Stability Assessment and Quantitative Evaluation of H/V Spectral Ratios for Site Response Studies in Kumaon Himalaya, India Using Ambient Noise Recorded by a Broadband Seismograph Network

The Kumaon Himalaya region in India has accumulated considerable seismic risk potential from moderate to high seismicity due to ongoing tectonic evolutionary processes. To assess conditions of high seismic risk arising from local site effects at populated locations, we applied the empirical horizontal to vertical (H/V) spectral amplitude ratio method (Nakamura in Quarterly Reports of the Railway Technical Research Institute Tokyo, 30:25–33, 1989) using ambient seismic noise recorded by a network of 32 digital broadband seismographs from June 2005 to June 2008. The data and the estimated parameters were subjected to stability tests to assess the effect of seasonal variations. Seasonal variations in the ambient noise data seemed to show a lesser effect on fundamental frequency estimates and a slightly greater effect on the peak H/V amplitudes. Validation of the ambient noise results was done by complementary tests using H/V ratios of local and regional earthquakes. The ‘peak’ corresponding to the fundamental resonance frequency is prominently present in both the ambient noise and the earthquake datasets. The study locations showed distinct H/V curve topologies, corresponding to the effects of both velocity contrast at well-defined frequencies and characteristic topographic effect around a certain frequency range. The clearly indicated ‘peaks’ in the H/V curves possibly correspond to velocity contrasts created by weathered sediments overlying hard rock basements in rocky hills. Our study indicates high site responses at many populated locations near the surface trace of the seismically active Main Central Thrust (MCT) and other fault boundaries. The fundamental resonance frequencies estimated from the site response studies at the 32 locations could be useful in preliminary site characterization, ground motion prediction and seismic hazard analysis.     

Water and Wastewater Treatment in Africa – Current Practices and Challenges

Sustainable access to safe drinking water and basic sanitation is an important part of the millennium development goals (MDGs). For most African countries, an extensive effort is needed for the last three remaining years for the achievement of the MDGs, especially in Sub‐Saharan Africa. Current practices for water and wastewater treatment in Africa are insufficient to ensure safe water and basic sanitation. To address this challenge, joint efforts are needed, including transforming to green economy, innovating technologies, improving operation and maintenance, harvesting energy, improving governance and management, promoting public participation, and establishing water quality standards.     

Independent component regression for predicting the responses of biaxial base‐isolated buildings

This paper presents a regression model to predict the base displacement responses of biaxial base‐isolated buildings using independent component analysis. The model proposed utilizes multiple ground motion intensity measures from North American and Japanese earthquakes as inputs, and transforms them into an independent component space using independent component regression (ICR). Unlike other latent variable methods, such as principal component regression, ICR does not readily allow for dimensionality reduction of the components that do not contribute significantly to the explained variance of the original data set. Hence, a whitening‐step to transform the correlated variables into uncorrelated ones is introduced prior to performing ICR. Prediction results are presented and compared with the simulation results for two building models with increasing degree of complexity. The results show that the model based on ICR results in good estimates for the base displacement responses, and the standard errors remain relatively small and constant across a range of isolation periods. Copyright © 2009 John Wiley & Sons, Ltd.     

Numerical Investigation of the Influence of Mineral Dust on the Tropospheric Chemistry of East Asia

An investigation of the influence of mineral dust ontrace gas cycles in the troposphere is carried out inthis study. A 3D regional scale atmospheric chemistrymodel (STEM-III) which includes aerosol processes isused for the numerical simulations for May 1987.Heterogeneous interactions between gaseous species(SO₂, N₂O₅, HNO₃, HO₂andH₂O₂) and the dust particles are considered.Emissions of dust behind convective cold fronts aremodeled. The transport and distribution of mineraldust predicted from the model is compared withsatellite measurements (aerosol index from TOMS). Themodel is shown to capture the synoptic variability inthe observed aerosol index. Calculations show twomajor dust events in May 1987, during which thedust levels close to the source reach more than500 g/m³. The transport of dust is mostlyrestricted towards the north, with the net continentaloutflow of 6 Tg for the entire month. Results showthat the presence of mineral aerosol can greatlyimpact sulfate and nitrate distributions. Averagedover the month of May, the presence of dust isestimated to increase particulate sulfate and nitratelevels in east Asia by 40%. Furthermore, the sulfateand nitrate on the dust particles are predicted to beassociated with the coarse mode (3–5 m particlediameter), consistent with observations over Japan.The influence of mineral dust on the photochemicaloxidant cycle is also investigated. For the entiremonth, a5–10% decrease in boundary layer ozone ispredicted by the model closer to regions of higherdust levels. The ratio of nitric acid to NO_x overmarine regions is reduced by a factor between 1 and 2in the boundary layer to more than 2 in the freetroposphere as a result of aerosol processes.     

Mineralogical and geochemical patterns of urban surface soils, the example of Pforzheim, Germany

This study presents a combined geochemical and mineralogical survey of urban surface soils. Many studies on urban soils are restricted to purely chemical surveys in order to investigate soil pollution caused by anthropogenic activities such as traffic, heating, industrial processing, waste disposal and many more. In environmental studies, chemical elements are often distinguished as lithogenic and anthropogenic elements. As a novel contribution to those studies, the authors combined the analysis of a broad set of chemical elements with the analysis of the main mineralogical phases. The semi-quantification of mineralogical phases supported the assignment of groups of chemical elements to lithogenic or anthropogenic origin. Minerals are important sinks for toxic elements. Thus, knowledge about their distribution in soils is crucial for the assessment of the environmental hazards due to pollution of urban soils. In Pforzheim, surface soils (0–5 cm depth) from various land use types (forest, agriculture, urban green space, settlement areas of various site densities) overlying different geological units (clastic and chemical sediments) were investigated. Urban surface soils of Pforzheim reflect to a considerable degree the mineral and chemical composition of parent rocks. Irrespective of the parent rocks, elevated concentrations of heavy metals (Zn, Cu, Pb, Sn, Ag) were found in soils throughout the whole inner urban settlement area of Pforzheim indicating pollution. These pollutants will tend to accumulate in inner urban surface soils according to the available adsorption capacity, which is normally higher in soils overlying limestone than in soils overlying sandstone. However, inner urban surface soils overlying sandstone show elevated concentrations of carbonates, phyllo-silicates and Fe and elevated pH values compared with forest soils overlying sandstone. Thus, in comparison to forest soils overlying sandstones, inner urban soils overlying sandstone affected by pollution concurrently possess elevated concentrations of mineral phases typically providing relatively high adsorption capacities for heavy metals.     

Shape Classification of AltiKa 40-Hz Waveforms using Linear Discriminant Analysis and Bayes Decision Rule in the Gujarat Coastal Region

Shape classification of the 40-Hz waveforms obtained by the recently launched AltiKa satellite has been attempted in the paper. Since retracking algorithms suitable for altimeter return echoes based on Brown model are not applicable for the echoes from coastal ocean, specific algorithms are to be devised for such echoes. In the coastal ocean, waveforms display a wide variety of shapes due to varying coastline geometry, and topography. Hence, a proper classification strategy is required for classifying the waveforms into various categories so that suitable retracker could be applied to each category for retrieving the oceanic parameters. The algorithm consists of three steps: feature selection, linear discriminant analysis, and Bayesian classifier. The classification algorithm has been applied to the waveforms in the close proximity of Gujarat coast. Independent validation has been done near the eastern coast of India. Confusion matrices obtained for both the coasts are quite encouraging. Individual examples of classification have been provided for the purpose of illustration.     

Future projections and uncertainty assessment of extreme rainfall intensity in the United States from an ensemble of climate models

Changes in climate are expected to lead to changes in the characteristics extreme rainfall frequency and intensity. In this study, we propose an integrated approach to explore potential changes in intensity-duration-frequency (IDF) relationships. The approach incorporates uncertainties due to both the short simulation periods of regional climate models (RCMs) and the differences in IDF curves derived from multiple RCMs in the North American Regional Climate Change Assessment Program (NARCCAP). The approach combines the likelihood of individual RCMs according to the goodness of fit between the extreme rainfall intensities from the RCMs’ historic runs and those from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data set and Bayesian model averaging (BMA) to assess uncertainty in IDF predictions. We also partition overall uncertainties into within-model uncertainty and among-model uncertainty. Results illustrate that among-model uncertainty is the dominant source of the overall uncertainty in simulating extreme rainfall for multiple locations in the U.S., pointing to the difficulty of predicting future climate, especially extreme rainfall regimes. For all locations a more intense extreme rainfall occurs in future climate; however the rate of increase varies among locations.