Transport of rimsulfuron and its metabolites in soil columns

This paper presents a study on degradation, sorption and transport of the sulfonylurea herbicide rimsulfuron and its major metabolites in alluvial soil columns. The formulation of rimsulfuron was found to strongly affect its degradability. Hydrolysis of pure rimsulfuron takes place rapidly in distilled water (t(1/2)=2.2 days) or indeed instantaneously in alkaline solution. The formulated rimsulfuron (Titus, 25% rimsulfuron, Du Pont De Nemours) is more persistent in alluvial soil suspensions (t(1/2)=7.5 days). The study of sorption of Titus and its two major metabolites (1 and 2) revealed that these three chemicals are potentially highly mobile in the studied soil: in suspension distribution coefficients of 0.0028, 0.125 and 0.149 cm3 g(-1) were obtained respectively. Given the instability of rimsulfuron in alkaline solutions, the pH effect was evaluated with metabolite 2 in water saturated Fontainebleau sand columns at pH 6, 8 and 10. Transport was found to be strongly dependent on pH; a linear relationship was obtained between pH and the retardation factor or the dispersion coefficient. In alluvial soil columns, rimsulfuron from Titus was found to be very mobile (R=1.2) and rapidly degraded into metabolites 1 and 2, which were transported at a similar velocity. Nevertheless, the risks of groundwater contamination by rimsulfuron seem very low, as it is rapidly degraded under dynamic conditions (t(1,2)=1.4 days). On the other hand the relatively stable metabolite 2 seems likely to persist in the soil and to be transported to the groundwater. Special attention should thus be given to this compound at least as long as its harmlessness is not demonstrated.     

São Paulo Aerosol Characterization Study

Abstract

The São Paulo Metropolitan area (SPMA) is characterized as having one of the worst air pollution problems in Brazil,with frequent violations of air quality standards for particulate matter. This paper presents the results of a eceptor model source apportionment study carried out to develop a quantitative database on which a control strategy could be developed. The study was conducted in four sites with distinct land uses. Fine, coarse (CP), and total suspended particles (TSP) samples were collected on Teflon and glass filters and analyzed by x-ray fluorescence XRF), ion chromatography, and thermal evolution. The sources were characterized by similar methodology. Chemical mass balance (CMB) receptor modeling indicated that carbonaceous material plays an important role in the aerosol composition; that the three major source categories contributing to the fine particles are vehicles, secondary carbon, and sulfates; and that the main contributors to CP and TSP are road dust and vehicles. All sampling sites presented the same general pattern in terms of source contribution, although this contribution varied from site to site.     

Effect of light supply on CO2 capture from atmosphere by Chlorella vulgaris and Pseudokirchneriella subcapitata

Carbon dioxide (CO₂) is one of the primary greenhouse gases that contribute to climate change. Consequently, emission reduction technologies will be needed to reduce CO₂ atmospheric concentration. Microalgae may have an important role in this context. They are photosynthetic microorganisms that are able to fix atmospheric CO₂ using solar energy with efficiency ten times higher than terrestrial plants. The objectives of this study were: (i) to analyse the effect of light supply on the growth of Chlorella vulgaris and Pseudokirchneriella subcapitata; (ii) to assess the atmospheric CO₂ capture by these microalgae; and (iii) to determine the parameters of the Monod model that describe the influence of irradiance on the growth of the selected microalgae. Both microalgae presented higher growth rates with high irradiance values and discontinuous light supply. The continuous supply of light at the highest irradiance value was not beneficial for C. vulgaris due to photooxidation. Additionally, C. vulgaris achieved the highest CO₂ fixation rate with the value of 0.305 g-CO₂ L^?1 d^?1. The parameters of the Monod model demonstrated that C. vulgaris can achieve higher specific growth rates (and higher CO₂ fixation rates) if cultivated under higher irradiances than the studied values. The presented results showed that microalgal culture is a promising strategy for CO₂ capture from atmosphere.     

Simulation and life cycle assessment of process design alternatives for biodiesel production from waste vegetable oils

This study uses the process simulator ASPEN Plus^® and Life Cycle Assessment (LCA) to compare three process design alternatives for biodiesel production from waste vegetable oils that are: the conventional alkali-catalyzed process including a free fatty acids (FFAs) pre-treatment, the acid-catalyzed process, and the supercritical methanol process using propane as co-solvent. Results show that the supercritical methanol process using propane as co-solvent is the most environmentally favorable alternative. Its smaller steam consumption in comparison with the other process design alternatives leads to a lower contribution to the potential environmental impacts (PEI’s). The acid-catalyzed process generally shows the highest PEI’s, in particular due to the high energy requirements associated with methanol recovery operations.     

Effects of hand weeding strip and nitrogen fertilizer on corn plants

The objective of the present research was to evaluate effects of different strip weed control associated with nitrogen fertilizer on corn applied after planting. The experiment was set and conducted in Botucatu, S?o Paulo State, Brazil, and the hybrid planted was Dekalb 333-B. A completely randomized block design with four replications was used. Experimental plots were disposed as a factorial scheme 2 x 2 x 4, constituted by two types of weeding on row (with or without manual hoeing), two types of weeding on inter-row (with or without manual hoeing), and four nitrogen levels applied after planting (00, 60, 90, and 120 kg ha(-1)). Plots were composed by six rows with 5 m length. Nitrogen fertilizer was applied at 35 days after emergence (d.a.e). For weed community it was evaluated: weed density, dominancy, frequency, and relative importance. The main weed species were: Brachiaria plantiginea, Amaranthus retroflexus, Bidens pilosa, Cyperus rotunds, Brachiaria decumbens, Euphorbia heterofila, Oxalis latifolia, Acanthospermum hispidum, Commelina benghalensis. It was evaluated corn height at 40 and 100 d.a.e., first ear insertion height at 100 d.a.e., and final grain yield at harvesting. Plants and first ear insertion height were affected when nitrogen fertilizer was not applied. Treatments without weed control showed that weed interfered negatively with plants height. There were no correlation between weeds and nitrogen fertilizer for all parameters evaluated. Parcels without weed showed the highest ear weights and final grain production. Treatments that received nitrogen fertilizer, independently of studied arrangement, provided higher yields.     

Prediction of ozone concentrations in Oporto city with statistical approaches

The performance of three statistical methods: time-series, multiple linear regression and feedforward artificial neural networks models were compared to predict the daily mean ozone concentrations. The study here reported was based on data from one urban site with traffic influences and one rural background site. The studies were performed for the year 2002 and the respective four trimesters separately. In the multiple linear regression and feedforward artificial neural network models, the concentrations of ozone, the concentrations of its precursors (nitrogen oxides) and some meteorological variables for one and two days before the prediction day were used as predictors. For the application of these models in the validation step, the inputs of ozone concentration for one and two days before were replaced by the ozone concentrations predicted by the models. The results showed that time-series modelling was not profitable. In the development step, similar performances were obtained with multiple linear regression and feedforward artificial neural network. Better performance indexes were achieved with feedforward artificial neural network models in validation step. Concluding, feedforward artificial neural network models were more efficient to predict ozone concentrations.     

Contribution of anthropogenic pollutants to the increase of tropospheric ozone levels in the Oporto Metropolitan Area, Portugal since the 19th century

The main purpose of this study was to evaluate the contribution of anthropogenic pollutants to the increase of tropospheric ozone levels in the Oporto Metropolitan Area (Portugal) since the 19th century. The study was based on pre-industrial and recent data series, the results being analyzed according to the atmospheric chemistry. The treatment of ozone and meteorological data was performed by classical statistics and by time-series analysis. It was concluded that in the 19th century the ozone present in the troposphere was not of photochemical origin, being possible to consider the respective concentrations as reference values. For recent data a cycle of 8h for ozone concentrations could be related to traffic. Compared to the 19th century, the current concentrations were 147% higher (252% higher in May) due to the increased photochemical production associated with the increased anthropogenic emissions.