Proposal of Indicators to Assess Urban Sustainability in Brazil

The research related here focuses on municipal situations where problems of sustainability may be defined and tackled on the basis of bottom-up management procedures with the participation of organized society. The aim is to build management models that may be implemented with reasonable administrative effort and cost. Implementation pursues the target of approaching a sustainable situation in the municipality. Environmental parameters for an ideal municipality with undefined geographical location are presented. For each parameter, a set of indicators is developed that can measure the prospect of sustainability. The indicators are defined in terms of numbers or literal concepts according to the possibility of measurement. Examples of management models are presented, which are able to approach the situation defined as sustainable by the indicators. The basic management tool is the learning curve of targeted communities, which is experimentally developed and applied. The indicators are grouped according to their range of applicability.     

Environmental performance evaluation of agro-industrial innovations – Part 2: methodological approach for performing vulnerability analysis of watersheds

Environmental vulnerability analysis has been sparsely used in environmental performance evaluation (EPE) of technological innovations. The present paper proposes a methodological approach to carry out vulnerability analysis of watersheds and to integrate this analysis into methods of environmental performance evaluation of agro-industrial innovations. This approach is applied to the Ambitec-Life Cycle method, described in Part 1 (this issue) of this study. The case study of green coconut substrate compared to ripe coconut substrate, also described in Part 1 (this issue), is now presented considering the vulnerability analysis of the watersheds where the life cycle stages of these products occur. The integration of vulnerability analysis in Ambitec-Life Cycle contributes to a better understanding of the environmental aspects of agro-industrial technological innovations with potential to cause significant impacts in watersheds where these innovations are implemented.     

The Spanish project on energy and environment: ENMA

The project ENMA assesses the atmospheric pollution caused by the transformation and consumption of energy. The project is in the following stages: (a) estimation of annual overall average emissions; (b) estimation of annual average concentrations of pollutants; and (c) estimation of doses. Estimation of annual overall average emissions is estimated, separately, for urban areas and point sources. Concentrations of pollutants are obtained for urban areas and point-sources by means of two different gaussian models. Finally, doses are calculated assuming that the effects of all pollutants are linear at low doses. Doses for each pollutant, and doses for exposure to several combined pollutants, are defined. The doses on population are also defined, assuming that the significance of pollution depends on the number of people exposed.     

Modeling biodiversity dynamics in countryside landscapes

The future of biodiversity hinges to a great extent on the conservation value of countryside, the growing fraction of Earth's surface heavily influenced by human activities. How many species, and which species, can persist in such landscapes (and analogous seascapes) are open questions. Here we explore two complementary theoretical frameworks to address these questions: species-area relationships and demographic models. We use the terrestrial mammal fauna of Central America to illustrate the application of both frameworks. We begin by proposing a multi-habitat species-area relationship, the countryside species-area relationship, to forecast species extinction rates. To apply it, we classify the mammal fauna by affinity to native and human-dominated habitats. We show how considering the conservation value of countryside habitats changes estimates derived from the classic species-area approach We also examine how the z value of the species-area relationship affects extinction estimates. Next, we present a framework for assessing the relative vulnerability of species to extinction in the countryside, based on the Skellam model of population dynamics. This model predicts the minimum area of contiguous native habitat required for persistence of a species, which we use as an indicator of vulnerability to habitat change. To apply the model, we use our habitat affinity classification of mammals and we estimate life-history parameters by species and habitat type. The resulting ranking of vulnerabilities is significantly correlated with the World Conservation Union (IUCN) Red List assessment.     

Acute effects of 3,4-dichloroaniline on biomarkers and spleen histology of the common goby Pomatoschistus microps

The aromatic amine 3,4-dichloroaniline (DCA) is a model environmental contaminant, precursor for synthesis and degradation product of several herbicides, which is commonly found in European estuarine ecosystems. In this work, the possibility of using biochemical and histological markers to assess sub-lethal effects of DCA in natural populations of Pomatoschistus microps juveniles was investigated. Alterations on the activities of the enzymes acetylcholinesterase (AChE), lactate dehydrogenase (LDH) and glutathione S-transferase (GST) and histological alterations on spleen were investigated after 96 h of exposure to sublethal concentrations of DCA (0.50-1.49 mg/l). At the concentrations tested, DCA had no effect on AChE activity. LDH and GST activities were significant altered in treated animals when compared to control groups. As already described for mammals, DCA induced splenic histological alterations in P. microps, including expansion of red pulp and deposition of hemosiderin granules in a concentration-dependent manner. This suggests that DCA is a xenobiotic of concern in estuaries receiving agricultural effluents.     

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.     

GC and GC-MS characterization of crude oil transformation in sediments and microbial mat samples after the 1991 oil spill in the Saudi Arabian Gulf coast

The massive oil discharge in the Saudi Arabian coast at the end of the 1991 Gulf War is used here as a natural experiment to study the ability of microbial mats to transform oil residues after major spills. The degree of oil transformation has been evaluated from the analysis of the aliphatic and aromatic hydrocarbons by gas chromatography (GC) and GC coupled to mass spectrometry (GC-MS). The oil-polluted microbial mat samples from coastal environments exhibited an intermediate degree of transformation between that observed in superficial and deep sediments. Evaporation, photo-oxidation and water-washing seemed to lead to more effective and rapid elimination of hydrocarbons than cyanobacteria and its associated microorganisms. Furthermore, comparison of some compounds (e.g. regular isoprenoid hydrocarbons or alkylnaphthalenes) in the oil collected in the area after the spill or in the mixtures retained by cyanobacterial growth gave rise to an apparent effect of hydrocarbon preservation in the microbial mat ecosystems.     

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.     

Potential of Eucalyptus globulus for the phytoremediation of metals in a Moroccan iron mine soil—a case study

Environmental Science and Pollution Research - The contamination left by abandoned mines demands sustainable mitigation measures. Hence, the aim of this study was to examine the phytoremediator...