Spectral trend of vegetation with rainfall in events of El Niño-Southern Oscillation for Atlantic Forest biome,Brazil

This study aimed to analyze the spectral trend of vegetation with rainfall in El Niño-Southern Oscillation events (ENSO) in the Atlantic Forest, Brazil. Monthly rainfall data were collected from 85 conventional meteorological stations (EMC), data from the Enhanced Vegetation Index 2 (EVI2) and ENSO events (El Niño, La Niña, and Neutral) in the period from 2001 to 2013. Afterwards, state cluster analysis was performed using the results of non-parametric tests. The Mann-Kendall (MK) non-parametric test did not identify a trend pattern in rainfall distribution in the Atlantic Forest. The results for EVI2 by state and region showed that the trend is decreasing in the Northeast Region, except for the states of Alagoas and Pernambuco. Southeast region showed an increasing trend of EVI2 (except for Rio de Janeiro and São Paulo), while the South region showed a decreasing trend. In the Midwest, the trend was significantly decreasing. In the prognosis elaborated for the future, the regions with significant declines of the vegetation were the Northeast and Midwest. This study shows that the Atlantic Forest in some regions of Brazil has been suffering from the growing urbanization process and there is a trend of soil degradation.     

Influence of different textile fibers on characterization of dyeing wastewater and final effluent

Textile industry needs to recover and reuse its wastewater as to fulfil the demand of increasingly strict regulations. The characterization of dyeing wastewater samples according to textile fiber and final textile effluent enables the application of different treatment methods. This study aims to characterize dyeing wastewater in black color of polyamide, polyester, and viscose fibers and final textile effluent. Samples were collected and characterized completely for major pollution indicator parameters. Dyeing wastewater of polyester showed higher values for some parameters, e.g., 4994.44% (49,944,400 mg L^?1 and 917 NTU) of turbidity and 4100.00% of phenol when compared to dyeing wastewater of other fibers. Other parameters such as pH, alkalinity, color, phosphorus, nitrogen, sulfides, chlorides, oil and grease, dissolved solids, and chemical and biochemical oxygen demand were also assessed. In addition to individual characterization, this study also presents a correlation of the contribution of each parameter to the final textile effluent. Although dyeing wastewater of polyamide contributes the most in terms of quantity for the final effluent, this study revealed that dyeing wastewater of polyester influenced the most on the final composition of the textile wastewater when evaluating color, turbidity, total iron, biochemical oxygen demand, chemical oxygen demand, phenol, mercury, oil and grease, and total phosphorus. The present study is focused on bringing new insights to provide future research with other strategies to improve the treatment of dyeing wastewater. In addition, some suggestions are also given for wastewater treatments according to type of textile fiber.     

FIA-coupled spectrophotometric method for determination of Cr (VI) traces in natural waters: application of in-line dissolution of 1,5-diphenylcarbazide after heat treatment and activated alumina as adsorbent for preconcentration

This work proposes the quantification of Cr (VI) ions in natural waters in trace level, using activated alumina (Al₂O₃) as preconcentration support, controlled in-line dissolution of the solidified chromophore diphenylcarbazide after heat treatment and spectrophotometric detection. The manifold ensures high sensitivity of analytical response, good repeatability, and stability. In this work, optimization of experimental conditions of a flow injection system was chosen as the parameters for greater sensitivity and better selectivity. The selected optimized conditions were 0.30 mol L^?1 for H₂SO₄ concentration, system flow rate as 0.40 mL min^?1, sample injection volume of 192.50 μL, 2 min for preconcentration time, and 0.10 mol L^?1 for eluent concentration. The analytical curves obtained for real sample analysis show linear range from 0.192 to 0.961 μM, linear correlation coefficient R?=?0.9997 and LOD?=?0.024 μM. The preconcentration factor of about four times was obtained through the passage of 800 μL of a standard solution containing 0.961 μM of Cr (VI) through mini-column of preconcentration followed by elution at 192.5 μL of NH₄OH 0.1 mol L^?1 solution. The solid chromogenic reagent presented high durability (weeks in daily use with mass of 0.0993 g) and good reproducibility in analytical signal. The reactivation of the mini-column of alumina should be executed after ten injections of eluent, using 800 μL of HCl 0.02 mol L^?1 solution in flow through the same. Each cycle of injection and elution of the sample takes about 5 min on the proposed terms. Despite the length of each cycle still be high, low concentrations can be detected using a technique of relatively low cost. This is due in part, the association dissolution of the chromogenic reagent directly in the line and the preconcentration step. Another important factor is the economy of reagent chromogenic, low generation of reject contributing to better quality of the environment, and the high potential for applications to work in field.     

An urban emissions inventory for South America and its application in numerical modeling of atmospheric chemical composition at local and regional scales

This work describes the development of an urban vehicle emissions inventory for South America, based on the analysis and aggregation of available inventories for major cities, with emphasis on its application in regional atmospheric chemistry modeling. Due to the limited number of available local inventories, urban emissions were extrapolated based on the correlation between city vehicle density and mobile source emissions of carbon monoxide (CO) and nitrogen oxides (NOx). Emissions were geographically distributed using a methodology that delimits urban areas using high spatial resolution remote sensing products. This numerical algorithm enabled a more precise representation of urban centers. The derived regional inventory was evaluated by analyzing the performance of a chemical weather forecast model in relation to observations of CO, NOx and O₃ in two different urban areas, São Paulo and Belo Horizonte. The gas mixing ratios simulated using the proposed regional inventory show good agreement with observations, consistently representing their hourly and daily variability. These results show that the integration of municipal inventories in a regional emissions map and their precise distribution in fine scale resolutions are important tools in regional atmospheric chemistry modeling.     

Thirty year monitoring of PCBs, organochlorine pesticides and tetrabromodiphenylether in eel from The Netherlands

Because of their excellent properties as a biomonitor, yellow eels (Anguilla anguilla) have been used for time-trend monitoring of polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and tetrabrominated diphenylether (tetra-BDE). The program has now lasted for thirty years and has delivered valuable information on trends and spatial differences of these compounds in the delta of the rivers Rhine and Meuse and other Dutch canals, rivers and lakes. Specific local PCB, HCH and dieldrin contaminations were identified. Temporal trends show a slow decrease of PCB concentrations since 1977. Eels from the rivers Rhine and Meuse still exceed present European maximum residue limits for dioxin-like PCBs. Apart from some exceptions, OCP and tetra-BDE concentrations have also decreased, and more than those of PCBs. Fat contents of eel have decreased from an average of 21 to ca. 13%. This decrease in fat contents, coincides with the strong reduction of the European eel stock.     

Appraisal of measurement methods, chemical composition and sources of fine atmospheric particles over six different areas of Northern Belgium

Daily and seasonal variation in the total elemental, organic carbon (OC) and elemental carbon (EC) content and mass of PM_2.5 were studied at industrial, urban, suburban and agricultural/rural areas. Continuous (optical Dustscan, standard tapered element oscillating micro-balance (TEOM), TEOM with filter dynamics measurement system), semi-continuous (Partisol filter-sampling) and non-continuous (Dekati-impactor sampling and gravimetry) methods of PM_2.5 mass monitoring were critically evaluated. The average elemental fraction accounted for 2-6% of the PM_2.5 mass measured by gravimetry. Metals, like K, Mn, Fe, Cu, Zn and Pb were strongly inter-correlated, also frequently with non-metallic elements (P, S, Cl and/or Br) and EC/OC. A high OC/EC ratio (2-9) was generally observed. The total carbon content of PM_2.5 ranged between 3 and 77% (averages: 12-32%), peaking near industrial/heavy trafficked sites. Principal component analysis identified heavy oil burning, ferrous/non-ferrous industry and vehicular emissions as the main sources of metal pollution.     

How life history contributes to stress response in the Manila clam <Emphasis Type="Italic">Ruditapes philippinarum</Emphasis>

Introduction  

Within the last decade, numerous studies have investigated the role of environmental history on tolerance to stress of many organisms. This study aims to assess if Manila clams Ruditapes philippinarum may react differently to cadmium exposure and trematode parasite infection (Himasthla elongata) depending on their origin and environmental history in Arcachon Bay (France).     

Comparison of land-use regression models between Great Britain and the Netherlands

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO₂ and PM_10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL).Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country.A common model for GB and NL explained NO₂ concentrations well (adjusted R² 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction.The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models.     

Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.