Provisional Elemental Values for IAEA‐Sewage Sludge by Instrumental Neutron Activation Analysis

The International Atomic Energy Agency (IAEA) organised a proficiency test (PT), IAEA‐CU‐2010‐02, for the determination of elements in sewage sludge. The PT sample was analysed by semi‐absolute standardless k₀‐instrumental neutron activation analysis (k₀‐INAA). Results for seven elements (As, Co, Cr, Fe, Hg, Se, Zn) were submitted to the IAEA by our laboratory. All of our results were scored ‘acceptable’ by the ‘result evaluation criteria’ adopted by the IAEA. The same analytical methodology produced quantitative results for twenty‐six additional elements. In total, thirty‐six elements were determined with uncertainty varying from 4 to 11%. This paper presents the provisional mass fractions of twenty‐six additional elements (Ag, Al, Br, Ca, Ce, Cl, Dy, Eu, Ga, Hf, I, K, La, Mg, Mn, Na, Rb, Sb, Sc, Sm, Ta, Tb, Th, V, U, W) not reported by the IAEA. The analytical methodology was discussed with important sources of spectral, nuclear and fission‐product interferences. It was shown that the important components of uncertainties were the k₀ factor, Q₀ factor, detector efficiency, mass and counting statistics. The methodology was validated by analysing the IAEA‐S7 reference material.     

Vulnerability and adaptability of wheat production in different climatic zones of Pakistan under climate change scenarios

Ten wheat production sites of Pakistan were categorized into four climatic zones i.e. arid, semi-arid, sub-humid and humid to explore the vulnerability of wheat production in these zones to climate change using CSM-Cropsim-CERES-Wheat model. The analysis was based on multi-year (1971–2000) crop model simulation runs using daily weather series under scenarios of increased temperature and atmospheric carbon dioxide concentration (CO₂) along with two scenarios of water management. Apart from this, sowing date as an adaptation option to offset the likely impacts of climate change was also considered. Increase in temperature resulted in yield declines in arid, semi-arid and sub-humid zone. But the humid zone followed a positive trend of gain in yield with rise in temperature up to 4°C. Within a water regime, increase in CO₂ concentration from 375 to 550 and 700 ppm will exert positive effect on gain in wheat yield but this positive effect is significantly variable in different climatic zones under rainfed conditions than the full irrigation. The highest response was shown by arid zone followed by semi-arid, sub-humid and humid zones. But if the current baseline water regimes (i.e. full irrigation in arid and semi-arid zones and rainfed in sub-humid and humid zones) persist in future, the sub-humid zone will be most benefited in terms of significantly higher percent gain in yield by increasing CO₂ level, mainly because of its rainfed water regime. Within a CO₂ level the changes in water supply from rainfed to full irrigation shows an intense degree of responsiveness in terms of yield gain at 375 ppm CO₂ level compared to 550 and 700 ppm. Arid and semi-arid zones were more responsive compared to sub-humid and humid zones. Rise in temperature reduced the length of crop life cycle in all areas, though at an accelerated rate in the humid zone. These results revealed that the climatic zones have shown a variable intensity of vulnerability to different scenarios of climate change and water management due to their inherent specific and spatial climatic features. In order to cope with the negative effects of climate change, alteration in sowing date towards cooler months will be an appropriate response by the farmers.     

A comprehensive study on the surface chemistry of particulate matter collected from Jeddah,Saudi Arabia

In this work, the X-ray Photoelectron Spectroscopy (XPS) technique is utilized to analyze the surface chemical composition of particulate matter (PM) which was collected from various locations at Jeddah, Saudi Arabia. The main elements found on the surface of PM are carbon (C), oxygen (O) and silicon (Si) with combined percentage of 89.4–94.9 while traces of nitrogen (N), calcium (Ca), aluminum (Al), sodium (Na), chlorine (Cl), manganese (Mg), and sulfur (S) were also present. The analyzed XPS chemical state of C, O and Si was further used to determine their bonding with other elements occurring over the surface of PM. Carbon was found in the form of carbides (18.86%), fluorides (2.39%) and carbonates (78.75%); oxygen was observed as oxides (21.05%) and hydroxides (73.42%) of other metals; and silicon was detected as silicones (12.16%), nitrides (82.53%) and silicates (5.25%). The particle size of a PM is also of great concern for health issues, and thus has been investigated by the Field Emission Scanning Electron Microscope (FESEM). The Energy Dispersive X-ray Spectroscopy (EDS) was employed for cross verification of detected elements by XPS.     

Improving Large Area Population Mapping Using Geotweet Densities

Many different methods are used to disaggregate census data and predict population densities to construct finer scale, gridded population data sets. These methods often involve a range of high resolution geospatial covariate datasets on aspects such as urban areas, infrastructure, land cover and topography; such covariates, however, are not directly indicative of the presence of people. Here we tested the potential of geo‐located tweets from the social media application, Twitter, as a covariate in the production of population maps. The density of geo‐located tweets in 1x1 km grid cells over a 2‐month period across Indonesia, a country with one of the highest Twitter usage rates in the world, was input as a covariate into a previously published random forests‐based census disaggregation method. Comparison of internal measures of accuracy and external assessments between models built with and without the geotweets showed that increases in population mapping accuracy could be obtained using the geotweet densities as a covariate layer. The work highlights the potential for such social media‐derived data in improving our understanding of population distributions and offers promise for more dynamic mapping with such data being continually produced and freely available.     

The North Pacific Oscillation: observations compared with simulations in a general circulation model

The study of the sea level pressure and the surface air temperatures in the North Pacific region in a 23-year integration of the Oregon State University coupled ocean-atmosphere general circulation model has shown that there is a signature of the North Pacific Oscillation in the model, comparable to that recorded in observations. In the model, the NPO index was defined in terms of an opposition in sign of mean temperature anomaly between two regions in the North Pacific region, close to those found in observations (viz. Dutch Harbor, Alaska, and Edmonton, Canada). Fluctuations of this index prompted the grouping of some of the 23 model years as those when the temperature at the model equivalent of Dutch Harbor was above normal and that at the model equivalent of Edmonton below normal (analogous to Aleutian above in observations), while other years displayed the opposite scenario (Aleutian below). Composites of sea level pressure, surface air temperatures, precipitation and sea surface temperatures in the Northern Hemisphere were found to be at times strikingly similar to those documented in observations by Rogers.     

Outlining a stepwise,multi-parameter debris flow monitoring and warning system: an example of application in Aizi Valley,China

In recent years, the increasing frequency of debris flow demands enhanced effectiveness and efficiency of warning systems. Effective warning systems are essential not only from an economic point of view but are also considered as a frontline approach to alleviate hazards. Currently, the key issues are the imbalance between the limited lifespan of equipment, the relatively long period between the recurrences of such hazards, and the wide range of critical rainfall that trigger these disasters. This paper attempts to provide a stepwise multi-parameter debris flow warning system after taking into account the shortcomings observed in other warning systems. The whole system is divided into five stages. Different warning levels can be issued based on the critical rainfall thresholds. Monitoring starts when early warning is issued and it continues with debris flow near warning, triggering warning, movement warning and hazard warning stages. For early warning, historical archives of earthquake and drought are used to choose a debris flow-susceptible site for further monitoring. Secondly, weather forecasts provide an alert of possible near warning. Hazardous precipitation, model calculation and debris flow initiation tests, pore pressure sensors and water content sensors are combined to check the critical rainfall and to publically announce a triggering warning. In the final two stages, equipment such as rainfall gauges, flow stage sensors, vibration sensors, low sound sensors and infrasound meters are used to assess movement processes and issue hazard warnings. In addition to these warnings, community-based knowledge and information is also obtained and discussed in detail. The proposed stepwise, multi-parameter debris flow monitoring and warning system has been applied in Aizi valley China which continuously monitors the debris flow activities.     

Entropy change and phase transitions in an expanding Universe

The work compiles a correlated study of a gravitational quasi equilibrium thermodynamic approach for establishing and signifying a unique behavior of the cosmological entropy and phase transitions in an expanding Universe. On the basis of prescribed boundary conditions for the cluster temperature a relation for the intra‐cluster medium (ICM) of galaxy clusters has been derived. A more productive and signifying approach of the correlation functions used for galaxy clustering phenomena shows a unique behavior of the entropy change where a phenomenon known as the gravitational phase transition occurs. This unique behavior occurs with a symmetry breaking from mild clustering to low clustering and from mild clustering to high clustering which differs from a normal symmetry breaking in material sciences. We also derive results for the specific latent heat associated with the phase transitions of 3.20 T_c and 0.55 T_c for the mildly clustered phase to the low clustered phase and from the mildly clustered phase to the highly clustered phase, respectively. (© 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)