Energy Security: A Robust Optimization Approach to Design a Robust European Energy Supply via TIAM-WORLD

Energy supply routes to a given region are subject to random events, resulting in partial or total closure of a route (corridor). For instance, a pipeline may be subject to technical problems that reduce its capacity. Or, oil supply by tanker may be reduced for political reasons or because of equipment mishaps at the point of origin or again, by a conscious decision by the supplier in order to obtain economic benefits. The purpose of this article is to formulate a simplified version of the above issue that mainly addresses long-term uncertainties. The formulation is done via a version of the TIAM-WORLD Integrated Model, modified to implement the approach of robust optimization. In our case, the approach can be interpreted as a revival of chance-constrained programming under the name of distributionally robust, or ambiguous, chance-constrained programming. We apply the approach to improve the security of supply to the European Energy system. The resulting formulation provides several interesting features regarding the security of EU energy supply and has also the advantage to be numerically tractable.     

Monitoring water quality in reservoirs for human supply through multi-biomarker evaluation in tropical fish

Paraíba do Sul River is located at a very densely inhabited region of Brazil crossing the three most industrialized states of the country (S?o Paulo, Minas Gerais and Rio de Janeiro states). As a result, industrial and farming residues as well as urban sewage are frequently disposed without appropriate treatment. The current study aimed at investigating the water quality in three reservoirs along the Paraíba do Sul River (Ilha dos Pombos, Santa Cecília and Santa Branca), through physiological, morphological, biochemical, and genetic biomarkers. The bioindicator chosen was the catfish Pimelodus maculatus, sampled during the dry (June 2008) and rainy (February 2009) seasons. Also, some water physicochemical parameters were analyzed from the sampling sites, but displayed no alterations according to the Brazilian Agency for Water Quality Legislation. Branchial carbonic anhydrase activity was inhibited in the dry season, while renal carbonic anhydrase activity was inhibited in the rainy season in the Santa Branca reservoir, indicating disturbance of osmoregulatory and acid-base regulation processes. Histopathological alterations were observed in the gills (neoplasic and tissue hyperplasia processes) and liver (necrosis), indicating serious damage to the functional integrity of these organs. A high incidence of melanomacrophage centers was observed in the liver, suggesting an intense immune response in all reservoirs. Acetylcholinesterase and catalase activity showed also differences corroborating some morphological results. Likewise, the induction of the micronucleus and DNA damage indicate genotoxicity, but mainly in the Santa Branca reservoir. Thus, the health status of P. maculatus warrants caution in the use of the water from the 3 reservoirs for direct human consumption, particularly after the accidental spill of endosulfan in November 2008, three months before the rainy season sampling.     

Workplace aerosol mass concentration measurement using optical particle counters

Direct-reading aerosol measurement usually uses the optical properties of airborne particles to detect and measure particle concentration. In the case of occupational hygiene, mass concentration measurement is often required. Two aerosol monitoring methods are based on the principle of light scattering: optical particle counting (OPC) and photometry. The former analyses the light scattered by a single particle, the latter by a cloud of particles. Both methods need calibration to transform the quantity of scattered light detected into particle concentration. Photometers are simpler to use and can be directly calibrated to measure mass concentration. However, their response varies not only with aerosol concentration but also with particle size distribution, which frequently contributes to biased measurement. Optical particle counters directly measure the particle number concentration and particle size that allows assessment of the particle mass provided the particles are spherical and of known density. An integrating algorithm is used to calculate the mass concentration of any conventional health-related aerosol fraction. The concentrations calculated thus have been compared with simultaneous measurements by conventional gravimetric sampling to check the possibility of field OPC calibration with real workplace aerosols with a view to further monitoring particle mass concentration. Aerosol concentrations were measured in the food industry using the OPC GRIMM? 1.108 and the CIP 10-Inhalable and CIP 10-Respirable (ARELCO?) aerosol samplers while meat sausages were being brushed and coated with calcium carbonate. Previously, the original OPC inlet had been adapted to sample inhalable aerosol. A mixed aerosol of calcium carbonate and fungi spores was present in the workplace. The OPC particle-size distribution and an estimated average particle density of both aerosol components were used to calculate the mass concentration. The inhalable and respirable aerosol fractions calculated from the OPC data are closely correlated with the results of the particle size-selective sampling using the CIP 10. Furthermore, the OPC data allow calculation of the thoracic fraction of workplace aerosol (not measured by sampling), which is interesting in the presence of allergenic particles like fungi spores. The results also show that the modified COP inlet adequately samples inhalable aerosol in the range of workplace particle-size distribution.     

Apportionment of the airborne PM10 in Spain. Episodes of potential negative impact for human health

The particulate matter with an aerodynamic diameter less than or equal to 10 and 2.5 microns respectively (PM10 and PM2.5) constitutes one of the main air pollutants, which is currently regulated in Europe through Directive 2008/50/EC due to its proven harmful effects on human health. In this paper, the airborne PM10 samples collected in Zaragoza city during 2001-2009 were apportioned by statistical tools based on principal component analysis with absolute principal component scores (PCA-APCS). PM10 samples were characterized regarding their concentrations of polycyclic aromatic hydrocarbons (PAH) and water-soluble ions. PAH were analyzed by gas chromatography-mass spectrometry-mass spectrometry detection (GC-MS-MS) and ions were analyzed by ion chromatography. A total of five factors were identified by PCA-APCS corresponding to different anthropogenic and natural sources. This work was focused on analyzing in more detail those samples involving higher negative impact on human health, in particular, PM10 samples exceeding the daily PM10 limit value of 50 μg m(-3) according to Directive 2008/50/EC and samples with concentrations of benzo[a]pyrene (BaP) higher than the upper assessment threshold (BaP > 0.6 ng m(-3)) established by the Directive 2004/107/EC. Most of the exceedances of the daily PM10 limit value were associated with direct and indirect North-African long-range transport. During these exceedances, it was observed that anthropogenic pollution sources slightly decreased with regard to the natural sources. This indicated that episodes of high PM10 could have a natural origin associated with long-range transport from the African continent. On the contrary, those exceedances with regional contribution and samples with BaP concentrations higher than 0.6 ng m(-3) showed an important contribution of anthropogenic pollution sources increasing their negative impact on human health.     

Investigations of mercury concentrations in walleye and other fish in the Athabasca River ecosystem with increasing oil sands developments

Recent studies have reported an increasing trend of mercury concentrations in walleye (Sander vitreus) from the Athabasca River, north eastern Alberta (Canada); these studies were based on three years of comparison and attributed the mercury increase to expanding oil sands developments in the region. In order to conduct a more comprehensive analysis of mercury trends in fish, we compiled an extensive database for walleye, lake whitefish (Coregonus clupeaformis), northern pike (Esox lucius) and lake trout (Salvelinus namaycush) using all available data obtained from provincial, federal, and industry-funded monitoring and other programs. Evidence for increasing trends in mercury concentrations were examined for each species by location and year also considering fish weight and length. In the immediate oil sands area of the Athabasca River, mercury concentrations decreased (p < 0.001) in walleye and lake whitefish over 1984-2011. In western Lake Athabasca and its delta, mercury concentrations decreased (p < 0.0001) in northern pike (1981-2009) although no trend was evident for walleye (1981-2005) and lake trout (1978-2009). Mercury concentrations in lake trout from Namur Lake, a small lake west of the oil sands area, were higher in 2007 than 2000 (p < 0.0001); it is difficult to ascribe this increase to an oil sands impact because similar increases in mercury concentrations have been observed in lake trout from similar sized lakes in the Northwest Territories. While mercury emissions rates have increased with oil sands development and the landscape become more disturbed, mercury concentrations remained low in water and sediments in the Athabasca River and its tributaries and similar to concentrations observed outside the development areas and in earlier decades. Our fish database was assembled from a series of studies that differed in study purpose, design, and analytical methods. Future monitoring programs investigating mercury trends in fish should be more rigorous in their design.     

Statistical modeling of crystalline silica exposure by trade in the construction industry using a database compiled from the literature

A quantitative determinants-of-exposure analysis of respirable crystalline silica (RCS) levels in the construction industry was performed using a database compiled from an extensive literature review. Statistical models were developed to predict work-shift exposure levels by trade. Monte Carlo simulation was used to recreate exposures derived from summarized measurements which were combined with single measurements for analysis. Modeling was performed using Tobit models within a multimodel inference framework, with year, sampling duration, type of environment, project purpose, project type, sampling strategy and use of exposure controls as potential predictors. 1346 RCS measurements were included in the analysis, of which 318 were non-detects and 228 were simulated from summary statistics. The model containing all the variables explained 22% of total variability. Apart from trade, sampling duration, year and strategy were the most influential predictors of RCS levels. The use of exposure controls was associated with an average decrease of 19% in exposure levels compared to none, and increased concentrations were found for industrial, demolition and renovation projects. Predicted geometric means for year 1999 were the highest for drilling rig operators (0.238 mg m(-3)) and tunnel construction workers (0.224 mg m(-3)), while the estimated exceedance fraction of the ACGIH TLV by trade ranged from 47% to 91%. The predicted geometric means in this study indicated important overexposure compared to the TLV. However, the low proportion of variability explained by the models suggests that the construction trade is only a moderate predictor of work-shift exposure levels. The impact of the different tasks performed during a work shift should also be assessed to provide better management and control of RCS exposure levels on construction sites.     

Attribution of Carbon Dioxide Fluxes to Crop Types in a Heterogeneous Agricultural Landscape of Argentina

The increasing proportion of agricultural lands worldwide makes it necessary to intensify the research concerning the carbon exchange at agricultural sites. In order to determine the Net Ecosystem Exchange (NEE) in an agricultural landscape in the province of Buenos Aires, Argentina, we carried out eddy covariance measurements with a flux tower, which was placed between two agricultural fields. Therefore, the measured CO₂ flux represents the accumulated flux from both areas, i.e., from different crop types. We here present an analysis method which attributes the flux to the two crop types. For this analysis, we applied the Hsieh footprint model to identify the contributing source area to the flux measurement. We then applied a multiple regression analysis to calculate the NEE in the growing season 2011/2012 for each field separately. The pronounced differences in the time courses of the CO₂ fluxes in the two fields can be explained by the different sowing times and different growth stages of both cultivations. The time courses furthermore show that the CO₂ uptake of the plants was strongly affected by the drought which lasted from December 2011 to January 2012. For the growth cycle of maize (216 days), the NEE was ?240 g C m^?2 and for the growth cycle of soybean (154 days) ?231 g C m^?2. In order to obtain the NEE of a complete agricultural cycle (from harvest to harvest), we also considered the NEE of autumn and winter 2011. Uncertainties of the spatially partitioned NEE are quantified and discussed.     

Adjusting the effect of seasonal variability in the bioassessment of streams

Bioassessment tools should distinguish between the effects of anthropogenic degradation in communities and natural temporal changes. The present study tests the influence of natural seasonal variability on macroinvertebrate stream communities assessed by a predictive model (PORTRIV) and a multimetric index (IPtI) calibrated for spring. The scores of PORTRIV decreased significantly between spring and autumn, and between spring and winter (ca. 37 to 53 %, respectively), while those of IPtI did not change significantly between seasons. For non-reference samples, the results of the predictive model also indicate no significant differences. A correction factor (CF) was calculated to adjust the existing differences in the model assessments between seasons, based on the percentage of variation of reference site scores from spring to autumn and winter. After the application of the CF to the OE50 scores of spring reference samples, the differences were no longer significant. Independent reference validation sites confirmed this tendency. This method has the advantage of avoiding large efforts required for the construction of databases from other seasons and the development of new models to allow the assessment of streams in seasons other than spring. Further tests with models developed in regions with more marked seasonal changes should be done to confirm its wider applicability.