Characterization and sources assignation of PM2.5 organic aerosol in a rural area of Spain

The results from a year-long study of the organic composition of PM2.5 aerosol collected in a rural area influenced by a highway of Spain are reported. The lack of prior information related to the organic composition of PM2.5 aerosol in Spain, concretely in rural areas, led definition of the goals of this study. As a result, this work has been able to characterize the main organic components of atmospheric aerosols, including several compounds of SOA, and has conducted a multivariate analysis in order to assign sources of particulate matter. A total of 89 samples were taken between April 2004 and April 2005 using a high-volume sampler. Features and abundance of n-alkanes, polycyclic aromatic hydrocarbons (PAHs), alcohols and acids were separately determined using gas chromatography/mass spectrometry and high performance liquid chromatography analysis. The Σn-alkane and ΣPAHs ranged from 3 to 81 ng m^?3 and 0.1 to 6 ng m^?3 respectively, with higher concentrations during colder months. Ambient concentrations of Σalcohols and Σacids ranged from 21 to 184 ng m^?3 and 39 to 733 ng m^?3, respectively. Also, several components of secondary organic aerosol have been quantified, confirming the biogenic contribution to ambient aerosol. In addition, factor analysis was used to reveal origin of organic compounds associated to particulate matter. Eight factors were extracted accounting more than 83% of the variability in the original data. These factors were assigned to a typical high pollution episode by anthropogenic particles, crustal material, plant waxes, fossil fuel combustion, temperature, microbiological emissions, SOA and dispersion of pollutants by wind action. Finally, a cluster analysis was used to compare the organic composition between the four seasons.     

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.     

Atmospheric nitrogen deposition in south-east Scotland: Quantification of the organic nitrogen fraction in wet,dry and bulk deposition

Water soluble organic nitrogen (WSON) compounds are ubiquitous in precipitation and in the planetary boundary layer, and therefore are a potential source of bioavailable reactive nitrogen. This paper examines weekly rain data over a period of 22 months from June 2005 to March 2007 collected in 2 types of rain collector (bulk deposition and “dry + wet” deposition) located in a semi-rural area 15 km southwest of Edinburgh, UK (N55°51′44″, W3°12′19″). Bulk deposition collectors are denoted in this paper as “standard rain gauges”, and they are the design used in the UK national network for monitoring precipitation composition. “Dry + wet” deposition collectors are flushing rain gauges and they are equipped with a rain detector (conductivity array), a spray nozzle, a 2-way valve and two independent bottles to collect funnel washings (dry deposition) and true wet deposition. On average, for the 27 weekly samples with 3 valid replicates for the 2 types of collectors, dissolved organic nitrogen (DON) represented 23% of the total dissolved nitrogen (TDN) in bulk deposition. Dry deposition of particles and gas on the funnel surface, rather than rain, contributed over half of all N-containing species (inorganic and organic). Some discrepancies were found between bulk rain gauges and flushing rain gauges, for deposition of both TDN and DON, suggesting biological conversion and loss of inorganic N in the flushing samplers.     

Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images

We have used Landsat-5 TM and Landsat-7 ETM+ images together with simultaneous ground-truth data at sample points in the Doñana marshes to predict water turbidity and depth from band reflectance using Generalized Additive Models. We have point samples for 12 different dates simultaneous with 7 Landsat-5 and 5 Landsat-7 overpasses. The best model for water turbidity in the marsh explained 38% of variance in ground-truth data and included as predictors band 3 (630–690 nm), band 5 (1550–1750 nm) and the ratio between bands 1 (450–520 nm) and 4 (760–900 nm). Water turbidity is easier to predict for water bodies like the Guadalquivir River and artificial ponds that are deep and not affected by bottom soil reflectance and aquatic vegetation. For the latter, a simple model using band 3 reflectance explains 78.6% of the variance. Water depth is easier to predict than turbidity. The best model for water depth in the marsh explains 78% of the variance and includes as predictors band 1, band 5, the ratio between band 2 (520–600 nm) and band 4, and bottom soil reflectance in band 4 in September, when the marsh is dry. The water turbidity and water depth models have been developed in order to reconstruct historical changes in Doñana wetlands during the last 30 years using the Landsat satellite images time series.     

Integrating Landscape Analysis and Planning: A Multi-Scale Approach for Oriented Management of Tourist Recreation

Tourism and landscape are interdependent concepts. Nature- and culture-based tourism are now quite well developed activities and can constitute an excellent way of exploiting the natural resources of certain areas, and should therefore be considered as key objectives in landscape planning and management in a growing number of countries. All of this calls for careful evaluation of the effects of tourism on the territory. This article focuses on an integrated spatial method for landscape analysis aimed at quantifying the relationship between preferences of visitors and landscape features. The spatial expression of the model relating types of leisure and recreational preferences to the potential capacity of the landscape to meet them involves a set of maps showing degrees of potential visitor satisfaction. The method constitutes a useful tool for the design of tourism planning and management strategies, with landscape conservation as a reference.     

Sorption of alkylphenols on Ebro River sediments: comparing isotherms with field observations in river water and sediments

This study reports sorption isotherms of the endocrine disruptors nonylphenol (NP) and octylphenol (OP) in three sediment samples from the Ebro River basin (NE Spain), with organic carbon fractions (f_OC) ranging from 0.0035 to 0.082 g_OC g⁻¹. All isotherms were fitted to the Freundlich model with slightly nonlinear exponents ranging from 0.80 to 0.94. The solubility of the compounds as well as the organic carbon (OC) content had the strongest influences on the sorption behavior of these compounds. Comparison of the laboratory-spiked samples with the native contamination of NP of 45 water and concurrent sediment samples resulted in reasonable matches between both data sets, even though the lowest concentrations in the field were not completely reached in laboratory tests. This good agreement indicates that sorption laboratory data can be extrapolated to environmental levels and therefore the distribution of nonylphenol between sediments and water can be predicted with a precision of one order of magnitude. Furthermore, laboratory experiments with simultaneous loading of NP and OP revealed negligible competition for sorption sites at low concentrations.     

Sediment integrative assessment of the Bay of Cádiz (Spain): An ecotoxicological and chemical approach

This study consisted of the sediment toxicity assessment of the Bay of Cádiz based on two endpoints: growth inhibition for Cylindrotheca closterium (benthic microalgae) and fecundity inhibition for Tisbe battagliai (harpacticoid copepod). A new methodology to eliminate (but not as storage technique) the autochthonous biota present in the sediment samples by immersing them in liquid nitrogen (? 196 °C) was also assessed. Sediment toxicity data showed different toxicity levels for both organisms. In general, T. battagliai was more sensitive; however a good correlation (r = 0.75; p  < 0.05) between sediment toxicity results for both species was found. Data in pore water (pH, redox potential, and toxicity for microalgae and copepod) and sediment (pH, redox potential, organic carbon, and metal concentrations) demonstrated that ultra-freezing did not alter sample characteristics; thus, this technique can be adopted as a pre-treatment in whole-sediment toxicity tests in order to avoid misleading results due to presence of autochthonous biota. Multivariate statistical analysis such as cluster and principal component analysis using chemical and ecotoxicological data were employed. Silt and organic matter percentage and lead concentration were found to be the factors that explain about 77% of sediment toxicity in the Bay of Cádiz. Assay methodology determined in this study for both assayed species is considered adequate to be used in sediment toxicity monitoring programs. Results obtained using both species show that the Bay of Cádiz can be considered a moderately polluted zone.     

Study of the comparative dynamics of the incorporation of tissue free-water tritium (TFWT) in bulrushes (Typha latifolia) and carp (Cyprinus carpio) in the Almaraz nuclear power plant cooling reservoir

The Almaraz nuclear power plant (Spain) uses the water of Arrocampo reservoir for cooling, and consequently raises the radioactive levels of the aquatic ecosystem of this reservoir. From July 2002 to June 2005, monthly samples of surface water, bulrushes (Typha latifolia) and carp (Cyprinus carpio) were collected from this reservoir. They were analyzed to determine the temporal evolution of the levels of ³H in surface water and of its transfer from the surface water to free-water in the tissues (TFWT) of the aforementioned two organisms. The tritium levels in the surface water oscillate with a biannual period, with their values in the study period ranging between 53 and 433 Bq/L. The incorporation of tritium to bulrushes and carp was fairly similar, the respective mean concentration factors being 0.74 and 0.8 (unitless, as Bq/L tissue water per Bq/L reservoir water). The temporal evolution of the levels fairly closely followed that observed for the surface water tritium, although detailed analysis showed the dominant periodicity for the bulrushes to be annual. This difference reflects the influence on the incorporation of tritium to bulrushes of diverse environmental and metabolic factors, especially evapotranspiration and the seasonal growth of this plant.     

New best estimates for radionuclide solid–liquid distribution coefficients in soils. Part 3: miscellany of radionuclides (Cd,Co, Ni,Zn, I,Se, Sb,Pu, Am,and others)

New best estimates for the solid–liquid distribution coefficient (K_d) for a set of radionuclides are proposed, based on a selective data search and subsequent calculation of geometric means. The K_d best estimates are calculated for soils grouped according to the texture and organic matter content. For a limited number of radionuclides this is extended to consider soil cofactors affecting soil–radionuclide interaction, such as pH, organic matter content, and radionuclide chemical speciation. Correlations between main soil properties and radionuclide K_d are examined to complete the information derived from the best estimates with a rough prediction of K_d based on soil parameters. Although there are still gaps for many radionuclides, new data from recent studies improve the calculation of K_d best estimates for a number of radionuclides, such as selenium, antimony, and iodine.