A hydrological model to estimate pollution from combined sewer overflows at the regional scale: Application to Europe

Study region Combined Sewer Overflows (CSO) of 671 Functional Urban Areas (FUAs) throughout the European Union + UK (EU28), representing almost half of the EU28 population. Study focus CSO loads can be quantified at the local scale through measurements, or with calibrated hydrological models. However, they are difficult to quantify at a large scale (e.g. regional or national), due to a lack of data, and the models used at local scale cannot be applied in the absence of knowledge of the combined sewer (CS) network. This paper presents a 6-parameter lumped hydrological model to simulate a CS network and its overflows, using population and rainfall data of 671 EU28 FUAs. New hydrological insights for the region When properly calibrated, the model can predict the CSO hydrographs as well as aggregated CSO descriptors of a catchment with known impervious surface area connected to a CS with a reasonable reliability. When model calibration is not possible, using default values of the parameters enables a first approximation estimate of CSOs, accurate within one order of magnitude, which can be used to support scenario analysis for regional and continental CSO management. At the EU28 scale, the estimated total CSO volume is 5.7·10$^3$ Mm$^3$/y, with a dry weather flow content in CSOs of 460 Mm$^3$/y (assuming a dry weather flow of 200 l/population equivalent (PE)/day including sanitary discharges, industrial discharge and infiltration). A collection of case studies on CSOs is also provided

A hydrological model to estimate pollution from combined sewer overflows at the regional scale: application to Europe

Study region Combined Sewer Overflows (CSO) of 671 Functional Urban Areas (FUAs) throughout the European Union + UK (EU28), representing almost half of the EU28 population. Study focus CSO loads can be quantified at the local scale through measurements, or with calibrated hydrological models. However, they are difficult to quantify at a large scale (e.g. regional or national), due to a lack of data, and the models used at local scale cannot be applied in the absence of knowledge of the combined sewer (CS) network. This paper presents a 6-parameter lumped hydrological model to simulate a CS network and its overflows, using population and rainfall data of 671 EU28 FUAs. New hydrological insights for the region When properly calibrated, the model can predict the CSO hydrographs as well as aggregated CSO descriptors of a catchment with known impervious surface area connected to a CS with a reasonable reliability. When model calibration is not possible, using default values of the parameters enables a first approximation estimate of CSOs, accurate within one order of magnitude, which can be used to support scenario analysis for regional and continental CSO management. At the EU28 scale, the estimated total CSO volume is 5.7·103 Mm3/y, with a dry weather flow content in CSOs of 460 Mm3/y (assuming a dry weather flow of 200 l/population equivalent (PE)/day including sanitary discharges, industrial discharge and infiltration). A collection of case studies on CSOs is also provided

Construction of an interactive online phytoplasma classification tool, iPhyClassifier, and its application in analysis of the peach X-disease phytoplasma group (16SrIII)

Phytoplasmas, the causal agents of numerous plant diseases, are insect-vector-transmitted, cell-wall-less bacteria descended from ancestral low-G+C-content Gram-positive bacteria in the Bacillus–Clostridium group. Despite their monophyletic origin, widely divergent phytoplasma lineages have evolved in adaptation to specific ecological niches. Classification and taxonomic assignment of phytoplasmas have been based primarily on molecular analysis of 16S rRNA gene sequences because of the inaccessibility of measurable phenotypic characters suitable for conventional microbial characterization. In the present study, an interactive online tool, iPhyClassifier, was developed to expand the efficacy and capacity of the current 16S rRNA gene sequence-based phytoplasma classification system. iPhyClassifier performs sequence similarity analysis, simulates laboratory restriction enzyme digestions and subsequent gel electrophoresis and generates virtual restriction fragment length polymorphism (RFLP) profiles. Based on calculated RFLP pattern similarity coefficients and overall sequence similarity scores, iPhyClassifier makes instant suggestions on tentative phytoplasma 16Sr group/subgroup classification status and ‘Candidatus Phytoplasma’ species assignment. Using iPhyClassifier, we revised and updated the classification of strains affiliated with the peach X-disease phytoplasma group. The online tool can be accessed at http://www.ba.ars.usda.gov/data/mppl/iPhyClassifier.html

Genetic correlations between temperature-induced plasticity of life-history traits in a soil arthropod.

Temperature is considered one of the most important mediators of phenotypic plasticity in ectotherms. However, the costs and benefits shaping the evolution of different thermal responses are poorly elucidated. One of the possible constraints to phenotypic plasticity is its intrinsic genetic cost, such as genetic linkage or pleiotropy. Genetic coupling of the thermal response curves for different life history traits may significantly affect the evolution of thermal sensitivity in thermally fluctuating environments. We used the collembolan Orchesella cincta to study if there is genetic variation in temperature-induced phenotypic plasticity in life history traits, and if the degree of temperature-induced plasticity is correlated across traits. Egg development rate, juvenile growth rate and egg size of 19 inbred isofemale lines were measured at two temperatures. Our results show that temperature was a highly significant factor for all three traits. Egg development rate and juvenile growth rate increased with increasing temperature, while egg size decreased. Line by temperature interaction was significant for all traits tested; indicating that genetic variation for temperature-induced plasticity existed. The degree of plasticity was significantly positively correlated between egg development rate and growth rate, but plasticity in egg size was not correlated to the other two plasticity traits. The findings suggest that the thermal plasticities of egg development rate and growth rate are partly under the control of the same genes or genetic regions. Hence, evolution of the thermal plasticity of traits cannot be understood in isolation of the response of other traits. If traits have similar and additive effects on fitness, genetic coupling between these traits may well facilitate the evolution of optimal phenotypes. However, for this we need to know the selective forces under field conditions. © 2010 Springer Science+Business Media B.V

Waterkwaliteitsspoor in breder perspectief: Sint Maartensdijk

Water ManagementCivil Engineering and Geoscience