Transfer of pesticides to the brew during mate drinking process and their relationship with physicochemical properties

In order to evaluate the extraction of pesticide residues that are transferred to the brew during mate drinking process of P.U.1 yerba mate leaves (Ilex paraguariensis), a special device to simulate the way in which mate is drunk in Uruguay was developed. The transfer to the brew of 12 organophosphates, 5 synthethic pyrethroids and one organochlorine pesticide from spiked samples was studied. The relationship between the transfer data thus obtained and physicochemical properties like water solubility (Ws), octanol-water coefficient (Kow) and Henry's constant (H) was evaluated. The extractability of the pesticide residues from yerba mate can be correlated with log Ws and log Kow. These transfer values allowed the calculation of ARLs (acceptable residue level) for the pesticides following Food and Agriculture Organization (FAO), World Health Organizaion (WHO) guidelines. These results can help the future establishment of maximum residue levels (MRLs).     

Urban and rural mortality rates during heat waves in Berlin and Brandenburg, Germany

In large cities such as Berlin, human mortality rates increase during intense heat waves. Analysis of relevant data from north-eastern Germany revealed that, during the heat waves that occurred between 1990 and 2006, health risks were higher for older people in both rural and urban areas, but that, during the two main heat waves within that 17-year period of time, the highest mortality rates were from the city of Berlin, and in particular from its most densely built-up districts. Adaptation measures will need to be developed, particularly within urban areas, in order to cope with the expected future intensification of heat waves due to global climate change.     

Trace elements and microbiological parameters in farmed Nile tilapia with emphasis on muscle,water, sediment and feed

Fish may bioaccumulate contaminants from the aquatic environment and extend them to the food chain provoking risks to human health. This study evaluated the microbiological parameters of the pond´s water and trace elements concentrations in samples of water, sediment, feed and muscle of farmed Nile tilapia used for human consumption in southern Brazil. A total of 240 fish were collected from 12 tilapia farms. Sediment, tank water and dry ration used in the animals' diet were collected for analysis. Analysis were performed by Energy Dispersion X-ray Fluorescence (EDXRF), Inductively Coupled Plasma Mass Spectrometer (ICP-MS), Induced Coupled Plasma Optical Emission Spectrometer (ICP-OES), and Atomic Absorption Spectrometer (AAS-VGA). In addition, the microbiological analysis of the water was carried out. The concentrations of Se, I, Fe, Cu and Zn in fish muscle were higher than the recommended by the Brazilian legislation, considering the advised daily intake for adults. The arsenic element had concentrations above the limit stipulated by the present Brazilian legislation, observed in all samples of muscle, sediment and tank water highlighting a possible environmental and fish contamination by the toxic element. Moreover, the arsenic concentration in the water presented a positive correlation (ρ?=?0.33) with arsenic in the muscle, suggesting that tilapia is a good environmental bioindicator, once they properly reflect the levels of arsenic in the water. It is suggested to perform an arsenic speciation for quantification of the inorganic form and accurate assessment of the degree of toxicity in the muscle samples and risks it can bring to human health. Regarding the other potentially toxic elements (Hg, Pb and Cd), and microbiological analysis of water it was verified that the consumption of the fish in question does not raise risks, since the values are within a quality benchmark established by law. The concentration of total and fecal coliforms in pond´s water in the facilities was in agreement with the microbiological indexes required by the legislation of CONAMA class II. Western region presented the lowest concentrations of fecal coliforms when compared to the other regions. There was no significant difference in the microbiological counts of total heterotrophic bacteria, Vibrio spp. and Pseudomonas spp. among the regions.     

BIO_ALGAE 2: improved model of microalgae and bacteria consortia for wastewater treatment

Environmental Science and Pollution Research - A new set up of the integral mechanistic BIO_ALGAE model that describes the complex interactions in mixed algal-bacterial systems was developed to...     

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.     

Digital sustainability: basic conditions for sustainable digital artifacts and their ecosystems

The modern age has heralded a shift from the industrial society, in which natural resources are crucial input factors for the economy, towards a knowledge society. To date, sustainability literature has treated knowledge—and in particular digital artifacts—mainly as a means to the end of achieving sustainable development. In this conceptual paper, we argue that digital artifacts themselves ought also to be considered as resources, which also need to be sustainable. While over-consumption is a problem facing natural resources, with sustainable digital artifacts, underproduction, and underuse are the biggest challenges. In our view, the sustainability of digital artifacts improves their potential impact on sustainable development. A theoretical foundation for digital artifacts and their ecosystem allows us to present the relevant research on digital information, knowledge management, digital goods, and innovation literature. Based on these insights, we propose ten basic conditions for sustainable digital artifacts and their ecosystem to ensure that they provide the greatest possible benefit for sustainable development. We then apply those characteristics to four exemplary cases: Linux kernel development, Bitcoin cryptocurrency, the Wikipedia project, and the Linking Open Drug Data repositories. The paper concludes with a research agenda identifying topics for sustainability scholars and information systems academics, as well as practitioners. A number of suggestions for future studies on digital sustainability are also put forward.     

Anti-oviposition activities of used sock media against a dengue vector: prospects of eco-friendly control and solutions to pollution

Yearly, huge amounts of sock refuse are discarded into the environment. Socks contain many molecules, and worn ones, which are rich in smell-causing bacteria, have a strong influence on animals’ behaviors. But the impacts of sock odor on the oviposition behavior of dengue vectors are unknown. We assessed whether Aedes albopictus changes its oviposition activity in response to the presence of used socks extract (USEx) in potential breeding grounds, using choice and no-choice bioassays (NCB). When furnished even chances to oviposit in two sites holding USEx and two others containing water (control), Ae. albopictus deposited significantly less eggs in USEx than in water sites. A similar pattern of oviposition preference was also observed when there were more oviposition options in water. When there were greater oviposition opportunities in USEx sites, Ae. albopictus oviposited preferentially in water. Females laid significantly more eggs during the NCB involving water than USEx. Also, significantly more mature eggs were retained by females in the NCB with USEx than in that with water. These observations strongly suggest the presence of molecules with either repellent or deterrent activities against Ae. albopictus females and provide an impetus to advocate the integration of used socks in dengue control programs. Such applications could be a realistic end-of-life recourse to reroute this waste from landfills.

     

Extreme value modeling for the analysis and prediction of time series of extreme tropospheric ozone levels: a case study

The occurrence of high concentrations of tropospheric ozone is considered as one of the most important issues of air management programs. The prediction of dangerous ozone levels for the public health and the environment, along with the assessment of air quality control programs aimed at reducing their severity, is of considerable interest to the scientific community and to policy makers. The chemical mechanisms of tropospheric ozone formation are complex, and highly variable meteorological conditions contribute additionally to difficulties in accurate study and prediction of high levels of ozone. Statistical methods offer an effective approach to understand the problem and eventually improve the ability to predict maximum levels of ozone. In this paper an extreme value model is developed to study data sets that consist of periodically collected maxima of tropospheric ozone concentrations and meteorological variables. The methods are applied to daily tropospheric ozone maxima in Guadalajara City, Mexico, for the period January 1997 to December 2006. The model adjusts the daily rate of change in ozone for concurrent impacts of seasonality and present and past meteorological conditions, which include surface temperature, wind speed, wind direction, relative humidity, and ozone. The results indicate that trend, annual effects, and key meteorological variables along with some interactions explain the variation in daily ozone maxima. Prediction performance assessments yield reasonably good results.     

Spatial Variation of Soil Salinity in the Mexicali Valley, Mexico: Application of a Practical Method for Agricultural Monitoring

The degradation of irrigated lands through the process of soil salinization, or the buildup of salts in the soil, has hampered recent increases in agricultural productivity and threatens the sustainability of large-scale cultivation in critical agricultural regions of the world. Rapid detection of soil salinity on a regional basis has been identified as key for effective mitigation of such land degradation. The ability to detect regional patterns of soil salinity at an accuracy sufficient for regional-scale resource management is demonstrated using Landsat 5 Thematic Mapper (TM) imagery. A case study of the Mexicali Valley of Baja California, Mexico was selected due to the region's agricultural significance and concern for future soil salinity increases. Surface soil salinity was mapped using georeferenced field measurements of electrical conductivity (EC), collected concurrently with Landsat 5 TM imagery. Correlations between EC measurements and common indices derived from the satellite imagery were used to produce a model of soil salinity through regression analysis. Landsat band 7, TNDVI, PCA 1, Tasseled Cap 3 and Tasseled Cap 5 were found to offer the most promising correlations with surface soil salinity. Generally low levels of soil salinity were detected, however, distinct areas of elevated surface salinity were detected at levels potentially impacting sensitive crops cultivated within the region. The difficulty detecting low levels of salinity and the mid-range spatial resolution of Landsat 5 TM imagery restrict the applicability of this methodology to the study of broad regional patterns of degradation most appropriate for use by regional resource managers.     

The Impacts of Different Meteorology Data Sets on Nitrogen Fate and Transport in the SWAT Watershed Model

In this study, we investigated how different meteorology data sets impacts nitrogen fate and transport responses in the Soil and Water Assessment Tool (SWAT) model. We used two meteorology data sets: National Climatic Data Center (observed) and Mesoscale Model 5/Weather Research and Forecasting (simulated). The SWAT model was applied to two 10-digit hydrologic unit code watersheds in the Coastal Plain and Piedmont zones of North Carolina. Nitrogen cycling and loading response to these meteorological data were investigated by exploring 19 SWAT nitrogen outputs relating to landscape delivery, biogeochemical assimilation, and atmospheric deposition. The largest difference in model output using both meteorology data sets was for large loads/fluxes. Landscape delivery outputs (e.g., NO^? ₃ watershed discharge, groundwater NO^? ₃ flux, soil NO^? ₃ percolation) showed the largest difference across all values. Use of the two weather data sources resulted in a nearly twofold difference in NO^? ₃ watershed discharge and groundwater NO^? ₃ flux. Differences for many nitrogen outputs were greater than those for sub-basin flow. Nitrogen outputs showed the greatest difference for agricultural land covers and there was no flow-related pattern in output differences across sub-basins or over time (years). In general, nitrogen parameter models that had a greater number of nitrate concentration, flow, and temperature terms (equation variables) in each transport model showed the greatest difference between both meteorology applications.