Monitoring PCDD/Fs, PCBs and metals in the ambient air of an industrial area of Catalonia, Spain

In 2005 and 2006, the levels of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated biphenyls (PCBs) and metals (As, Be, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sn, Tl and V) were measured in air samples collected in an industrial area of Sant Adrià del Besòs (Barcelona, Catalonia, Spain) where a municipal solid waste incinerator (MSWI) is placed, and in a background/control area. In general terms, concentrations of all environmental pollutants were higher at the industrial site. No significant seasonal/temporal variations were observed in any of the areas. No Pearson correlation was found between the PCDD/F concentrations and the environmental conditions of the two sampling periods considered. Principal component analyses (PCA) were performed to get information on the relationship among samples, pollutants, and emission sources. The results indicate that the MSWI of S. Adrià de Besòs is not a significant emission source of the above compounds for the area under its direct influence. Moreover, a notable difference in the PCDD/F congener profiles was found between ambient air and stack gas emissions, indicating that the current levels of PCDD/Fs are more related to other potential emissions sources rather than to those from the MSWI.     

Model approach for estimating potato pesticide bioconcentration factor

We presented a model that estimates the bioconcentration factor (BCF) of pesticides in potatoes supposing that the pesticide in the soil solution is absorbed by the potato by passive diffusion, following Fick's second law. The pesticides in the model are nonionic organic substances, traditionally used in potato crops that degrade in the soil according to a first-order kinetic equation. This presents an expression that relates BCF with the pesticide elimination rate by the potato, with the pesticide accumulation rate within the potato, with the rate of growth of the potato and with the pesticide degradation rate in the soil. BCF was estimated supposing steady state equilibrium of the quotient between the pesticide concentration in the potato and the pesticide concentration in the soil solution. It is suggested that a negative correlation exists between the pesticide BCF and the soil sorption partition coefficient. The model was built based on the work of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato model. Environ. Sci. Technol. 41 (9), 3103-3108], in which an expression to calculate the diffusivity of persistent organic substances in potatoes is presented. The model consists in adding to the expression of Trapp et al. [Trapp, S., Cammarano, A., Capri, E., Reichenberg, F., Mayer, P., 2007. Diffusion of PAH in potato and carrot slices and application for a potato model. Environ. Sci. Technol. 41 (9), 3103-3108] the hypothesis that the pesticide degrades in the soil. The value of BCF suggests which pesticides should be monitored in potatoes.     

Chemosensory discrimination of familiar and unfamiliar conspecifics by lizards: implications of field spatial relationships between males

The ability of territorial lizards to discriminate between scents of neighbors and non-neighbors might contribute to decreasing the costs of aggressive interactions. To test this hypothesis, we conducted a field study to analyze the spatial relationships between male Iberian rock-lizards, Lacerta monticola. We then used the same individuals in a laboratory experiment to test whether male lizards can use chemical cues to discriminate between familiar conspecific males (those whose home ranges overlapped) and unfamiliar conspecific males (those whose home ranges did not overlap, and whose home range centers were at least 50 m apart). Differences in tongue-flick rates in the presence of chemical cues suggested that male L. monticola discriminated between odors of familiar and unfamiliar males. The behavioral responses were also dependent on relative differences in body size between the responding male and the unfamiliar male that donated the scent: There was a significant negative correlation between tongue-flick rates emitted in cages of unfamiliar males and the body size differences between males. In contrast, when the donor of the scent was a familiar male, the tongue-flick rate was not dependent on body size differences. These results are compatible with individual discrimination through chemical cues in male L. monticola.     

Particulate matter levels in a South American megacity: the metropolitan area of Lima-Callao,Peru

The temporal and spatial trends in the variability of PM₁₀ and PM_2.5 from 2010 to 2015 in the metropolitan area of Lima-Callao, Peru, are studied and interpreted in this work. The mean annual concentrations of PM₁₀ and PM_2.5 have ranges (averages) of 133–45 μg m^?3 (84 μg m^?3) and 35–16 μg m^?3 (26 μg m^?3) for the monitoring sites under study. In general, the highest annual concentrations are observed in the eastern part of the city, which is a result of the pattern of persistent local winds entering from the coast in a south-southwest direction. Seasonal fluctuations in the particulate matter (PM) concentrations are observed; these can be explained by subsidence thermal inversion. There is also a daytime pattern that corresponds to the peak traffic of a total of 9 million trips a day. The PM_2.5 value is approximately 40% of the PM₁₀ value. This proportion can be explained by PM₁₀ re-suspension due to weather conditions. The long-term trends based on the Theil-Sen estimator reveal decreasing PM₁₀ concentrations on the order of ?4.3 and ?5.3% year^?1 at two stations. For the other stations, no significant trend is observed. The metropolitan area of Lima-Callao is ranked 12th and 16th in terms of PM₁₀ and PM_2.5, respectively, out of 39 megacities. The annual World Health Organization thresholds and national air quality standards are exceeded. A large fraction of the Lima population is exposed to PM concentrations that exceed protection thresholds. Hence, the development of pollution control and reduction measures is paramount.     

A Novel Formulation for Designing a Monitoring Strategy: Application to the Design of a River Quality Monitoring System

In this work, we propose a technique to automatically optimize the monitoring of any distributed indicator (concentration of a substance along a river, blood pressure of a patient over time, etc.) for which a reliable estimate is previously available. From a mathematical point of view, the problem is based on obtaining a reliable estimate of the chosen indicator (e.g., by numerical simulation), and then solving a multi-objective optimization problem (with mixed real and integer variables) whose solution must provide an efficient and satisfactory monitoring strategy. As an illustrative case, we show the steps to follow in order to implement that strategy when designing a system for monitoring water quality in a river. Finally, we present and analyze the results when applying the proposed technique to study a real case in the Neuse River (North Carolina, USA).     

The use of sensory perception indicators for improving the characterization and modelling of total petroleum hydrocarbon (TPH) grade in soils

This paper proposes a multistep approach for creating a 3D stochastic model of total petroleum hydrocarbon (TPH) grade in potentially polluted soils of a deactivated oil storage site by using chemical analysis results as primary or hard data and classes of sensory perception variables as secondary or soft data. First, the statistical relationship between the sensory perception variables (e.g. colour, odour and oil–water reaction) and TPH grade is analysed, after which the sensory perception variable exhibiting the highest correlation is selected (oil–water reaction in this case study). The probabilities of cells belonging to classes of oil–water reaction are then estimated for the entire soil volume using indicator kriging. Next, local histograms of TPH grade for each grid cell are computed, combining the probabilities of belonging to a specific sensory perception indicator class and conditional to the simulated values of TPH grade. Finally, simulated images of TPH grade are generated by using the P-field simulation algorithm, utilising the local histograms of TPH grade for each grid cell. The set of simulated TPH values allows several calculations to be performed, such as average values, local uncertainties and the probability of the TPH grade of the soil exceeding a specific threshold value.