Fukushima fallout in Northwest German environmental media

Traces of short- and long-lived fallout isotopes (¹³¹I, ¹³⁴Cs and ¹³⁷Cs) were found in environmental samples collected in Northwest Germany (rain water, river sediment, soil, grass and cow milk) from March to May 2011, following the radioactivity releases after the nuclear accident in Fukushima, Japan. The measured concentrations are consistent with reported concentrations in air, amount of rainfall and expected values applying simple radioecological models. The [¹³⁴Cs]/[¹³⁷Cs] ratio reported for air (about 1) allows for discrimination between “recent” and “old” ¹³⁷Cs. Expected ¹³⁶Cs values fell below the detection limits of the instrumentation, despite large sample masses and long counting times.     

Trace metals in soil and leaves of Jacaranda mimosifolia in Tshwane area,South Africa

Plant and soil have been identified as major sink of pollutants in the environment. We evaluated the reliability of biomonitoring of heavy metals in Tshwane area with the use of leaves of Jacaranda mimosifolia. The concentrations of heavy metals such as Ca, Mg, Fe, Pb, Zn, Cu, Sb were measured in leaves of J. mimosifolia and soils collected from 10 sites in the city of Tshwane during two sampling periods. The metals were analyzed with the use of ICP-MS. The result shows significant differences in the concentration of trace metals in all the sites (p < 0.01). The differences between the two sampling periods were statistically significant (p < 0.01). Concentration of metals from high traffic and industrial sites were significantly higher than in the residential areas (p < 0.01). Concentration factor suggests that translocation of metals from roots to leaves could be relevant only for some metals such as Ca, Mg and Sb. The study reveals an anthropogenic source for the trace metals. Leaves of J. mimosifolia were found to be a useful biomonitor of the determined trace metals.     

Use of cholinesterase activity in monitoring chlorpyrifos exposure of steer cattle after topical administration

The aim of this work was to study the pharmacokinetic behavior and the inhibitory effect of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) activities of chlorpyrifos (CPF) in steer cattle after pour-on administration. Determination of cholinesterase activity in plasma and erythrocyte was carried out according to Ellman kinetic method. CPF was analyzed by gas chromatography. AChE was the predominant form of cholinesterase analyzed, with low levels of BChE in plasma. Following the treatment with CPF, the maximum inhibitory effect on AChE or BChE were 50.88 ± 11.57 and 42.66 ± 12.01%, respectively. The chlorpyrifos plasma concentrations observed were low and they presented a high variability. Chlorpyrifos peak plasma concentration (10.42 ± 4.76 μ g/L) was reached at 8.42 ± 13.97 h. The pesticide was not detected in plasma after 48 h post treatment. The values of area under the curve (AUC) were 118.48 ± 87.46 μ g· h/L and mean resistance time (MRT) were 13.38 ± 10.41 h. The pour-on exposure to the organophosphate chlorpyrifos significantly reduced AChE and BChE activity in steer cattle and the recovery was not reached on 50 days post-treatment.     

Using penalty functions to evaluate aggregation models for environmental indices

The purpose of indices is to summarize a large volume of information into a single number that is easy to understand and interpret. Environmental indices provide a composite picture of an environmental condition derived from a series of observed measurements and parameters. They are used as communication tools by regulatory agencies to characterize the state of a specific environmental system (air, water, and sediments) and to study the impact of regulatory policies on various environmental management practices. In the development of environmental indices, a few issues and problems have been encountered arising as a result of the abstraction of information and data. These problems are referred to as characteristic properties that include ambiguity, eclipsing, compensation and rigidity. These characteristic properties have long been identified and interpreted in Boolean (e.g., Yes/No) or qualitative (e.g., low, medium, high) terms. In this paper, we propose a new approach to describe the above stated characteristic properties on a continuous scale to evaluate and compare the behavior of various aggregation models. Our approach is based on developing penalty functions for each characteristic property. A water quality index example by Swamee and Tyagi (2000) is used to explain our approach. A detailed case study for a developing microbial risk index is also provided to show how the proposed approach can be extended to complex hierarchical systems. Results show that it is possible to improve aggregation models for index development. Future research directions to improve index development are also discussed.     

How Should Support for Climate-Friendly Technologies Be Designed?

Stabilizing global greenhouse gas concentrations at levels to avoid significant climate risks will require massive “decarbonization” of all the major economies over the next few decades, in addition to the reduced emissions from other GHGs and carbon sequestration. Achieving the necessary scale of emissions reductions will require a multifaceted policy effort to support a broad array of technological and behavioral changes. Change on this scale will require sound, well-thought-out strategies. In this article, we outline some core principles, drawn from recent social science research, for guiding the design of clean technology policies, with a focus on energy. The market should be encouraged to make good choices: pricing carbon emissions and other environmental damage, removing distorting subsidies and barriers to competition, and supporting RD&D broadly. More specific policies are required to address particular market failures and barriers. For those technologies identified as being particularly desirable, some narrower RD&D policies are available.     

Comparison of land-use regression models between Great Britain and the Netherlands

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO₂ and PM_10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL).Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country.A common model for GB and NL explained NO₂ concentrations well (adjusted R² 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction.The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models.     

Evaluating Environmental Parameters for Minimum Ammonium Losses during Composting of Trimming Residues

Abstract

A neural fuzzy system was used to investigate the influence of environmental variables (time, aeration, moisture, and particle size) on composting parameters (pH, organic matter [OM], nitrogen [N], ammonium nitrogen [NH₄ ⁺-N] and nitrate nitrogen [NO₃ ^--N]). This was to determine the best composting conditions to ensure the maximum quality on the composts obtained with the minimum ammonium losses. A central composite experimental design was used to obtain the neural fuzzy model for each dependent variable. These models, consisting of the four independent process variables, were found to accurately describe the composting process (the differences between the experimental values and those estimated by using the equations never exceeded 5–10% of the former). Results of the modeling showed that creating a product with acceptable chemical properties (pH, NH₄ ⁺-N and NO₃ ^--N) entails operating at medium moisture content (55%) and medium to high particle size (3–5 cm). Moderate to low aeration (0.2 L air/min · kg) would be the best compromise to compost this residue because of the scant statistical influence of this independent variable.     

Short-run allocation of emissions allowances and long-term goals for climate policy

We use economic analysis to evaluate grandfathering, auctioning, and benchmarking approaches for allocation of emissions allowances and then discuss practical experience from European and American schemes. In principle, auctions are superior from the viewpoints of efficiency, fairness, transparency, and simplicity. In practice, auctions have been opposed by important sectors of industry, which argue that carbon pricing without compensation would harm international competitiveness. In the European Union's Emissions Trading System, this concern led to grandfathering that is updated at various intervals. Unfortunately, updating gives industry an incentive to change behavior to influence future allocation. Furthermore, the wealth transferred to incumbent firms can be significantly larger than the extra costs incurred, leading to windfall profits. Meanwhile, potential auction revenues are not available to reduce other taxes. By circumscribing free allocation, benchmarking can target competitiveness concerns, incur less wealth transfer, and provide a strategy consistent with transitioning to auctions in the long run.     

Levels of organochlorine pesticides and polychlorinated biphenyls in the critically endangered Iberian lynx and other sympatric carnivores in Spain

Accumulation of organochlorine compounds is well studied in aquatic food chains whereas little information is available from terrestrial food chains. This study presents data of organochlorine levels in tissue and plasma samples of 15 critically endangered Iberian lynx (Lynx pardinus) and other 55 wild carnivores belonging to five species from three natural areas of Spain (Doñana National Park, Sierra Morena and Lozoya River) and explores their relationship with species diet. The Iberian lynx, with a diet based on the consumption of rabbit, had lower PCB levels (geometric means, plasma: <0.01 ng mL⁻¹, liver: 0.4 ng g⁻¹ wet weight, fat: 87 ng g⁻¹ lipid weight) than other carnivores with more anthropic and opportunistic foraging behavior, such as the red fox (Vulpes vulpes; plasma: 1.11 ng mL⁻¹, liver: 459 ng g⁻¹, fat: 1984 ng g⁻¹), or with diets including reptiles at higher proportion, such as the Egyptian mongoose (Herpestes ichneumon; plasma: 7.15 ng mL⁻¹, liver: 216 ng g⁻¹, fat: 540 ng g⁻¹), or the common genet (Genetta genetta; liver: 466 ng g⁻¹, fat: 3854 ng g⁻¹). Chlorinated pesticides showed interspecific variations similar to PCBs. Organochlorine levels have declined since the 80s in carnivores from Doñana National Park, but PCB levels are still of concern in Eurasian otters (Lutra lutra; liver: 3873-5426 ng g⁻¹) from the industrialized region of Madrid.