Morphological and chemical characteristics of atmospheric particles in the Metropolitan Zone of Toluca Valley (Mexico)

Scanning electron microscopy with energy-dispersive spectroscopy has been used for both morphological and elemental chemistry analyses of atmospheric particles. This technique allows the in situ observation of individual aerosol particles in the sample chamber. Aerotransported particles were analysed from seven monitoring stations located in the Metropolitan Zone of Toluca Valley (MZTV). Several different morphologies were identified: aggregates, porous spheres, rough and smooth compact material. The elemental composition included C, Na, Mg, Al, Si, S, Cl, K, Mn, Ca, Ti, V, Cr, Fe, Ni, Cu, Zn and Ce. These are semiquantitative analyses considering the bulk sample or individual particles. It was possible to correlate or confirm some chemical associations such as C–S, Ca–S–O and Si–Al–O, probably due to the presence of compounds derived from incomplete combustion, building tailing materials and aluminosilicates of cortical origin. Bioaerosols such as pollen, spores, brochosomes and diatoms were identified in the zone; all these types of particles have a natural origin too. Several types of suspended particles were identified in the MZTV, they were from different sources (natural and anthropogenic) to which the population can be potentially exposed, and may cause harm in the short- and long-term, according to their chemical element composition and size.     

Sorption and mobility of polyethylene glycol (PEG 4000) in tropical soils

Millions of tons of polyethylene glycols (PEGs) are manufactured worldwide and most of them will reach conventional sewage disposal systems after industrial utilization. This raises environmental concerns, but not much is known about the environmental fate of these polymers. The main goals of this research were to evaluate sorption and mobility of PEG in sandier soils of Brazil. PEG 4000 was applied to the soils either freely in solution or as a simulated bioassay residue. The bioassay was prepared to simulate PEG as it is present in the animal feces. It allowed us to compare PEG mobility for both forms of environment disposal. PEG showed very low sorption (<22% of the applied PEG) and high mobility potential (>43% of the applied amount in the free-PEG and >24% of the applied amount in the bioassay-PEG experiment) in the studied soils. When PEG was applied, simulating its supply to animal diets, about 30% of its applied amount was retained into the bioassay residues and its leaching potential was reduced, whereas the remaining amount (about 70%) was readily available in solution and could be directly released into the environment.     

Modeling and optimization of Nile blue sulfate mineralization by heterogeneous fenton oxidation

Artificial neural network and response surface methodology have been used to develop a model for simulation and optimization of the removal of Nile blue sulfate by heterogeneous Fenton oxidation. Experimental data were used to train an artificial neural network model with linear transfer function at the output layer and a tangent sigmoid transfer function at the hidden layer. A Box–Behnken design was employed to assess the effects of input process parameters on the total organic carbon removal. First order kinetics and lumped kinetics models were used to describe the reaction; a high regression coefficient indicated that the latter fitted best. The formation of non-oxidizable compounds was shown by liquid chromatography–mass spectrometry.     

Sensitivity of a coupled physical–biological model to turbulence: high-frequency simulations in a northern Adriatic station

This paper investigates the impacts of different turbulence models on the biological state at an ocean station in the northern Adriatic sea, named S3, comparing them with other uncertainties inherent to coupled physical–biological simulations. The numerical tool is a 1-D model resulting from the coupling of two advanced numerical models. The hydrodynamic part is modelled using the General Ocean Turbulence Model (www.gotm.net), in a version adopting state-of-the-art second-moment Turbulence Closure Models (TCMs). Marine biogeochemistry is parameterized with the Biogeochemical Flux Model (http://www.bo.ingv.it/bfm), which is a direct descendant of ERSEM (European Regional Sea Ecosystem Model). Results, obtained by forcing the model with hourly wind and solar radiation data and assimilating salinity casts, are compared against monthly observations made at the station during 2000–2001. Provided that modern second-moment TCMs are employed, the comparisons indicate that both the physical and the biological dynamics are relatively insensitive to the choice of the particular scheme adopted, suggesting that TCMs have finally ‘converged’ in recent years. As a further example, the choice of the nutrient boundary conditions has an impact on the system evolution that is more significant than the choice of the specific TCM, therefore representing a possible limitation of the 1-D model applied to stations located in a Region of Freshwater Influence. The 1-D model simulates the onset and intensity of the spring–summer bloom quite well, although the duration of the bloom is not as prolonged as in the data. Since local dynamics appears unable to sustain the bloom conditions well into summer, phytoplankton at the station was most likely influenced by river input or advection processes, an aspect that was not found when the S3 behaviour was adequately modelled using climatological forcings. When the focus is in predicting high-frequency dynamics, it is more likely that lateral advection cannot be neglected. While the physical state can be satisfactorily estimated at these short time scales, the accurate estimation of the biological state in coastal regions still appears as rather elusive.     

Social cost–benefit analysis of Karnataka Watershed Development (KAWAD) project,Karnataka, India

This paper presents results of a social cost–benefit analysis (CBA) of afforestation and soil moisture treatment of common lands under an integrated watershed development programme in Karnataka State, India. The aim of the study was to find out if soil moisture conservation and afforestation measures were justified in terms of economic efficiency. The assessment was undertaken by calculating the economic internal rate of return (EIRR) for five village common lands in two watersheds, Uparhalla and Chinnahagari, in central Karnataka. Focused group discussions were organised, using a semi-structured questionnaire and various stakeholders, including project implementing agencies, self help groups and other community-based organisations. The attractiveness of the programme in both watersheds for landless and land owners was high in three out of five sampled villages, with an EIRR ranging from 19% to 91%, while two villages in Chinnahagari watershed had extremely low EIRR, reflecting poor management of soil moisture and afforestation interventions and lack of institutional cohesion to sustain investments made to develop common lands. Therefore, the CBA conducted in the KAWAD project, except for two villages, shows that the investment made to develop common lands should yield substantial economic returns in the long term under a business as usual scenario.     

Estimating non-native plant richness with a species-accumulation model along roads

Monitoring non-native plant richness is important for biodiversity conservation and scientific research. The species-area model (SA model) has been used frequently to estimate the total species richness within a region. However, the conventional SA model may not provide robust estimations of non-native plant richness because the ecological processes associated with the accumulation of exotic and native plants may differ. Because roads strongly dictate the distributions of exotic plants, we propose a species-accumulation model along roads (SR model), rather than an SA model, to estimate the non-native plant richness within a region. Using 270 simulated data sets, we compared the differences in performance between the SR and SA models. A decision tree based on prediction accuracy was created to guide model application, which was validated using field data from 3 national nature reserves in 3 different provinces in China. The SR model significantly outperformed the SA model when non-native species were restricted to the roadsides and the proportion of uncommon exotic species was small. More importantly, the SR model accurately estimated the non-native plant richness in all field sites with an error of <1 species per site. We believe our new model meets the practical need to efficiently and robustly estimate non-native plant richness, which may facilitate effective biodiversity conservations and promote research on non-native plant invasion and vegetation dynamics.