Mechanical Behavior of Clayey Soil Reinforced with Recycled Tire Rubber Using Chips and Fibers

Geotechnical and Geological Engineering - The volume of discarded tires continues to increase each year, becoming a major topic of concern for society. Motivated by this environmental issue, this...     

Comparative measurements and seasonal variations in energy and carbon exchange over forest and pasture in South West Amazonia

Summary Comparative measurements of radiation flux components and turbulent fluxes of energy and CO₂ are made at two sites in South West Amazonia: one in a tropical forest reserve and one in a pasture. The data were collected from February 1999 to September 2002, as part of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). During the dry seasons, although precipitation and specific humidity are greatly reduced, the soil moisture storage profiles down to 3.4m indicate that the forest vegetation continues to withdraw water from deep layers in the soil. For this reason, seasonal changes observed in the energy partition and CO₂ fluxes in the forest are small, compared to the large reductions in evaporation and photosynthesis observed in the pasture. For the radiation balance, the reflected short wave radiation increases by about 55% when changing from forest to pasture. Combined with an increase of 4.7% in long wave radiation loss, this causes an average reduction of 13.3% in net radiation in the pasture, compared to the forest. In the wet season, the evaporative fraction (E/R_n) at the pasture is 17% lower than at the forest. This difference increases to 24% during the dry season. Daytime CO₂ fluxes are 20–28% lower (in absolute values) in the pasture compared to the forest. The night-time respiration in the pasture is also reduced compared to the forest, with averages 44% and 57% lower in the wet and dry seasons, respectively. As the reduction in the nocturnal respiration is larger than the reduction in the daytime uptake, the combined effect is a 19–67% higher daily uptake of CO₂ in the pasture, compared to the forest. This high uptake of CO₂ in the pasture site is not surprising, since the growth of the vegetation is constantly renewed, as the cattle remove the biomass.     

Radon and progeny (Pb and Bi) in urban water-supply systems of São Paulo State,Brazil

Many water-supply systems in South America utilize the waters of the Guarani aquifer at least as part of their networks. However, there is little present knowledge in Brazil of the factors affecting Rn presence in the water supplied for end-users, despite the economic importance of Guarani aquifer. ²²²Rn analyzes of 162 water samples were performed at 8 municipalities in São Paulo State, Brazil, with the aim of investigating the major factors affecting its presence in solution. The ²²²Rn activity concentration ranged from 0.04 up to 204.9 Bq/L, with three samples exceeding the World Health Organization maximum limit of 100 Bq/L. Aeration was confirmed as the most important factor for Rn release, as expected due to its gaseous nature. Accumulation in pipes and stratification in the water column were other significant factors explaining the data obtained in some circumstances. The Rn daughters ²¹⁴Pb and ²¹⁴Bi were also determined in a set of selected samples and their presence was directly related to the occurrence of Rn dissolved in water.     

Sources and transport of lipids on Amazon continental shelf

Dissolved material and recent sediment from the Amazon continental shelf have been analyzed for hydrocarbons to study the sources and potential fate of the transported organic matter. Dissolvedn-alkanes are present at low concentrations (ppb level) and are dominated by lipids from marine phytoplankton with carbon number maxima (C_max) at C₁₈/C₂₂ and an even-to-odd carbon predominance < C₃₀ (CPI_17–27 from 0.18 to 0.54). In the sediments, bimodal distributions ofn-alkane chain length suggest a mixed input of terrestrial (C_max at C₂₇/C₂₉/C₃₁ and CPI_25–33 from 0.75 to 1.82) and phytoplanktonic/microbial (C_max at C₂₀ and CPI_15–25 from 0.38 to 0.62) organic matter. Sesquiterpenes were the most significant cyclic compounds in all the dissolved samples analyzed reflecting a contribution from resinous trees to the terrestrial organic pool. On the other hand, enhanced concentrations of these compounds in the dissolved phase on the northwest portion of the Amazon shelf, contrasting with decreased concentrations in the sediment samples, suggest that dissolved lipids are released from solid phase in the intensely stirred seabed. Structured organic matter in the sediment has been characterized as being composed of, on average: 19% plant cuticles, 25% woody tissue, 13% pollens and spores, 24% amorphous material, 7% bituminite and 12% altered organic material.     

The use of hydroxyacids as geochemical indicators

The distributions of hydroxyacids in a variety of Recent and ancient sediments have been determined by gas chromatography-mass spectrometry. A lacustrine sediment (Rostherne Mere, U.K.) and two marine situations (Cariaco Trench, Black Sea) were analyzed as examples of Recent depositional environments. β-hydroxyacids occurred in all of the Recent sediments, consistent with their presumed microbial origin, whereas di- and trihydroxyacids were present in the sediments with a significant higher plant input (Black Sea and Rostherne Mere sediments). The two ancient (Eocene) sediments examined, viz. the Greene River (U.S.) and Messel (Germany) oil-shales, contained only trace amounts of hydroxyacids. These results provide evidence that hydroxyacids are in general not well preserved over geological time.     

Fitzgerald: A Return to the Neighborhood and Its Contemporary Structural and Geographical Contexts

William Bunge's Fitzgerald: Portrait of a Revolution, initially published in 1971, is an enthralling verbal and visual account of the historical and geographical development of a one-square-mile neighborhood in Detroit. The original analysis of the Fitzgerald neighborhood was based on intensive field-based research conducted in a theoretical context of race and racism. The research reported here maintains that context but updates Fitzgerald's account of the neighborhood's built environment through a spatial analysis that uses parcel-by-parcel data generated in Google Earth and Google Street View instead of data collected in the field. Current spatial patterns of deterioration in the built environment are similar to those described in Fitzgerald, but positive sites are also apparent and often colocated with negative ones.     

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution part 2: historical and future simulations of precipitation

This paper presents the first multi-model ensemble of 10-year, “convection-permitting” kilometer-scale regional climate model (RCM) scenario simulations downscaled from selected CMIP5 GCM projections for historical and end of century time slices. The technique is to first downscale the CMIP5 GCM projections to an intermediate 12–15 km resolution grid using RCMs, and then use these fields to downscale further to the kilometer scale. The aim of the paper is to provide an overview of the representation of the precipitation characteristics and their projected changes over the greater Alpine domain within a Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study and the European Climate Prediction system project, tasked with investigating convective processes at the kilometer scale. An ensemble of 12 simulations performed by different research groups around Europe is analyzed. The simulations are evaluated through comparison with high resolution observations while the complementary ensemble of 12 km resolution driving models is used as a benchmark to evaluate the added value of the convection-permitting ensemble. The results show that the kilometer-scale ensemble is able to improve the representation of fine scale details of mean daily, wet-day/hour frequency, wet-day/hour intensity and heavy precipitation on a seasonal scale, reducing uncertainty over some regions. It also improves the representation of the summer diurnal cycle, showing more realistic onset and peak of convection. The kilometer-scale ensemble refines and enhances the projected patterns of change from the coarser resolution simulations and even modifies the sign of the precipitation intensity change and heavy precipitation over some regions. The convection permitting simulations also show larger changes for all indices over the diurnal cycle, also suggesting a change in the duration of convection over some regions. A larger positive change of frequency of heavy to severe precipitation is found. The results are encouraging towards the use of convection-permitting model ensembles to produce robust assessments of the local impacts of future climate change.

     

Future surface temperature changes for the Iberian Peninsula according to EURO-CORDEX climate projections

Climate Dynamics - Future changes in the mean, maximum and minimum temperature in the Iberian Peninsula were investigated using bias-corrected EURO-CORDEX climate projections. The results show that...     

Machine Learning Based Predictive Modeling of Debris Flow Probability Following Wildfire in the Intermountain Western United States

It has been recognized that wildfire, followed by large precipitation events, triggers both flooding and debris flows in mountainous regions. The ability to predict and mitigate these hazards is crucial in protecting public safety and infrastructure. A need for advanced modeling techniques was highlighted by re-evaluating existing prediction models from the literature. Data from 15 individual burn basins in the intermountain western United States, which contained 388 instances and 26 variables, were obtained from the United States Geological Survey (USGS). After randomly selecting a subset of the data to serve as a validation set, advanced predictive modeling techniques, using machine learning, were implemented using the remaining training data. Tenfold cross-validation was applied to the training data to ensure nearly unbiased error estimation and also to avoid model over-fitting. Linear, nonlinear, and rule-based predictive models including naïve Bayes, mixture discriminant analysis, classification trees, and logistic regression models were developed and tested on the validation dataset. Results for the new non-linear approaches were nearly twice as successful as those for the linear models, previously published in debris flow prediction literature. The new prediction models advance the current state-of-the-art of debris flow prediction and improve the ability to accurately predict debris flow events in wildfire-prone intermountain western United States.