澳大利亚铁矿业的先进技术介绍

介绍了澳大利亚RioTinto矿业集团的HIsmelt Plant、帕拉布杜和恰那铁矿、汤姆普莱斯铁矿、扬地库吉那铁矿、皮尔巴拉铁路公司和Dampier港的先进技术、质量控制体系、生产体系，及其作业的主要步骤、不同矿体的矿石特性、铁路系统运作和丹皮尔港的基本情况。     

Quantitative X-ray powder diffraction analysis of clay minerals in Australian coals using Rietveld methods

The mineralogy of clay-rich mineral matter isolated from a range of Australian bituminous coals has been evaluated in quantitative terms from X-ray powder diffraction (XRD) patterns using a Rietveld-based data processing technique. The chemical composition of coal ash derived from this mineral matter has been calculated and compared to the directly determined composition of the ash prepared from the same coal samples. Although there are some minor differences due in part to uncertainty regarding the actual composition of several minerals, the compositions indicated by the two methods show a relatively high correlation, suggesting that the Rietveld technique provides mineralogical analyses that are consistent with independently determined chemical data. Comparison of the normalised clay mineral percentages from the Rietveld analysis to quantitative interpretations based on a peak intensities in glycolated and heat-treated oriented aggregates of the respective clay fractions also shows a high correlation, confirming mutual consistency of the two different mineralogical analysis methods. Such quantitative mineralogical data are significant to a range of coal exploration, mining and utilization activities, including seam correlation, material handling and ash and slag formation in combustion processes.     

Mobility of trace elements from selected Australian fly ashes and its potential impact on aquatic ecosystems

Batch leaching tests have been performed on fly ashes collected from four Australian power stations fuelled by chemically different coals. Two acidic and two alkaline fly ashes were subjected to long-term (144 h) leaching tests, and the behaviour of As, B, Mo and Se was investigated to obtain data on their potential for mobilisation during fly ash-water interactions. All four elements are mobile under different conditions and over different leaching times. The concentrations of these elements released in leaching solutions with initial pH values of 4, 7 and 10 were used to assess the influence of pH conditions on element mobility from the acidic and alkaline fly ashes. The most mobile of the four elements leached were Mo from alkaline fly ashes and B from acidic fly ashes. Arsenic concentration increased with time in leachate solutions from acidic and alkaline fly ashes; however, in solutions in contact with alkaline fly ashes the As concentration, after reaching a maximum, later decreased with time. Selenium mobility shows a similar pattern to that of As, with similar leaching concentrations. Boron has the highest relative mobility of all four elements. A process possibly responsible for the decrease in concentration of B, As and Se in alkaline leaching solutions is the formation of ettringite. Equilibrium between the solid phase (ash) and the leaching solution was not reached in any of the leaching experiments. The pH of the leaching solution is the key factor affecting the mobility of these trace elements in these fly ashes.     

A customised approach to determining the geomorphic effectiveness of small flood events in a regulated river

The construction of dams significantly alters flow and sediment regimes with subsequent deleterious effects on the morphological and ecological character of rivers. Effective experimental floods can ameliorate the downstream geomorphic impacts of dams. The traditional view is that large floods are required to perform effective geomorphic work, and the geomorphic outcomes of small floods are often overlooked. Many river restoration frameworks do not consider small floods. Yet, there is evidence that the hydrological characteristics that ameliorate specific geomorphic impacts in a river are unique to each river, and a customised approach to setting the right mix of floods (including small experimental floods) is needed. In this study, we modify an existing flood effectiveness model developed for large floods, for determining the geomorphic effectiveness of small floods in a highly regulated Australian river. Two flood classes were added to the model (medium peak stream power and moderate total energy expenditure), and the flood power characteristics were rescaled to reflect the relative difference in the magnitude of the small floods and the magnitude of the geomorphic work performed. Using a step‐wise approach, this customised model determined the geomorphic effectiveness of small floods. The best flood for ameliorating the geomorphic impacts of flow regulation had medium to long duration (10 to 51 days), high peak unit stream power (77 to 123 Wm^?2) and moderate to large total energy expenditure (78,600 to 342,320 × 10³ J). This approach to determining flood effectiveness for small floods is applicable to other geomorphically impacted river channels downstream of dams and can be used to inform experimental flood releases for geomorphic outcomes.     

Mapping seagrass species, cover and biomass in shallow waters: An assessment of satellite multi-spectral and airborne hyper-spectral imaging systems in Moreton Bay (Australia)

Understanding, monitoring and modelling attributes of seagrass biodiversity, such as species composition, richness, abundance, spatial patterns, and disturbance dynamics, requires spatial information. This work assessed the accuracy of commonly available airborne hyper-spectral and satellite multi-spectral image data sets for mapping seagrass species composition, horizontal horizontal-projected foliage cover and above-ground dry-weight biomass. The work was carried out on the Eastern Banks in Moreton Bay, Australia, an area of shallow and clear coastal waters, containing a range of seagrass species, cover and biomass levels. Two types of satellite image data were used: Quickbird-2 multi-spectral and Landsat-5 Thematic Mapper multi-spectral. Airborne hyper-spectral image data were acquired from a CASI-2 sensor using a pixel size of 4.0 m. The mapping was constrained to depths shallower than 3.0 m, based on past modelling of the separability of seagrass reflectance signatures at increasing water depths. Our results demonstrated that mapping of seagrass cover, species and biomass to high accuracy levels (> 80%) was not possible across all image types. For each parameter mapped, airborne hyper-spectral data produced the highest overall accuracies (46%), followed by Quickbird-2 and then Landsat-5 Thematic Mapper. The low accuracy levels were attributed to the mapping methods and difficulties in matching locations on image and field data sets. Accurate mapping of seagrass cover, species composition and biomass, using simple approaches, requires further work using high-spatial resolution (< 5 m) and/or hyper-spectral image data. Further work is required to determine if and how the seagrass maps produced in this work are suitable for measuring attributes of seagrass biodiversity, and using these data for modelling floral and fauna biodiversity properties of seagrass environments, and for scaling-up seagrass ecosystem models.     

The impact of misregistration on SRTM and DEM image differences

Image differences between Shuttle Radar Topography Mission (SRTM) data and other Digital Elevation Models (DEMs) are often performed for either accuracy assessment or for estimating vegetation height across the landscape. It has been widely assumed that the effect of sub-pixel misregistration between the two models on resultant image differences is negligible, yet this has not previously been tested in detail. The aim of this study was to determine the impact that various levels of misregistration have on image differences between SRTM and DEMs. First, very accurate image co-registration was performed at two study sites between higher resolution DEMs and SRTM data, and then image differences (SRTM–DEM) were performed after various levels of misregistration were systematically introduced into the SRTM data. It was found that: (1) misregistration caused an erroneous and dominant correlation between elevation difference and aspect across the landscape; (2) the direction of the misregistration defined the direction of this erroneous and systematic elevation difference; (3) for sub-pixel misregistration the error due solely to misregistration was greater than, or equal to the true difference between the two models for substantial proportions of the landscape (e.g., greater than 33% of the area for a half-pixel misregistration); and (4) the strength of the erroneous relationship with aspect was enhanced by steeper terrain. Spatial comparisons of DEMs were found to be sensitive to even sub-pixel misregistration between the two models, which resulted in a strong erroneous correlation with aspect. This misregistration induced correlation with aspect is not likely specific to SRTM data only; we expect it to be a generic relationship present in any DEM image difference analysis.     

Dust source identification using MODIS: A comparison of techniques applied to the Lake Eyre Basin, Australia

The impact of mineral aerosol (dust) in the Earth's system depends on particle characteristics which are initially determined by the terrestrial sources from which the sediments are entrained. Remote sensing is an established method for the detection and mapping of dust events, and has recently been used to identify dust source locations with varying degrees of success. This paper compares and evaluates five principal methods, using MODIS Level 1B and MODIS Level 2 aerosol data, to: (a) differentiate dust (mineral aerosol) from non-dust, and (2) determine the extent to which they enable the source of the dust to be discerned. The five MODIS L1B methods used here are: (1) un-processed false colour composite (FCC), (2) brightness temperature difference, (3) Ackerman's (1997: J.Geophys. Res., 102, 17069-17080) procedure, (4) Miller's (2003:Geophys. Res. Lett. 30, 20, art.no.2071) dust enhancement algorithm and (5) Roskovensky and Liou's (2005: Geophys. Res. Lett. 32, L12809) dust differentiation algorithm; the aerosol product is MODIS Deep Blue (Hsu et al., 2004: IEEE Trans. Geosci. Rem. Sensing, 42, 557-569), which is optimised for use over bright surfaces (i.e. deserts). These are applied to four significant dust events from the Lake Eyre Basin, Australia. OMI AI was also examined for each event to provide an independent assessment of dust presence and plume location. All of the techniques were successful in detecting dust when compared to FCCs, but the most effective technique for source determination varied from event to event depending on factors such as cloud cover, dust plume mineralogy and surface reflectance. Significantly, to optimise dust detection using the MODIS L1B approaches, the recommended dust/non-dust thresholds had to be considerably adjusted on an event by event basis. MODIS L2 aerosol data retrievals were also found to vary in quality significantly between events; being affected in particular by cloud masking difficulties. In general, we find that OMI AI and MODIS AQUA L1B and L2 data are complementary; the former are ideal for initial dust detection, the latter can be used to both identify plumes and sources at high spatial resolution. Overall, approaches using brightness temperature difference (BT10-11) are the most consistently reliable technique for dust source identification in the Lake Eyre Basin. One reason for this is that this enclosed basin contains multiple dust sources with contrasting geochemical signatures. In this instance, BTD data are not affected significantly by perturbations in dust mineralogy. However, the other algorithms tested (including MODIS Deep Blue) were all influenced by ground surface reflectance or dust mineralogy; making it impossible to use one single MODIS L1B or L2 data type for all events (or even for a single multiple-plume event). There is, however, considerable potential to exploit this anomaly, and to use dust detection algorithms to obtain information about dust mineralogy.     

Recovering limonite from Australia iron ores by flocculation-high intensity magnetic separation

Successful recovery of limonite from iron fines was achieved by using flocculation-high intensity magnetic separation （FIMS） and adding hydrolyzed and causticized flocculants according to the characteristic of iron fines. The separation results of the three iron samples are as follows： iron grade 66.77%- 67.98% and the recovery of iron 69.26%-70.70% by the FIMS process with flocculants. The comparative results show that under the same separation conditions the F1MS process can effectively increase the recovery of iron by 10. 97%- 15.73%. The flowsheet results confirm the reliability of the process in a SHP high intensity magnetic separator. The concentrate product can he used as raw materials for direct reduction iron-smelting. The hydrolyzed and causticized flocculants can selectively flocculate fine feebly-magnetic iron mineral particles to increase their apparent separation sizes. The larger the separation size, the stronger the magnetic force. By comparing the separation results of the three samples it is found that among the three samples the higher the limonite content, the better the separation result. This means that the separation result relates closely to the flocculation process and the adding pattern of the flocculant.     

Estimation of catchment-scale water-balance with a soil-vegetation-atmosphere transfer model

Catchments with a small elevation range and relatively long dry periods in high radiation conditions may be described as an array of vertical one-dimensional pathways for water and energy. Such a representation enhances the ability of SVAT modeling to simulate mass exchanges across the catchment. This note reports on a comparison of a Soil-Vegetation-Atmosphere Transfer (SVAT) model (Braud et al., 1995), a deterministic hydrological model (Dawes and Hatton, 1993) and a stochastic hydrological model (Sivapalan and Woods, 1995; Kalma et al., 1995). The original version of the SVAT model only considers vertical transport and this one-dimensional representation must be aggregated to describe the entire catchment. Therefore, two new versions have been developed: a deterministic SVAT model which sub-divides the catchment into 40 sub-regions linked by surface flow, and a stochastic model which provides a distribution of the output fluxes as related to the spatial distribution of initial water content and/or soil properties. All simulations have been made for a 60-day period.     

从澳大利亚TAFE学院看行业组织在职业教育中的作用

文中对我们在澳大利亚看到的、听到的、了解到的职业培训与教育做一简略介绍，并就我国的职业教育做了一些思考。