Leaching of seven pesticides currently used in cotton crop in Mato Grosso State-Brazil

This study aimed to evaluate the leaching of pesticides and the applicability of the Attenuation Factor (AF) Model to predict their leaching. The leaching of carbofuran, carbendazim, diuron, metolachlor, alpha and beta endosulfan and chlorpyrifos was studied in an Oxisol using a field experiment lysimeter located in Dom Aquino-Mato Grosso. The samples of percolated water were collected by rain event and analyzed. Chemical and physical soil attributes were determined before pesticide application to the plots. The results showed that carbofuran was the pesticide that presented a higher leaching rate in the studied soil, so was the one representing the highest contamination potential. From the total carbofuran applied in the soil surface, around 6% leached below 50 cm. The other pesticides showed lower mobility in the studied soil. The calculated values to AF were 7.06E-12 (carbendazim), 5.08E-03 (carbofuran), 3.12E-17 (diuron), 6.66E-345 (alpha-endosulfan), 1.47E-162 (beta-endosulfan), 1.50E-06 (metolachlor), 3.51E-155 (chlorpyrifos). AF Model was useful to classify the pesticides' potential for contamination; however, that model underestimated pesticide leaching.     

A practical method for quantification of phosphorus- and glycogen-accumulating organism populations in activated sludge systems.

Enhanced biological phosphorus removal (EBPR) from wastewater relies on the enrichment of activated sludge with phosphorus-accumulating organisms (PAOs). The presence and proliferation of glycogen-accumulating organisms (GAOs), which compete for substrate with PAOs, may be detrimental for EBPR systems, leading to deterioration and, in extreme cases, failure of the process. Therefore, from both process evaluation and modeling perspectives, the estimation of PAO and GAO populations in activated sludge systems is a relevant issue. A simple method for the quantification of PAO and GAO population fractions in activated sludge systems is presented in this paper. To develop such a method, the activity observed in anaerobic batch tests executed with different PAO/GAO ratios, by mixing highly enriched PAO and GAO cultures, was studied. Strong correlations between PAO/GAO population ratios and biomass activity were observed (R2 > 0.97). This served as a basis for the proposal of a simple and practical method to quantify the PAO and GAO populations in activated sludge systems, based on commonly measured and reliable analytical parameters (i.e., mixed liquor suspended solids, acetate, and orthophosphate) without requiring molecular techniques. This method relies on the estimation of the total active biomass population under anaerobic conditions (PAO plus GAO populations), by measuring the maximum acetate uptake rate in the presence of excess acetate. Later, the PAO and GAO populations present in the activated sludge system can be estimated, by taking into account the PAO/GAO ratio calculated on the basis of the anaerobic phosphorus release-to-acetate consumed ratio. The proposed method was evaluated using activated sludge from municipal wastewater treatment plants. The results from the quantification performed following the proposed method were compared with direct population estimations carried out with fluorescence in situ hybridization analysis (determining Candidatus Accumulibacter Phosphatis as PAO and Candidatus Competibacter Phosphatis as GAO). The method showed to be potentially suitable to estimate the PAO and GAO populations regarding the total PAO-GAO biomass. It could be used, not only to evaluate the performance of EBPR systems, but also in the calibration of potential activated sludge mathematical models, regarding the PAO-GAO coexistence.     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.     

Effect of typhoon on atmospheric particulates in autumn in central Taiwan

Previous studies have suggested that the ongoing global climate change will likely increase the intensity and frequency of extreme weather, such as typhoons. Since the beginning of global warming, it has become necessary to understand the influence of typhoons on air quality. Rare data, especially particulate measurements data could be used to establish the relationship between the air pollution and typhoons. One of main limiting factors is that most of the previous chemical analyses of particulates used a relatively long sampling time, which could dilute the temporal impact of particulate characteristics and their sources. This work, depending more time-resolved measurements, focus on the characteristics and sources of high particulate matter levels and the influence of typhoons and the Pacific high system. Depending on the measurements, two pollutant groups were clearly identified in this work. The first pollutant group was the emissions from neighboring riverbeds under the strong circulation of the typhoon in the driest season and characterized as high coarse particle concentrations with high mass fraction of Ca²⁺. The second pollutant group was characterized as the formation and transport of secondary particles with prevalent ions of NH₄⁺, NO₃^?, and SO₄^2? and occurred in the sea-land breeze circulation under the influence the Pacific high system.     

Organic aerosol characterization by complementary measurements of chemical bonds and molecular fragments

Organic aerosol chemical markers from normalized concentrations of independent measurements of mass fragments (using Aerosol Mass Spectrometry, AMS) are compared to bond-based functional groups (from Fourier Transform Infrared spectroscopy, FTIR) during eight field projects in the western hemisphere. Several field projects show weak correlations between alcohol group fractions and m/z 60 fractions, consistent with the organic hydroxyl groups and the fragmentation of saccharides, but the weakness of the correlations indicate chemical differences among the relationships for ambient aerosols in different regions. Carboxylic acid group fractions and m/z 44 fractions are correlated weakly for three projects, with correlations expected for aerosols dominated by di-acid compounds since their fragmentation is typically dominated by m/z 44. Despite differences for three projects with ratios of m/z 44 to m/z 57 fragments less than 10, five projects showed a linear trend between the project-average m/z 44 to m/z 57 ratio and the ratio of acid and alkane functional groups. While this correlation explains only a fraction of the fragment and bond variability measured, the consistency of this relationship at multiple sites indicates a general agreement with the interpretation of the relative amount of m/z 44 as a carboxylic acid group marker and m/z 57 as an alkane group marker.     

Trend evaluation of water quality parameters in the Niagara and St. Lawrence Rivers

Physical and chemical (nutrients and major ions) indicators of water quality monitored by Environment Canada between 1977 and 1987 in the Niagara River at Niagara-on-the-Lake and in the St. Lawrence River at Wolfe Island are analyzed for seasonal and annual variations. Parametric methods such as moving averages and linear regression and nonparametric methods (Spearman's rank coefficient) are used to test for the existence of trends in these data. The results indicate that specific conductivity, sodium and chloride have decreased significantly over the period of study. During the same period there is no significant trend for either discharge and nutrients.