Aluminium speciation in streams and lakes of the UK Acid Waters Monitoring Network, modelled with WHAM

Tipping, Edward; Carter, Heather

doi:10.1016/j.scitotenv.2010.12.030

Cited by 19 publications

(14 citation statements)

References 27 publications

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“…Examples include 71 the acidification of soils [7][8][9][10][11][12][13][14] and surface waters [15] , trace metal behaviour in soils [16][17][18][19][20][21][22] , surface 72 waters [23][24][25][26][27][28][29][30][31] and groundwaters [32] , lake sediment diagenesis [33,34] , rare earth geochemistry [35-73 37] , iron and manganese geochemistry [38][39][40][41] , radionclide geochemistry [42][43][44][45] , organic matter 74 solubility in soils [46,47] , catchment modelling [48,49] , interactions of metals with biota [50,51] , 75 ecotoxicology [52][53][54][55][56][57][58][59] and Critical Loads …”

Section: Tipping Et Al Humic Ion-binding Model Vii_revisionmentioning

confidence: 99%

Humic Ion-Binding Model VII: a revised parameterisation of cation-binding by humic substances

2011

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Article (refereed) -postprintTipping, E.; Lofts, S.; Sonke, J.E.. 2011. Humic Ion-Binding Model VII: a revised parameterisation of cation-binding by humic substances. Environmental Chemistry, 8 (3). 225-235. 10.1071/EN11016Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. [1,2] incorporating Humic Ion-Binding Model 55 V [3] or VI [4] permits the calculation of equilibrium chemical speciation for waters and soils in 56 which natural organic matter plays a significant role. The ion-binding models are based on 57 conventional chemical reactions involving O-containing weak acids, with empirical estimation 58 of the influence of soft ligand atoms (N, S) and electrostatic corrections, and are 59 parameterised from laboratory studies with isolated humic and fulvic acids. The NICA 60 model [5] is similarly parameterised and provides an alternative picture based on continuous 61 binding-site distributions. Tipping [2] identified both the Humic Ion-Binding Models and NICA 62 as comprehensive models, meaning that they deal with competitive interactions involving all 63 cations (including H + ), and take account of ionic strength effects and metal-proton exchange 64 ratios. They seek to represent cation-binding by the complex mixtures that comprise natural 65 organic matter as efficiently as possible, with the minimum number of parameters, in order to 66 be useful in addressing chemical processes in the environment. A different approach to 67 these parameterised models, but also potentially comprehensive, is the "forward modelling" 68 developed by Cabaniss [6] in which binding is calculated a priori from the known or assumed 69 distributed chemistry of humic substances. 70 Tipping et al. Humic Ion-Binding Model VII_REVISIONWHAM has been applied in a variety of research and regulatory areas. Examples include 71 the acidification of soils [7][8][9][10][11][12][13][14] and surface waters [15] , trace metal behaviour in soils [16][17][18][19][20][21][22] , surface 72 waters [23][24][25][26][27][28][29][30][31] and groundwaters [32] , lake sediment diagenesis [33,34] , rare earth geochemistry [35-73 37] , iron and manganese geochemistry [38][39][40][41] , radionclide geochemistry [42][43][44][45] , organic matter 74 solubility in soils [46,47] , catchment modelling [48,49] , interactions of metals with biota [50,51] , 75 ecotoxicology [52][53][54][55][56][57][58][59] and Critical Loads [60][61][62] . Given this evident utility, it is worthwhile to 76 continue to improve the humic ion-binding model and incorporate new data into its 77 parameterisation. Here we report on activities undertaken towards these goals, namely 78 modification of assumptions about multidentate binding, the fitting of new data, and the 79 introduction of a procedure to obtain more internally-consistent parameters. 80Changes in binding site formulation were prompte...

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Section: Tipping Et Al Humic Ion-binding Model Vii_revisionmentioning

confidence: 99%

Humic Ion-Binding Model VII: a revised parameterisation of cation-binding by humic substances

2011

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“…The predicted speciation of Al for each of the three test organisms in the presence of each DOC source is provided in the Supplemental Data (Tables S3 and S4 , on Al toxicity is likely to be due to these species directly competing with each other for binding sites [27]. Figure 4 shows for all three organisms the increased proportion of Al-FA complex and the decrease in Al 3þ and Al(OH) 2þ with increasing SRFA and SBFA.…”

Section: Effect Of Each Doc Source On Al Speciationmentioning

confidence: 99%

“…For practical reasons, studies that have investigated the influence of DOC on Al toxicity have used commercial humic substances/organic ligands, with the exception of a study by Burton and Allan [25]. However, more recent investigations comparing the influence of various DOC sources on the speciation and toxicity of U, Cu, and Al, have demonstrated that DOC sources can differ greatly in their capacity to complex metals [6,[26][27]. Thus, to accurately predict the toxicity of Al in natural systems, the nature of DOC within the system in question, and its influence on Al bioavailability must be considered.…”

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Dissolved organic carbon reduces the toxicity of aluminum to three tropical freshwater organisms

Trenfield¹,

Markich²,

Ng³

et al. 2012

Enviro Toxic and Chemistry

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The influence of dissolved organic carbon (DOC) on the toxicity of aluminum (Al) at pH 5 (relevant to acid mine drainage conditions), to the tropical green hydra (Hydra viridissima), green alga (Chlorella sp.), and cladoceran (Moinodaphnia macleayi) was assessed. Two DOC sources, a natural in situ DOC in soft billabong water (SBW) and Suwannee River fulvic acid (SRFA) standard, were compared. The order of sensitivity of the test organisms to dissolved Al (0.1 µm fraction) was Hydra viridissima > Moinodaphnia macleayi > Chlorella sp. with DOC reducing dissolved Al toxicity most for Hydra viridissima. However, colloidal or precipitated Al may contribute indirectly to the toxicity for M. macleayi and Chlorella sp. The toxicity of dissolved Al was up to six times lower in test waters containing 10 mg L(-1) DOC (in the form of SRFA), relative to toxicity observed at 1 mg L(-1) DOC. In contrast, the toxicity of Al was up to two times lower in SBW containing 10 mg L(-1) DOC, relative to water containing 1 mg L(-1) DOC. The increased ability of SRFA in reducing Al toxicity was linked to its greater affinity for complexing Al compared with the in situ DOC. This has important implications for studies that use commercial standards of humic substances to predict Al toxicity in local environments. Speciation modeling demonstrated that Al(3+) and AlOH(2+) provided a strong relationship with toxicity. An empirical relationship is provided for each organism that can be used to predict Al toxicity at a given Al and DOC concentration.

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“…Chemical modeling is a very useful tool to address these issues when speciation needs to be considered. This strategy has proved to be an appropriate approach to understand the trace element behavior in many natural environments [15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Using Chemical Modeling to Asses Water Quality in the Raigón Aquifer System in Southern Uruguay

Torres¹,

Gonzatto²,

Goso³

et al. 2015

JEPHH

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The Raigón aquifer is an important groundwater system in southern Uruguay. The increasing use of groundwater resources in the last decades has provoked changes in the concentration of many elements which are strongly related to anthropogenic pollution sources. Concentration levels are useful to detect changes in reservoir status but it is also necessary to analyze their chemical significance in order to make an accurate assessment of the sources of contamination and the causes of changes. In this work we use the available thermodynamic data to calculate chemical speciation on these groundwater samples. Trace elements present as anions, in particular Se and . Results show that these anions interact in solution and are greatly influenced by the concentration of the abundant calcium ion. Localized changes in pH can strongly affect the situation. The same is observed with the pE parameter, but only in the case of Se. Chemical speciation of trace elements is in general highly dependent on pH, pE and concentration of major elements. In consequence, for a fixed analytical total concentration, these parameters can markedly change the situation, affecting the mobility, the bioavailability and environmental fate of these elements. The strategy employed in this work can also be extended to the study of many other environmental water scenarios.

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Aluminium speciation in streams and lakes of the UK Acid Waters Monitoring Network, modelled with WHAM

Cited by 19 publications

References 27 publications

Humic Ion-Binding Model VII: a revised parameterisation of cation-binding by humic substances

Humic Ion-Binding Model VII: a revised parameterisation of cation-binding by humic substances

Dissolved organic carbon reduces the toxicity of aluminum to three tropical freshwater organisms

Using Chemical Modeling to Asses Water Quality in the Raigón Aquifer System in Southern Uruguay

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