Uplift and submarine formation of some Melanesian porphyry copper deposits: Stable isotope evidence

Hydrogen and oxygen isotope analyses of sericites and kaolinites from four young porphyry copper deposits (Ok Tedi (1.2 Ma) and Yandera (6.5 Ma), Papua New Guinea; Koloula (1.5 Ma), Solomon Islands; and Waisoi (<5 Ma), Fiji) indicate that the fluids from which these minerals precipitated were of mixed magmatic and non-magmatic sources. The non-magmatic component of the fluid from the island arc deposits (Koloula, Waisoi) was ocean water.For Ok Tedi, the non-magmatic component was a meteoric water with an isotopic composition different from that of the present meteoric water in the region. The isotopic signature of the former meteoric water is consistent with a surface elevation of 200 m a.s.l. or less at the time of mineralization. The deposit was later exposed and supergene kaolinitization commenced at approximately 1200 m a.s.l. Uplift and erosion has continued to the present at which time the elevation of the exposed deposit is 1800 m a.s.l. This rate of uplift is consistent with that known from other geological evidence. If the rate of uplift were approximately constant during the last 1.2 Ma, the age of supergene enrichment can be dated at approximately 0.4 Ma B.P.Similarly, influx of meteoric water at Yandera occurred when the ground surface above the deposit was at an elevation of approximately 600 m a.s.l. The deposit's present elevation is 1600 m a.s.l. In this case a total uplift of approximately 2.2 km is indicated, with removal of 1.2 km of overburden by erosion.     

Arsenic and presumed resistate trace element geochemistry of the Lincolnshire (UK) sedimentary ironstones,as revealed by a regional geochemical survey using soil,water and stream sediment sampling

A regional geochemical survey using soils, stream sediment and stream water sampling revealed multi-element geochemical anomalies, though of low environmental mobility, associated with Mesozoic sedimentary ironstones in Lincolnshire, UK. The most prominent of these anomalies were of As and V in soils and sediments, but elevated levels of elements such as Cr, La, Ce and Th were also observed. These were initially thought to be part of a residual resistate element or heavy-mineral suite, but careful examination suggests that these too may be primarily associated with the process of Fe oxide precipitation during the initial formation of the ironstones.     

Considering river structure and stability in the light of evolution: feedbacks between riparian vegetation and hydrogeomorphology

River ecological functioning can be conceptualized according to a four‐dimensional framework, based on the responses of aquatic and riparian communities to hydrogeomorphic constraints along the longitudinal, transverse, vertical and temporal dimensions of rivers. Contemporary riparian vegetation responds to river dynamics at ecological timescales, but riparian vegetation, in one form or another, has existed on Earth since at least the Middle Ordovician (c. 450 Ma) and has been a significant controlling factor on river geomorphology since the Late Silurian (c. 420 Ma). On such evolutionary timescales, plant adaptations to the fluvial environment and the subsequent effects of these adaptations on fluvial sediment and landform dynamics resulted in the emergence, from the Silurian to the Carboniferous, of a variety of contrasted fluvial biogeomorphic types where water flow, morphodynamics and vegetation interacted to different degrees. Here we identify several of these types and describe the consequences for biogeomorphic structure and stability (i.e. resistance and resilience), along the four river dimensions, of feedbacks between riparian plants and hydrogeomorphic processes on contrasting ecological and evolutionary timescales. Copyright © 2014 John Wiley & Sons, Ltd.     

Hybrid Model for Urban Air Pollution Forecasting: A Stochastic Spatio-Temporal Approach

Air pollution is usually driven by a complex combination of factors in which meteorology, physical obstacles, and interactions between pollutants play significant roles. Considering the characteristics of urban atmospheric pollution and its consequent impacts on human health and quality of life, forecasting models have emerged as an effective tool to identify and forecast air pollution episodes. The overall objective of the present work is to produce forecasts of pollutant concentrations with high spatio-temporal resolution and to quantify the uncertainty in those forecasts. Therefore, a new approach was developed based on a two-step methodology. Firstly, neural network models were used to generate short-term temporal forecasts based on air pollution and meteorology data. The accuracy of those forecasts was then evaluated against an independent set of historical data. Secondly, local conditional distributions of the observed values with respect to the predicted values were used to perform spatial stochastic simulations for the entire geographic area of interest. With this approach the spatio-temporal dispersion of a pollutant can be predicted, while accounting for both the temporal uncertainty in the forecast (reflecting the neural networks efficiency at each monitoring station) and the spatial uncertainty as revealed by the spatial variograms. Based on an analysis of the results, our proposed method offers a highly promising alternative for the characterization of urban air quality.