Spatial distribution of heavy metal concentrations in urban, suburban and agricultural soils in a Mediterranean city of Algeria

As part of a larger program aiming at assessing transfer and effects of metals in food webs, this work studied the spatial distribution of Cd, Cr, Cu, Pb, and Zn in 101 sub-surface soils, systematically sampled (1 × 1 km regular grid) over a large area around Annaba, the fourth most-populated city of Algeria. Cd and Cr exhibited only one abnormally high value, with all other concentrations being close to pedogeological background. Some places in the centre of the city were polluted by Pb (up to 823 mg kg⁻¹), probably due to aerial deposition from gasoline exhausts. Zn never exceeded regulatory limits over the whole sampling area. Cu was the only element for which a spatial autocorrelation occurred. A spatial interpolation by cokriging allowed the identification of agricultural activities as the main Cu pollution source. Our approach revealed various anthropogenic pollution sources, more efficiently for large-scale patterns than for local abnormalities.     

大连周家沟黄土元素地球化学特征与环境

分析了辽南大连周家沟黄土剖面的常量元素、CaC03、pH值、有机质,并与相关反应的环境变化指标进行了对比.结果表明,周家沟黄土与黄土高原化学成分及含量相差不大,元素差异反映沉积期后气候环境因素不同;元素迁移和积聚在马兰黄土和离石黄土中表现不同,说明在中更新世晚期和晚更新世气候发生由温湿变为冷干的明显变化;氧化物比值综合参数表明,周家沟在晚更新世气候总的变暖趋势下经历了三次气候旋回波动.     

Zinc kinetics in the ant Myrmica rubra originating from a metal pollution gradient

Ants are efficient trace metal accumulators, but metal kinetics in ants has not been described. Workers of Myrmica rubra collected in seven meadows along a metal pollution gradient were exposed to dietary Zn (1000 mg kg⁻¹) for a 80 day uptake period followed by 30 days of clean food. Zn concentrations in the ants from all study sites were found to have been maintained on a stable level, indicating very efficient Zn regulation. No proof of adaptation in terms of enhanced elimination or restricted accumulation of Zn was found. Nevertheless, the results illustrate the general kinetics of Zn in M. rubra, irrespective of the differences between sites.     

Water Quality of Medium Size Watercourse Under Baseflow Conditions: The Case Study of River Sutla in Croatia

The study on medium size river Sutla in Croatia indicated considerable water contamination at specific sites during the baseflow period, probably associated to low flow-rate (0.73-68.8 m3 s(-1)), and consequently low dilution capacity of this river. Various aspects of contamination were observed: increased conductivity to 1,000 microS cm(-1), decreased dissolved oxygen level to 50%, 4-5 degrees C increased water temperature, increased concentrations of several dissolved trace elements (e.g., maximal values of Li: 45.4 microg l(-1); Rb: 10.4 microg l(-1); Mo: 20.1 microg l(-1); Cd: 0.31 microg l(-1); Sn: 30.2 microg l(-1); Sb: 11.8 microg l(-1); Pb: 1.18 microg l(-1); Ti: 1.03 microg l(-1); Mn: 261.1 microg l(-1); and Fe: 80.5 microg l(-1)) and macro elements (e.g., maximal values of Na: 107.5 mg l(-1); and K: 17.3 mg l(-1)), as well as moderate or even critical fecal (E. coli: 4,888 MPN/100 ml; total coliforms: 45,307 MPN/100 ml; enterococci: 1,303 MPN/100 ml) and organic pollution (heterotrophic bacteria: 94,000 cfu/ml). Although metal concentrations still have not exceeded the limits considered as hazardous for aquatic life or eventually for human health, the observed prominent increases of both metal concentrations and bacterial counts in the river water should be considered as a warning and incentive to protect the small and medium size rivers from the future deterioration, as recommended by EU Water Framework Directive.     

Pattern recognition and classification of sediments according to their metal content using chemometric tools. A case study: the estuary of Nerbioi-Ibaizabal River (Bilbao, Basque Country)

Chemometrics are increasingly used in environmental monitoring studies, but are still far from being accepted as routine tools by field specialists. The multivariate character of usually highly correlated environmental data recommends the use of advanced chemometrics as part of the analytical methodology in order to get information on the basic structure of data. In this work, we have applied a battery of non-supervised (Principal Component Analysis (PCA)) and supervised (k-Nearest Neighbour (k-NN), Soft Independent Modelling of Class Analogies (SIMCA), Linear Discriminant Analysis (LDA) and Artificial Neural Networks (ANNs)) multivariate techniques on a specific environmental dataset. The dataset consists on the concentration of 14 elements (Al, As, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Sn, V and Zn) in 95 sediments collected at eight different locations of the estuary of the Nerbioi-Ibaizabal River (Bilbao, Basque Country) during 12 sampling campaigns conducted every 3 months between 2005 and 2008. The study aims to present a simple methodology of general applicability which may result in a flexible and practical tool to assess chemical pollution in sediments of a given specific site.     

Trace metal uptake by tropical vegetables grown on soil amended with urban sewage sludge

Trace metal uptake was measured for tropical and temperate leafy vegetables grown on soil from an urban sewage disposal farm in the UK. Twenty-four leafy vegetables from East Africa and the UK were assessed and the five vegetable types that showed the greatest Cd concentrations were grown on eight soils differing in the severity of contamination, pH and other physico-chemical properties. The range of Cd concentrations in the edible shoots was greater for tropical vegetables than for temperate types. Metal uptake was modelled as a function of (i) total soil metal concentration, (ii) CaCl₂-soluble metal, (iii) soil solution concentration and (iv) the activity of metal ions in soil pore water. Tropical vegetables were not satisfactorily modelled as a single generic ‘green vegetable’, suggesting that more sophisticated approaches to risk assessment may be required to assess hazard from peri-urban agriculture in developing countries.     

Eighty-year sedimentary record of heavy metal inputs in the intertidal sediments from the Nanliu River estuary, Beibu Gulf of South China Sea

²¹⁰Pb analysis in the sediment core C11 was used to reconstruct the historical fluxes of Hg, Cu, Pb, Zn, Cd, Cr and As in the Nanliu River estuary during the last ∼81 year. The ²¹⁰Pb_xs-derived sedimentation rates, molar C/N ratios, enrichment factors and excess fluxes indicated that the natural inputs prevailed till the early 1990s. When the erosion related to land-use modifications enhanced, it promoted higher accumulation rates of the sedimentary material. In the recent sediments they were found a moderate enrichment of Cd and Hg (maximum 3.5- and 2.8-fold corresponding to the local background levels, respectively) and a slight enrichment of Cr, Zn, As and Pb (maximum 1.3-, 1.3-, 1.3- and 1.2-fold, respectively). The excess metal fluxes also showed a consistently increasing tread since the early 1990s, which could be associated with the intensive use of phosphate fertilizers and the combustion of fossil fuels derived from human activities.     

Impact of atmospheric deposition of anthropogenic and natural trace metals on Northwestern Mediterranean surface waters: a box model assessment

Under stratified oligotrophic conditions (May-November), the surface mixed layer of the Northwestern Mediterranean constitutes a homogeneous water volume of 10-30 m depth. In other respects, the mean residence time of Ligurian surface waters (0-200 m) is 102 days. It is therefore possible to quantify the extent to which atmospheric deposition of trace metals affects surface waters. On the basis of literature data on anthropogenic and natural trace metals, we demonstrate that the ratios between total seawater labile atmospheric deposition during 102 days (Δc) and dissolved TM concentrations in Ligurian surface waters (c) illustrate the impact of atmospheric deposition on surface seawater (Δc/c). High ratios indicate surface TM enrichments, while low ratios indicate surface TM depletion, due to the quasi-complete sorption and removal of TMs by plankton during spring bloom. The simple box model proposed here may be used for other marine regions where hydrodynamical and physico-chemical constraints are well defined.     

Linking chemical elements in forest floor humus (Oh-horizon) in the Czech Republic to contamination sources

While terrestrial moss and other plants are frequently used for environmental mapping and monitoring projects, data on the regional geochemistry of humus are scarce. Humus, however, has a much larger life span than any plant material. It can be seen as the “environmental memory” of an area for at least the last 60-100 years. Here concentrations of 39 elements determined by ICP-MS and ICP AES, pH and ash content are presented for 259 samples of forest floor humus collected at an average sample density of 1 site/300 km² in the Czech Republic. The scale of anomalies linked to known contamination sources (e.g., lignite mining and burning, metallurgical industry, coal fired power plants, metal smelters) is documented and discussed versus natural processes influencing humus quality. Most maps indicate a local impact from individual contamination sources: often more detailed sampling than used here would be needed to differentiate between likely sources.     

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.