The value of bioenergy in low stabilization scenarios: an assessment using REMIND-MAgPIE

This study investigates the use of bioenergy for achieving stringent climate stabilization targets and it analyzes the economic drivers behind the choice of bioenergy technologies. We apply the integrated assessment framework REMIND-MAgPIE to show that bioenergy, particularly if combined with carbon capture and storage (CCS) is a crucial mitigation option with high deployment levels and high technology value. If CCS is available, bioenergy is exclusively used with CCS. We find that the ability of bioenergy to provide negative emissions gives rise to a strong nexus between biomass prices and carbon prices. Ambitious climate policy could result in bioenergy prices of 70 $/GJ (or even 430 $/GJ if bioenergy potential is limited to 100 EJ/year), which indicates a strong demand for bioenergy. For low stabilization scenarios with BECCS availability, we find that the carbon value of biomass tends to exceed its pure energy value. Therefore, the driving factor behind investments into bioenergy conversion capacities for electricity and hydrogen production are the revenues generated from negative emissions, rather than from energy production. However, in REMIND modern bioenergy is predominantly used to produce low-carbon fuels, since the transport sector has significantly fewer low-carbon alternatives to biofuels than the power sector. Since negative emissions increase the amount of permissible emissions from fossil fuels, given a climate target, bioenergy acts as a complement to fossils rather than a substitute. This makes the short-term and long-term deployment of fossil fuels dependent on the long-term availability of BECCS.     

Molecular systems in a strong magnetic field

Brief overview of one-two electron molecular systems made out of protons and/or α-particles in a strong magnetic field B≤4.414×10¹³ G is presented. A particular emphasis is given to the one-electron exotic ions H₃⁺⁺(pppe), He₂³⁺(α α e) and to two-electron ionsH₃⁺(pppee), He₂⁺⁺(α α ee). Quantitative studies in a strong magnetic field are very complicated technically. Novel approach to the few-electron Coulomb systems in magnetic field, which provides accurate results, based on variational calculus with physically relevant trial functions is briefly described.      

South Australian rainfall variability and climate extremes

Rainfall extremes over South Australia are connected with broad-scale atmospheric rearrangements associated with strong meridional sea surface temperature (SST) gradients in the eastern Indian Ocean. Thirty-seven years of winter radiosonde data is used to calculate a time series of precipitable water (PW) and convective available potential energy (CAPE) in the atmosphere. Principle component analysis on the parameters of CAPE and PW identify key modes of variability that are spatially and seasonally consistent with tropospheric processes over Australia. The correlation of the leading principle component of winter PW to winter rainfall anomalies reveal the spatial structure of the northwest cloudband and fronts that cross the southern half of the continent during winter. Similarly the second and third principle components, respectively, reveal the structures of the less frequent northern and continental cloudbands with remarkable consistency. 850 hPa-level wind analysis shows that during dry seasons, anomalous offshore flow over the northwest of Australia inhibits advection of moisture into the northwest, while enhanced subsidence from stronger anticyclonic circulation over the southern half of the continent reduces CAPE. This coincides with a southward shift of the subtropical ridge resulting in frontal systems passing well to the south of the continent, thus producing less frequent interaction with moist air advected from the tropics. Wet winters are the reverse, where a weaker meridional pressure gradient to the south of the continent allows rain-bearing fronts to reach lower latitudes. The analysis of SSTs in the Indian Ocean indicate that anomalous warm (cool) waters in the southeast Indian Ocean coincide with a southward (northward) shift in the subtropical ridge during dry (wet) seasons.     

Toward Improved Solar Irradiance Forecasts: a Simulation of Deep Planetary Boundary Layer with Scattered Clouds Using the Weather Research and Forecasting Model

Accurate forecasts of solar irradiance are required for electric utilities to economically integrate substantial amounts of solar power into their power generation portfolios. A common failing of numerical weather models is the prediction of scattered clouds at the top of deep PBL which are generally difficult to be resolved due to complicated processes in the planetary boundary layer. We improved turbulence parameterization for better predicting solar irradiance during the scattered clouds’ events using the Weather Research and Forecasting model. Sensitivity tests show that increasing the exchange coefficient leads to enhanced vertical mixing and a deeper mixed layer. At the top of mixed layer, an adiabatically ascending air parcel achieved the water vapor saturation and finally scattered cloud is generated.     

Partial polygon pruning of hydrographic features in automated generalization

This article demonstrates a working method to automatically detect and prune portions of waterbody polygons to support creation of a multi‐scale hydrographic database. Water features are sensitive to scale change, therefore multiple representations are required to maintain visual and geographic logic at smaller scales. Partial pruning of polygonal features – such as long, sinuous reservoir arms, stream channels too narrow at the target scale, and islands that begin to coalesce – entails concurrent management of the length and width of polygonal features as well as integrating pruned polygons with other generalized point and linear hydrographic features to maintain stream network connectivity. The implementation follows data representation standards developed by the US Geological Survey (USGS) for the National Hydrography Dataset (NHD). Portions of polygonal rivers, streams, and canals are automatically characterized for width, length, and connectivity. This article describes an algorithm for automatic detection and subsequent processing, and shows results for a sample of NHD subbasins in different landscape conditions in the US.     

How friends share urban space: An exploratory spatiotemporal analysis using mobile phone data

This study proposes a framework to investigate the roles of urban spaces in connecting social contacts (i.e., “friends”). The framework is applied to a Call Detail Record (CDR) dataset collected in Singapore. First, a comparative analysis is performed to understand how friends share urban space differently from random people. Then, we derive two metrics to quantify the “bonding” and “bridging” capabilities of places in the city. The two metrics reflect the potential of a place in connecting friends and random people (e.g., chance encounters), respectively. Finally, we examine the temporal signature of the places’ bonding capabilities, and associate the results with various types of Points of Interest (POIs). We find that: (1) friends are more likely to share urban space than random people, and they also share more locations; (2) a place could play different roles in connecting friends vs. random people, and the relationship (between bonding and bridging) varies depending on the time and type of a day (weekdays vs. weekends); (3) the temporal signature of bonding capability is strongly related to the semantics of a place; (4) certain POI types (e.g., shopping malls) tend to have a much higher impact on bonding capability than others (e.g., sports centers).     

MultiscaleDTM: An open-source R package for multiscale geomorphometric analysis

Digital terrain models (DTMs) are datasets containing altitude values above or below a reference level, such as a reference ellipsoid or a tidal datum over geographic space, often in the form of a regularly gridded raster. They can be used to calculate terrain attributes that describe the shape and characteristics of topographic surfaces. Calculating these terrain attributes often requires multiple software packages that can be expensive and specialized. We have created a free, open-source R package, MultiscaleDTM , that allows for the calculation of members from each of the five major thematic groups of terrain attributes: slope, aspect, curvature, relative position, and roughness, from a regularly gridded DTM. Furthermore, these attributes can be calculated at multiple spatial scales of analysis, a key feature that is missing from many other packages. Here, we demonstrate the functionality of the package and provide a simulation exploring the relationship between slope and roughness. When roughness measures do not account for slope, these attributes exhibit a strong positive correlation. To minimize this correlation, we propose a new roughness measure called adjusted standard deviation. In most scenarios tested, this measure produced the lowest rank correlation with slope out of all the roughness measures tested. Lastly, the simulation shows that some existing roughness measures from the literature that are supposed to be independent of slope can actually exhibit a strong inverse relationship with the slope in some cases.     

The stability of geodemographic cluster assignments over an intercensal period

A geodemographic classification provides a set of categorical summaries of the built and socio-economic characteristics of small geographic areas. Many classifications, including that developed in this paper, are created entirely from data extracted from a single decennial census of population. Such classifications are often criticised as becoming less useful over time because of the changing composition of small geographic areas. This paper presents a methodology for exploring the veracity of this assertion, by examining changes in UK census-based geodemographic indicators over time, as well as a substantive interpretation of the overall results. We present an innovative methodology that classifies both 2001 and 2011 census data inputs utilising a unified geography and set of attributes to create a classification that spans both census periods. Through this classification, we examine the temporal stability of the clusters and whether other secondary data sources and internal measures might usefully indicate local uncertainties in such a classification during an intercensal period.     

Routing through open spaces – A performance comparison of algorithms

Abstract

Finding the shortest path through open spaces is a well-known challenge for pedestrian routing engines. A common solution is routing on the open space boundary, which causes in most cases an unnecessarily long route. A possible alternative is to create a subgraph within the open space. This paper assesses this approach and investigates its implications for routing engines. A number of algorithms (Grid, Spider-Grid, Visibility, Delaunay, Voronoi, Skeleton) have been evaluated by four different criteria: (i) Number of additional created graph edges, (ii) additional graph creation time, (iii) route computation time, (iv) routing quality. We show that each algorithm has advantages and disadvantages depending on the use case. We identify the algorithms Visibility with a reduced number of edges in the subgraph and Spider-Grid with a large grid size to be a good compromise in many scenarios.     

Low-altitude geophysical magnetic prospecting based on multirotor UAV as a promising replacement for traditional ground survey

Abstract

The prospects for expanding the mineral resource base in many countries are linked with the exploration of stranded sites localized at unexplored areas with complex natural and landscape conditions that make any ground survey, including magnetic prospecting, difficult and expensive. The current level of geology requires high-precision and large-scale data at the first stages of geological exploration. Since 2012, technologies of aeromagnetic surveying with unmanned aircraft vehicles (UAV) enter the market, but most of them are based on big fixed-wing UAV and do not allow to substantially increase the level of survey granularity compared with traditional aerial methods. To increase the scale of survey, it is necessary to reduce the altitude and speed of flight, for which the authors develop the methodical and technical solutions described in this article. To obtain data at altitudes of 5 m above the terrain even in a rugged relief, we created heavy multirotor UAVs that are stable in flight and may be used in a wide range of environmental conditions (even a moderate snowfall), and develop a special software to generate flight missions on the basis of digital elevation models. A UAV has special design to reduce magnetic interference of the flight platform; the magnetic sensor is hung below the aircraft. This technology was conducted in a considerable amount of magnetic surveys in the mountainous regions of East Siberia between 2014 and 2016. The results of the comparison between airborne and ground surveys are presented, which show that the sensitivity of the developed system in conjunction with low-altitude measurements can cover any geologically significant anomalies of the magnetic field. An unmanned survey is cheaper and more productive; the multirotor-based technologies may largely replace traditional ground magnetic exploration in scales of 1:10,000?1:1000.