A study on toxic and essential elements in rice from the Republic of Kazakhstan: comparing the level of contamination in rice from the European Community

Selected toxic elements (total As, Cd, Cr, Hg, Pb, Sr, U and V) and essential elements (Co, Cu, Fe, Mn and Zn) were analyzed using an inductively coupled plasma mass spectrometry (ICP-MS) in unpolished and milled rice collected from Kazakhstan and milled rice from Spain and Portugal to evaluate the potential health risk to the population. Arsenic species (arsenite, arsenate, arsenobetaine, dimethylarsinate and monomethilarsonate) were analyzed using HPLC-IC-MS. From 146 samples analyzed, none of them exceeded the maximum limit set by the European Legislation for Cd or Pb or values recommended by the Codex Alimentarius. Concentrations of Sr, U and V were below LOD and those of Hg, Pb, Co and Cr between <LOD and 0.54 mg/kg (highest concentration of Cr) in milled rice. Portuguese rice samples contained the highest mean concentration of As, Hg, Pb, Co, Cr, Cu, Mn and Zn. The highest mean of arsenobetaine (0.001 mg/kg), dimethylarsinate (0.27 mg/kg) and monomethilarsonate (0.02 mg/kg) was found in Spanish rice and that of arsenite (0.30 mg/kg) in Kazakh rice. Inorganic As in samples from Kazakhstan was above the ML (0.2 mg/kg) proposed by FAO/WHO, but in seven samples from Spain and in four from Portugal were above the limit. The estimated weekly intake of total or inorganic As(III, V), Cd, Hg and Pb for rice consumption by Kazakh, Spanish and Portuguese adults and children was lower than the provisional tolerable weekly intake established by Joint FAO/WHO Expert Committee on Food Additives and the European Food Safety Authority.

     

Circuit-theory applications to connectivity science and conservation

Conservation practitioners have long recognized ecological connectivity as a global priority for preserving biodiversity and ecosystem function. In the early years of conservation science, ecologists extended principles of island biogeography to assess connectivity based on source patch proximity and other metrics derived from binary maps of habitat. From 2006 to 2008, the late Brad McRae introduced circuit theory as an alternative approach to model gene flow and the dispersal or movement routes of organisms. He posited concepts and metrics from electrical circuit theory as a robust way to quantify movement across multiple possible paths in a landscape, not just a single least-cost path or corridor. Circuit theory offers many theoretical, conceptual, and practical linkages to conservation science. We reviewed 459 recent studies citing circuit theory or the open-source software Circuitscape. We focused on applications of circuit theory to the science and practice of connectivity conservation, including topics in landscape and population genetics, movement and dispersal paths of organisms, anthropogenic barriers to connectivity, fire behavior, water flow, and ecosystem services. Circuit theory is likely to have an effect on conservation science and practitioners through improved insights into landscape dynamics, animal movement, and habitat-use studies and through the development of new software tools for data analysis and visualization. The influence of circuit theory on conservation comes from the theoretical basis and elegance of the approach and the powerful collaborations and active user community that have emerged. Circuit theory provides a springboard for ecological understanding and will remain an important conservation tool for researchers and practitioners around the globe.     

Ozonisation coupled with biological degradation for treatment of phenolic pollutants: a mechanistically based study

Phenolic acids constitute an important group of pollutants which are reluctant to biological treatment. Solutions containing a mixture of cinnamic acid, p-coumaric acid, caffeic acid and ferulic acid were submitted to ozonisation. Then, the changes in biodegradability along the process were studied by means of respirometry. There is an optimum ozone dosage in the interval 3-5 min of treatment which allows to achieve the maximum increase in biodegradability (more than 10 times) and a high efficiency of the ozonisation process (COD decreases to a half of its initial value). Further ozonisation does not help to increase biodegradability and is clearly disadvantageous. Similar results are obtained with actual samples of olive oil wastewaters. This behaviour is explained based on the formation of highly biodegradable benzaldehydes as key ozonisation intermediates, in the early reaction stages.     

An Aegean island earthquake protection strategy: an integrated analysis and policy methodology

Viewing an insular setting as a distinct risk environment, an effort is made here to develop a methodology for identifying core issues related to earthquake risk and disaster protection policy, adjusted to the 'specificities' of such a context. The methodology's point of departure is the inherent condition of the 'island operating as a closed system', requiring an attempt to assess and optimise local capacity (social, political, economic, institutional and technical) to deal with an earthquake emergency. The island is then treated as an 'open system', implying that in the event of a disaster, it should be able to maximise its ability to receive and distribute external aid and to manage effectively population evacuation and inflows/outflows of aid resources. Hence, an appropriate strategic policy approach could be developed by integrating the 'open' and 'closed' system components of an island setting. Three islands from the Aegean Archipelagos in Greece--Chios, Kos and Nissyros--serve as case study areas.     

Tree growth inference and prediction from diameter censuses and ring widths.

Estimation of tree growth is based on sparse observations of tree diameter, ring widths, or increments read from a dendrometer. From annual measurements on a few trees (e.g., increment cores) or sporadic measurements from many trees (e.g., diameter censuses on mapped plots), relationships with resources, tree size, and climate are extrapolated to whole stands. There has been no way to formally integrate different types of data and problems of estimation that result from (1) multiple sources of observation error, which frequently result in impossible estimates of negative growth, (2) the fact that data are typically sparse (a few trees or a few years), whereas inference is needed broadly (many trees over many years), (3) the fact that some unknown fraction of the variance is shared across the population, and (4) the fact that growth rates of trees within competing stands are not independent. We develop a hierarchical Bayes state space model for tree growth that addresses all of these challenges, allowing for formal inference that is consistent with the available data and the assumption that growth is nonnegative. Prediction follows directly, incorporating the full uncertainty from inference with scenarios for "filling the gaps" for past growth rates and for future conditions affecting growth. An example involving multiple species and multiple stands with tree-ring data and up to 14 years of tree census data illustrates how different levels of information at the tree and stand level contribute to inference and prediction.     

Assessment of the Viability of NIH3T3 Fibroblast Cells Cultured in Polymer Matrices with rhGH

Developing a biomaterial that functions as a scaffold (osteoconductor), combined with a growth factor (osteoinductor), is of great interest for clinical application in oral and maxillofacial surgery. Growth hormone (GH) is a good candidate, as it is a major regulator of postnatal bone growth and remodeling. Pure PLGA and 70/30 PLGA/PCL matrices were prepared by the solvent evaporation method, combined or not with GH, and tested for toxicity and cell viability using an MTT assay with NIH3T3 mouse cells (ATCC). Cell toxicity was assessed at 24, 48, 72 h, and 7 days of biomaterial exposure to culture medium. All polymers had high cell viability rates. However, from 48 h onwards, the groups with GH-polymer combinations had better results than the polymer groups without association with GH when compared to the control group. At 7 days of culture, only the pure PLGA matrix showed a significant difference from the control group. These results may suggest a preference of cells for the presence of GH in the biomaterial in culture medium, especially in the PLGA matrix. GH appeared to contribute to the increase in cell viability observed at some assessment time points, especially when combined with PLGA as compared to pure PLGA.     

The European Union and the Paris Climate Agreement: moving forward without the United States

<正>"Make our Planet Great Again!"These are the final words of the three-minute speech delivered in English by newly elected French President Emmanuel Macron(https://www.makeourplanetgreatagain.fr/home).The speech was made in response to US President Donald Trump's decision to take the United States out of the Paris Climate Agreement and to cut funding intended to support developing countries in adapting to climate     

Vehicular particulate matter emissions in road tunnels in Sao Paulo, Brazil

In the metropolitan area of S?o Paulo, Brazil, ozone and particulate matter (PM) are the air pollutants that pose the greatest threat to air quality, since the PM and the ozone precursors (nitrogen oxides and volatile organic compounds) are the main source of air pollution from vehicular emissions. Vehicular emissions can be measured inside road tunnels, and those measurements can provide information about emission factors of in-use vehicles. Emission factors are used to estimate vehicular emissions and are described as the amount of species emitted per vehicle distance driven or per volume of fuel consumed. This study presents emission factor data for fine particles, coarse particles, inhalable particulate matter and black carbon, as well as size distribution data for inhalable particulate matter, as measured in March and May of 2004, respectively, in the Janio Quadros and Maria Maluf road tunnels, both located in S?o Paulo. The Janio Quadros tunnel carries mainly light-duty vehicles, whereas the Maria Maluf tunnel carries light-duty and heavy-duty vehicles. In the Janio Quadros tunnel, the estimated light-duty vehicle emission factors for the trace elements copper and bromine were 261 and 220 microg km(-1), respectively, and 16, 197, 127 and 92 mg km(-1), respectively, for black carbon, inhalable particulate matter, coarse particles and fine particles. The mean contribution of heavy-duty vehicles to the emissions of black carbon, inhalable particulate matter, coarse particles and fine particles was, respectively 29, 4, 6 and 6 times higher than that of light-duty vehicles. The inhalable particulate matter emission factor for heavy-duty vehicles was 1.2 times higher than that found during dynamometer testing. In general, the particle emissions in S?o Paulo tunnels are higher than those found in other cities of the world.     

Ensemble Techniques to Improve Air Quality Assessment: Focus on O3 and PM

Five air quality models were applied over Portugal for July 2006 with an ensemble purpose. These models were used, with their own meteorology, parameterizations, boundary conditions and chemical mechanisms, but with the same emission data. The validation of the individual models and its ensemble for ozone (O₃) and particulate matter was performed using monitoring data from 22 background stations over Portugal. After removing the bias from each model, different ensemble techniques were applied and compared. Besides the median, several weighted ensemble approaches were tested and intercompared: static (SLR) and dynamic (DLR) multiple linear regressions (using less-square optimization method) and the Bayesian Model Averaging (BMA) methodology. The goal of the comparison is to estimate to what extent the ensemble analysis is an improvement with respect to the single model results. The obtained results revealed that no one of the 4 tested ensembles clearly outperforms the others on the basis of statistical parameters and probabilistic analysis (reliability and resolution properties). Nevertheless, statistical results have shown that the application of the weights slightly improves ensemble performance when compared to those obtained from the median ensemble. The same statistical analysis together with the probabilistic measures demonstrates that the SLR and BMA methods are the best performers amongst the assessed methodologies.     

Evaluation of the European population intake fractions for European and Finnish anthropogenic primary fine particulate matter emissions

The intake fraction (iF) has been defined as the integrated incremental intake of a pollutant released from a source category or region summed over all exposed individuals. In this study we evaluated the iFs in the population of Europe for emissions of anthropogenic primary fine particulate matter (PM_2.5) from sources in Europe, with a more detailed analysis of the iF from Finnish sources. Parameters for calculating the iFs include the emission strengths, the predicted atmospheric concentrations, European population data, and the average breathing rate per person. Emissions for the whole of Europe and Finland were based on the inventories of the European Monitoring and Evaluation Programme (EMEP) and the Finnish Regional Emission Scenario (FRES) model, respectively. The atmospheric dispersion of primary PM_2.5 was computed using the regional-scale dispersion model SILAM. The iFs from Finnish sources were also computed separately for six emission source categories. The iFs corresponding to the primary PM_2.5 emissions from the European countries for the whole population of Europe were generally highest for the densely populated Western European countries, second highest for the Eastern and Southern European countries, and lowest for the Northern European and Baltic countries. For the entire European population, the iF values varied from the lowest value of 0.31 per million for emissions from Cyprus, to the highest value of 4.42 per million for emissions from Belgium. These results depend on the regional distribution of the population and the prevailing long-term meteorological conditions. Regarding Finnish primary PM_2.5 emissions, the iF was highest for traffic emissions (0.68 per million) and lowest for major power plant emissions (0.50 per million). The results provide new information that can be used to find the most cost-efficient emission abatement strategies and policies.