L., Hayhoe, K., Castro, C.L., and Wuebble, D., 2016. Use of Climate Information for Decision-Making and Impacts Research: State of Our Understanding. Department of Defense, Strategic Environmental Research and Development Program (SERDP), 55pp. Free download from: [https://www.serdp-estcp.org/content/download/38568/364489/file/Use_of_Climate_Information_for_Decision-Making_Technical_Report.pdf SERDP-ESTCP]</ref>
 
  
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* Applying Climate Change Information to Hydrologic and Coastal Design of Transportation Infrastructure, Design Practices<ref name="Kilgore2019">Kilgore, R., Thomas, W.O. Jr., Douglass, S., Webb, B., Hayhoe, K., Stoner, A., Jacobs, J.M., Thompson, D.B., Herrmann, G.R., Douglas, E., and Anderson, C., 2019.  Applying Climate Change Information to Hydrologic and Coastal Design of Transportation Infrastructure, Design Practices. The National Cooperative Highway Research Program, Transportation Research Board, Project 15-61, 154 pages. Free download from: [http://onlinepubs.trb.org/Onlinepubs/nchrp/docs/NCHRP1561_DesignProcedures.pdf The Transportation Research Board]</ref>
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'''Key Resources:'''
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*A Novel In Situ Toxicity Identification Evaluation (iTIE) System for Determining which Chemicals Drive Impairments at Contaminated Sites<ref name="BurtonEtAl2020">Burton, G.A., Cervi, E.C., Meyer, K., Steigmeyer, A., Verhamme, E., Daley, J., Hudson, M., Colvin, M., Rosen, G., 2020. A novel In Situ Toxicity Identification Evaluation (iTIE) System for Determining which Chemicals Drive Impairments at Contaminated Sites. Environmental Toxicology and Chemistry, 39(9), pp. 1746-1754. [https://doi.org/10.1002/etc.4799 doi: 10.1002/etc.4799]</ref>
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*An in situ toxicity identification and evaluation water analysis system: Laboratory validation<ref name="SteigmeyerEtAl2017">Steigmeyer, A.J., Zhang, J., Daley, J.M., Zhang, X., Burton, G.A. Jr., 2017. An in situ toxicity identification and evaluation water analysis system: Laboratory validation. Environmental Toxicology and Chemistry, 36(6), pp. 1636-1643. [https://doi.org/10.1002/etc.3696 doi: 10.1002/etc.3696]</ref>
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*Sediment Toxicity Identification Evaluation (TIE) Phases I, II, and III Guidance Document<ref>United States Environmental Protection Agency, 2007.  Sediment Toxicity Identification Evaluation (TIE) Phases I, II, and III Guidance Document, EPA/600/R-07/080. 145 pages. [https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=P1003GR1.txt Free Download]&nbsp; [[Media: EPA2007.pdf | Report.pdf]]</ref>
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*In Situ Toxicity Identification Evaluation (iTIE) Technology for Assessing Contaminated Sediments, Remediation Success, Recontamination and Source Identification<ref>In Situ Toxicity Identification Evaluation (iTIE) Technology for Assessing Contaminated Sediments, Remediation Success, Recontamination and Source Identification [https://serdp-estcp.mil/projects/details/88a8f9ba-542b-4b98-bfa4-f693435535cd/er18-1181-project-overview Project Website]&nbsp; [[Media: ER18-1181Ph.II.pdf | Final Report.pdf]]</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]&nbsp;&nbsp; ISBN: 978-1-107-06605-2</ref>
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==Introduction==
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In waterways impacted by numerous naturally occurring and anthropogenic chemical stressors, it is crucial for environmental practitioners to be able to identify which chemical classes are causing the highest degrees of toxicity to aquatic life. Previously developed methods, including the Toxicity Identification Evaluation (TIE) protocol developed by the US Environmental Protection Agency (EPA)<ref>Norberg-King, T., Mount, D.I., Amato, J.R., Jensen, D.A., Thompson, J.A., 1992. Toxicity identification evaluation: Characterization of chronically toxic effluents: Phase I. Publication No. EPA/600/6-91/005F. U.S. Environmental Protection Agency, Office of Research and Development. [https://www.epa.gov/sites/default/files/2015-09/documents/owm0255.pdf Free Download from US EPA]&nbsp; [[Media: usepa1992.pdf | Report.pdf]]</ref>, can be confounded by sample manipulation artifacts and temporal limitations of ''ex situ'' organism exposures<ref name="BurtonEtAl2020"/>. These factors may disrupt causal linkages and mislead investigators during site characterization and management decision-making. The ''in situ'' Toxicity Identification Evaluation (iTIE) technology was developed to allow users to strengthen stressor-causality linkages and rank chemical classes of concern at impaired sites, with high degrees of ecological realism.
  
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* Downscaling Techniques for High-Resolution Climate Projections: From Global Change to Local Impacts<ref name="Kotamarthi2021">Kotamarthi, R., Hayhoe, K., Wuebbles, D., Mearns, L.O., Jacobs, J. and Jurado, J., 2021. Downscaling Techniques for High-Resolution Climate Projections: From Global Change to Local Impacts. Cambridge University Press, Cambridge, UK. 202 pages. [https://doi.org/10.1017/9781108601269 DOI: 10.1017/9781108601269]&nbsp;&nbsp; ISBN: 978-1-108-47375-0</ref>
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The technology has undergone a series of improvements in recent years, with the most recent prototype being robust, operable in a wide variety of site conditions, and cost-effective compared to alternative site characterization methods<ref>Burton, G.A. Jr., Nordstrom, J.F., 2004. An in situ toxicity identification evaluation method part I: Laboratory validation. Environmental Toxicology and Chemistry, 23(12), pp. 2844-2850. [https://doi.org/10.1897/03-409.1 doi: 10.1897/03-409.1]</ref><ref>Burton, G.A. Jr., Nordstrom, J.F., 2004. An in situ toxicity identification evaluation method part II: Field validation. Environmental Toxicology and Chemistry, 23(12), pp. 2851-2855. [https://doi.org/10.1897/03-468.1 doi: 10.1897/03-468.1]</ref><ref name="BurtonEtAl2020"/><ref name="SteigmeyerEtAl2017"/>. The latest prototype can be used in any of the following settings: in marine, estuarine, or freshwater sites; to study surface water or sediment pore water; in shallow waters easily accessible by foot or in deep waters only accessible by pier or boat. It can be used to study sites impacted by a wide variety of stressors including ammonia, [[Metal and Metalloid Contaminants | metals]], pesticides, polychlorinated biphenyls (PCB), [[Polycyclic Aromatic Hydrocarbons (PAHs) | polycyclic aromatic hydrocarbons (PAH)]], and [[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) | per- and polyfluoroalkyl substances (PFAS)]], among others. The technology is applicable to studies of acute toxicity via organism survival or of chronic toxicity via responses in growth, reproduction, or gene expression<ref name="BurtonEtAl2020"/>.
  
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==Downscaling of Global Climate Models==
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==System Components and Validation==
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Some communities and businesses have begun to improve their resilience to climate change by building adaptation plans based on national scale climate datatsets ([https://unfccc.int/topics/adaptation-and-resilience/workstreams/national-adaptation-plans National Adaptation Plans]), regional datasets ([https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State Flood Risk Management Guidance]<ref name="NYDEC2020">New York State Department of Environmental Conservation, 2020. New York State Flood Risk Management Guidance for Implementation of the Community Risk and Resiliency Act. Free download from: [https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State]&nbsp;&nbsp; [[Media: NewYorkState2020.pdf | Report.pdf]]</ref>), and datasets generated at local spatial resolutions.  Resilience to the changing climate has also been identified by the US Department of Defense (DoD) as a necessary part of the installation planning and basing process ([https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD Report on Effects of a Changing Climate]<ref name="DoD2019">US Department of Defense, 2019. Report on Effects of a Changing Climate to the Department of Defense. Free download from: [https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD]&nbsp;&nbsp; [[Media: DoD2019.pdf | Report.pdf]]</ref>). More than 79 installations were identified as facing potential threats from climate change. The threats faced due to changing climate include recurrent flooding, droughts, desertification, wildfires and thawing permafrost.  
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[[File: CraneFig1.png | thumb | 600 px | Figure 1: A schematic diagram of the iTIE system prototype. The system is divided into three sub-systems: 1) the Pore Water/Surface Water Collection Sub-System (blue); 2) the Pumping Sub-System (red); and 3) the iTIE Resin, Exposure, and Sampling Sub-System (green). Water first enters the system through the Pore Water/Surface Water Collection Sub-System. Porewater can be collected using Trident-style probes, or surface water can be collected using a simple weighted probe. The water is composited in a manifold before being pumped to the rest of the iTIE system by the booster pump. Once in the iTIE Resin, Exposure, and Sampling Sub-System, the water is gently oxygenated by the Oxygen Coil, separated from gas bubbles by the Drip Chamber, and diverted to separate iTIE Resin and Exposure Chambers (or iTIE units) by the Splitting Manifold. Water movement through each iTIE unit is controlled by a dedicated Regulation Pump. Finally, the water is gathered in Sample Collection bottles for analysis.]]
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The&nbsp;latest&nbsp;iTIE&nbsp;prototype consists of an array of sorptive resins that differentially fractionate sampled water, and a series of corresponding flow-through organism chambers that receive the treated water ''in situ''. Resin treatments can be selected depending on the chemicals suspected to be present at each site to selectively sequester certain chemical of concern (CoC) classes from the whole water, leaving a smaller subset of chemicals in the resulting water fraction for chemical and toxicological characterization. Test organism species and life stages can also be chosen depending on factors including site characteristics and study goals. In the full iTIE protocol, site water is continuously sampled either from the sediment pore spaces or the water column at a site, gently oxygenated, diverted to different iTIE units for fractionation and organism exposure, and collected in sample bottles for off-site chemical analysis (Figure 1). All iTIE system components are housed within waterproof Pelican cases, which allow for ease of transport and temperature control.
  
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Assessing the threats climate change poses at regional and local scales requires data with higher spatial resolution than is currently available from global climate models. Global-scale climate models typically have spatial resolutions of 100 to 300 km, and output from these models needs to be spatially and/or temporally disaggregated in order to be useful in performing assessments at smaller scales. The process of producing higher spatial-temporal resolution climate model output from coarser global climate model outputs is referred to as “downscaling” and results in climate change projections (datasets) at scales that are useful for evaluating potential threats to regional and local communities and businesses. These datasets provide information on temperature, precipitation and a variety of other climate variables for current and future climate conditions under various greenhouse gas (GHG) emission scenarios. There are a variety of web-based tools available for accessing these datasets to evaluate potential climate change impacts at regional and local scales.
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===Porewater and Surface Water Collection Sub-system===
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[[File: CraneFig2.png | thumb | 600 px | Figure 2: a) Trident probe with auxiliary sensors attached, b) a Trident probe with end caps removed (the red arrow identifies the intermediate space where glass beads are packed to filter suspended solids), c) a Trident probe being installed using a series of push poles and a fence post driver]]
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Given&nbsp;the&nbsp;importance&nbsp;of sediment porewater to ecosystem structure and function, investigators may employ the iTIE system to evaluate the toxic effects associated with the impacted sediment porewater. To accomplish this, the iTIE system utilizes the Trident probe, originally developed for Department of Defense site characterization studies<ref>Chadwick, D.B., Harre, B., Smith, C.F., Groves, J.G., Paulsen, R.J., 2003. Coastal Contaminant Migration Monitoring: The Trident Probe and UltraSeep System. Hardware Description, Protocols, and Procedures. Technical Report 1902. Space and Naval Warfare Systems Center.</ref>. The main body of the Trident is comprised of a stainless-steel frame with six hollow probes (Figure 2). Each probe contains a layer of inert glass beads, which filters suspended solids from the sampled water. The water is drawn through each probe into a composite manifold and transported to the rest of the iTIE system using a high-precision peristaltic pump.  
  
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==Methods for Downscaling==
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The Trident also includes an adjustable stopper plate, which forms a seal against the sediment and prevents the inadvertent dilution of porewater samples with surface water. (Figure 2). Preliminary laboratory results indicate that the Trident is extremely effective in collecting porewater samples with minimal surface water infiltration in sediments ranging from coarse sand to fine clay. Underwater cameras, sensors, passive samplers, and other auxiliary equipment can be attached to the Trident probe frame to provide supplemental data.
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{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
 
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|+Table 1.  Two widely used methods for developing downscaled higher resolution climate model projections
 
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|-
 
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!Dynamical Downscaling
 
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!Statistical Downscaling
 
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|-
 
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|Deterministic climate change simulations that output</br>many climate variables with sub-daily information ||Primarily limited to daily temperature and precipitation
 
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|-
 
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|Computationally expensive; hence, limited number of simulations – both</br>GHG emission scenarios and global climate models downscaled||Computationally efficient; hence, downscaled data typically</br>available for many different global climate models and GHG emission scenarios
 
−
|-
 
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|May require additional bias correction||Method incorporates bias correction
 
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|-
 
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|Observational data at the downscaled location are not necessary</br>to obtain the downscaled output at the location||Best suited for locations with 30 years or more of observational data
 
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|-
 
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|Does not assume stationarity or in other words the model</br>simulates the future regardless of what has happened in the past||Stationarity assumption - assumes that the statistical relationship between global</br>climate model and observations will remain constant in the future
 
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|}
 
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There are two main approaches to downscaling. One method, commonly referred to as “statistical downscaling”, uses the empirical-statistical relationships between large-scale weather phenomena and historical local weather data. In this method, these statistical relationships are applied to output generated by global climate models. A second method uses physics-based numerical models (regional-scale climate models or RCMs) of weather and climate that operate over a limited region of the earth (e.g., North America) and at spatial resolutions that are typically 3 to 10 times finer than the global-scale climate models. This method is known as “dynamical downscaling”.  These regional-scale climate models are similar to the global models with respect to their reliance on the principles of physics, but because they operate over only part of the earth, they require information about what is coming in from the rest of the earth as well as what is going out of the limited region of the model. This is generally obtained from a global model.  The primary differences between statistical and dynamical downscaling methods are summarized in Table 1.
 
  
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It is important to realize that there is no “best” downscaling method or dataset, and that the best method/dataset for a given problem depends on that problem’s specific needs. Several data products based on downscaling higher level spatial data are available ([https://cida.usgs.gov/gdp/ USGS], [http://maca.northwestknowledge.net/ MACA], [https://www.narccap.ucar.edu/ NARCCAP], [https://na-cordex.org/ CORDEX-NA]). The appropriate method and dataset to use depends on the intended application. The method selected should be able to credibly resolve spatial and temporal scales relevant for the application. For example, to develop a risk analysis of frequent flooding, the data product chosen should include precipitation at greater than a diurnal frequency and over multi-decadal timescales. This kind of product is most likely to be available using the dynamical downscaling method.  SERDP reviewed the various advantages and disadvantages of using each type of downscaling method and downscaling dataset, and developed a recommended process that is publicly available<ref name="Kotamarthi2016"/>. In general, the following recommendations should be considered in order to pick the right downscaled dataset for a given analysis:
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Alternatively, practitioners may employ the iTIE system to evaluate site surface water. To sample surface water, weighted intake tubes can collect surface water from the water column using a peristaltic pump.
  
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* When a problem depends on using a large number of climate models and emission scenarios to perform preliminary assessments and to understand the uncertainty range of projections, then using a statistical downscaled dataset is recommended.
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===Oxygen Coil, Overflow Bag and Drip Chamber===
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* When the assessment needs a more extensive parameter list or is analyzing a region with few long-term observational data, dynamically downscaled climate change projections are recommended.  
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[[File: CraneFig3.png | thumb | left | 400 px | Figure 3. Contents of the iTIE system cooler. The pictured HDPE rack (47.6 cm length x 29.7 cm width x 33.7 cm height) is removable from the iTIE cooler. Water enters the system at the red circle, flows through the oxygen coil, and then travels to each of the individual iTIE units where diagnostic resins and organisms are located. The water then briefly leaves the cooler to travel through peristaltic regulation pumps before being gathered in sample collection bottles.]]
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Porewater&nbsp;is&nbsp;naturally&nbsp;anoxic due to limited mixing with aerated surface water and high oxygen demand of sediments, which may cause organism mortality and interfere with iTIE results. To preclude this, sampled porewater is exposed to an oxygen coil. This consists of an interior silicone tube connected to a pressurized oxygen canister, threaded through an exterior reinforced PVC tube through which water is slowly pumped (Figure 3). Pump rates are optimized to ensure adequate aeration of the water. In addition to elevating DO levels, the oxygen coil facilitates the oxidation of dissolved sulfides, which naturally occur in some marine sediments and may otherwise cause toxicity to organisms if left in its reduced form.
  
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==Uncertainty in Projections==
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Gas bubbles may form in the oxygen coil over the course of a deployment. These can be disruptive, decreasing water sample volumes and posing a danger to sensitive organisms like daphnids. To account for this, the water travels to a drip chamber after exiting the oxygen coil, which allows gas bubbles to be separated and diverted to an overflow system. The sample water then flows to a manifold which divides the flow into different paths to each of the treatment units for fractionation and organism exposure.
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{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
 
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|+Table 2.  Downscaling model characteristics and output<ref name="Kotamarthi2016"/>
 
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|-
 
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!Model or</br>Dataset Name
 
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!Model<br />Method
 
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!Output<br />Variables
 
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!Output<br />Format
 
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!Spatial</br>Resolution
 
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!Time</br>Resolution
 
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|-
 
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| colspan="6" style="text-align: left; background-color:white;" |'''Statistical Downscaled Datasets'''
 
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|-
 
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| [https://worldclim.org/data/index.html WorldClim]<ref name="Hijmans2005">Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. and Jarvis, A., 2005. Very High Resolution Interpolated Climate Surfaces for Global Land Areas. International Journal of Climatology: A Journal of the Royal Meteorological Society, 25(15), pp 1965-1978.  [https://doi.org/10.1002/joc.1276 DOI: 10.1002/joc.1276]</ref>
 
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|Delta||T(min, max,</br>avg), Pr||NetCDF||grid: 30 arc sec to</br>10 arc min||month
 
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|-
 
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| Bias Corrected / Spatial</br>Disaggregation (BCSD)<ref name="Wood2002">Wood, A.W., Maurer, E.P., Kumar, A. and Lettenmaier, D.P., 2002. Long‐range experimental hydrologic forecasting for the eastern United States. Journal of Geophysical Research: Atmospheres, 107(D20), 4429, pp. ACL6 1-15. [https://doi.org/10.1029/2001JD000659 DOI:10.1029/2001JD000659]&nbsp;&nbsp; Free access article available from: [https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2001JD000659 American Geophysical Union]&nbsp;&nbsp; [[Media: Wood2002.pdf | Report.pdf ]]</ref>
 
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|Empirical Quantile</br>Mapping||Runoff,</br>Streamflow||NetCDF||grid: 7.5 arc min||day
 
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|-
 
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| [https://cida.usgs.gov/thredds/catalog.html?dataset=dcp Asynchronous Regional Regression</br>Model (ARRM v.1)]<ref name="Stoner2013">Stoner, A.M., Hayhoe, K., Yang, X., and Wuebbles, D.J., 2013. An Asynchronous Regional Regression Model for Statistical Downscaling of Daily Climate Variables. International Journal of Climatology, 33(11), pp. 2473-2494.  [https://doi.org/10.1002/joc.3603 DOI:10.1002/joc.3603]</ref>
 
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|Parameterized</br>Quantile Mapping||T(min, max), Pr||NetCDF||stations plus</br>grid: 7.5 arc min||day
 
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|-
 
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| [https://sdsm.org.uk/ Statistical Downscaling Model (SDSM)]<ref name="Wilby2013">Wilby, R.L., and Dawson, C.W., 2013. The Statistical DownScaling Model: insights from one decade of application. International Journal of Climatology, 33(7), pp. 1707-1719. [https://doi.org/10.1002/joc.3544 DOI: 10.1002/joc.3544]</ref>
 
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|Weather Generator||T(min, max), Pr||PC Code||stations||day
 
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|-
 
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| [https://climate.northwestknowledge.net/MACA/ Multivariate Adaptive</br>Constructed Analogs (MACA)]<ref name="Hidalgo2008">Hidalgo, H.G., Dettinger, M.D. and Cayan, D.R., 2008. Downscaling with Constructed Analogues: Daily Precipitation and Temperature Fields Over the United States. California Energy Commission PIER Final Project, Report CEC-500-2007-123. [[Media: Hidalgo2008.pdf | Report.pdf]]</ref>
 
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|Constructed Analogues||10 Variables||NetCDF||grid: 2.5 arc min||day
 
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|-
 
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| [http://loca.ucsd.edu/ Localized Constructed</br>Analogs (LOCA)]<ref name="Pierce2013">Pierce, D.W., Cayan, D.R. and Thrasher, B.L., 2014. Statistical Downscaling Using Localized Constructed Analogs (LOCA). Journal of Hydrometeorology, 15(6), pp. 2558-2585. [https://doi.org/10.1175/JHM-D-14-0082.1 DOI: 10.1175/JHM-D-14-0082.1]&nbsp;&nbsp; Free access article available from: [https://journals.ametsoc.org/view/journals/hydr/15/6/jhm-d-14-0082_1.xml American Meteorological Society].&nbsp;&nbsp; [[Media: Pierce2014.pdf | Report.pdf]]</ref>
 
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|Constructed Analogues||T(min, max), Pr||NetCDF||grid: 3.75 arc min||day
 
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|-
 
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| [https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-dcp30 NASA Earth Exchange Downscaled</br>Climate Projections (NEX-DCP30)]<ref name="Wood2002"/>
 
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|Bias Correction /</br>Spatial Disaggregation||T(min, max), Pr||NetCDF||grid: 30 arc sec||month
 
−
|-
 
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| colspan="6" style="text-align: left; background-color:white;" |'''Dynamical Downscaled Datasets'''
 
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|-
 
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| [http://www.narccap.ucar.edu/index.html North American Regional Climate</br>Change Assessment Program (NARCCAP)]<ref name="Mearns2009">Mearns, L.O., Gutowski, W., Jones, R., Leung, R., McGinnis, S., Nunes, A. and Qian, Y., 2009. A Regional Climate Change Assessment Program for North America. Eos, Transactions, American Geophysical Union, 90(36), p.311.  [https://doi.org/10.1029/2009EO360002 DOI: 10.1029/2009EO360002]&nbsp;&nbsp; Free access article from: [https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2009EO360002 American Geophysical Union]&nbsp;&nbsp; [[Media: Mearns2009.pdf  | Report.pdf]]</ref>
 
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|Multiple Models||49 Variables||NetCDF||grid: 30 arc min||3 hours
 
−
|-
 
−
| [https://cordex.org/about/ Coordinated Regional Climate</br>Downscaling Experiment (CORDEX)]<ref name="Giorgi2009">Giorgi, F., Jones, C., and Asrar, G.R., 2009. Addressing climate information needs at the regional level: the CORDEX framework. World Meteorological Organization (WMO) Bulletin, 58(3), pp. 175-183. Free access article from: [https://public.wmo.int/en/bulletin/addressing-climate-information-needs-regional-level-cordex-framework World Meteorological Organization]&nbsp;&nbsp; [[Media: Giorgi2009.pdf | Report.pdf]]</ref>
 
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|Multiple Models||66 Variables||NetCDF||grid: 30 arc min||3 hours
 
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|-
 
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| [https://esrl.noaa.gov/gsd/wrfportal/ Strategic Environmental Research and</br>Development Program (SERDP)]<ref name="Wang2015">Wang, J., and Kotamarthi, V.R., 2015. High‐resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America. Earth's Future, 3(7), pp. 268-288.  [https://doi.org/10.1002/2015EF000304 DOI: 10.1002/2015EF000304]&nbsp;&nbsp; Free access article from: [https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2015EF000304 American Geophysical Union]&nbsp;&nbsp; [[Media: Wang2015.pdf | Report.pdf]]</ref>
 
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|Weather Research and</br>Forecasting (WRF v3.3)||80+ Variables||NetCDF||grid: 6.5 arc min||3 hours
 
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|}
 
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A primary cause of uncertainty in climate change projections, especially beyond 30 years into the future, is the uncertainty in the greenhouse gas (GHG) emission scenarios used to make climate model projections. The best method of accounting for this type of uncertainty is to apply a climate change model to multiple GHG emission scenarios (see also: [[Wikipedia: Representative Concentration Pathway]]).  
 
  
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The uncertainties in climate projections over shorter timescales, less than 30 years out, are dominated by something known as “internal variability” in the models. Different approaches are used to address the uncertainty from internal variability<ref name="Kotamarthi2021"/>. A third type of uncertainty in climate modeling, known as scientific uncertainty, comes from our inability to numerically solve every aspect of the complex earth system. We expect this scientific uncertainty to decrease as we understand more of the earth system and improve its representation in our numerical models. As discussed in [[Climate Change Primer]], numerical experiments based on global climate models are designed to address these uncertainties in various ways. Downscaling methods evaluate this uncertainty by using several independent regional climate models to generate future projections, with the expectation that each of these models will capture some aspects of the physics better than the others, and that by using several different models, we can estimate the range of this uncertainty. Thus, the commonly accepted methods for accounting for uncertainty in climate model projections are either using projections from one model for several emission scenarios, or applying multiple models to project a single scenario.  
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===iTIE Units: Fractionation and Organism Exposure Chambers===
 +
[[File: CraneFig4.png | thumb | 300px | Figure 4. A diagram of the iTIE prototype. Water flows upward into each resin chamber through the unit bottom. After being chemically fractionated in the resin chamber, water travels into the organism chamber, where test organisms have been placed. Water is drawn through the units by high-precision peristaltic pumps.]]
 +
At&nbsp;the&nbsp;core&nbsp;of&nbsp;the&nbsp;iTIE&nbsp;system are separate dual-chamber iTIE units, each with a resin fractionation chamber and an organism exposure chamber (Figure 4). Developed by Burton ''et al.''<ref name="BurtonEtAl2020"/>, the iTIE prototype is constructed from acrylic, with rubber O-rings to connect each piece. Each iTIE unit can contain a different diagnostic resin matrix, customizable to remove specific chemical classes from the water. Sampled water flows into each unit through the bottom and is differentially fractionated by the resin matrix as it travels upward. Then it reaches the organism chamber, where test organisms are placed for exposure. The organism chamber inlet and outlet are covered by mesh to prevent the escape of the test organisms. This continuous flow-through design allows practitioners to capture the temporal heterogeneity of ambient water conditions over the duration of an ''in situ'' exposure. Currently, the iTIE system can support four independent iTIE treatment units.
  
−
A comparison of the currently available methods and their characteristics is provided in Table 2 (adapted from Kotamarthi et al., 2016<ref name="Kotamarthi2016"/>). The table lists the various methodologies and models used for producing downscaled data, and the climate variables that these methods produce.  These datasets are mostly available for download from the data servers and websites listed in the table and in a few cases by contacting the respective source organizations.
+
After being exposed to test organisms, water is collected in sample bottles. The bottles can be pre-loaded with preservation reagents to allow for later chemical analysis. Sample bottles can be composed of polyethylene, glass or other materials depending on the CoC.
  
−
The most popular and widely used format for atmospheric and climate science is known as [[Wikipedia:NetCDF | NetCDF]], which stands for Network Common Data Form. NetCDF is a self-describing data format that saves data in a binary format. The format is self-describing in that a metadata listing is part of every file that describes all the data attributes, such as dimensions, units and data size and in principal should not need additional information to extract the required data for analysis with the right software.  However, specially built software for reading and extracting data from these binary files is necessary for making visualizations and further analysis. Software packages for reading and writing NetCDF datasets and for generating visualizations from these datasets are widely available and obtained free of cost ([https://www.unidata.ucar.edu/software/netcdf/docs/ NetCDF-tools]). Popular geospatial analysis tools such as ARC-GIS, statistical packages such as ‘R’ and programming languages such as Fortran, C++, and Python have built in libraries that can be used to directly read NetCDF files for visualization and analysis.  
+
===Pumping Sub-system===
 +
[[File: CraneFig5.png | thumb | 300px | Figure 5. The iTIE system pumping sub-system. The sub-system consists of: A) a single booster pump, which is directly connected to the water sampling device and feeds water to the rest of the iTIE system, and B) a set of four regulation pumps, which each connect to the outflow of an individual iTIE unit. Each pump set is housed in a waterproof case with self-contained rechargeable battery power. A tablet is mounted inside the lid of the four pump case, which can be used to program and operate all of the pumps when connected to the internet.]]
 +
Water&nbsp;movement&nbsp;through&nbsp;the&nbsp;system is driven by a series of high-precision, programmable peristaltic pumps ([https://ecotechmarine.com/ EcoTech Marine]). Each pump set is housed in a Pelican storm travel case. Power is supplied to each pump by internal rechargeable lithium-iron phosphate batteries ([https://www.bioennopower.com/ Bioenno Power]).
  
 +
First, water is supplied to the system by a booster pump (Figure 5A). This pump is situated between the water sampling sub-system and the oxygen coil. The booster pump: 1) facilitates pore water collection, especially from sediments with high fine particle fractions; 2) helps water overcome vertical lifts to travel to the iTIE system; and 3) prevents vacuums from forming in the iTIE system interior, which can accelerate the formation of disruptive gas bubbles in the oxygen coil. The booster pump should be programmed to supply an excess of water to prevent vacuum formation.
  
 +
Second, a set of four regulation pumps ensure precise flow rates through each independent iTIE unit (Figure 5B). Each regulation pump pulls water from the top of an iTIE unit and then dispenses that water into a sample bottle for further analysis.
  
−
[[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.]]
+
==Study Design Considerations==
−
Environmental media such as sediments typically contain many different materials or phases, including liquid solutions (e.g. water, [[Light Non-Aqueous Phase Liquids (LNAPLs)| nonaqueous phase liquids]] like spilled oils) and diverse solids (e.g., quartz, aluminosilicate clays, and combustion-derived soots).  Further, the chemical concentration in the porewater medium includes both molecules that are "truly dissolved" in the water and others that are associated with colloids in the porewater<ref name="Brownawell1986">Brownawell, B.J., and Farrington, J.W., 1986. Biogeochemistry of PCBs in interstitial waters of a coastal marine sediment. Geochimica et Cosmochimica Acta, 50(1), pp. 157-169.  [https://doi.org/10.1016/0016-7037(86)90061-X DOI: 10.1016/0016-7037(86)90061-X]&nbsp;&nbsp; Free download available from: [https://semspub.epa.gov/work/01/268631.pdf US EPA].</ref><ref name="Chin1992">Chin, Y.P., and Gschwend, P.M., 1992. Partitioning of Polycyclic Aromatic Hydrocarbons to Marine Porewater Organic Colloids. Environmental Science and Technology, 26(8), pp. 1621-1626. [https://doi.org/10.1021/es00032a020 DOI: 10.1021/es00032a020]</ref><ref name="Achman1996">Achman, D.R., Brownawell, B.J., and Zhang, L., 1996. Exchange of Polychlorinated Biphenyls Between Sediment and Water in the Hudson River Estuary. Estuaries, 19(4), pp. 950-965.  [https://doi.org/10.2307/1352310 DOI: 10.2307/1352310]&nbsp;&nbsp; Free download available from: [https://www.academia.edu/download/55010335/135231020171114-2212-b93vic.pdf Academia.edu]</ref>. As a result, contaminant chemicals distribute among these diverse media (Figure 1) according to their affinity for each and the amount of each phase in the system<ref name="Gustafsson1996">Gustafsson, Ö., Haghseta, F., Chan, C., MacFarlane, J., and Gschwend, P.M., 1996. Quantification of the Dilute Sedimentary Soot Phase: Implications for PAH Speciation and Bioavailability. Environmental Science and Technology, 31(1), pp. 203-209.  [https://doi.org/10.1021/es960317s  DOI: 10.1021/es960317s]</ref><ref name="Luthy1997">Luthy, R.G., Aiken, G.R., Brusseau, M.L., Cunningham, S.D., Gschwend, P.M., Pignatello, J.J., Reinhard, M., Traina, S.J., Weber, W.J., and Westall, J.C., 1997. Sequestration of Hydrophobic Organic Contaminants by Geosorbents. Environmental Science and Technology, 31(12), pp. 3341-3347. [https://doi.org/10.1021/es970512m DOI: 10.1021/es970512m]</ref><ref name="Lohmann2005">Lohmann, R., MacFarlane, J.K., and Gschwend, P.M., 2005. Importance of Black Carbon to Sorption of Native PAHs, PCBs, and PCDDs in Boston and New York Harbor Sediments. Environmental Science and Technology, 39(1), pp.141-148.  [https://doi.org/10.1021/es049424+  DOI: 10.1021/es049424+]</ref><ref name="Cornelissen2005">Cornelissen, G., Gustafsson, Ö., Bucheli, T.D., Jonker, M.T., Koelmans, A.A., and van Noort, P.C., 2005. Extensive Sorption of Organic Compounds to Black Carbon, Coal, and Kerogen in Sediments and Soils: Mechanisms and Consequences for Distribution, Bioaccumulation, and Biodegradation. Environmental Science and Technology, 39(18), pp. 6881-6895. [https://doi.org/10.1021/es050191b  DOI: 10.1021/es050191b]</ref><ref name="Koelmans2009">Koelmans, A.A., Kaag, K., Sneekes, A., and Peeters, E.T.H.M., 2009. Triple Domain in Situ Sorption Modeling of Organochlorine Pesticides, Polychlorobiphenyls, Polyaromatic Hydrocarbons, Polychlorinated Dibenzo-p-Dioxins, and Polychlorinated Dibenzofurans in Aquatic Sediments. Environmental Science and Technology, 43(23), pp. 8847-8853. [https://doi.org/10.1021/es9021188 DOI: 10.1021/es9021188]</ref>. As such, the chemical concentration in any one medium (e.g., truly dissolved in porewater) in a multi-material system like sediment is very hard to know from measures of the total sediment concentration, which unfortunately is the information typically found by analyzing for chemicals in sediment samples.
+
===Diagnostic Resin Treatments===
 +
Several commercially available resins have been verified for use in the iTIE system. Investigators can select resins based on stressor classes of interest at each site. Each resin selectively removes a CoC class from site water prior to organism exposure.
 +
*[https://www.dupont.com/products/ambersorb560.html DuPont Ambersorb 560] for removal of 1,4-dioxane and other organic chemicals<ref>Woodard, S., Mohr, T., Nickelsen, M.G., 2014. Synthetic media: A promising new treatment technology for 1,4-dioxane. Remediation Journal, 24(4), pp. 27-40. [https://doi.org/10.1002/rem.21402 doi: 10.1002/rem.21402]</ref>
 +
*C18 for nonpolar organic chemicals
 +
*[https://www.bio-rad.com/en-us Bio-Rad] [https://www.bio-rad.com/en-us/product/chelex-100-resin?ID=6448ab3e-b96a-4162-9124-7b7d2330288e Chelex] for metals
 +
*Granular activated carbon for metals, general organic chemicals, sulfide<ref>Lemos, B.R.S., Teixeira, I.F., de Mesquita, J.P., Ribeiro, R.R., Donnici, C.L., Lago, R.M., 2012. Use of modified activated carbon for the oxidation of aqueous sulfide. Carbon, 50(3), pp. 1386-1393. [https://doi.org/10.1016/j.carbon.2011.11.011 doi: 10.1016/j.carbon.2011.11.011]</ref>
 +
*[https://www.waters.com/nextgen/us/en.html Waters] [https://www.waters.com/nextgen/us/en/search.html?category=Shop&isocode=en_US&keyword=oasis%20hlb&multiselect=true&page=1&rows=12&sort=best-sellers&xcid=ppc-ppc_23916&gad_source=1&gad_campaignid=14746094146&gbraid=0AAAAAD_uR00nhlNwrhhegNh06pBODTgiN&gclid=CjwKCAiAtLvMBhB_EiwA1u6_PsppE0raci2IhvGnAAe5ijciNcetLaGZo5qA3g3r4Z_La7YAPJtzShoC6LoQAvD_BwE Oasis HLB] for general organic chemicals<ref name="SteigmeyerEtAl2017"/>
 +
*[https://www.waters.com/nextgen/us/en.html Waters] [https://www.waters.com/nextgen/us/en/search.html?category=All&enableHL=true&isocode=en_US&keyword=Oasis%20WAX%20&multiselect=true&page=1&rows=12&sort=most-relevant Oasis WAX] for PFAS, organic chemicals of mixed polarity<ref>Iannone, A., Carriera, F., Di Fiore, C., Avino, P., 2024. Poly- and Perfluoroalkyl Substance (PFAS) Analysis in Environmental Matrices: An Overview of the Extraction and Chromatographic Detection Methods. Analytica, 5(2), pp. 187-202. [https://doi.org/10.3390/analytica5020012 doi: 10.3390/analytica5020012]&nbsp; [[Media: IannoneEtAl2024.pdf | Open Access Article]]</ref>
 +
*Zeolite for ammonia, other organic chemicals
  
−
If an animal moves into this system, it will also accumulate the chemical in its tissues from the loads in all the other materials (Figure 1).  This can lead to exposures of the chemical to other organisms, including humans, who may eat such animals. Predicting the quantity of contaminant in the animal requires knowledge of the relative affinities of the chemical for the animal versus the sediment materials.  For example, if one knew the chemical's truly dissolved concentration in the porewater and could reasonably assume the chemical of interest in the animal has mostly accumulated in its lipids (as is often the case for very hydrophobic compounds), then one could estimate the chemical concentration in the animal (''C<sub><small>animal</small></sub>'', typically in units of &mu;g/kg animal wet weight) using a lipid-water [[Wikipedia: Partition coefficient | partition coefficient]], ''K<sub><small>lipid-water</small></sub>'', typically in units of (&mu;g/kg lipid)'''/'''(&mu;g/L water), and the porewater concentration of the chemical (''C<sub><small>porewater</small></sub>'', in &mu;g/L) with Equation 1.
+
Resins must be adequately conditioned prior to use. Otherwise, they may inadequately adsorb toxicants or cause stress to organisms. New resins should be tested for efficacy and toxicity before being used in an iTIE system.  
−
{|
 
−
|
 
−
|-
 
−
| || Equation 1.
 
−
| 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>
 
−
|-
 
−
| where:
 
−
|-
 
−
| || ''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
 
−
|-
 
−
| || ''C<sub><small>porewater</small></sub>'' || is the freely dissolved contaminant concentration in the porewater surrounding the animal.
 
−
|}
 
  
−
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>.
+
===Test Organism Species and Life Stages===
 +
Practitioners can also select different organism species and life stages for use in the iTIE system, depending on site characteristics and study goals. The iTIE system can accommodate various small test organisms, including embryo-stage fish and most macroinvertebrates. The following common toxicity tests can be adapted for application within iTIE systems<ref>U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, 1994. Catalogue of Standard Toxicity Tests for Ecological Risk Assessment. ECO Update, 2(2), 4 pages. Publication No. 9345.0.05I [https://www.epa.gov/sites/default/files/2015-09/documents/v2no2.pdf Free Download]&nbsp; [[Media: usepa1994.pdf | Report.pdf]]</ref>.
 +
<ul><u>Freshwater acute toxicity:</u></ul>
 +
*[[Wikipedia: Daphnia magna | ''Daphnia magna'']] or [[Wikipedia: Daphnia pulex | ''Daphnia pulex'']] 24-, 48-, and 96-hour survival
 +
<ul><u>Freshwater chronic toxicity:</u></ul>
 +
*[[Wikipedia: Ceriodaphnia dubia | ''Ceriodaphnia dubia'']] 7-day survival and reproduction
 +
*''D. magna'' 7-day survival and reproduction
 +
*[[Wikipedia: Fathead minnow | ''Pimephales promelas'']] 7-day embryo-larval survival and teratogenicity
 +
*[[Wikipedia: Hyalella azteca | ''Hyalella Azteca'']] 10- or 30-day survival and reproduction
 +
<ul><u>Marine acute toxicity:</u></ul>
 +
*[[Wikipedia: Americamysis bahia | ''Americamysis bahia'']] 24- and 48-hour survival
 +
<ul><u>Marine chronic toxicity:</u></ul>
 +
*''Americamysis'' survival, growth and fecundity
 +
*[[Wikipedia: Topsmelt silverside | ''Atherinops affinis'']] embryo-larval survival and growth
  
−
==Passive Samplers==
+
Acute toxicity is quantifiable via organism survival rates immediately following the termination of an iTIE system field deployment. Chronic toxicity can be quantified by continuing to culture and observe test organisms in-lab. Common chronic endpoints include stunted growth, altered development such as teratogenicity in larval fish, decreased reproduction rates, and changes in gene expression.  
−
One approach to address this problem for contaminated sediments is to insert into the sediment billets of organic polymers like low density polyethylene (LDPE), polydimethylsiloxane (PDMS), or polyoxymethylene (POM) that can absorb such hydrophobic chemicals from their surroundings<ref name="Mayer2000">Mayer, P., Vaes, W.H., Wijnker, F., Legierse, K.C., Kraaij, R., Tolls, J., and Hermens, J.L., 2000. Sensing Dissolved Sediment Porewater Concentrations of Persistent and Bioaccumulative Pollutants Using Disposable Solid-Phase Microextraction Fibers. Environmental Science and Technology, 34(24), pp. 5177-5183.  [https://doi.org/10.1021/es001179g DOI: 10.1021/es001179g]</ref><ref name="Booij2003">Booij, K., Hoedemaker, J.R., and Bakker, J.F., 2003. Dissolved PCBs, PAHs, and HCB in Pore Waters and Overlying Waters of Contaminated Harbor Sediments. Environmental Science and Technology, 37(18), pp. 4213-4220.  [https://doi.org/10.1021/es034147c DOI: 10.1021/es034147c]</ref><ref name="Cornelissen2008">Cornelissen, G., Pettersen, A., Broman, D., Mayer, P., and Breedveld, G.D., 2008. Field testing of equilibrium passive samplers to determine freely dissolved native polycyclic aromatic hydrocarbon concentrations. Environmental Toxicology and Chemistry, 27(3), pp. 499-508.  [https://doi.org/10.1897/07-253.1 DOI: 10.1897/07-253.1]</ref><ref name="Tomaszewski2008">Tomaszewski, J.E., and Luthy, R.G., 2008. Field Deployment of Polyethylene Devices to Measure PCB Concentrations in Pore Water of Contaminated Sediment. Environmental Science and Technology, 42(16), pp. 6086-6091.  [https://doi.org/10.1021/es800582a DOI: 10.1021/es800582a]</ref><ref name="Fernandez2009">Fernandez, L.A., MacFarlane, J.K., Tcaciuc, A.P., and Gschwend, P.M., 2009. Measurement of Freely Dissolved PAH Concentrations in Sediment Beds Using Passive Sampling with Low-Density Polyethylene Strips. Environmental Science and Technology, 43(5), pp. 1430-1436.  [https://doi.org/10.1021/es802288w DOI: 10.1021/es802288w]</ref><ref name="Arp2015">Arp, H.P.H., Hale, S.E., Elmquist Kruså, M., Cornelissen, G., Grabanski, C.B., Miller, D.J., and Hawthorne, S.B., 2015. Review of polyoxymethylene passive sampling methods for quantifying freely dissolved porewater concentrations of hydrophobic organic contaminants. Environmental Toxicology and Chemistry, 34(4), pp. 710-720.  [https://doi.org/10.1002/etc.2864 DOI: 10.1002/etc.2864]&nbsp;&nbsp;  [https://setac.onlinelibrary.wiley.com/doi/epdf/10.1002/etc.2864 Free access article.]&nbsp;&nbsp; [[Media: Arp2015.pdf | Report.pdf]]</ref><ref name="Apell2016"/>. In this approach, the polymer is inserted in the sediment bed where it absorbs some of the contaminant load via the contaminant's diffusion into the polymer from the surroundings. When the polymer achieves sorptive equilibration with the sediments, the chemical concentration in the polymer, ''C<sub><small>polymer</small></sub>'' (&mu;g/kg polymer), can be used to find the corresponding concentration in the porewater,  ''C<sub><small>porewater</small></sub>'' (&mu;g/L), using a polymer-water partition coefficient, ''K<sub><small>polymer-water</small></sub>'' ((&mu;g/kg polymer)'''/'''(&mu;g/L water)), that has previously been found in laboratory testing<ref name="Lohmann2012">Lohmann, R., 2012. Critical Review of Low-Density Polyethylene’s Partitioning and Diffusion Coefficients for Trace Organic Contaminants and Implications for Its Use as a Passive Sampler. Environmental Science and Technology, 46(2), pp. 606-618.  [https://doi.org/10.1021/es202702y DOI: 10.1021/es202702y]</ref><ref name="Ghosh2014">Ghosh, U., Kane Driscoll, S., Burgess, R.M., Jonker, M.T., Reible, D., Gobas, F., Choi, Y., Apitz, S.E., Maruya, K.A., Gala, W.R., Mortimer, M., and Beegan, C., 2014. Passive Sampling Methods for Contaminated Sediments: Practical Guidance for Selection, Calibration, and Implementation. Integrated Environmental Assessment and Management, 10(2), pp. 210-223.  [https://doi.org/10.1002/ieam.1507 DOI: 10.1002/ieam.1507]&nbsp;&nbsp; [https://setac.onlinelibrary.wiley.com/doi/epdf/10.1002/ieam.1507 Free access article.]&nbsp;&nbsp; [[Media: Ghosh2014.pdf | Report.pdf]]</ref>, as shown in Equation 2.
 
−
{|
 
−
|
 
−
|-
 
−
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|| Equation&nbsp;2.
 
−
| 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>'' (&mu;g/kg animal), would be found by combining Equations 1 and 2 to get Equation 3.
+
Several gene expression endpoints have been detectable in bioassays following an iTIE system deployment and in-lab culturing period. Steigmeyer ''et al.''<ref name="SteigmeyerEtAl2017"/> were able to detect changes in the expression of two genes in ''D. magna'' after a 24-hour exposure to bisphenol A. In a separate study, Nichols<ref>Nichols, E., 2023. Methods for Identification and Prioritization of Stressors at Impaired Sites. Masters thesis, University of Michigan. University of Michigan Library Deep Blue Documents. [https://deepblue.lib.umich.edu/bitstream/handle/2027.42/176142/Nichols_Elizabeth_thesis.pdf?sequence=1 Free Download]&nbsp; [[Media: Nichols2023.pdf | Report.pdf]]</ref> found a significant decline in acetylcholinesterase activity in ''H. azteca'' after a 24-hour exposure to chlorpyrifos. These results indicate a potential to adapt other gene expression bioassays for use in conjunction with iTIE system field exposures to prove stressor-causality linkages.
−
{|
 
−
|
 
−
|-
 
−
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|| Equation&nbsp;3.
 
−
|style="width:700px; text-align:center;" |<big>'''''C<sub><small>animal</small></sub> '''=''' f<sub><small>lipid</small></sub> '''x''' K<sub><small>lipid-water</small></sub> '''x''' C<sub><small>polymer</small></sub> '''/''' K<sub><small>polymer-water</small></sub>'''''</big>
 
−
|}
 
−
[[File: Gschwend1w2fig2a.PNG | thumb | 300px | Figure 2a. Plot of the initial concentrations of a PRC (green lines) in a polyethylene (PE) sheet inserted in a sediment showing constant concentration across the PE and zero concentration outside the PE. At the same time, a target contaminant of interest (red lines) initially has a constant concentration in the sediment outside the PE and zero concentration inside the PE.]][[File: Gschwend1w2fig2b.PNG | thumb | 300px | Figure 2b. After the PE has been deployed for a time, the PRC is depleted from the PE (green lines), especially near the surfaces contacting the sediment, and its concentration is building up outside the PE and diffusing away into the sediment. Meanwhile, the target chemical leaves the sediment and begins to diffuse into the PE (red lines). The "jumps" in concentration  at the PE-sediment boundary reflect the equilibrium paritioning coefficient,</br>''K<sub>PE-sed</sub>&nbsp;=&nbsp;C<sub>PE</sub>&nbsp;/&nbsp;C<sub>sediment</sub>''.]]
 
  
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==Performance Reference Compounds (PRCs)==
+
===Cost Effectiveness Study===
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Perhaps unsurprisingly, pollutants with low water solubility like PAHs, PCBs, etc. do not diffuse quickly through sediment beds.  As a result, their accumulation in polymeric materials in sediments can take a long time to achieve equilibration<ref name="Fernandez2009b">Fernandez, L. A., Harvey, C.F., and Gschwend, P.M., 2009. Using Performance Reference Compounds in Polyethylene Passive Samplers to Deduce Sediment Porewater Concentrations for Numerous Target Chemicals. Environmental Science and Technology, 43(23), pp. 8888-8894. [https://doi.org/10.1021/es901877a DOI: 10.1021/es901877a]</ref><ref name="Lampert2015">Lampert, D.J., Thomas, C., and Reible, D.D., 2015. Internal and external transport significance for predicting contaminant uptake rates in passive samplers. Chemosphere, 119, pp. 910-916.  [https://doi.org/10.1016/j.chemosphere.2014.08.063 DOI: 10.1016/j.chemosphere.2014.08.063]&nbsp;&nbsp; Free download available from: [https://www.academia.edu/download/44146586/chemosphere_2014.pdf Academia.edu]</ref><ref name="Apell2016b">Apell, J.N., Tcaciuc, A.P., and Gschwend, P.M., 2016. Understanding the rates of nonpolar organic chemical accumulation into passive samplers deployed in the environment: Guidance for passive sampler deployments. Integrated Environmental Assessment and Management, 12(3), pp. 486-492.  [https://doi.org/10.1002/ieam.1697 DOI: 10.1002/ieam.1697]</ref>. This problem was recognized previously for passive samplers called [[Wikipedia: Semipermeable membrane devices | semipermeable membrane devices]] (SPMDs, e.g. polyethylene bags filled with triolein<ref name="Huckins2002">Huckins, J.N., Petty, J.D., Lebo, J.A., Almeida, F.V., Booij, K., Alvarez, D.A., Cranor, W.L., Clark, R.C., and Mogensen, B.B., 2002. Development of the Permeability/Performance Reference Compound Approach for In Situ Calibration of Semipermeable Membrane Devices. Environmental Science and Technology, 36(1), pp. 85-91.  [https://doi.org/10.1021/es010991w DOI: 10.1021/es010991w]</ref>) that were deployed in surface waters. As a result, representative chemicals called performance reference compound (PRCs) were dosed inside the samplers before their deployment in the environment, and the PRCs' diffusive losses out of the SPMD could be used to quantify the fractional approach toward sampler-environmental surroundings equilibration<ref name="Booij2002">Booij, K., Smedes, F., and van Weerlee, E.M., 2002. Spiking of performance reference compounds in low density polyethylene and silicone passive water samplers. Chemosphere 46(8), pp.1157-1161.  [https://doi.org/10.1016/S0045-6535(01)00200-4 DOI: 10.1016/S0045-6535(01)00200-4]</ref><ref name="Huckins2002"/>. A similar approach can be used for polymers inserted in sediment beds<ref name="Fernandez2009b"/><ref name="Apell2014"/>. Commonly, isotopically labeled forms of the compounds of interest such as deuterated or <sup>13</sup>C-labelled PAHs or PCBs are homogeneously impregnated into the polymers before their deployments. Upon insertion of the polymer into the sediment bed (or overlying waters or even air), the initially evenly distributed PRCs begin to diffuse out of the sampling polymer and into the surroundings (Figure 2).  
+
Burton ''et al.''<ref name="BurtonEtAl2020"/> conducted a cost effectiveness study comparing the iTIE technology with the traditional US EPA Phase 1 TIE method. Comparisons were based on the estimated time required to complete various sub-tasks within each method. Sub-tasks included organism care, equipment preparation, mobilization and deployment, test maintenance, test termination, demobilization, and test termination analyses. It was ultimately estimated that the iTIE protocol requires 47% less time (67 fewer hours) to complete than the Phase 1 TIE method, with the largest time differences in equipment preparation, deployment, test maintenance, and demobilization. It is important to note that the iTIE method may require additional initial costs for equipment and training.
  
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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.
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==Field Application==
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{|
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[[File: CraneFig6.png | thumb | left | 400px | Figure 6. iTIES deployment at the Rouge River, Detroit, MI.  In the foreground is the iTIE Cooler Sub-System, which contains iTIE resin treatments and test organism groups, as well as the oxygenation coil and sample collection bottles. Next to the iTIE Cooler are the two pump cases. The Trident can be seen above the pump cases, installed in the river channel near shore.]]
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|
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The&nbsp;iTIE&nbsp;system&nbsp;has&nbsp;been successfully deployed at a variety of marine and freshwater sites during the proof-of-concept phase of prototype development. One example is the 2024 iTIE system deployment completed near the mouth of the Rouge River in Detroit, MI (Figure 6). The Rouge River watershed has a long history of industrialization, with a legacy of chemical dumping, channelization, damming, and urban runoff<ref>Ridgway, J., Cave, K., DeMaria, A., O’Meara, J., Hartig, J. H., 2018. The Rouge River Area of Concern—A multi-year, multi-level successful approach to restoration of Impaired Beneficial Uses. Aquatic Ecosystem Health and Management, 21(4), pp. 398-408. [https://doi.org/10.1080/14634988.2018.1528816 doi: 10.1080/14634988.2018.1528816]</ref>. This has led to degraded environmental conditions, with previous detections of a wide range of chemicals including heavy metals and various organics.
−
|-
 
−
| || Equation 4.
 
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| style="text-align:center;"| <big>'''''C(<sub>&infin;</sub>)<sub><small>polymer</small></sub> '''=''' C(<small>t</small>)<sub><small>polymer</small></sub> '''/''' f<sub><small>PRC lost</small></sub>'''''</big>
 
−
|-
 
−
| where:
 
−
|-
 
−
| || ''f<sub><small>PRC lost</small></sub>'' || is the fraction of the PRC lost to outward diffusion,  
 
−
|-
 
−
| || ''C(<sub>&infin;</sub>)<sub><small>polymer</small></sub>'' || is the concentration of the contaminant in the polymer at equilibrium, and
 
−
|-
 
−
| || ''C(<small>t</small>)<sub><small>polymer</small></sub>'' || is the concentration of the contaminant in the polymer after deployment time, t.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
−
|}
 
  
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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.
+
[[File: CraneFig7.png | thumb | 300px | Figure 7. Survival and healthy development of ''P. promelas'' embryos and larvae following a 48-hour iTIE exposure near the mouth of the Rouge River. Organisms were exposed to site porewater as embryos for 48 hours and cultured post-exposure for an additional 5 days.]]
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[[File: CraneFig8.png | thumb | 300px | Figure 8. Survival of ''C. dilutus'' larvae after an iTIE exposure near the mouth of the Rouge River. Organisms were exposed to site porewater for 48 hours and cultured post-exposure for an additional 5 days. Error bars show standard deviation.]]
 +
An&nbsp;iTIE&nbsp;system&nbsp;deployment&nbsp;was designed and completed to determine which chemical classes are most responsible for causing toxicity at the site. Resin treatments included glass wool (inert, non-fractionating substance), Chelex (metals sorption), Oasis HLB (general organics sorption), and Oasis WAX (organics sorption, with a high affinity for PFAS). The study utilized fathead minnow (''P. promelas'') embryos, due to their relative sensitivity to metals and PAHs, as well as second-instar midge ([[Wikipedia: Chironomus |''Chironomus dilutus'']]) larvae due to their relative sensitivity to PFAS.  
  
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==Field Applications==
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The test organisms were exposed to fractionated porewater ''in situ'' for 48 hours. Following exposure, organisms were cultured for an additional five days, and survival was recorded (Figures 7 and 8). Moderate declines in survival were seen in both species in the glass wool treatment, indicating toxicity at the site. For ''P. promelas'', the highest proportion of healthy development occurred in the Chelex treatment, supporting the hypothesis that metals are a dominant cause of toxicity. ''C. dilutus'' had the greatest survival in the Oasis WAX treatment, suggesting that an organic stressor class like PFAS is also present at harmful concentrations in the river.
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[[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.]]
 
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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).
 
  
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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>.
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Water chemical analyses of fractionated and unfractionated water samples were completed to support biological results. Analyses were conducted for a range of stressor classes including metals, PAHs, PCBs, an organophosphate pesticide (chlorpyrifos), a PFAS compound (PFOS) and a pyrethroid insecticide (permethrin). Of these analytes, only heavy metals and PFOS were detected. Some chemical classes including PAHs and PCBs were not detected at the site.
 +
To reach similar conclusions using traditional Phase 1 TIE methods, one would need to complete the following tests: baseline toxicity, filtration, aeration, EDTA, C18 SPE, and methanol elution of C18 SPE. The iTIE method allows the same conclusions to be drawn with significantly less time and effort required.
  
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Subsequently, since the passive sampling reveals the concentrations of contaminants in a sediment bed's porewater and the overlying bottom water<ref name="Booij2003"/>, the data can be used to estimate bed-to-water column diffusive fluxes of contaminants<ref name="Koelmans2010">Koelmans, A.A., Poot, A., De Lange, H.J., Velzeboer, I., Harmsen, J., and van Noort, P.C.M., 2010. Estimation of In Situ Sediment-to-Water Fluxes of Polycyclic Aromatic Hydrocarbons, Polychlorobiphenyls and Polybrominated Diphenylethers. Environmental Science and Technology, 44(8), pp. 3014-3020.  [https://doi.org/10.1021/es903938z DOI: 10.1021/es903938z]</ref><ref name="Fernandez2012"/> and bioirrigation-affected fluxes<ref name="Apell2018">Apell, J.N., Shull, D.H., Hoyt, A.M., and Gschwend, P.M., 2018. Investigating the Effect of Bioirrigation on In Situ Porewater Concentrations and Fluxes of Polychlorinated Biphenyls Using Passive Samplers.  Environmental Science and Technology, 52(8), pp. 4565-4573.  [https://doi.org/10.1021/acs.est.7b05809 DOI: 10.1021/acs.est.7b05809]</ref>. The data are also useful for assessing the tendency of the contaminants to accumulate in benthic organisms<ref name="Vinturella2004">Vinturella, A.E., Burgess, R.M., Coull, B.A., Thompson, K.M., and Shine, J.P., 2004. Use of Passive Samplers to Mimic Uptake of Polycyclic Aromatic Hydrocarbons by Benthic Polychaetes. Environmental Science and Technology, 38(4), pp. 1154-1160.  [https://doi.org/10.1021/es034706f DOI: 10.1021/es034706f]</ref><ref name="Yates2011">Yates, K., Pollard, P., Davies, I.M., Webster, L., and Moffat, C.F., 2011. Application of silicone rubber passive samplers to investigate the bioaccumulation of PAHs by Nereis virens from marine sediments. Environmental Pollution, 159(12), pp. 3351-3356.  [https://doi.org/10.1016/j.envpol.2011.08.038 DOI: 10.1016/j.envpol.2011.08.038]</ref><ref name="Fernandez2015">Fernandez, L.A. and Gschwend, P.M., 2015.  Predicting bioaccumulation of polycyclic aromatic hydrocarbons in soft-shelled clams  (Mya arenaria) using field deployments of polyethylene passive samplers.  Environmental Toxicology and Chemistry, 34(5), pp. 993-1000.  [https://doi.org/10.1002/etc.2892 DOI: 10.1002/etc.2892]</ref>, and by extension into food webs that include such benthic species<ref name="vonStackelberg2017">von Stackelberg, K., Williams, M.A., Clough, J., and Johnson, M.S., 2017. Spatially explicit bioaccumulation modeling in aquatic environments: Results from 2 demonstration sites. Integrated Environmental Assessment and Management, 13(6), pp. 1023-1037.  [https://doi.org/10.1002/ieam.1927 DOI: 10.1002/ieam.1927]</ref>. Furthermore, recent efforts have found that passive sampling observations can be used to infer ''in situ'' transformations of substances like nitro aromatic compounds<ref name="Belles2016">Belles, A., Alary, C., Criquet, J., and Billon, G., 2016. A new application of passive samplers as indicators of in-situ biodegradation processes. Chemosphere, 164, pp. 347-354.  [https://doi.org/10.1016/j.chemosphere.2016.08.111 DOI: 10.1016/j.chemosphere.2016.08.111]</ref> and DDT<ref name="Tcaciuc2018">Tcaciuc, A.P., Borrelli, R., Zaninetta, L.M., and Gschwend, P.M., 2018. Passive sampling of DDT, DDE and DDD in sediments: accounting for degradation processes with reaction–diffusion modeling. Environmental Science: Processes and Impacts, 20(1), pp. 220-231.  [https://doi.org/10.1039/C7EM00501F DOI: 10.1039/C7EM00501F]&nbsp;&nbsp; Open access article available from: [https://pubs.rsc.org/--/content/articlehtml/2018/em/c7em00501f Royal Society of Chemistry].</ref>.
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==Summary==
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The ''in situ'' Toxicity Identification Evaluation technology and protocol is a powerful tool that investigators can use to strengthen causal linkages between chemical stressors and ecological toxicity. By fractionating sampled water and exposing test organisms ''in situ'', investigators can gather toxicity response data while minimizing sample manipulation and accurately representing environmental conditions.
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==References==
 
==References==
 
<references />
 
<references />
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==See Also==
 
==See Also==
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[https://www.serdp-estcp.org/Tools-and-Training/Tools/PRC-Correction-Calculator A PRC Correction Calculator for LDPE deployed in sediments]
 

Latest revision as of 16:10, 3 March 2026

In Situ Toxicity Identification Evaluation (iTIE)

The in situ Toxicity Identification Evaluation system is a tool to incorporate in weight-of-evidence studies at sites with numerous chemical toxicant classes present. The technology works by continuously sampling site water, immediately fractionating the water using diagnostic sorptive resins, and then exposing test organisms to the water to observe toxicity responses with minimal sample manipulation. It is compatible with various resins, test organisms, and common acute and chronic toxicity tests, and can be deployed at sites with a wide variety of physical and logistical considerations.

Related Article(s):

Contributors: Dr. G. Allen Burton Jr., Austin Crane

Key Resources:

  • A Novel In Situ Toxicity Identification Evaluation (iTIE) System for Determining which Chemicals Drive Impairments at Contaminated Sites[1]
  • An in situ toxicity identification and evaluation water analysis system: Laboratory validation[2]
  • Sediment Toxicity Identification Evaluation (TIE) Phases I, II, and III Guidance Document[3]
  • In Situ Toxicity Identification Evaluation (iTIE) Technology for Assessing Contaminated Sediments, Remediation Success, Recontamination and Source Identification[4]

Introduction

In waterways impacted by numerous naturally occurring and anthropogenic chemical stressors, it is crucial for environmental practitioners to be able to identify which chemical classes are causing the highest degrees of toxicity to aquatic life. Previously developed methods, including the Toxicity Identification Evaluation (TIE) protocol developed by the US Environmental Protection Agency (EPA)[5], can be confounded by sample manipulation artifacts and temporal limitations of ex situ organism exposures[1]. These factors may disrupt causal linkages and mislead investigators during site characterization and management decision-making. The in situ Toxicity Identification Evaluation (iTIE) technology was developed to allow users to strengthen stressor-causality linkages and rank chemical classes of concern at impaired sites, with high degrees of ecological realism.

The technology has undergone a series of improvements in recent years, with the most recent prototype being robust, operable in a wide variety of site conditions, and cost-effective compared to alternative site characterization methods[6][7][1][2]. The latest prototype can be used in any of the following settings: in marine, estuarine, or freshwater sites; to study surface water or sediment pore water; in shallow waters easily accessible by foot or in deep waters only accessible by pier or boat. It can be used to study sites impacted by a wide variety of stressors including ammonia, metals, pesticides, polychlorinated biphenyls (PCB), polycyclic aromatic hydrocarbons (PAH), and per- and polyfluoroalkyl substances (PFAS), among others. The technology is applicable to studies of acute toxicity via organism survival or of chronic toxicity via responses in growth, reproduction, or gene expression[1].

System Components and Validation

Figure 1: A schematic diagram of the iTIE system prototype. The system is divided into three sub-systems: 1) the Pore Water/Surface Water Collection Sub-System (blue); 2) the Pumping Sub-System (red); and 3) the iTIE Resin, Exposure, and Sampling Sub-System (green). Water first enters the system through the Pore Water/Surface Water Collection Sub-System. Porewater can be collected using Trident-style probes, or surface water can be collected using a simple weighted probe. The water is composited in a manifold before being pumped to the rest of the iTIE system by the booster pump. Once in the iTIE Resin, Exposure, and Sampling Sub-System, the water is gently oxygenated by the Oxygen Coil, separated from gas bubbles by the Drip Chamber, and diverted to separate iTIE Resin and Exposure Chambers (or iTIE units) by the Splitting Manifold. Water movement through each iTIE unit is controlled by a dedicated Regulation Pump. Finally, the water is gathered in Sample Collection bottles for analysis.

The latest iTIE prototype consists of an array of sorptive resins that differentially fractionate sampled water, and a series of corresponding flow-through organism chambers that receive the treated water in situ. Resin treatments can be selected depending on the chemicals suspected to be present at each site to selectively sequester certain chemical of concern (CoC) classes from the whole water, leaving a smaller subset of chemicals in the resulting water fraction for chemical and toxicological characterization. Test organism species and life stages can also be chosen depending on factors including site characteristics and study goals. In the full iTIE protocol, site water is continuously sampled either from the sediment pore spaces or the water column at a site, gently oxygenated, diverted to different iTIE units for fractionation and organism exposure, and collected in sample bottles for off-site chemical analysis (Figure 1). All iTIE system components are housed within waterproof Pelican cases, which allow for ease of transport and temperature control.

Porewater and Surface Water Collection Sub-system

Figure 2: a) Trident probe with auxiliary sensors attached, b) a Trident probe with end caps removed (the red arrow identifies the intermediate space where glass beads are packed to filter suspended solids), c) a Trident probe being installed using a series of push poles and a fence post driver

Given the importance of sediment porewater to ecosystem structure and function, investigators may employ the iTIE system to evaluate the toxic effects associated with the impacted sediment porewater. To accomplish this, the iTIE system utilizes the Trident probe, originally developed for Department of Defense site characterization studies[8]. The main body of the Trident is comprised of a stainless-steel frame with six hollow probes (Figure 2). Each probe contains a layer of inert glass beads, which filters suspended solids from the sampled water. The water is drawn through each probe into a composite manifold and transported to the rest of the iTIE system using a high-precision peristaltic pump.

The Trident also includes an adjustable stopper plate, which forms a seal against the sediment and prevents the inadvertent dilution of porewater samples with surface water. (Figure 2). Preliminary laboratory results indicate that the Trident is extremely effective in collecting porewater samples with minimal surface water infiltration in sediments ranging from coarse sand to fine clay. Underwater cameras, sensors, passive samplers, and other auxiliary equipment can be attached to the Trident probe frame to provide supplemental data.

Alternatively, practitioners may employ the iTIE system to evaluate site surface water. To sample surface water, weighted intake tubes can collect surface water from the water column using a peristaltic pump.

Oxygen Coil, Overflow Bag and Drip Chamber

Figure 3. Contents of the iTIE system cooler. The pictured HDPE rack (47.6 cm length x 29.7 cm width x 33.7 cm height) is removable from the iTIE cooler. Water enters the system at the red circle, flows through the oxygen coil, and then travels to each of the individual iTIE units where diagnostic resins and organisms are located. The water then briefly leaves the cooler to travel through peristaltic regulation pumps before being gathered in sample collection bottles.

Porewater is naturally anoxic due to limited mixing with aerated surface water and high oxygen demand of sediments, which may cause organism mortality and interfere with iTIE results. To preclude this, sampled porewater is exposed to an oxygen coil. This consists of an interior silicone tube connected to a pressurized oxygen canister, threaded through an exterior reinforced PVC tube through which water is slowly pumped (Figure 3). Pump rates are optimized to ensure adequate aeration of the water. In addition to elevating DO levels, the oxygen coil facilitates the oxidation of dissolved sulfides, which naturally occur in some marine sediments and may otherwise cause toxicity to organisms if left in its reduced form.

Gas bubbles may form in the oxygen coil over the course of a deployment. These can be disruptive, decreasing water sample volumes and posing a danger to sensitive organisms like daphnids. To account for this, the water travels to a drip chamber after exiting the oxygen coil, which allows gas bubbles to be separated and diverted to an overflow system. The sample water then flows to a manifold which divides the flow into different paths to each of the treatment units for fractionation and organism exposure.

iTIE Units: Fractionation and Organism Exposure Chambers

Figure 4. A diagram of the iTIE prototype. Water flows upward into each resin chamber through the unit bottom. After being chemically fractionated in the resin chamber, water travels into the organism chamber, where test organisms have been placed. Water is drawn through the units by high-precision peristaltic pumps.

At the core of the iTIE system are separate dual-chamber iTIE units, each with a resin fractionation chamber and an organism exposure chamber (Figure 4). Developed by Burton et al.[1], the iTIE prototype is constructed from acrylic, with rubber O-rings to connect each piece. Each iTIE unit can contain a different diagnostic resin matrix, customizable to remove specific chemical classes from the water. Sampled water flows into each unit through the bottom and is differentially fractionated by the resin matrix as it travels upward. Then it reaches the organism chamber, where test organisms are placed for exposure. The organism chamber inlet and outlet are covered by mesh to prevent the escape of the test organisms. This continuous flow-through design allows practitioners to capture the temporal heterogeneity of ambient water conditions over the duration of an in situ exposure. Currently, the iTIE system can support four independent iTIE treatment units.

After being exposed to test organisms, water is collected in sample bottles. The bottles can be pre-loaded with preservation reagents to allow for later chemical analysis. Sample bottles can be composed of polyethylene, glass or other materials depending on the CoC.

Pumping Sub-system

Figure 5. The iTIE system pumping sub-system. The sub-system consists of: A) a single booster pump, which is directly connected to the water sampling device and feeds water to the rest of the iTIE system, and B) a set of four regulation pumps, which each connect to the outflow of an individual iTIE unit. Each pump set is housed in a waterproof case with self-contained rechargeable battery power. A tablet is mounted inside the lid of the four pump case, which can be used to program and operate all of the pumps when connected to the internet.

Water movement through the system is driven by a series of high-precision, programmable peristaltic pumps (EcoTech Marine). Each pump set is housed in a Pelican storm travel case. Power is supplied to each pump by internal rechargeable lithium-iron phosphate batteries (Bioenno Power).

First, water is supplied to the system by a booster pump (Figure 5A). This pump is situated between the water sampling sub-system and the oxygen coil. The booster pump: 1) facilitates pore water collection, especially from sediments with high fine particle fractions; 2) helps water overcome vertical lifts to travel to the iTIE system; and 3) prevents vacuums from forming in the iTIE system interior, which can accelerate the formation of disruptive gas bubbles in the oxygen coil. The booster pump should be programmed to supply an excess of water to prevent vacuum formation.

Second, a set of four regulation pumps ensure precise flow rates through each independent iTIE unit (Figure 5B). Each regulation pump pulls water from the top of an iTIE unit and then dispenses that water into a sample bottle for further analysis.

Study Design Considerations

Diagnostic Resin Treatments

Several commercially available resins have been verified for use in the iTIE system. Investigators can select resins based on stressor classes of interest at each site. Each resin selectively removes a CoC class from site water prior to organism exposure.

Resins must be adequately conditioned prior to use. Otherwise, they may inadequately adsorb toxicants or cause stress to organisms. New resins should be tested for efficacy and toxicity before being used in an iTIE system.

Test Organism Species and Life Stages

Practitioners can also select different organism species and life stages for use in the iTIE system, depending on site characteristics and study goals. The iTIE system can accommodate various small test organisms, including embryo-stage fish and most macroinvertebrates. The following common toxicity tests can be adapted for application within iTIE systems[12].

    Freshwater acute toxicity:
    Freshwater chronic toxicity:
    Marine acute toxicity:
    Marine chronic toxicity:
  • Americamysis survival, growth and fecundity
  • Atherinops affinis embryo-larval survival and growth

Acute toxicity is quantifiable via organism survival rates immediately following the termination of an iTIE system field deployment. Chronic toxicity can be quantified by continuing to culture and observe test organisms in-lab. Common chronic endpoints include stunted growth, altered development such as teratogenicity in larval fish, decreased reproduction rates, and changes in gene expression.

Several gene expression endpoints have been detectable in bioassays following an iTIE system deployment and in-lab culturing period. Steigmeyer et al.[2] were able to detect changes in the expression of two genes in D. magna after a 24-hour exposure to bisphenol A. In a separate study, Nichols[13] found a significant decline in acetylcholinesterase activity in H. azteca after a 24-hour exposure to chlorpyrifos. These results indicate a potential to adapt other gene expression bioassays for use in conjunction with iTIE system field exposures to prove stressor-causality linkages.

Cost Effectiveness Study

Burton et al.[1] conducted a cost effectiveness study comparing the iTIE technology with the traditional US EPA Phase 1 TIE method. Comparisons were based on the estimated time required to complete various sub-tasks within each method. Sub-tasks included organism care, equipment preparation, mobilization and deployment, test maintenance, test termination, demobilization, and test termination analyses. It was ultimately estimated that the iTIE protocol requires 47% less time (67 fewer hours) to complete than the Phase 1 TIE method, with the largest time differences in equipment preparation, deployment, test maintenance, and demobilization. It is important to note that the iTIE method may require additional initial costs for equipment and training.

Field Application

Figure 6. iTIES deployment at the Rouge River, Detroit, MI. In the foreground is the iTIE Cooler Sub-System, which contains iTIE resin treatments and test organism groups, as well as the oxygenation coil and sample collection bottles. Next to the iTIE Cooler are the two pump cases. The Trident can be seen above the pump cases, installed in the river channel near shore.

The iTIE system has been successfully deployed at a variety of marine and freshwater sites during the proof-of-concept phase of prototype development. One example is the 2024 iTIE system deployment completed near the mouth of the Rouge River in Detroit, MI (Figure 6). The Rouge River watershed has a long history of industrialization, with a legacy of chemical dumping, channelization, damming, and urban runoff[14]. This has led to degraded environmental conditions, with previous detections of a wide range of chemicals including heavy metals and various organics.

Figure 7. Survival and healthy development of P. promelas embryos and larvae following a 48-hour iTIE exposure near the mouth of the Rouge River. Organisms were exposed to site porewater as embryos for 48 hours and cultured post-exposure for an additional 5 days.
Figure 8. Survival of C. dilutus larvae after an iTIE exposure near the mouth of the Rouge River. Organisms were exposed to site porewater for 48 hours and cultured post-exposure for an additional 5 days. Error bars show standard deviation.

An iTIE system deployment was designed and completed to determine which chemical classes are most responsible for causing toxicity at the site. Resin treatments included glass wool (inert, non-fractionating substance), Chelex (metals sorption), Oasis HLB (general organics sorption), and Oasis WAX (organics sorption, with a high affinity for PFAS). The study utilized fathead minnow (P. promelas) embryos, due to their relative sensitivity to metals and PAHs, as well as second-instar midge (Chironomus dilutus) larvae due to their relative sensitivity to PFAS.

The test organisms were exposed to fractionated porewater in situ for 48 hours. Following exposure, organisms were cultured for an additional five days, and survival was recorded (Figures 7 and 8). Moderate declines in survival were seen in both species in the glass wool treatment, indicating toxicity at the site. For P. promelas, the highest proportion of healthy development occurred in the Chelex treatment, supporting the hypothesis that metals are a dominant cause of toxicity. C. dilutus had the greatest survival in the Oasis WAX treatment, suggesting that an organic stressor class like PFAS is also present at harmful concentrations in the river.

Water chemical analyses of fractionated and unfractionated water samples were completed to support biological results. Analyses were conducted for a range of stressor classes including metals, PAHs, PCBs, an organophosphate pesticide (chlorpyrifos), a PFAS compound (PFOS) and a pyrethroid insecticide (permethrin). Of these analytes, only heavy metals and PFOS were detected. Some chemical classes including PAHs and PCBs were not detected at the site. To reach similar conclusions using traditional Phase 1 TIE methods, one would need to complete the following tests: baseline toxicity, filtration, aeration, EDTA, C18 SPE, and methanol elution of C18 SPE. The iTIE method allows the same conclusions to be drawn with significantly less time and effort required.

Summary

The in situ Toxicity Identification Evaluation technology and protocol is a powerful tool that investigators can use to strengthen causal linkages between chemical stressors and ecological toxicity. By fractionating sampled water and exposing test organisms in situ, investigators can gather toxicity response data while minimizing sample manipulation and accurately representing environmental conditions.

References

  1. ^ 1.0 1.1 1.2 1.3 1.4 1.5 Burton, G.A., Cervi, E.C., Meyer, K., Steigmeyer, A., Verhamme, E., Daley, J., Hudson, M., Colvin, M., Rosen, G., 2020. A novel In Situ Toxicity Identification Evaluation (iTIE) System for Determining which Chemicals Drive Impairments at Contaminated Sites. Environmental Toxicology and Chemistry, 39(9), pp. 1746-1754. doi: 10.1002/etc.4799
  2. ^ 2.0 2.1 2.2 2.3 Steigmeyer, A.J., Zhang, J., Daley, J.M., Zhang, X., Burton, G.A. Jr., 2017. An in situ toxicity identification and evaluation water analysis system: Laboratory validation. Environmental Toxicology and Chemistry, 36(6), pp. 1636-1643. doi: 10.1002/etc.3696
  3. ^ United States Environmental Protection Agency, 2007. Sediment Toxicity Identification Evaluation (TIE) Phases I, II, and III Guidance Document, EPA/600/R-07/080. 145 pages. Free Download  Report.pdf
  4. ^ In Situ Toxicity Identification Evaluation (iTIE) Technology for Assessing Contaminated Sediments, Remediation Success, Recontamination and Source Identification Project Website  Final Report.pdf
  5. ^ Norberg-King, T., Mount, D.I., Amato, J.R., Jensen, D.A., Thompson, J.A., 1992. Toxicity identification evaluation: Characterization of chronically toxic effluents: Phase I. Publication No. EPA/600/6-91/005F. U.S. Environmental Protection Agency, Office of Research and Development. Free Download from US EPA  Report.pdf
  6. ^ Burton, G.A. Jr., Nordstrom, J.F., 2004. An in situ toxicity identification evaluation method part I: Laboratory validation. Environmental Toxicology and Chemistry, 23(12), pp. 2844-2850. doi: 10.1897/03-409.1
  7. ^ Burton, G.A. Jr., Nordstrom, J.F., 2004. An in situ toxicity identification evaluation method part II: Field validation. Environmental Toxicology and Chemistry, 23(12), pp. 2851-2855. doi: 10.1897/03-468.1
  8. ^ Chadwick, D.B., Harre, B., Smith, C.F., Groves, J.G., Paulsen, R.J., 2003. Coastal Contaminant Migration Monitoring: The Trident Probe and UltraSeep System. Hardware Description, Protocols, and Procedures. Technical Report 1902. Space and Naval Warfare Systems Center.
  9. ^ Woodard, S., Mohr, T., Nickelsen, M.G., 2014. Synthetic media: A promising new treatment technology for 1,4-dioxane. Remediation Journal, 24(4), pp. 27-40. doi: 10.1002/rem.21402
  10. ^ Lemos, B.R.S., Teixeira, I.F., de Mesquita, J.P., Ribeiro, R.R., Donnici, C.L., Lago, R.M., 2012. Use of modified activated carbon for the oxidation of aqueous sulfide. Carbon, 50(3), pp. 1386-1393. doi: 10.1016/j.carbon.2011.11.011
  11. ^ Iannone, A., Carriera, F., Di Fiore, C., Avino, P., 2024. Poly- and Perfluoroalkyl Substance (PFAS) Analysis in Environmental Matrices: An Overview of the Extraction and Chromatographic Detection Methods. Analytica, 5(2), pp. 187-202. doi: 10.3390/analytica5020012  Open Access Article
  12. ^ U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, 1994. Catalogue of Standard Toxicity Tests for Ecological Risk Assessment. ECO Update, 2(2), 4 pages. Publication No. 9345.0.05I Free Download  Report.pdf
  13. ^ Nichols, E., 2023. Methods for Identification and Prioritization of Stressors at Impaired Sites. Masters thesis, University of Michigan. University of Michigan Library Deep Blue Documents. Free Download  Report.pdf
  14. ^ Ridgway, J., Cave, K., DeMaria, A., O’Meara, J., Hartig, J. H., 2018. The Rouge River Area of Concern—A multi-year, multi-level successful approach to restoration of Impaired Beneficial Uses. Aquatic Ecosystem Health and Management, 21(4), pp. 398-408. doi: 10.1080/14634988.2018.1528816

See Also

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