Estimation of Cumulative Frequency Distribution for Carbon Monoxide Concentration from Wind-Speed Data, in Buenos Aires (Argentina)

In this article we apply and test a methodology to estimate cumulative frequency distribution for air pollutant concentration from wind-speed data. We use the inverse relationship after Simpson et al. (Atmospheric Environment, 19, 75–82, 1985) between the opposing percentile values in the statistical distributions for air pollutant concentrations and wind-speed data. This relationship is valid, irrespective of the statistical distributions of both variables, if an inverse relationship between them is also applicable. The available data are five years of 8-h average carbon monoxide concentration and 8-h mean wind-speed, observed in Buenos Aires (Argentina). The performance of the obtained empirical expressions in estimating cumulative frequency distributions for 8-h CO is statistically evaluated. The results show that it is possible to obtain an acceptable cumulative frequency distribution for 8-h CO concentration at the site if the cumulative frequency distribution for wind-speed is known. Q–Q plots show a good agreement between estimated and observed values. From our data, the mean relative error of the estimations was found to be as much as 8.0%.     

Landscapes and environments on the island of Ouessant,Brittany, France: From traditional maintenance to the management of abandoned areas

For about 50 years the desertion of areas by traditional activities has led to an important evolution of landscapes and environments on the island of Ouessant. The study of this evolution has been undertaken at different spatial and temporal scales. On one part of the island, a scientific investigation carried out at the scale of the parcel enabled the form of the landscape in 1850 to be compared with that of 1985. On the whole island, the evolution of spatial organization and land use was compared between 1950 and 1985. For each of three main ecological environments, vegetational successions after the decrease of agriculture have been studied along with their future potential changes. This work highlights some considerations about the present management of the environment in relation to the major objectives of island environmental policies.     

Evaluation of Material Biodegradability in Real Conditions–Development of a Burial Test and an Analysis Methodology Based on Numerical Vision

This work validated a burial protocol for in situ testing and presents a robust, repeatable and time-saving technique to measure degraded areas in the sample, i.e. an image analysis method. 1440 specimens of degraded samples have been compiled in a data base. To this end, twenty samples presenting different levels of biodegradability (i.e. PHBV/HV, PLA, PCL, PCL-Starch, paper, PE, PE-Starch) were buried at 4 different locations and then disinterred at 4, 6, 9, 12, 18, and 24-month intervals. The biodegradation levels of these samples were determined by computing weight and area loss. Weight loss was measured after careful cleaning, whereas area loss was quantified using image analysis. Image analysis gives reliable information on visual pollution while only requiring a rudimentary and thus quicker cleaning of the samples.     

Interpretation of analytical data on n-alkanes and polynuclear aromatic hydrocarbons in Arbacia lixula from the coasts of Tenerife (Canary Islands, Spain) by multivariate data analysis

The hydrocarbons contents (n-alkanes, polycyclic aromatic hydrocarbons) were determined in the sea urchin Arbacia lixula. Multivariate data analysis as principal component analysis, factor analysis and, cluster analysis were applied to elucidate sources of pollution. PCA and FA were performed to establish the relationships between variables (hydrocarbons), samples (sea urchin) and sources of pollution.     

Interpretation of heavy metal data from mussel by use of multivariate classification techniques

Different strategies of multivariate analysis of metals concentrations (Mn, Fe, Ni, V, Co, Cu, Cd, Hg, Pb, Na, K) in mussel samples from different spanish markets are used to interpret a data base and identify differences between species and origin of the samples. Principal Component Analysis and Potential curves are applied to properly classify unknown samples from representative mussels samples (Mytilus edulis and Perna canaliculus). Also, Principal Components Analysis is used as display method to visualize the relation between the variables and objects of interest.     

Feeding habits of marine cladocerans in the Inland Sea of Japan

Natural food items of five species of marine cladocerans, Evadne nordmanni, E. tergestina, Penilia avirostris, Podon leuckarti and P. polyphemoides, were investigated in the Inland Sea of Japan between April 1986 and May 1987. Gut content examination with SEM (scanning electron microscopy) revealed that feeding was largely limited to centric diatoms and a few exceptions of pennate diatoms and dinoflagellates. No animal remains were detected, and some unidentified materials were also found. Phytoplankton smaller than 35 m in size (cell diameter in centric diatoms and longest dimension in others) was found most frequently in the gut of cladocerans. The role of grazing of marine cladocerans in trophodynamic pathways of the pelagic realm is discussed.     

Simulating urban waste compost effects on carbon and nitrogen dynamics using a biochemical index

Composting has emerged as a valuable route for the disposal of urban waste, with the prospect of applying composts on arable fields as organic amendments. Proper management of urban waste composts (UWCs) requires a capacity to predict their effects on carbon and nitrogen dynamics in the field, an issue in which simulation models are expected to play a prominent role. However, the parameterization of soil organic amendments within such models generally requires laboratory incubation data. Here, we evaluated the benefit of using a biochemical index based on Van Soest organic matter fractions to parameterize a deterministic model of soil C and N dynamics, NCSOIL, as compared with a standard alternative based on laboratory incubation data. The data included C mineralization and inorganic N dynamics in samples of a silt loam soil (Typic Hapludalf) mixed with various types of UWC and farmyard manure. NCSOIL successfully predicted the various nitrogen mineralization-immobilization patterns observed, but underestimated CO(2) release by 10 to 30% with the less stable amendments. The parameterization based on the biochemical index achieved a prediction error significantly larger than the standard parameterization in only 10% of the tested cases, and provided an acceptable fit to experimental data. The decomposition rates and C to N ratios of compost organic matter varied chiefly according to the type of waste processed. However, 62 to 66% of their variance could be explained by the biochemical index. We thus suggest using the latter to parameterize organic amendments in C and N models as a substitute for time-consuming laboratory incubations.