Simulating the long-term chemistry of an upland UK catchment: major solutes and acidification

Long-term effects of atmospheric deposition on British plant species richness

The effects of atmospheric pollution on plant species richness (n_sp) are of widespread concern. We carried out a modelling exercise to estimate how n_sp in British semi-natural ecosystems responded to atmospheric deposition of nitrogen (N_dep) and sulphur (S_dep) between 1800 and 2010. We derived a simple four-parameter equation relating n_sp to measured soil pH, and to net primary productivity (NPP), calculated with the N14CP ecosystem model. Parameters were estimated from a large data set (n = 1156) of species richness in four vegetation classes, unimproved grassland, dwarf shrub heath, peatland, and broadleaved woodland, obtained in 2007. The equation performed reasonably well in comparisons with independent observations of n_sp. We used the equation, in combination with modelled estimates of NPP (from N14CP) and soil pH (from the CHUM-AM hydrochemical model), to calculate changes in average n_sp over time at seven sites across Britain, assuming that variations in n_sp were due only to variations in atmospheric deposition. At two of the sites, two vegetation classes were present, making a total of nine site/vegetation combinations. In four cases, n_sp was affected about equally by pH and NPP, while in another four the effect of pH was dominant. The ninth site, a chalk grassland, was affected only by NPP, since soil pH was assumed constant. Our analysis suggests that the combination of increased NPP, due to fertilization by N_dep, and decreased soil pH, primarily due to S_dep, caused an average species loss of 39% (range 23-100%) between 1800 and the late 20th Century. The modelling suggests that in recent years n_sp has begun to increase, almost entirely due to reductions in S_dep and consequent increases in soil pH, but there are also indications of recent slight recovery from the eutrophying effects of N_dep.

The use of assemblage models to describe trace element partitioning, speciation, and fate: a review

The fate of trace elements in soils, sediments, and surface waters is largely determined by their binding to reactive components, of which organic matter, metal oxides, and clays are considered most important. Assemblage models, combining separate mechanistic complexation models for each of the reactive components, can be used to predict the solid-solution partitioning and speciation of trace elements in natural environments. In the present review, the authors provide a short overview of advanced ion-binding models for organic matter and oxides and of their application to artificial and natural assemblages. Modeling of artificial assemblages of mineral components and organic matter indicates that the interactions between organic and mineral components are important for trace element binding, particularly for oxyanions. The modeling of solid-solution partitioning in natural systems is generally adequate for metal cations but less so for oxyanions, probably because of the neglect of organic matter-oxide interactions in most assemblage models. The characterization of natural assemblages in terms of their components (active organic matter, reactive oxide surface) is key to successful model applications. Improved methods for characterization of reactive components in situ will enhance the applicability of assemblage models. Collection of compositional data for soil and water archetypes, or the development of relationships to estimate compositions from geospatially available data, will further facilitate assemblage model use for predictive purposes.

Dynamic modelling of the long term behaviour of cadmium, lead and mercury in Swiss forest soils using CHUM-AM

The applicability of the dynamic soil model CHUM-AM was tested to simulate concentrations of Cd, Pb and Hg in five Swiss forest soils. Soil cores of up to 50 cm depth were sampled and separated into two defined soil layers. Soil leachates were collected below the litter by zero-tension lysimeters and at 15 and 50 cm soil depths by tension lysimeters over two years. The concentrations of Cd, Pb and Hg in the solid phase and soil solution were measured by ICP-MS (Cd, Pb) or CV-AFS (Hg). Measured metal concentrations were compared with modelled concentrations using CHUM-AM. Additionally we ran the model with three different deposition scenarios (current deposition; maximum acceptable deposition according to the Swiss ordinance on Air Pollution Control; critical loads according to CLRTAP) to predict metal concentrations in the soils for the next 1000 years. Assuming current loads concentrations of Cd and Pb showed varying trends (increasing/decreasing) between the soils. Soils rich in organic carbon or with a high pH value showed increasing trends in Cd and Pb concentrations whereas the concentrations in the other soils decreased. In contrast Hg concentrations are predicted to further increase in all soils. Critical limits for Pb and Hg will partly be exceeded by current loads or by the critical loads proposed by the CLRTAP but the critical limits for Cd will rarely be reached within the next 1000 years. In contrast, maximal acceptable deposition will partly lead to concentrations above the critical limits for Pb in soils within the next 400 years, whereas the acceptable deposition of Cd will not lead to concentrations above the proposed critical limits. In conclusion the CHUM-AM model is able to accurately simulate heavy metal (Cd, Pb and Hg) concentrations in Swiss forest soils of various soil properties.

An intermediate complexity dynamic model for predicting accumulation of atmospherically-deposited metals (Ni, Cu, Zn, Cd, Pb) in catchment soils: 1400 to present

The Intermediate Dynamic Model for Metals (IDMM) is a model for prediction of the pools of metals (Ni, Cu, Zn, Cd, Pb) in topsoils of catchments resulting from deposition of metals from the atmosphere. We used the model to simulate soil metal pools from 1400 onwards in ten UK catchments comprising semi-natural habitats, and compared the results with present day observations of soil metal pools. Generally the model performed well in simulating present day pools, and further improvements were made to simulations of Ni, Cu, Zn and Cd by adjusting the strength of metal adsorption to the soils. Some discrepancies between observation and prediction for Pb appeared to be due either to underestimation of cumulative deposition, or to overestimation of the metal pool under 'pristine', pre-industrial conditions. The IDMM provides a potential basis for large scale assessment of metal dynamics in topsoils.

Indirect human exposure assessment of airborne lead deposited on soil via a simplified fate and speciation modelling approach

In order to estimate the total exposure to the lead emissions from a municipal waste combustion plant in Denmark, the indirect pathway via ingestion of lead deposited on soil has to be quantified. Multi-media fate models developed for both Risk Assessment (RA) and Life Cycle Assessment (LCA) can be used for this purpose, but present high uncertainties in the assessment of metal's fate. More sophisticated and metal-specific geochemical models exist, that could lower the uncertainties by e.g. accounting for metal speciation, but they require a large amount of data and are unpractical to combine broadly with other fate and dispersion models. In this study, a Simplified Fate & Speciation Model (SFSM) is presented, that is based on the parsimony principle: "as simple as possible, as complex as needed", and that can be used for indirect human exposure assessment in different context like RA and regionalized LCA. SFSM couples traditional multi-media mass balances with empirical speciation models in a tool that has a simple theoretical framework and that is not data-intensive. The model calculates total concentration, dissolved concentration, and free ion activity of Cd, Cu, Ni, Pb and Zn in different soil layers, after accounting for metal deposition and dispersion. The model is tested for these five metals by using data from peer reviewed literature. Results show good accordance between measured and calculated values (factor of 3). The model is used to predict the human exposure via soil to lead initially emitted into air by the waste combustion plant and both the lead cumulative exposure and intake fraction are calculated.

Using advanced surface complexation models for modelling soil chemistry under forests: Solling forest, Germany

Various dynamic soil chemistry models have been developed to gain insight into impacts of atmospheric deposition of sulphur, nitrogen and other elements on soil and soil solution chemistry. Sorption parameters for anions and cations are generally calibrated for each site, which hampers extrapolation in space and time. On the other hand, recently developed surface complexation models (SCMs) have been successful in predicting ion sorption for static systems using generic parameter sets. This study reports the inclusion of an assemblage of these SCMs in the dynamic soil chemistry model SMARTml and applies this model to a spruce forest site in Solling Germany. Parameters for SCMs were taken from generic datasets and not calibrated. Nevertheless, modelling results for major elements matched observations well. Further, trace metals were included in the model, also using the existing framework of SCMs. The model predicted sorption for most trace elements well.

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

The Windermere Humic Aqueous Model (WHAM) incorporating Humic Ion-Binding Model VI was applied to analytical data from the United Kingdom Acid Waters Monitoring Network, collected for 22 streams and lakes over the period 1988-2007, to calculate the chemical speciation of monomeric aluminium (Al(mon)) in 3087 water samples. Model outputs were compared with analytical measurements of labile and non-labile Al(mon) concentrations, the former being equated with inorganic forms of Al(mon) and the latter with organically-complexed metal. Raw analytical data were used, and also data produced by applying a correction for the possible dissociation of organically-complexed Al(mon), and therefore its underestimation, during passage through the analytical cation-exchange column. Model calibration was performed by finding the conversion factor, F(FADOC), between the concentration of isolated fulvic acid, with default ion-binding properties, required by the model, and the measured concentration of dissolved organic carbon, [DOC]. For both uncorrected and corrected data, the value of F(FADOC) for streams was greater than for lakes, indicating greater binding activity towards aluminium. Model fits were better using uncorrected analytical data, but the values of F(FADOC) obtained from corrected data agreed more closely with previous estimates. The model provided reasonably good explanations of differences in aluminium speciation between sampling sites, and of temporal variations at individual sites. With total monomeric concentration as input, WHAM calculations might substitute for analytical speciation measurements, or aid analytical quality control. Calculated Al(3+) activities, a(Al3+), showed a pH-dependence similar to that previously found for other surface waters, and the modelling exercise identified differences between waters of up to two orders of magnitude in the value of a(Al3+) at a given pH. The model gives the net charge of dissolved organic matter, which is calculated to have risen significantly at 15 of the AWMN sites, due to increases in pH and decreases in aluminium concentration.

Dynamic modelling of atmospherically-deposited Ni, Cu, Zn, Cd and Pb in Pennine catchments (northern England)

Simulation modelling with CHUM-AM was carried out to investigate the accumulation and release of atmospherically-deposited heavy metals (Ni, Cu, Zn, Cd and Pb) in six moorland catchments, five with organic-rich soils, one with calcareous brown earths, in the Pennine chain of northern England. The model considers two soil layers and a third layer of weathering mineral matter, and operates on a yearly timestep, driven by deposition scenarios covering the period 1400-2010. The principal processes controlling heavy metals are competitive solid-solution partitioning of solutes, chemical interactions in solution, and chemical weathering. Agreement between observed and simulated soil metal pools and surface water concentrations for recent years was generally satisfactory, the results confirming that most contemporary soil metal is from atmospheric pollution. Metals in catchments with organic-rich soils show some mobility, especially under more acid conditions, but the calcareous mineral soils have retained nearly all anthropogenic metal inputs. Complexation by dissolved organic matter and co-transport accounts for up to 80% of the Cu in surface waters.

Long-term nitrate increases in two oligotrophic lakes, due to the leaching of atmospherically-deposited N from moorland ranker soils

During the last 50 years nitrate concentrations in Buttermere and Wastwater (Cumbria, UK) have risen significantly, by 70 and 100%, respectively. By estimating contemporary nitrate fluxes in the lakes' catchments and in sub-catchments and comparing them with the fractional areas of different soil types, it is deduced that the surface water nitrate is derived almost entirely from organic-rich ranker soils that have a limited ability to retain atmospherically-deposited nitrogen. Little or no nitrate leaches from the other major soil type, a brown podzol, despite it having a lower C:N ratio (12.0 g g(-1)) than the ranker (17.0 g g(-1)), nor is there much contribution from the small areas of improved (chemically fertilised) grassland within the catchments. Although some nitrate leaching is occurring, total N losses are appreciably smaller than atmospheric inputs, so the catchment soils are currently accumulating between 3 and 4 g N m(-2) a(-1).

Simulating the long-term chemistry of an upland UK catchment: heavy metals

CHUM-AM was used to investigate the behaviours of atmospherically-deposited heavy metals (Ni, Cu, Zn, Cd and Pb) in three moorland sub-catchments in Cumbria UK. The principal processes controlling cationic metals are competitive partitioning to soil organic matter, chemical interactions in solution, and chemical weathering. Metal deposition histories were generated by combining measured data for the last 30 years with local lake sediment records. For Ni, Cu, Zn and Cd, default parameters for the interactions with organic matter provided reasonable agreement between simulated and observed present-day soil metal pools and average streamwater concentrations. However, for Pb, the soil binding affinity in the model had to be increased to match the observations. Simulations suggest that weakly-sorbing metals (Ni, Zn, Cd) will respond on timescales of decades to centuries to changes in metal inputs or acidification status. More strongly-sorbing metals (Cu, Pb) will respond over centuries to millennia.