Absolute principal component analysis of atmospheric aerosols in Mexico city

A receptor model is presented based on absolute principal component analysis (APCA) of elemental concentrations in atmospheric aerosols from Mexico City during the Summer of 1995. Elemental contents on samples collected with a Stacking Filter Unit of the Davis design was carried out using Particle Induced X-ray Emission (PIXE). The sampling device allowed the separation of particles with mean aerodynamic diameters ranging from 2.5 μm to 15 μm (coarse fraction) and smaller than 2.5 μm (fine fraction). Sampling was divided into morning, afternoon and night periods, with higher concentrations being found during the morning. Seasonal variation is observed when comparisons with other studies are carried out. The application of APCA allowed identification of four sources for each fraction, with a soil-derived dust predominance in the coarse one. The influence of meteorological parameters is studied using cluster analysis, showing that during the morning there is a transport of pollutants from the west towards the sampling site, while the night transport corresponds to soil-derived dust from the north.     

Spatial analysis of land use impact on ground water nitrate concentrations

In spatial analyses of causes or health effects of environmental pollutants, small units of analyses are usually preferred for internal environmental homogeneity reasons but can only be done when fine resolution data are available for most units. Objectives of this study were to determine which land use practices were spatially associated with ground water nitrate concentrations across Prince Edward Island (PEI), Canada, and which spatial aggregation is the preferred unit of analyses. Nitrate concentrations were determined for 4855 samples from private wells. Validated field-by-field land use data were available. Average nitrate concentration and percentage of area for the 14 major land use categories in PEI were determined for each of three spatial aggregations: watersheds based on topography and hydrology; freeform polygon boundaries based on similar neighboring nitrate concentrations; and 500-m buffer zones around each well. Results showed that the percentages of potato, grain, and hay coverage were positive predictors of ground water nitrate concentrations. Percentage of blueberry was a marginally significant negative predictor in the watershed and freeform polygon models, and percentage of residential coverage was a positive predictor in the freeform polygon and buffer zone models. Spatial autocorrelation was present in the freeform polygon and buffer zone models even after land use was taken into account. In conclusion, analyses based on watersheds produced the best predictive model with the percentages of land cover of potato, hay, and grain being significantly associated with ground water nitrate concentrations, and the percentages of blueberry, clear-cut woodland, and other agriculture being marginally significant.     

Comparing the Use of Indigenous Knowledge with Classification and Ordination Techniques for Assessing the Species Composition and Structure of Vegetation in a Tropical Forest

dentification of groups that are similar in their floristic composition and structure (habitat types) is essential for conservation and forest managers to allocate high priority areas and to designate areas for reserves, refuges, and other protected areas. In this study, the use of indigenous knowledge for the identification of habitat types in the field was compared against an ecological characterization of habitat types, including their species composition obtained by using classification and ordination techniques for a tropical landscape mosaic in a rural Mayan area of Quintana Roo, Mexico. Plant diversity data calculated from 141 sampled sites chosen randomly on a vegetation class’s thematic map obtained by multispectral satellite image classification were used for this propose. Results indicated high similarity in the categorization of vegetation types between the Mayan classification and those obtained by cluster and detrended correspondence analysis. This suggests that indigenous knowledge has a practical use and can be comparable to that obtained by using science-based methods. Finally, identification and mapping of vegetation classes (habitat types) using satellite image classification allowed us to discriminate significantly different species compositions, in such a way that they can provide a useful mechanism for interpolating diversity values over the entire landscape.     

Development of models for predicting toxicity from sediment chemistry by partial least squares-discriminant analysis and counter-propagation artificial neural networks

There is strong interest in developing tools to link chemical concentrations of contaminants to the potential for observing sediment toxicity that can be used in initial screening-level sediment quality assessments. This paper presents new approaches for predicting toxicity in sediments, based on 10-day survival tests with marine amphipods, from sediment chemistry, by means of the application of Partial Least Squares-Discriminant Analysis (PLS-DA) and Counter-propagation Artificial Neural Networks (CP-ANNs) to large historical databases of chemical and toxicity data. The exploration of the internal structure of the developed models revealed inherent limitations of predicting toxicity from common chemical analyses of bulk contaminant concentrations. However, the results obtained in the validation of these models combined relevant values of non-error classification rate, sensitivity and specificity of, respectively, 76, 87 and 73% with PLS-DA and 92, 75 and 97% with CP-ANNs, outperforming the results reported for previous approaches.     

Environmental impacts associated with manufacturing of solar and wind power alternative energy systems

The Air Force Center for Engineering and the Environment (AFCEE) is performing Environmental Restoration Program Optimization (E‐RPO) at various United States Air Force (USAF) installations to evaluate existing remediation strategies and recommend actions to advance issues impacting the remediation program. As sustainability practices (including green and sustainable remediation [GSR]) increase at Air Force facilities and throughout the environmental industry, the use of alternative energy‐collection sources (i.e., solar photovoltaics [PV] and wind turbines) is likely to increase dramatically. Although PV and wind power systems exhibit a low environmental footprint during their use, there are potential human health and environmental impacts from the manufacturing and recycling processes. This article presents a summary of available information regarding the environmental impacts associated with life‐cycle assessments that include raw material extraction and refinement, product manufacturing, use, and postuse disposal for PV and wind turbines (i.e., cradle‐to‐grave impacts). © 2010 Wiley Periodicals, Inc.     

Alterations observed in the endothelial HUVEC cell line exposed to pure Cylindrospermopsin

The cyanobacterial toxin Cylindrospermopsin (CYN) is receiving great interest due to its increasing presence in waterbodies, which has lead to recognize it as a potential threat to drinking water safety. CYN is a potent inhibitor of protein and glutathione synthesis. The present work studies for the first time the effects of CYN in endothelial cells. The basal cytotoxicity endpoints studied at 24 and 48 h were total protein content (PC), neutral red (NR) uptake and the tretazolium salt, MTS, reduction. Moreover, the effect of subcytotoxic concentrations of CYN on the generation of intracellular reactive oxygen species (ROS), the activity of γ-glutamylcysteine synthetase (GCS) and glutathione (GSH) content have been investigated. In addition, morphological alterations of HUVEC cells subsequent to CYN exposure were recorded.The cytotoxicity endpoints revealed a decrease in the cellular viability in a time and concentration-dependent way. The most sensitive cytotoxicity endpoint was NR uptake assay, with reductions in cell viability of 95% at 48 h of exposure to 40 μg mL⁻¹ CYN. Intracellular ROS production was increased only at the lowest concentration assayed, while GCS activity and GSH content underwent concentration-dependent enhancements. The most remarkable morphological alterations observed were: nucleolar segregation with altered nuclei, degenerated Golgi apparatus, increases in the presence of granules and apoptosis.     

In vitro biological effects of airborne PM₂.₅ and PM₁₀ from a semi-desert city on the Mexico-US border

Compelling evidence indicates that exposure to urban airborne particulate matter (PM) affects health. However, how PM components interact with PM-size to cause adverse health effects needs elucidation, especially when considering soil and anthropogenic sources. We studied PM from Mexicali, Mexico, where soil particles contribute importantly to air pollution, expecting to differentiate in vitro effects related to PM-size and composition. PM samples with mean aerodynamic diameters ≤2.5μm (PM(2.5)) and ≤10μm (PM(10)) were collected in Mexicali (October 2005-March 2006) from a semi-urban (expected larger participation of soil sources) and an urban (predominately combustion sources) site. Samples were pooled by site and size, analyzed for elemental composition (particle-induced X-ray emission) and tested in vitro for: induction of human erythrocytes membrane disruption (hemolysis) (colorimetrically); inhibition of cell proliferation (ICP) (crystal violet) and TNFα/IL-6 secretion (ELISA) using J774.A1 murine monocytic cells; and DNA degradation using Balb/c3T3 cell naked DNA (electrophoretically). Results of PM elemental composition principal component analysis were used in associating cellular effects. Sixteen elements identified in PM grouped in two principal components: Component(1) (C(1)): Mg, Al, Si, P, Cl, K, Ca, Ti, V, Cr, Fe, and Component(2) (C(2)): Cu, Zn. Hemolysis was predominately induced by semi-urban-PM(10) (p<0.05) and was associated with urban-PM(10)C(1) (r=0.62, p=0.003). Major ICP resulted with semi-urban PM(2.5) (p<0.05). TNFα was mainly induced by urban samples regardless of size (p<0.05) and associated with urban-PM(2.5)C(2) (r=0.48, p=0.02). Both PM(10) samples induced highest DNA degradation (p<0.05), regardless of location. We conclude that PM-size and PM-related soil or anthropogenic elements trigger specific biological-response patterns.     

Intercomparison exercise for gases emitted by a cement industry in Spain: a functional data approach

This paper describes the results of an intercomparison exercise referring to the measurement of atmospheric pollutants emitted by cement plants. The research was conducted in 2008 in Catalonia, Spain. Thirteen Spanish companies accredited to make pollutant measurements and with suitably approved equipment and trained staff participated in the research. The aim of the research was to evaluate the technical competence of the accredited companies in conducting tests in situ. The results obtained from the application of the methodology described in international standards--on the basis of conventional statistical analyses--were compared with those obtained using functional data analysis. On comparing the two methods, it was concluded that the functional method, although more complex, has advantages over the conventional statistical method. This is because the functional approach compares curves rather than mean values. Furthermore, it does not presuppose a normal distribution of the data.     

Heading for the hills: climate-driven community relocations in the Solomon Islands and Alaska provide insight for a 1.5 °C future

Whilst future air temperature thresholds have become the centrepiece of international climate negotiations, even the most ambitious target of 1.5 °C will result in significant sea-level rise and associated impacts on human populations globally. Of additional concern in Arctic regions is declining sea ice and warming permafrost which can increasingly expose coastal areas to erosion particularly through exposure to wave action due to storm activity. Regional variability over the past two decades provides insight into the coastal and human responses to anticipated future rates of sea-level rise under 1.5 °C scenarios. Exceeding 1.5 °C will generate sea-level rise scenarios beyond that currently experienced and substantially increase the proportion of the global population impacted. Despite these dire challenges, there has been limited analysis of how, where and why communities will relocate inland in response. Here, we present case studies of local responses to coastal erosion driven by sea-level rise and warming in remote indigenous communities of the Solomon Islands and Alaska, USA, respectively. In both the Solomon Islands and the USA, there is no national government agency that has the organisational and technical capacity and resources to facilitate a community-wide relocation. In the Solomon Islands, communities have been able to draw on flexible land tenure regimes to rapidly adapt to coastal erosion through relocations. These relocations have led to ad hoc fragmentation of communities into smaller hamlets. Government-supported relocation initiatives in both countries have been less successful in the short term due to limitations of land tenure, lacking relocation governance framework, financial support and complex planning processes. These experiences from the Solomon Islands and USA demonstrate the urgent need to create a relocation governance framework that protects people’s human rights.