Rising concentrations of atmospheric carbon dioxide are causing acidification of the oceans. This results in changes to the concentrations of key chemical species such as hydroxide, carbonate and ...bicarbonate ions. These changes will affect the distribution of different forms of trace metals. Using IPCC data for pCO2 and pH under four future emissions scenarios (to the year 2100) we use a chemical speciation model to predict changes in the distribution of organic and inorganic forms of trace metals. Under a scenario where emissions peak after the year 2100, predicted free ion Al, Fe, Cu, and Pb concentrations increase by factors of up to approximately 21, 2.4, 1.5, and 2.0 respectively. Concentrations of organically complexed metal typically have a lower sensitivity to ocean acidification induced changes. Concentrations of organically complexed Mn, Cu, Zn, and Cd fall by up to 10%, while those of organically complexed Fe, Co, and Ni rise by up to 14%. Although modest, these changes may have significance for the biological availability of metals given the close adaptation of marine microorganisms to their environment.
This paper describes an agricultural model (Roth-CNP) that estimates carbon (C), nitrogen (N) and phosphorus (P) pools, pool changes, their balance and the nutrient fluxes exported from arable and ...grassland systems in the UK during 1800–2010. The Roth-CNP model was developed as part of an Integrated Model (IM) to simulate C, N and P cycling for the whole of UK, by loosely coupling terrestrial, hydrological and hydro-chemical models. The model was calibrated and tested using long term experiment (LTE) data from Broadbalk (1843) and Park Grass (1856) at Rothamsted. We estimated C, N and P balance and their fluxes exported from arable and grassland systems on a 5km×5km grid across the whole of UK by using the area of arable of crops and livestock numbers in each grid and their management. The model estimated crop and grass yields, soil organic carbon (SOC) stocks and nutrient fluxes in the form of NH4-N, NO3-N and PO4-P. The simulated crop yields were compared to that reported by national agricultural statistics for the historical to the current period. Overall, arable land in the UK have lost SOC by −0.18, −0.25 and −0.08MgCha−1y−1 whereas land under improved grassland SOC stock has increased by 0.20, 0.47 and 0.24MgCha−1y−1 during 1800–1950, 1950–1970 and 1970–2010 simulated in this study. Simulated N loss (by leaching, runoff, soil erosion and denitrification) increased both under arable (−15, −18 and −53kgNha−1y−1) and grass (−18, −22 and −36kgNha−1y−1) during different time periods. Simulated P surplus increased from 2.6, 10.8 and 18.1kgPha−1y−1 under arable and 2.8, 11.3 and 3.6kgPha−1y−1 under grass lands 1800–1950, 1950–1970 and 1970–2010.
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•Roth-CNP model estimates C, N and P cycling within the UK agriculture for 1800–2010.•Simulated crop yields were comparable to the yields of UK's agricultural statistics.•Simulated SOC stock decreased under arable and increased under improved grassland.•Simulated N and P losses increased under both arable and grasslands.•Results shows the effect of local agriculture in a larger context of space and time.
Aims We investigated whether density fractionation can be used to determine the distribution of organic phosphorus (OP) between free and mineral-associated soil organic matter (SOM). Methods We ...performed density fractionations using sodium polytungstate solution (specific gravity 1.6 g cm−3) on 20 soils from UK semi-natural and pasture ecosystems, to obtain a light fraction (LF) and a heavy fraction (HF) for each soil. The fractions were quantified by weight, and analysed for organic carbon (OC), total N (TN), total P (TP), inorganic P (IP), and OP (by difference). Results Good recoveries of soil mass (96%), OC and TN (both ∼ 90%) were obtained, but recovery of OP only averaged 56%. The average P:C ratio of HF SOM exceeded that of LF SOM by a factor of six, greater than the factor of two obtained for TN:OC. For the soils studied, the elements of SOM were predominantly in the HF, with averages of 75% for C, 82% for N, and 90% for P. Conclusions The incomplete recovery of OP demands further work. Nonetheless, the results show that HF SOM is much richer in P than LF SOM.
Understanding metal and proton toxicity under field conditions requires consideration of the complex nature of chemicals in mixtures. Here, we demonstrate a novel method that relates streamwater ...concentrations of cationic metallic species and protons to a field ecological index of biodiversity. The model WHAM-
F
TOX postulates that cation binding sites of aquatic macroinvertebrates can be represented by the functional groups of natural organic matter (humic acid), as described by the Windermere Humic Aqueous Model (WHAM6), and supporting field evidence is presented. We define a toxicity function (
F
TOX) by summing the products: (amount of invertebrate-bound cation)
×
(cation-specific toxicity coefficient,
α
i
). Species richness data for Ephemeroptera, Plecoptera and Trichoptera (EPT), are then described with a lower threshold of
F
TOX, below which all organisms are present and toxic effects are absent, and an upper threshold above which organisms are absent. Between the thresholds the number of species declines linearly with
F
TOX. We parameterised the model with chemistry and EPT data for low-order streamwaters affected by acid deposition and/or abandoned mines, representing a total of 412 sites across three continents. The fitting made use of quantile regression, to take into account reduced species richness caused by (unknown) factors other than cation toxicity. Parameters were derived for the four most common or abundant cations, with values of
α
i
following the sequence (increasing toxicity) H
+
<
Al
<
Zn
<
Cu. For waters affected mainly by H
+ and Al,
F
TOX shows a steady decline with increasing pH, crossing the lower threshold near to pH 7. Competition effects among cations mean that toxicity due to Cu and Zn is rare at lower pH values, and occurs mostly between pH 6 and 8.
Dialysis and chemical speciation modelling have been used to calculate activities of Fe
3+
for a range of UK surface waters of varying chemistry (pH 4.3–8.0; dissolved organic carbon 1.7–40.3 mg l
−1
...) at 283 K. The resulting activities were regressed against pH to give the empirical model:
. Predicted Fe
3+
activities are consistent with a solid–solution equilibrium with hydrous ferric oxide, consistent with some previous studies on Fe(III) solubility in the laboratory. However, as has also sometimes been observed in the laboratory, the slope of the solubility equation is lower than the theoretical value of 3. The empirical model was used to predict concentrations of Fe in dialysates and ultrafiltrates of globally distributed surface and soil/groundwaters. The predictions were improved greatly by the incorporation of a temperature correction for
, consistent with the temperature dependence of previously reported hydrous ferric oxide solubility. The empirical model, incorporating temperature effects, may be used to make generic predictions of the ratio of free and complexed Fe(III) to dissolved organic matter in freshwaters. Comparison of such ratios with observed Fe:dissolved organic matter ratios allows an assessment to be made of the amounts of Fe present as Fe(II) or colloidal Fe(III), where no separate measurements have been made.
Published experimental data for Al(III) and Fe(III) binding by fulvic and humic acids can be explained approximately by the Humic Ion-Binding Model VI. The model is based on conventional equilibrium ...reactions involving protons, metal aquo ions and their first hydrolysis products, and binding sites ranging from abundant ones of low affinity, to rare ones of high affinity, common to all metals. The model can also account for laboratory competition data involving Al(III), Fe(III) and trace elements, supporting the assumption of common binding sites. Field speciation data (116 examples) for Al in acid-to-neutral waters can be accounted for, assuming that 60–70 % (depending upon competition by iron, and the chosen fulvic acid : humic acid ratio) of the dissolved organic carbon (DOC) is due to humic substances, the rest being considered inert with respect to ion binding. After adjustment of the model parameter characterizing binding affinity within acceptable limits, and with the assumption of equilibrium with a relatively soluble form of Fe(OH)
3, the model can simulate the results of studies of two freshwater samples, in which concentrations of organically complexed Fe were estimated by kinetic analysis.
The model was used to examine the pH dependence of Al and Fe binding by dissolved organic matter (DOM) in freshwaters, by simulating the titration with Ca(OH)
2 of an initially acid solution, in equilibrium with solid-phase Al(OH)
3 and Fe(OH)
3. For the conditions considered, Al, which is present at higher free concentrations than Fe(III), competes significantly for the binding of Fe(III), whereas Fe(III) has little effect on Al binding. The principal form of Al simulated to be bound at low pH is Al
3+, AlOH
2+ being dominant at pH >6; the principal bound form of Fe(III) is FeOH
2+ at all pH values in the range 4–9. Simulations suggest that, in freshwaters, both Al and Fe(III) compete significantly with trace metals (Cu, Zn) for binding by natural organic matter over a wide pH range (4–9). The competition effects are especially strong for a high-affinity trace metal such as Cu, present at low total concentrations (∼1 nM). As a result of these competition effects, high-affinity sites in humic matter may be less important for trace metal binding in the field than they are in laboratory systems involving humic matter that has been treated to remove associated metals.
Concentrations of Al, Fe, Mn, Ni, Cu, Cd, Pb, and Zn were measured using DGT (diffusive gradients in thin-films) devices deployed in situ in 34 headwater streams in Northern England. Mean values of ...filtered samples analyzed by ICP-MS (inductively coupled plasma mass spectrometry) were used, along with DOC (dissolved organic carbon), pH and major ions, to calculate the distribution of metal species using the speciation code WHAM. DGT-measured concentrations, MeDGT, of Zn and Cd were generally similar to concentrations in filtered samples, Mefilt. For the other metals, MeDGT was similar to or lower than Mefilt. Calculation of the maximum dynamic metal from the speciation predicted using WHAM showed that most of the lower values of CuDGT could be attributed to the dominance of Cu−fulvic acid complexes, which diffuse more slowly than simple inorganic species. Similar calculations for Al, Pb, and Mn were consistent with appreciable proportions of these metals being present as colloids that are not simple complexes with humic substances. Differences between WHAM predictions and the measured NiDGT indicated that WHAM used with the default binding parameters underestimates Ni binding to natural organic matter. Plots of MeDGT versus the ratio of bound metal to DOC provided slight evidence of heterogeneous binding of Pb and Cu, while results for Mn, Cd, and Zn were consistent with weak binding and complete lability.
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