Malcolm S. Cresser

The nitrogen composition of streams in upland Scotland: some regional and seasonal differences

The nitrogen (N) composition of streams draining four upland regions of Scotland was compared in samples collected monthly between April 1997 and April 1998. Stream samples were analysed for total N (TN), particulate N (PN), nitrate (NO3), ammonium (NH4), dissolved organic N (DON) and dissolved organic carbon (DOC). Concentrations of TN were small, generally less than 1 mg l(-1) , dominated by dissolved forms of N, and varied significantly between upland regions. Nitrate accounted for most of the variability in TN; largest concentrations were observed in the Southern Uplands and smallest concentrations were observed in the Highlands. Nitrate concentrations were positively correlated with the percentage cover of improved grasslands and brown forest soils and negatively correlated with the percentage cover of peat. Concentrations of DON also varied between regions, but to a lesser extent than those of NO3. Largest concentrations occurred in SW Scotland and smallest concentrations in the Cairngorms. Although a significant positive correlation between DON and DOC was observed, stream water DON content was not related to the percentage cover of peat in the catchment, as was the case for DOC. The average DOC:DON ratio was narrower for streams in the Southern Uplands than for those in the Cairngorms and Highlands. Nitrate and DON displayed contrasting seasonal trends; NO3 concentrations were larger in the winter while DON concentrations were larger in the summer. Only a small proportion, < 8% and < 7%, of TN was PN and NH4, respectively, the majority of N was present as either NO3 or DON. Nitrate was the dominant fraction (58-65%) in all regions except the Highlands where DON accounted for 57% of TN. However, the relative importance of the DON component increased in the summer in all regions. This study has demonstrated that the DON fraction is an important component of the total N transported by streams from upland catchments in Scotland. Thus, assessments of anthropogenic impacts on N losses from upland ecosystems need to consider not only the dissolved inorganic species but also DON.

Riparian zone influence on stream water chemistry at different spatial scales: a GIS-based modelling approach, an example for the Dee, NE Scotland

A geographical information system (GIS-ARC/INFO) was used to collate existing spatial data sets on catchment characteristics to predict stream water quality using simple empirical models. The study, based on the river Dee catchment in NE Scotland, found that geological maps and associated geochemical information provided a suitable framework for predicting chemical parameters associated with acidification sensitivity (including alkalinity and base cation concentrations). In particular, it was found that in relatively undisturbed catchments, the parent material and geochemistry of the riparian zone, when combined with a simple hydrological flow path model, could be used to accurately predict stream water chemistry at a range of flows (Q95 to > Q5) and spatial scales (1-1000 km2). This probably reflects the importance of the riparian zone as an area where hydrological inputs to stream systems occur via flow paths in the soil and groundwater zones. Thus, evolution of drainage water chemistry appears to retain the geochemical characteristics of the riparian area as it enters the channel network. In more intensively managed catchments, riparian land use is a further influential factor, which can be incorporated into models to improve predictions for certain base cations. The utility in providing simple hydrochemical models, based on readily available data sets, to assist environmental managers in planning land use in catchment systems is discussed.

The influence of catchment characteristics on the seasonality of carbon and nitrogen species concentrations in upland rivers of Northern Scotland

Data from 13 catchments with no arable land in Northern Scotland were used to develop empirical linear regression models of average monthly NO3− concentrations and average summer and winter concentrations for NH4+, dissolved organic N (DON) and dissolved organic carbon (DOC) as a function of catchment characteristics. All catchments displayed a pronounced seasonal NO3− cycle. Variation in monthly mean NO3− concentration within and between catchments could be predicted from mean monthly air temperature using separate regression equations for temperatures < and ≥ 5 °C. Soil type, climate and land use influenced NH4+ concentrations. In summer, concentrations of NH4+ were largest in catchments with extensive areas of brown forest soils, which are less acidic and more base-rich than other upland soils. However, concentrations declined with increasing conifer cover and summer rainfall. In winter, however, % conifer cover had a positive effect, while higher temperature and higher humus iron podzol cover had negative influences. DON concentration decreased with increasing catchment elevation in both summer and winter. Surprisingly, concentrations of DON only displayed a positive relationship with percentage peat cover in the summer. The most important factor controlling DOC concentration was soil type, with a positive relationship being observed between DOC and peat and humus iron podzol coverage. Elevation was also important, but only in the winter when concentrations were negatively correlated with maximum catchment elevation. Overall, multivariate regression equations explained the spatial and seasonal variability in N species concentrations over a range of catchments within Northern Scotland.

An evaluation of current environmental management systems as indicators of environmental performance

Purpose – This paper aims to evaluate current environmental management systems as indicators of the environmental performance of an organisation.Design/methodology/approach – It considers, in particular, the development of current environmental management systems BS EN ISO 14001:1996 and the eco‐management and audit scheme (EMAS) 761/2001 EEC.Findings – Currently, organisations implementing either BS EN ISO 14000:1996 or EMAS do not need to comment on overall environmental performance. Environmental management is viewed as the control of all human activities that have significant impact on the environment. Neither standard comments on the degree of control exercised, the approach taken, or the effectiveness of that control.Originality/value – Environmental performance evaluation guidelines are appraised, and quality awards as a conceptual framework for classification of environmental performance are introduced.

An evaluation of multielement analysis of historic soil contamination to differentiate space use and former function in and around abandoned farms

Historic and prehistoric human activity can cause accumulation of elements in the soil. Multielement soil analysis has been used extensively over the last two decades to study element patterns of historic soil enrichment as a means of prospecting for sites and as an aid to interpretation of space use within archaeological structures. However, there have been surprisingly few of studies designed to assist with the interpretation of the analytical results. In this investigation soils from six abandoned farms with a known history of spatial use were sampled to determine if similar patterns of trace element enhancement occur between different farms. The preliminary results show significant differences in soil elemental concentrations between the functional areas, and highlight similar patterns of element enhancement between the farms. Concentrations of Ca, P, Sr, Ba, Zn and Pb are elevated in the buildings and fields of all the farms and provide valuable information about past human activity.

Toxicological response of a bioluminescent microbial assay to Zn, Pb and Cu in an artificial soil solution: relationship with total metal concentrations and free ion activities.

The relationship between toxicological response and both total concentrations and free ion activities of Pb, Cu and Zn in an artificial soil solution has been investigated using lux-marked Escherichia coli HB101 (pUCD607) as a bioassay. SO4(2-) (as K2SO4) was added as an inorganic complexing agent up to 0.01 M representing the range of ionic strengths found in soil solutions and giving a wide range of free metal ion activities. EC50 values expressed in terms of concentration, varied significantly with K2SO4 molarity for all metals. However, when EC50 values were expressed in terms of free ion activity they were not significantly different for Pb and Zn, supporting the free ion activity model. Conversely, EC50 values expressed as free Cu activity did vary significantly with K2SO4 molarity, possibly due to a greater degree of adsorption of Cu onto inactive sites on the cell surfaces than for Zn and Pb. Linear regression analysis of bioluminescence on free ion activity revealed significant correlations for each metal above the toxicity threshold. In conclusion, lux-marked E. coli is suitable for investigating the toxicity of metal ions and complexes in non saline systems although cell surface adsorption effects could be important for some metals, e.g. Cu.

Modelling DOC export from watersheds in Scotland using neural networks

A wide variety of watershed-scale attributes can be used as predictors of the export of dissolved organic carbon (DOC) from a watershed. However, the complexity and number of relationships makes the development of generally applicable mechanistic models for prediction of DOC export based on measurement of factors difficult. Here we have applied neural network modelling methods to the prediction of stream flux and daily DOC export from several watersheds of varying size within the Dee valley, in north-east Scotland. A two-stage process was carried out in which first a model was developed which used a large number of variables thought to be relevant to DOC export, and then the possibility of using a restricted set of variables was investigated in order to reduce the amount of analysis required in order to produce accurate DOC export predictions. The results showed that it is possible to predict DOC export using input variables corresponding broadly to the factors responsible for soil formation, and that a single sample site may provide enough information to allow prediction for an entire watershed. However, in order to achieve a model with statistically significant results, it is necessary to use multiple sample sites per watershed, and to use measured rather than modelled flow values. Discussion is made of the effectiveness of the neural network method in developing models of DOC export, and of problems with the method (particularly in the inability to use NN models for process-based models).

A model for predicting chloride concentrations in river water in a relatively unpolluted catchment in north-east Scotland

The River Dee is an oligotrophic soft water system, in the NE of Scotland, with a catchment area of approximately 2100 km2. The river rises in the Cairngorm Mountains and enters the North Sea at Aberdeen, approximately 140 km from its source. Water chemical quality data was collected every 2 weeks over 12 months for 59 sites distributed throughout the catchment. River water chloride concentrations increased significantly from west to east. In depth investigation of the relationship with distance from the coast revealed the significant difference in spatial distribution of river water chloride concentrations between upland and lowland/agricultural areas, suggesting the possible importance of agricultural practices to streamwater chloride concentrations. Thirty of the sample sites are independent and have been used to develop a simple model for prediction of streamwater Cl- concentration throughout the catchment. The model has been validated using data from the remaining sub-catchments. The model shows that mean Cl- concentration may be reliably predicted from distance from the coast and the percentage of improved grassland and arable land cover in each sub-catchment (r2 = 0.98). It is postulated that the land use effects may be partly due to the evolved link between landuse and catchment altitude characteristics, rather than just the direct effect of applied potassium chloride fertiliser on agricultural land. It was noted that there was insufficient forestry within the River Dee Catchment to reliably include % forest cover in the model.

Heavy Metal Pollution in Some Soil and Water Resources of Bursa Province, Turkey

Abstract Bursa, the fourth most densely populated province in Turkey, is important to the national economy for agricultural and industrial production. During the past two decades, substantial migration into the region has increased drastically the risk of soil degradation. Urbanization and industrial development in the province have mainly occurred on soil types with land capability Class 1 and 2 and produce large amounts of nonbiodegradable urban and industrial waste, much of which is disposed of in the Nilufer River, the Ayvali Canal, and on agricultural land. Regulation of effluent quality disposed of to surface waters has been limited, so it was decided to conduct a preliminary survey of selected potentially toxic element (PTE) concentrations in agricultural soils and the PTEs in irrigation waters in the area to determine what potential pollution and health risk may exist. The pH and concentrations of calcium (Ca), magnesium (Mg), and heavy metals were determined in water samples from along the Nilufer River, above and below the industrialized area, and one of its tributaries, the Ayvali Canal. The results indicated considerable pollution from industry and city sewage in the surface waters, which are used directly by local farmers for irrigation of adjacent fields. Total heavy metal contents of the Fluvisols and Vertisols showed that these agricultural soils were polluted with iron (Fe), manganese (Mn), zinc (Zn), copper (Cu), cadmium (Cd), cobalt (Co), chromium (Cr), nickel (Ni), and lead (Pb). The DTPA‐extractable Cd, Cu, Fe, Mn, and Zn concentrations in irrigated Fluvisols and Vertisols indicated that the practice caused the accumulation of the Cd and Cu in the upper parts of the soil profiles. In the longer term, irrigation of the soils with the polluted waters may damage soil, crop, and human health.

Extent and causes of 3D spatial variations in potential N mineralization and the risk of ammonium and nitrate leaching from an N-impacted permanent grassland near York, UK

Changes in the dynamics of inorganic N species transformations with depth have been investigated for seven soil profiles from a nitrogen-impacted ancient grassland on a nature reserve outside York in the UK, using incubation experiments. In five of the profiles, both ammonification and nitrification are occurring below the rooting zone, probably partly in response to the low C:N ratio in the soils. This contributes to elevated nitrate concentrations found in an adjacent stream. Accumulation of ammonium during incubation in the sub-soils of these five profiles suggests a high probability of ammonium leaching down the profiles as ammonium inputs and outputs at a given depth approach equilibrium. This ammonium may also be nitrified at depth. However, in the two profiles with the most acidic surface horizons, net mineralization was negligible or negative; some initial ammonium-N and ammonium-N produced during incubation were nitrified, so the loss in ammonium-N was closely balanced by nitrate-N production.