The role of the rural settlements in the Brazilian savanna deforesting process

Although the drivers of deforestation in Brazil are relatively well known, there is still limited understanding of the role of family farm-based rural settlements in land cover changes, particularly in the Brazilian savanna. This research aims to identify land use patterns within rural settlements and examine how they are influenced by regional dynamics. The study is based on GIS techniques and satellite image classification (Landsat 5-TM and RapidEye imagery), combined with geo-referenced fieldwork data in three different regions of the State of Goiás. The results reveal that the deforestation arrangement within the studied rural settlements is very similar to the deforestation found in the surrounding regions. As a positive outcome, the rural settlements have a higher share of remnant vegetation when compared to the surrounding areas, but this is still concentrated within legal reserves. We conclude that the changing patterns of rural settlement land cover are highly influenced by regional dynamics.     

A Three-Dimensional Water Quality Model of Chicago Area Waterway System (CAWS)

As outfalls from various water reclamation plants, pumping stations, and combined sewer overflow outfalls discharge into the Chicago Area Waterway System (CAWS), an enhanced understanding of the final fate of crucial water quality state variables is of utmost importance. This paper reports the development and application of a 3D water quality model for a modified CAWS combined with the hydrodynamic kernel of Environmental Fluid Dynamics Code (EFDC). The modified CAWS is used to demonstrate the usefulness of the model while eliminating complications beyond the scope of this initial effort. The water quality model developed and presented in this research is a simplistic dissolved oxygen (DO)—biochemical oxygen demand model with the facility to account for the interaction between the water column and the bed. The aforementioned model is applied for the month of May 2009. The results from the hydrodynamic (EFDC) and water quality model is validated with the help of the observed data obtained from United States Geological Survey gaging stations and Metropolitan Water Reclamation District of Greater Chicago monitoring stations present inside the modeled domain. The 3D modeling captured the hydrodynamic and water-quality processes in CAWS in a satisfactory manner. Furthermore, modeling results showed and proved the interdependence of water quality characteristics in Bubbly Creek and CAWS with the effluent concentration from Racine Avenue Pumping Station situated at the head of Bubbly Creek, South Fork of South Branch of Chicago River.     

Monitoring of marine mucilage formation in Italian seas investigated by infrared spectroscopy and independent component analysis

The aim of this study is to present and to discuss some characteristics of recalcitrant organic matter mechanism and formation. These aggregates called mucilages that are produced by the degradation reactions of several algae, have been investigated by infrared (FTIR) spectroscopy. FTIR spectra of macroaggregates produced by different algal samples have been daily collected in order to investigate the steps of aggregation. Afterwards, they have been elaborated by means of Independent Component Analysis (ICA). ICA investigation of FTIR spectra showed that the global aggregation process of marine mucilage always consisted of two different phases or independent components (ICs). One IC is related to the first degradation step of algal cells leading to the production of mono and oligosaccharides with aminoacids and oligopeptides. The second IC is related to the polymerization of oligosaccharides with aminoacids and oligopeptides and to their interaction with less polar compounds such as lipids thus producing supramolecular structures. The emerging mechanisms of anomalous size aggregates of organic matter match those of natural organic matter aggregation. The approach we suggest is to use synthetic mucilages which allows to monitor the macroaggregates formation because it can hardly be performed by means of natural marine macroaggregates.     

Using condition factor and blood variable biomarkers in fish to assess water quality

The condition factor and blood variables, including erythrocyte lipid peroxidation (LPO) and the activity of antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx), in two ecologically distinct fish species (Astyanax fasciatus and Pimelodus maculatus) were evaluated at five sites in the Furnas Hydroelectric Power Station reservoir (Brazil) to assess water quality. Aldrin/dieldrin, endosulfan, heptachlor epoxide, and metolachlor were detected at different concentrations in four of the sites. Condition factor was not directly affected by such contaminants. A negative correlation between hematocrit and heptachlor was detected in P. maculatus. Positive correlations between red blood cells and heptachlor as well as an interactive effect of metolachlor and aldrin/dieldrin were detected in A. fasciatus. The erythrocytes of both species collected from the contaminated sites showed high levels of LPO, an increase in SOD and GPx activities and a decrease in CAT activity. Although the leukocyte number and the differential percentage of leukocytes varied among the sites, the hematological variables, the LPO levels, and the antioxidant enzyme activities could be used to assess water quality, regardless of the differences in the responses of the fish species.     

Toxicity persistence in runoff and soil from experimental soybean plots following insecticide applications

Persistence of toxicity in runoff water and soil was investigated in experimental soybean plots subjected to successive runoff events following pesticide application. Runoff events were produced by irrigation using a sprinkler system. The pesticides applied were cypermethrin and endosulfan, which are widely used in soy production in Argentina. Toxicity tests were performed on two abundant components of the regional fauna, the amphipod Hyalella curvispina and the fish Cnesterodon decemmaculatus. Runoffs from two pesticide applications were assayed at different stages of the growing season: an early application when the soil was almost bare and a late one close to harvest, when the ground was covered by vegetation and just before soy leaves fell. Toxicity to H. curvispina in runoff ceased almost one month after the early application of the two pesticides, while it persisted for over three months after the late application. Soil toxicity to H. curvispina and runoff toxicity to C. decemmaculatus followed the same pattern. Higher temperatures and solar radiation are likely to have enhanced insecticide degradation after the early application. Lower temperatures and solar radiation in combination with increased organic matter from litter probably contributed to the longer persistence of toxicity recorded after the late application, as compared with the early application. Cypermethrin caused no mortality to C. decemmaculatus after the early application, while endosulfan toxicity persisted for almost four months after the late one.     

Transport of simazine in unsaturated sandy soil and predictions of its leaching under hypothetical field conditions

The potential contamination of groundwater by herbicides is often controlled by processes in the vadose zone, through which herbicides travel before entering groundwater. In the vadose zone, both physical and chemical processes affect the fate and transport of herbicides, therefore it is important to represent these processes by mathematical models to predict contaminant movement. To simulate the movement of simazine, a herbicide commonly used in Chilean vineyards, batch and miscible displacement column experiments were performed on a disturbed sandy soil to quantify the primary parameters and processes of simazine transport. Chloride (Cl(-)) was used as a non-reactive tracer, and simazine as the reactive tracer. The Hydrus-1D model was used to estimate the parameters by inversion from the breakthrough curves of the columns and to evaluate the potential groundwater contamination in a sandy soil from the Casablanca Valley, Chile. The two-site, chemical non-equilibrium model was observed to best represent the experimental results of the miscible displacement experiments in laboratory soil columns. Predictions of transport under hypothetical field conditions using the same soil from the column experiments were made for 40 years by applying herbicide during the first 20 years, and then halting the application and considering different rates of groundwater recharge. For recharge rates smaller than 84 mm year(-1), the predicted concentration of simazine at a depth of 1 m is below the U.S. EPA's maximum contaminant levels (4 microg L(-1)). After eight years of application at a groundwater recharge rate of 180 mm year(-1) (approximately 50% of the annual rainfall), simazine was found to reach the groundwater (located at 1 m depth) at a higher concentration (more than 40 microg L(-1)) than the existing guidelines in the USA and Europe.     

Discrete event simulation to aid decision-making and mitigation in solid waste management

This article aims to evaluate municipal solid waste (MSW) management schemes in order to promote sustainability and eco-efficiency, core elements in global mitigation strategies in both public and private policies. A discrete event simulation (DES) approach was used to integrate the economic, environmental, and social aspects related to aseptic carton packages (ACP) in Itajuba, Brazil. The simulated scenarios consider three alternatives for disposing ACP: landfills, recycling, and incineration with energy recovery. According to our findings, incineration alternatives are preferred from an eco-efficiency perspective, given the potential greenhouse gas (GHG) emissions reductions and due to the possibility of energy recover, which reinforces the contribution of this technology to promote sustainability as largely found in the international literature. Given the context of MSW management in Brazil, this represents a significant opportunity to increase the effectiveness of mitigation strategies adopted in the country. Taking into account that this is by far the least applied technology, the authors strongly advocate that global strategies for mitigation consider different approaches to integrate carbon dioxide (CO₂) emission reductions related to the entire MSW management system and its alternatives, thus advancing from a waste disposal-oriented system to a life cycle–oriented system.

     

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.     

The quantitative real-time PCR applications in the monitoring of marine harmful algal bloom (HAB) species

In the last decade, various molecular methods (e.g., fluorescent hybridization assay, sandwich hybridization assay, automatized biosensor detection, real-time PCR assay) have been developed and implemented for accurate and specific identification and estimation of marine toxic microalgal species. This review focuses on the recent quantitative real-time PCR (qrt-PCR) technology developed for the control and monitoring of the most important taxonomic phytoplankton groups producing biotoxins with relevant negative impact on human health, the marine environment, and related economic activities. The high specificity and sensitivity of the qrt-PCR methods determined by the adequate choice of the genomic target gene, nucleic acid purification protocol, quantification through the standard curve, and type of chemical detection method make them highly efficient and therefore applicable to harmful algal bloom phenomena. Recent development of qrt-PCR-based assays using the target gene of toxins, such as saxitoxin compounds, has allowed more precise quantification of toxigenic species (i.e., Alexandrium catenella) abundance. These studies focus only on toxin-producing species in the marine environment. Therefore, qrt-PCR technology seems to offer the advantages of understanding the ecology of harmful algal bloom species and facilitating the management of their outbreaks.     

Analysis of the global warming dynamics from temperature time series

Global warming is the observed increase of the average temperature of the Earth. The primary cause of this phenomenon is the release of the greenhouse gases by burning of fossil fuels, land cleaning, agriculture, among others, leading to the increase of the so-called greenhouse effect. An approach to deal with this important problem is the time series analysis. In this regard, different techniques can be applied to evaluate the global warming dynamics. This kind of analysis allows one to make better predictions increasing our comprehension of the phenomenon. This article applies nonlinear tools to analyze temperature time series establishing state space reconstruction and prediction. Since noise contamination is unavoidable in data acquisition, it is important to employ robust techniques. The method of delay coordinates is employed for state space reconstruction and delay parameters are evaluated using the method of average mutual information and the method of false nearest neighbors. Afterwards, the simple nonlinear prediction method is employed to estimate temperatures of the future. Temperature time series from different places of the planet are used. Initially, the approach is verified considering known parts of the time series and afterwards, results are extrapolated for future values estimating temperature until 2028. Results show that these techniques are interesting to estimate temperature time history, presenting coherent estimations.