Predicting dioxin-like PCBs soil contamination levels using milk of grazing animal as indicator

Dioxin-like PCBs (dl-PCBs) are ubiquitous persistent organic pollutants of recognized negative effects on human health. Assessing highly polluted areas should be an important public health issue. This study proposes to use the milk of grazing animals as a bioindicator of dl-PCB contamination in the environment. The hypothesis is that milk concentration of dl-PCBs are related to soil concentrations of these compounds, and that soils are generally reflective of a larger environmental issue of dl-PCB contamination. In this study, we evaluate the possibility of predicting soil concentrations using milk of sheep, cows and buffalos in a spatial model. For this purpose, samples of soil and milk collected in Campania (Italy) were introduced in a GIS platform to perform geostatistical analysis for building a simple predictive model. The ordinary least squares regressions (OLS) showed a statistically significant correlation (p < 0.05) between soil and milk contamination. However, this relationship was spatially variable. Thus, a geographically weighted regression (GWR) was performed, obtaining R² values of 0.91, 0.77 and 0.66 for sheep’s, buffalo’s and cow’s milk respectively. Assessed the mathematical relationships between the variables, new data was introduced to evaluate the performance of the model. Predictions of soil contamination with dl-PCBs using sheep’s, cow’s and buffalo’s milk showed a mean error of 23%, 25% and 36% respectively. According to these results the sheep’s milk can be considered the best bioindicator of dl-PCBs contamination among the three species. The results of this project evidence the potentialities of the proposed approach to assess bioindicator performance in a spatial predictive model.     

Experimental evaluation of PCDD/Fs and PCBs release and mass balance of a WTE plant

The behaviour of waste incineration plants with respect to organic toxic trace contaminants such as PCDDs, PCDFs and, to a minor extent, PCBs, is still a matter of concern for the public opinion and the decision makers. It is therefore very important, first, to evaluate the release of these organic toxic trace contaminants in the environment during waste incineration, not only through the stack gas emission but also with the solid and liquid residues, and then to compare the total release with the input through the treated waste in order to assess the plant behaviour as a “sink” rather than a “source” of organic toxic trace contaminants. The experimental investigation carried out on an Italian full scale incineration plant has shown a total 17 PCDD/Fs and 12 dioxin-like PCBs release of 5.5-27 μg WHO-TEQ per tonne of treated waste and an input flux of 1.6-44 μg WHO-TEQ per tonne of waste, with the difference between the input and the output fluxes rather small and the plant behaviour toward organic trace toxic contaminants in average neutral. Results are compared with similar evaluations conducted in the last decade on a number of waste-to-energy (WTE) plants operating in Italy.     

Environmental and lifestyle factors affect benzene uptake biomonitoring of residents near a petrochemical plant

Background

We monitored urinary benzene excretion to examine factors affecting benzene uptake in a sample of the general population living near a petrochemical plant.

Methods

Our study population included 143 subjects: 33 petrochemical plant workers (W) with low level occupational benzene exposure; 30 residents in a small town 2 km from the plant (2kmR); 26 residents in a second small town located 2 to 4 km from the plant (4kmR); and 54 urban residents 25 km from the plant (25kmR). Exposure to benzene was evaluated by personal air sampling during one work-shift for the W group, and from 8.00 to 20:00 for general population subgroups, and by urinary benzene (BEN-U).

Results

Median airborne benzene exposure was 25, 9, 7 and 6 μg/m³ benzene among the W, 2kmR, 4kmR, and 25kmR subgroups, respectively; the highest level was found among the workers, while there was no significant difference among the other groups. Median BEN-U was 2 to 14-fold higher in smokers compared to non-smokers; among non-smokers BEN-U was the highest in W (median 236 ng/L), and lower in the 2kmR (48 ng/L) and 4kmR (63 ng/L) subgroups than in the 25kmR (120 ng/L) subgroup. A multiple linear regression analysis, explaining up to 73% of BEN-U variability, confirmed that active smoking and airborne benzene most strongly affected BEN-U. Among the non-smoking, non-occupationally exposed study subjects, a positive association was found between BEN-U and the distance of residence from the plant. This association was explained by increased exposure to urban traffic emissions in the study group residing at a greater distance from the plant. Environmental tobacco smoke had a marginally positive role.

Conclusion

Among factors affecting benzene uptake in non-occupationally exposed individuals, urban residence contributes to benzene exposure more than residing in close proximity to a petrochemical plant.     

Incidence of thyroid disease following exposure to polybrominated biphenyls and polychlorinated biphenyls, Michigan, 1974-2006

Thyroid hormones, which influence body metabolism and development, could be affected by persistent organic pollutants. We sought to examine the relationship between polybrominated biphenyls (PBBs) and polychlorinated biphenyls (PCBs) and thyroid disease. We employed incidence density sampling to perform a nested case control analysis of the Michigan Long-Term PBB Cohort. Cohort members (n = 3333) were exposed to PBBs through contaminated cattle feed in 1973-1974 and to PCBs through daily life. Those with detectable serum PBB and PCB concentrations at enrollment were categorized into tertiles of PBB and PCB exposure. Case-patients were cohort members answering “Yes” to “Has a healthcare provider ever told you that you had a thyroid problem?” during follow-up interviews; control-patients were cohort members answering “No”. We used odds ratios (OR) with 95% confidence intervals (CI) to compare odds of thyroid disease by PBB and PCB exposure and by various risk factors. Total cumulative thyroid disease incidence after 33 years was 13.9% among women and 2.6% among men. After adjusting for body mass index, we found no statistically significant differences in odds of any type of thyroid disease among women or men with elevated PBB or PCB exposure. Compared to control-patients, women with thyroid disease had increased odds of being overweight/obese (OR = 2.82, 95% CI: 1.94-4.11) and developing infertility (OR = 1.71, 95% CI: 1.08-2.69), diabetes (OR = 1.61, 95% CI: 1.04-2.51), or arthritis (OR = 1.71, 95% CI: 1.18-2.50) during follow-up. Additional research should explore potential associations between PBBs/PCBs and thyroid disease among children exposed in utero.     

Combined steam distillation and electrochemical peroxidation (ECP) treatment of river sediment contaminated by PCBs

A combined treatment process utilizing steam distillation followed by electrochemical peroxidation (ECP) has been utilized to remove >90% of the polychlorinated biphenyls (PCBs) in St. Lawrence River sediment and destroy 95% of the PCBs recovered in the condensate. 2 l of condensate were collected by boiling 500 grams of sediment containing 4.3 mg PCBs. Most of the PCBs (82.3%) were recovered as a small volume (<1 ml) of yellow oil floating on the condensate and coating glassware surfaces. The aqueous phase PCBs (182 μg/l) were destroyed (95%) by three sequential ECP treatments at 16.8°C and pH 5, utilizing 1 ml of H₂O₂ (3%) and periodically reversed current (0.75–1.0 A @ 10 volts). Oxidation is primarily mediated by hydroxyl radicals produced by the reaction of hydrogen peroxide with electrochemically generated ferrous iron (Fenton's reagent). This work suggests steam extraction, in combination with advanced oxidation technologies, provides an effective treatment strategy for contaminated solids.     

Estimating trend precision and power to detect trends across grouped count data

Ecologists commonly use grouped or clustered count data to estimate temporal trends in counts, abundance indices, or abundance. For example, the U.S. Breeding Bird Survey data represent multiple counts of birds from within each of multiple, spatially defined routes. Despite a reliance on grouped counts, analytical methods for prospectively estimating precision of trend estimates or statistical power to detect trends that explicitly acknowledge the characteristics of grouped count data are undescribed. These characteristics include the fact that the sampling variance is an increasing function of the mean, and that sampling and group-level variance estimates are generally estimated on different scales (the sampling and log scales, respectively). We address these issues for repeated sampling of a single population using an analytical approach that has the flavor of a generalized linear mixed model, specifically that of a negative binomial-distributed count variable with random group effects. The count mean, including grand intercept, trend, and random group effects, is modeled linearly on the log scale, while sampling variance of the mean is estimated on the log scale via the delta method. Results compared favorably with those derived using Monte Carlo simulations. For example, at trend = 5% per temporal unit, differences in standard errors and in power were modest relative to those estimated by simulation (< or = /11/% and < or = /16/%, respectively), with relative differences among power estimates decreasing to < or = /7/% when power estimated by simulations was > or = 0.50. Similar findings were obtained using data from nine surveys of fingernail clams in the Mississippi River. The proposed method is suggested (1) where simulations are not practical and relative precision or power is desired, or (2) when multiple precision or power calculations are required and where the accuracy of a fraction of those calculations will be confirmed using simulations.     

Agronomic adaptation strategies under climate change for winter durum wheat and tomato in southern Italy: irrigation and nitrogen fertilization

Agricultural crops are affected by climate change due to the relationship between crop development, growth, yield, CO₂ atmospheric concentration and climate conditions. In particular, the further reduction in existing limited water resources combined with an increase in temperature may result in higher impacts on agricultural crops in the Mediterranean area than in other regions. In this study, the cropping system models CERES-Wheat and CROPGRO-Tomato of the Decision Support System for Agrotechnology Transfer (DSSAT) were used to analyse the response of winter durum wheat (Triticum aestivum L.) and tomato (Lycopersicon esculentum Mill.) crops to climate change, irrigation and nitrogen fertilizer managements in one of most productive areas of Italy (i.e. Capitanata, Puglia). For this analysis, three climatic datasets were used: (1) a single dataset (50?km?×?50?km) provided by the JRC European centre for the period 1975–2005; two datasets from HadCM3 for the IPCC A2 GHG scenario for time slices with +2°C (centred over 2030–2060) and +5°C (centred over 2070–2099), respectively. All three datasets were used to generate synthetic climate series using a weather simulator (model LARS-WG). Adaptation strategies, such as irrigation and N fertilizer managements, have been investigated to either avoid or at least reduce the negative impacts induced by climate change impacts for both crops. Warmer temperatures were primarily shown to accelerate wheat and tomato phenology, thereby resulting in decreased total dry matter accumulation for both tomato and wheat under the +5°C future climate scenario. Under the +2°C scenario, dry matter accumulation and resulting yield were also reduced for tomato, whereas no negative yield effects were observed for winter durum wheat. In general, limiting the global mean temperature change of 2°C, the application of adaptation strategies (irrigation and nitrogen fertilization) showed a positive effect in minimizing the negative impacts of climate change on productivity of tomato cultivated in southern Italy.     

In situ measures of foraging success and prey encounter reveal marine habitat-dependent search strategies

Predators are thought to reduce travel speed and increase turning rate in areas where resources are relatively more abundant, a behavior termed "area-restricted search." However, evidence for this is rare, and few empirical data exist for large predators. Animals exhibiting foraging site fidelity could also be spatially aware of suitable feeding areas based on prior experience; changes in movement patterns might therefore arise from the anticipation of higher prey density. We tested the hypothesis that regions of area-restricted search were associated with a higher number of daily speed spikes (a proxy for potential prey encounter rate) and foraging success in southern elephant seals (Mirounga leonina), a species exhibiting both area-restricted searches and high interannual foraging site fidelity. We used onshore morphological measurements and diving data from archival tags deployed during winter foraging trips. Foraging success was inferred from in situ changes in relative lipid content derived from measured changes in buoyancy, and first-passage time analysis was used to identify area-restricted search behavior. Seals exhibited relatively direct southerly movement on average, with intensive search behavior predominantly located at the distal end of tracks. The probability of being in search mode was positively related to changes in relative lipid content; thus, intensively searched areas were associated with the highest foraging success. However, there was high foraging success during the outward transit even though seals moved through quickly without slowing down and increasing turning rate to exploit these areas. In addition, the probability of being in search mode was negatively related to the number of daily speed spikes. These results suggest that movement patterns represent a response to prior expectation of the location of predictable and profitable resources. Shelf habitat was 4-9 times more profitable than the other habitats, emphasizing the importance of the East Antarctic shelf for this and other predators in the region. We have provided rare empirical data with which to investigate the relationship between predator foraging strategy and prey encounter/ foraging success, underlining the importance of inferring the timing and spatial arrangement of successful food acquisition for interpreting foraging strategies correctly.