Biodegradable chelate enhances the phytoextraction of copper by Oenothera picensis grown in copper-contaminated acid soils

Oenothera picensis plants (Fragrant Evening Primrose) grow in the acid soils contaminated by copper smelting in the coastal region of central Chile. We evaluated the effects of the biodegradable chelate MGDA (methylglycinediacetic acid) on copper extraction by O. picensis and on leaching of copper through the soil profile, using an ex situ experiment with soil columns of varying heights. MGDA was applied in four rates: 0 (control), 2, 6 and 10 mmol plant⁻¹. MGDA application significantly increased biomass production and foliar concentration, permitting an effective increase in copper extraction, from 0.09 mg plant⁻¹ in the control, to 1.3 mg plant⁻¹ in the 6 and 10 mmol plant⁻¹ treatments. With 10 mmol plant⁻¹ rate of MGDA, the copper concentration in the leachate from the 30 cm columns was 20 times higher than in the control. For the 60 cm columns, copper concentration was 2 times higher than the control. It can be concluded that at increased soil depths, copper leaching would be minimal and that MGDA applications at the studied rates would not pose a high risk for leaching into groundwater. It can thus be stated that applications of MGDA are an effective and environmentally safe way to improve copper extraction by O. picensis in these soils.     

Arsenic distribution in soils and plants of an arsenic impacted former mining area

A mining area affected by the abandoned exploitation of an arsenical tungsten deposit was studied in order to assess its arsenic pollution level and the feasibility of native plants for being used in phytoremediation approaches. Soil and plant samples were collected at different distances from the polluting sources and analysed for their As content and distribution. Critical soil total concentrations of As were found, with values in the range 70-5330 mg kg⁻¹ in the uppermost layer. The plant community develops As tolerance by exclusion strategies. Of the plant species growing in the most polluted site, the shrubs Salix atrocinerea Brot. and Genista scorpius (L.) DC. exhibit the lowest bioaccumulation factor (BF) values for their aerial parts, suggesting their suitability to be used with revegetation purposes. The species Scirpus holoschoenus L. highlights for its important potential to stabilise As at root level, accumulating As contents up to 3164 mg kg⁻¹.     

Spectral estimation of global levels of atmospheric pollutants

Underlying levels of atmospheric pollutants, assumed to be governed by smoothing mechanisms due to atmospheric dispersion, can be estimated from global emissions source databases on greenhouse gases and ozone-depleting compounds. However, spatial data may be contaminated with noise or even missing or zero-valued at many locations. Therefore, a problem that arises is how to extract the underlying smooth levels. This paper sets out a structural spatial model that assumes data evolve across a global grid constrained by second-order smoothing restrictions. The frequency-domain approach is particularly suitable for global datasets, reduces the computational burden associated with two-dimensional models and avoids cumbersome zero-inflated skewed distributions. Confidence intervals of the underlying levels are also obtained. An application to the estimation of global levels of atmospheric pollutants from anthropogenic emissions illustrates the technique which may also be useful in the analysis of other environmental datasets of similar characteristics.     

Substituting missing data in compositional analysis

Multivariate analysis of environmental data sets requires the absence of missing values or their substitution by small values. However, if the data is transformed logarithmically prior to the analysis, this solution cannot be applied because the logarithm of a small value might become an outlier. Several methods for substituting the missing values can be found in the literature although none of them guarantees that no distortion of the structure of the data set is produced. We propose a method for the assessment of these distortions which can be used for deciding whether to retain or not the samples or variables containing missing values and for the investigation of the performance of different substitution techniques. The method analyzes the structure of the distances among samples using Mantel tests. We present an application of the method to PCDD/F data measured in samples of terrestrial moss as part of a biomonitoring study.     

Antiradical activity of natural honeys and antifungal effect against Penicillium genera

The purpose of the study was to examine the antiradical activity of 11 natural honeys and to evaluate the antifungal properties of honey. Honey samples (10) were collected from different locations of Slovak Republic. Honeys were native to different plant species of Robinia pseudoacaccia, Brassica napus subs. napus, Castanea sativa Mill. Thymus serpyllum vulgaris and the other samples had multifloral origin. The low antiradical activitity in honey samples was determined. The best results were found in thyme honey from Rhodos (11.84 %) and Castanea honey from Nitra (10.61 %). The lowest antiradical activity was found in Acacia honey and determined to be 7.62 %. Statistically significant differences (P< 0.001) were found among thyme/Rhodos and Castanea/Nitra. The antifungal activities of honey samples were tested by 10 %, 25 % and 50 % (by mass per volume) concentration against fungi Penicillium crustosum, P. expansum, P. griseofulvum, P. raistrickii and P. verrucosum and by the agar well diffusion method. The solutions containing 10 % (by mass per volume) of honey did not have any effect on the growth of fungi. The strongest antifungal effect was shown by 50 % honey concentration against P. raistrickii.     

Photophysical and photochemical properties of the pharmaceutical compound salbutamol in aqueous solutions

Salbutamol is a potent β₂-adrenergic receptor agonist widely used in the treatment of bronchial asthma and chronic obstructive pulmonary disease. An increasing number of studies have detected salbutamol in natural water systems worldwide. Studies have shown that sunlight degrades salbutamol resulting in the formation of products; some showing higher toxicity to bacteria Vibrio fischeri than the parent compound. In this contribution, steady-state absorption and emission techniques, high-performance liquid chromatography, and transient absorption spectroscopy are used to investigate the photochemistry of salbutamol in aqueous buffer solutions at controlled pH values. Ground- and excited-state calculations that include solvent effects are performed to guide the interpretation of the experimental results. Salbutamol is sensitive to UVB light absorption in the pH range from 3 to 12, forming products that absorb light at longer wavelengths than the parent compound. Quantum yields of degradation reveal that the deprotonated species is 10-fold more photo-active than the protonated species. In line with this result, the fluorescence quantum yield of the protonated species is more than an order of magnitude higher than that of the deprotonated species. Transient absorption spectroscopy shows that population of the triplet state occurs with a rate constant of 7.1 × 10⁸ s⁻¹ in the protonated species, while a rate constant of 1.7 × 10¹⁰ s⁻¹ is measured for the deprotonated species. While degradation of the deprotonated species is not affected by the presence of molecular oxygen, a twofold increase in the photodegradation yield of the protonated species in air-saturated conditions is observed.     

Remediation of metal-contaminated soils with the addition of materials--part I: characterization and viability studies for the selection of non-hazardous waste materials and silicates

Contamination episodes in soils require interventions to attenuate their impact. These actions are often based on the addition of materials to increase contaminant retention in the soil and to dilute the contaminant concentration. Here, non-hazardous wastes (such as sugar foam, fly ash and a material produced by the zeolitization of fly ash) and silicates (including bentonites) were tested and fully characterized in the laboratory to select suitable materials for remediating metal-contaminated soils. Data from X-ray fluorescence (XRF), N₂ adsorption/desorption isotherms, X-ray diffraction (XRD) and scanning electron microscopy/energy-dispersive X-ray spectroscopy (SEM-EDX) analyses revealed the chemical composition, specific surface area and the phases appearing in the materials. A pH titration test allowed the calculation of their acid neutralization capacity (ANC). The metal sorption and desorption capacities of the waste materials and silicates were also estimated. Sugar foam, fly ash and the zeolitic material were the best candidate materials. Sugar foam was selected because of its high ANC (17 000 meq kg⁻¹), and the others were selected because of their larger distribution coefficients and lower sorption reversibilities than those predicted in the contaminated soils.     

Looking beyond the average agricultural impacts in defining adaptation needs in Europe

The effects of climate change on agriculture are often characterised by changes in the average productivity of crops; however, these indicators provide limited information regarding the risks associated with fluctuations in productivity resulting from future changes in climate variability that may also affect agriculture. In this context, this study evaluates the combined effects of the risks associated with anomalies reflected by changes in the mean crop yield and the variability of productivity in European agro-climatic regions under future climate change scenarios. The objective of this study is to evaluate adaptation needs and to identify regional effects that should be addressed with greater urgency in the light of the risks and opportunities that are identified. The results show differential effects on regional agriculture and highlight the importance of considering both regional average impacts and the variability in crop productivity in setting priorities for the adaptation and maintenance of rural incomes and agricultural insurance programmes.     

Integrated hydrologic–economic decision support system for groundwater use confronting climate change uncertainties in the Tunuyán River basin,Argentina

This study presents an integrated hydrologic–economic model as decision support system for groundwater use and incorporates uncertainties of climate change. The model was developed with the Vensim software (Ventana Systems) for system dynamic simulations. The software permitted the integration of economic variables along with hydrologic variables, in a unified format with the aim of evaluating the economic impacts of climate change on arid environments. To test the model, we applied it in one of the upper Tunuyán River sub-basin, located in the Mendoza Province (Argentina), where irrigation comes from groundwater. The model defines the best mix of crops and the total land use required to maximize the total river sub-basin monetary income, considering as a limit the amount of water that does not exceed the natural annual aquifer recharge. To estimate the impacts of climatic changes, four scenarios were compared: the business as usual (with the number of existing wells) in a dry year with a temperature increase of 4 °C; the business as usual in a wet year with an increase in temperature of 1.1 °C; an efficient use of wells in a dry year and a temperature increase of 4 °C and an efficient use of wells in a wet year with a temperature increase of 1.1 °C. Outputs calculated by the model were: land use per crop, total sub-basin net benefit, total sub-basin water extraction, water extraction limit depending on river discharge and total number of wells required to irrigate the entire area. Preliminary results showed that the number of existing wells exceeded the optimized number of wells required to sustainably irrigate the entire river sub-basin. Results indicated that in an average river discharge year, if wells were efficiently used, further rural development would be possible, until the limit of 350 million m³ of water extraction per year was reached (650 million m³ for a wet year and 180 million m³ for a dry year). The unified format and the low cost of the software license make the model a useful tool for Water Resources Management Institutions, particularly in developing countries.     

Potential impacts of climate change on agricultural land use suitability of the Hungarian counties

Central and Eastern European countries are a hotspot area when analyzing the impacts of climate change on agricultural and environmental sectors. This paper conducts a socio-economic evaluation of climate risks on crop production in Hungary, using panel data models. The region has a special location in the Carpathian basin, where the spatial distribution of precipitation varies highly from humid conditions in the western part to semiarid conditions in eastern Hungary. Under current conditions, crop systems are mainly rainfed, and water licences are massively underexploited. However, water stress projected by climate change scenarios could completely change this situation. In the near future (2021–2050), most of the crops examined could have better climatic conditions, while at the end of the century (2071–2100), lower yields are expected. Adaptation strategies must be based on an integrated evaluation which links economic and climatic aspects, and since the results show important differences in the case of individual systems, it is clear that the response has to be crop and region specific.