Chronic Toxicity of Iron to Aquatic Organisms under Variable pH, Hardness, and Dissolved Organic Carbon Conditions

Cardwell, Allison S.; Rodriquez, Patricio H; Stubblefield, William A.; DeForest, David K.; Adams, William J.

doi:10.1002/etc.5627

Cited by 5 publications

(9 citation statements)

References 26 publications

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“…Testing for all three species was skewed somewhat toward waters with relatively low hardness and pH compared with the distribution in natural waters. However, this was a necessary consequence of Fe having relatively low toxicity and issues with Fe precipitation in waters with high hardness and pH (Cardwell et al, 2023) rather than an intentional avoidance of naturally occurring conditions in the toxicity testing study design.…”

Section: Resultsmentioning

confidence: 99%

“…The methods and results of toxicity testing conducted with R. subcapitata , C. dubia , and P. promelas are provided in a companion paper (Cardwell et al, 2023; Supporting Information, Tables S1–S3). These were the only data identified for development of species‐specific MLRs.…”

Section: Methodsmentioning

confidence: 99%

“…To understand how the toxicity data described in Cardwell et al (2023) are distributed as a function of pH, DOC, and hardness, we compared them with a previously described natural waters data set from the United States (Brix et al, 2020). This comparison was conducted using previously described methods (Brix et al, 2021) in which a principal component analysis (PCA) of the z ‐scores of log(DOC), log(Hardness), and pH from the United States natural waters data set was conducted in R ( prcomp ()) to reduce the data set to two dimensions.…”

Section: Methodsmentioning

confidence: 99%

“…Our study aimed to develop chronic Fe MLR models for use in deriving site-specific WQGs. The MLR models were developed for three phylogenetically diverse taxa relying on relatively small toxicity data sets that were generated specifically for the purpose of developing bioavailability models (Cardwell et al, 2023). Models for all three species indicate that DOC is an important TMF for Fe.…”

Section: Mlr Model Development and Performancementioning

confidence: 99%

“…In a companion article in this issue, the influence of dissolved organic carbon (DOC), hardness, and pH on chronic Fe (added as Fe(III)) toxicity to an alga ( Raphidocelis subcapitata ), an invertebrate ( Ceriodaphnia dubia ), and a fish ( Pimephales promelas ) are characterized (Cardwell et al, 2023 [companion paper]). The objective of our study was to use these data to develop empirical bioavailability models that predict Fe toxicity as a function of these TMFs.…”

Section: Introductionmentioning

confidence: 99%

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Development of Multiple Linear Regression Models for Predicting Chronic Iron Toxicity to Aquatic Organisms

Brix

Tear

DeForest

et al. 2023

Enviro Toxic and Chemistry

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We developed multiple linear regression (MLR) models for predicting iron (Fe) toxicity to aquatic organisms for use in deriving site‐specific water quality guidelines (WQGs). The effects of dissolved organic carbon (DOC), hardness, and pH on Fe toxicity to three representative taxa (Ceriodaphnia dubia, Pimephales promelas, and Raphidocelis subcapitata) were evaluated. Both DOC and pH were identified as toxicity‐modifying factors (TMFs) for P. promelas and R. subcapitata, whereas only DOC was a TMF for C. dubia. The MLR models based on effective concentration 10% and 20% values were developed and performed reasonably well, with adjusted R2 of 0.68–0.89 across all species and statistical endpoints. Differences among species in the MLR models precluded development of a pooled model. Instead, the species‐specific models were assumed to be representative of invertebrates, fish, and algae and were applied accordingly to normalize toxicity data. The species sensitivity distribution (SSD) included standard laboratory toxicity data and effects data from mesocosm experiments on aquatic insects, with aquatic insects being the predominant taxa in the lowest quartile of the SSD. Using the European Union approach for deriving WQGs, application of MLR models to this SSD resulted in WQGs ranging from 114 to 765 μg l−1 Fe across the TMF conditions evaluated (DOC: 0.5–10 mg l−1; pH: 6.0–8.4), with slightly higher WQGs (199–910 μg l−1) derived using the US Environmental Protection Agency (USEPA) methodology. An important uncertainty in these derivations is the applicability of the C. dubia MLR model (no pH parameter) to aquatic insects, and understanding the pH sensitivity of aquatic insects to Fe toxicity is a research priority. An Excel‐based tool for calculating Fe WQGs using both European Union and USEPA approaches across a range of TMF conditions is provided. Environ Toxicol Chem 2023;42:1386–1400. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Mlr Model Development and Performancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Development of Multiple Linear Regression Models for Predicting Chronic Iron Toxicity to Aquatic Organisms

Brix

Tear

DeForest

et al. 2023

Enviro Toxic and Chemistry

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Recommended updates to the USEPA Framework for Metals Risk Assessment: Aquatic ecosystems

Adams¹,

Garman²

2023

Integr Envir Assess & Manag

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In 2007, the US Environmental Protection Agency issued its “Framework for Metals Risk Assessment.” The framework provides technical guidance to risk assessors and regulators when performing human health and environmental risk assessments of metals. This paper focuses on advances in the science including assessing bioavailability in aquatic ecosystems, short‐ and long‐term fate of metals in aquatic ecosystems and advances in risk assessment of metals in sediments. Notable advances have occurred in the development of bioavailability models for assessing toxicity as a function of water chemistry in freshwater ecosystems. The Biotic Ligand Model (BLM), Multiple Linear Regression model (MLR) and Multi‐Metal BLM (mBLM) now exist for most of the common mono‐ and di‐valent metals. Species sensitivity distributions (SSDs) for many metals exist making it possible for many jurisdictions to develop or update their water quality criteria or guidelines. The understanding of the fate of metals in the environment has undergone significant scrutiny over the past 20 years. Transport and toxicity models have evolved including the Unit World Model (UWM) allowing for estimation of concentrations of metals in various compartments as a function of loading and time. There has been significant focus on the transformation of metals in sediments to forms that are less bioavailable and on understanding conditions that result in re‐solubilization or redistribution of metals in and from sediments. Methods for spiking sediments have advanced such that the resulting chemistry in the laboratory mimics that in natural systems. Sediment bioavailability models are emerging including models that allow for prediction of toxicity in sediments for copper and nickel. Biodynamic models have been developed for several organisms and many metals. The models allow for estimates of transport of metals from sediments to organisms via their diet as well as their water exposure. All these advances expand the tool set available to risk assessors.

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Morinda coreia fruits derived green-emissive nitrogen-doped carbon quantum dots: Selective and sensitive detection of ferric ions from water

Tony Elizabeth,

Denis Arockiaraj,

Rajasekaran

et al. 2024

Inorganic Chemistry Communications

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Chronic Toxicity of Iron to Aquatic Organisms under Variable pH, Hardness, and Dissolved Organic Carbon Conditions

Cited by 5 publications

References 26 publications

Development of Multiple Linear Regression Models for Predicting Chronic Iron Toxicity to Aquatic Organisms

Development of Multiple Linear Regression Models for Predicting Chronic Iron Toxicity to Aquatic Organisms

Recommended updates to the USEPA Framework for Metals Risk Assessment: Aquatic ecosystems

Morinda coreia fruits derived green-emissive nitrogen-doped carbon quantum dots: Selective and sensitive detection of ferric ions from water

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